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ISSN 0096-4522

SOIL and CROP SCIENCE SOCIETY of FLORIDA

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PROCEEDINGS VOLUME 66

2007

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SIXTY-SIXTH ANNUAL MEETING TAMPA MARRIOTT WESTSHORE

TAMPA, FLORIDA 4-6 JUNE 2006

Mission Statement for Soil and Crop Science Society of Florida

The objectives of the Soil and Crop Science Society of Florida shall be those of an educational and scientific corporation qualified for exemption under Section 501 (c)3 of the Internal Revenue Code of 1954 as amended, or a comparable section of subsequent legislation. The mission of the Society is: 1) To advance the discipline and profession of soil and crop science in Florida a) by fostering excellence in the acquisition of new knowledge and in the training of scientists who work with crops and soils, b) through the education of Florida citizens, and c) by applying knowledge to challenges facing the State, and 2) to contribute to the long-term sustainability of agriculture, soils, the environment, and society by using scientifically-based principles of soil and crop science to promote informed and wise stewardship of Florida's land and water resources.

The Soil and Crop Science Society of Florida provides a non-regulatory and non-political forum to foster scientific ideas and exchange of in-formation for those interested in agricultural production and the sustenance of the agro-ecosystem in Florida. The mechanisms by which this so-ciety fosters exchange and displays of objective information include: 1) The presentation, at annual meetings, of papers by those who have completed scientifically-designed and analyzed data on subject matter that is pertinent to agriculture and environmental quality. 2) The publication of scientifically-designed treatments and analyzed experiments in papers on specific subject matters that are peer reviewed and published in a long-standing series of the Proceedings (Soil and Crop Science Society of Florida Proceedings). 3) The publication of position papers in the Proceedings that are needed by those who design laws and statutes on contemporary and applied subject matters related to agriculture and the environment in Florida that require objective viewpoints based on scientifically-attained information. 4) The fostering and training of students to participate in sci-entific dialogue by providing them with a competitive forum at the annual meeting of the Society where they can present their scientifically-attained data on agriculture and the environment and by providing them with opportunities to interact with professional people from universities, commer-cial companies, agribusiness, and growers. 5) The establishment of educational credits (e.g. C.E.U.s) which allow professionals to maintain their competency and certified status.

Drs. G. H. Snyder and T. A. Kucharek, January 2000.

Logo of the Soil and Crop Science Society of Florida. At the 40th Annual Business Meeting at 1120 h, 8 Oct. 1980 at the Holiday Inn, Longboat

Key, Sarasota, FL, a report was presented by the ad hoc Logo Committee composed of J. J. Street, Chair, R. S. Kalmbacher, and K. H. Quesenberry. All Society members were eligible to participate in the contest which would result in the selection of a logo design for the SCSSE The presentation of the winning entry would be made at the 1981 Annual Meeting. David H. Hubbell was announced as the winner of the contest and was awarded a free 10-yr membership in the Society. The design, shown above, depicted the chief interests of the Society: Florida Soils, and Crops. Soils and Crops were given equal weight with Florida. Soils was depicted as the soil texture triangle which shows the percentage of sand, silt, and clay in each of the textural classes, but simplified so as to permit clarity in reduction when printed. Crops was shown as a stylized broadleaf plant, including the roots. Florida was shown, minus its keys, with only one physical feature in its interior, Lake Okeechobee. Enclosed within nine rays such as might be envisioned as being made by the sun emitting light (sunburst) behind the symbols are two concentric circles containing the words "SOIL AND CROP SCIENCE SOCIETY" in the top semicircle and "FLORIDA" at the bottom of the lower semicircle. A schematic likeness of the State of Florida occupies 0.5 of the area within the smaller circle, while the symbol for Soils and the symbol for Crops occupy 0.25 of the area each, with the sum of the three parts totalling unity.

The first printing of Society stationery following the award on 28 Oct. 1981, and the printed program of the Society since the 1982 meetings, have featured the logo.

V. E. Green, Jr., Editor, Volume 45

2006 OFFICERS SOIL AND CROP SCIENCE SOCIETY OF FLORIDA President ………………………….. Ken Boote

Dept. of Agronomy P.O. Box 110500 Gainesville, FL 32611-0500

VOLUME 66 CONTENTS 2007

President-Elect ………………..... Martin Adjei Range Cattle REC 3401 Experiment Stn. Ona, FL 33865-9706

Dedication ……………………………………………………………………………………………………………………..

GENERAL SESSION PAPERS

Secretary-Treasurer………………T. A. Obreza Soil & Water Science Dept. P.O. Box 110510 Gainesville, FL 32611-0510

Response of Tropical Grasses to Nitrogen Sources of Fertilizer .................................................... M.B. Adjei and J.E. Rechcigl 1

Carbon Balance of Sugarcane Agriculture on Histosols of the Everglades Agricultural Area: Review, Analysis, and

Global Energy Perspectives .............................................................................................................................. L.H. Allen, Jr. 7

Nutrient Composition of Tifton-9 Bahiagrass in the First Season of a Silvopastoral System with Boer x Spanish Goats Directors: N. Gordon-Bradley and O.U. Onokpise 15

Lena Ma (2006) Soil & Water Science P.O. Box 110290 Gainesville, FL 32611-0290

Spectral Changes Associated with Bacterial Wilt Stress in Tomato Leaves

G. Hacisalihoglu, K.A. Milla, P. Ji, T. Mochena, S. Olson, and T.M. Momol

19

Fertilization, Aeration, and Sewage Biosolid Effects on Kikuyugrass Pasture Productivity

Greg McDonald (2007) Dept. of Agronomy P.O. Box 110500 Gainesville, FL 32611-0500

B.W. Mathews and J.R. Carpenter 24

Population Abundance and within Plant Distribution of Frankliniella thrips in Cotton

E.A. Osekre, D.L. Wright, and J.J. Marois 35

Samira Daroub (2008) Everglades REC - Belle Glade PO Box 111564 Belle Glade, FL 33430-4702

Modeling Shallow Groundwater Flow and Nitrate Discharge into River from an Agricultural Land ........................ Y. Ouyang 39

Use of Soil Amendments to Reduce Leaching of Nitrogen and Other Nutrients in Sandy Soil of Florida J.Y. Yang, Z.L. He, Y.G. Yang, and P.J. Stoffella 49

EDITORIAL BOARD GRADUATE STUDENT FORUM ABSTRACTS - CROPS

Co-Editors: Enhancing Turf Quality in Bahiagrass by Over-Expression of a Gibberellin Catabolizing Enzyme

Ken Boote Dept. of Agronomy P.O. Box 110500

Gainesville, FL 32611-0500 Mimi Williams

USDA-NRCS 2614 NW 43rd Street Gainesville, FL 34606-6611

The Editors express appreciation to the following individuals who assisted with review of manuscripts: S. L. Albrecht , USDA-ARS-Oregon

William Crow, Department of Entomology and Nematology

Wendy Graham, University of Florida Water Institute

Robert McGovern, Department of Entomology and Nematology

Tom Obreza, Soil and Water Science Department

Dilip Shinde, South Florida Ecosystem Office

M. Agharkar, F. Altpeter, H. Zhang, M. Gallo, K. Quesenberry, D.S. Wofford, and G.L. Miller 58

Growth and Phenology of Native Legumes in Two Light Environments .................................... S.E. Cathey and T. R. Sinclair 58

Extended Daylength and Fertilization Effects on Above- and Below-Ground Bahiagrass Mass and Chemical Composition

S.M. Interrante, L.E. Sollenberger, A.R. Blount, T.R. Sinclair, J.C.B. Dubeux, and J.M.B. Vendramini 59

Predicting Tomato Fruit Growth Dynamics in Terms of Fresh Weight and Size: A Review and Modeling Approach

M.R. Rybak, K.J. Boote, J.M.S. Scholberg, C.H. Porter, and J.W. Jones 59

Enhancing Biosafety of Transgenic Bahiagrass by Engineering Inducible Cell Death

S. Sandhu, F. Altpeter, A.S. Blount, K. Quesenberry, M. Gallo, and M. Singh 60

Plant Regeneration of Lotononis through Cotyledon Culture ................................................ M.L. Vidoz and K.H. Quesenberry 60

Preliminary Studies on the Effect of Chitosan on the Germination of Cabbage Seeds Inoculated with Xanthomonas

campestris pv campestris (Pammel) ......................................... C. Webster, K. U. Onokpise, M. Abazinge, and J. Muchovej 61

Cool-season Forage Production in Silvopastoral Systems in North Florida

S.K. Bambo, J. Nowak, A.R. Blount, A.J. Long, and R.O. Myer 61

GRADUATE STUDENT FORUM ABSTRACTS - SOILS AND ENVIRONMENTAL QUALITY

Soil Properties in Traffic and No-Traffic Areas in Golf Courses and Relationship with Goosegrass Growth

C. Arrieta, P. Busey, and S. Daroub 62

Soil Carbon Pools in Slash Pine-Based Silvopastoral Systems of Florida ..................... S.G. Haile, P.K.R. Nair, and V.D. Nair 62

Manure Components Affecting Phosphorus Stability of Dairy Manure-Amended Soils M.S. Josan, V.D. Nair, and W.G. Harris 63

Published annually by the Soil and Crop Science Society of Florida. Membership dues, including subscription to the annual Proceedings, are $30.00 per year for domestic members and $35.00 per year for foreign members. At least one author of a paper submitted for publication in the Proceedings must be an active or honorary member of the Society except for invitational papers. Ordinarily, contributions shall have been presented at annual meetings; exceptions must have approval of the Executive Committee and the Editorial Board. Contributions may be (1) papers on original research or (2) invitational papers of a philosophical or review nature presented before general assemblies or in symposia.

Reducing Phosphorus Loss from Pastureland through Silvopasture ................................. G.-A. Michel, V.D. Nair, P.K.R. Nair 63

Basis for Estimating P Source Coefficients for the Florida P Index ................ O.O. Oladeji, G. A. O’Connor, and J.B. Sartain 63

Controlling Phosphorus Loss from a Manure-Impacted Soil with Aluminum Water Treatment Residuals

T.J. Rew, D.A. Graetz, V.D. Nair, and G.A. O'Connor 64

GENERAL SESSION ABSTRACTS - SOILS

Sugarcane Plant Crop Response to Phosphorus Fertilizer in Two Locations on Organic Soils in Florida

J.M. McCray, Y. Luo, R.W. Rice, and I.V. Ezenwa 65

Application Rate of Water Treatment Residuals Based on Agro-Environmental Thresholds

O.O. Oladeji, J.B. Sartain, and G.A. O’Connor 65

Loading of Heavy Metals in Runoff Water from Citrus Groves and Vegetable Fields in the Indian River Area

Z.L. He, P.J. Stoffella, X.E. Yang, D.V. Calvert, and Y.C. Li 66

(continued on next page)

Soil-test Phosphorus Trends in Everglades Agricultural Area Histosol Profiles ..... Y. Luo, G. Kingston, R.W. Rice, and J.M. Shine, Jr. 66

Utility of Mehlich 1 and Mehlich 3 Soil Tests to Predict Citrus Tree Nutritional Status ..... T.A. Obreza, R.E. Rouse, and K.T. Morgan 67

GENERAL SESSION ABSTRACTS - CROPS

Effect of Topsin M and Karate on Square Abortion and Incidence of Hardlock Disease in Cotton

E.A. Osekre, D.L. Wright, and J. Marois 67

Chemical Composition of Soils Under Forages Grown Between Tree Rows of Loblolly Pine Trees

O.U. Onokpise, L. Whilby, and N.G. Bradley 68

Energy Fluxes and Land Surface Parameters in Grassland Ecosystems: Remote Sensing Prospective

A.M. Melesse, A. Frank, J. Hanson, M. Liebig, and V. Nangia 68

Importance of Soil Organic Matter in Florida Citrus Production ................................. A.W. Schumann, Q.U. Zaman, and K.H. Hostler 68

Soil Conditions Affect Sweet Corn and Sunnhemp Initial Growth and Root Proliferation

B.R.Morton, J.C. Linares, J.M.S. Scholberg, and K.J. Boote 69

Fertilization of Grazed Bahiagrass Pastures in South Florida ..................................................................... M.B. Adjei and J.E. Rechcigl 69

Preliminary Observations on Growth and Yield of Kenaf in Florida ............................... J.J. Ferguson, G.W. Feaster, and J.J. Sifontes 70

Efficacy of Jack Frost Foam® for Frost Protection on Vegetable and Strawberry Transplants R.J. McGovern, C.R. Semer IV, and L. Pecsenka 70

Influence of Grazing Frequency on Cynodon Grasses Grown in Peninsular Florida ............................................................... P. Mislevy 70

A Model for Sustainable Production of Habanero Peppers ............................................... G.L. Queeley, C.S. Gardner, and T.A. Hylton 71

Response of Scotch Bonnet Hot Pepper to Incremental Phosphorous Levels on a Sandy Loam Soil .... C.S. Gardner and G.L. Queeley 71

SOCIETY AFFAIRS

2006 Program Summary ...……………………………………………………………………………………………………..…………. 72 Business Meeting Minutes, 06 June 2006 ....…………………………………………..……………………………………………. 75 Board Meeting Minutes, 15 March 2006 ....…………………………………………..……………………………………………. 76

Financial Report ………………………………………………………………………………………………………………………….. 78 2007 Committees …………………………………………………………………………………………………………………………. 78 Membership Lists Regular Members 2006 ……………………………………………………………………………………………………………... 79 Honorary Life Members 2006 ………………………………………………………………………………………………………. 81 Emeritus Members 2006 ……………………………………………………………………………………………………………. 82

Subscribing Members 2006 …………………………………………………………………………………………………………. 82 Historical Record of Society Officers ……………………………………………………………………………………………………. 84 List of Honorary Life Members and Editors ……………………………………………………………………………………………... 85 List of Dedication of Proceedings ………………………………………………………………………………………………………... 86

DEDICATION OF THE SIXTY-SIXTH PROCEEDINGS SOIL AND CROP SCIENCE SOCIETY OF FLORIDA

Carroll Gene Chambliss

Carroll G. Chambliss

Dr. Carrol G. Chambliss served as President of

the Soil and Crop Science Society of Florida for 2004 and President-elect (Program Chair) for 2003. From 1988-1993, he served as Secretary-Treasurer of the Society.

Carrol Chambliss was born in Jefferson County, Arkansas on May 14, 1942. He received the B.S. (1964) and M.S. (1965) degrees in Agronomy from the University of Arkansas. He received the Ph.D. degree in Agronomy from the University of Illinois in 1969. Following the Ph.D. degree, Dr. Chambliss served the University of Illinois as an Area Agronomist from 1970-1976.

Dr. Chambliss joined the University of Florida as an Assistant Professor (Forage Extension Specialist) in the Agronomy Department in 1976, first serving at the Gulf Coast Research and Education Center in Bradenton, FL for several years before moving to the UF main campus in Gainesville in 1984. Dr. Chambliss was widely recognized for his expertise and knowledge of forage crops where he led extension and research programs that provided information to assist crop producers with the management and production of a number of forage grasses and legumes. Dr. Chambliss published numerous research and extension papers, was well-known for editing IFAS' Florida Forage Handbook, for leading the annual Forage Workers Group and

for his close working relationship with county agricultural extension agents across the state and nation. He was a leader of the South Florida Beef/Forage Agents organization and he helped to annually organize the IFAS Extension Forage and Pasture Management School. Dr. Chambliss was active in the International Grassland Congress and the American Forage and Grassland Conference, and participated in meetings of those organizations both nationally and abroad in France, New Zealand, and Brazil. He was an active member of the American Society of Agronomy, the Crop Science Society of America, the Southern Branch of the American Society of Agronomy, the Florida Agricultural Extension Agents Professional Association, and the honorary agricultural societies of Gamma Sigma Delta and Alpha Zeta. Dr. Chambliss was Chairman of the Southern Pasture and Forage Improvement Conference in 2005.

Dr. Chambliss was an Associate Professor in the Agronomy Department at the University of Florida when he passed away on April 23, 2005 at the age of 62. His expertise in forage crop management was widely sought by growers and extension personnel in Florida. Dr. Chambliss served the University of Florida with distinction for 29 years.

Proceedings, Volume 66, 2007 1

GENERAL SESSION PAPERS

Response of Tropical Grasses to Nitrogen Sources of Fertilizer

Martin B. Adjei and J.E. Rechcigl*

ABSTRACT

Field experiments were conducted at two sites, on ‘Argentine’ bahiagrass (Paspalum notatum) and ‘Floralta’ limpograss (Hemarthria altissima), to compare the effects of four types of N-fertilizer sources on forage production and nutritive value. The bahiagrass experiment consisted of one spring application of 67 kg N ha-1 while the limpograss experiment had both a spring and fall application of 67 kg N ha-1 each (total of 134 kg N ha-1 yr-1). For both grass types, the N was supplied from 1) ammonium nitrate, 2) ammonium nitrate + elemental S, 3) ammonium sulfate, or 4) calcium nitrate and the effect of N fertilization was compared to a control (no fertilizer). Bahiagrass annual forage dry matter yield (DMY) varied inconsistently among N-sources between sites. Limpograss DMY was consistently highest when ammonium sulfate was applied compared to the other N-sources. Generally, forage crude protein (CP) and in vitro organic matter digestion (IVOMD) were either unaffected or improved equally by all N sources over the control. Bahiagrass tissue S concentration averaged 2.4 and 3.2 g kg-1 depending on site, but was not affected by N-source, while hemarthria tissue S increased from 1.7 to 2.3 g kg-1 at one site in response to S inclusion in the N-fertilizer. Addition of S or Ca to N-fertilizer has little effect on performance of grazed bahiagrass pasture. However, S inclusion did enhance hemarthria forage production.

INTRODUCTION

Bahiagrass is the primary forage grass grown and grazed on Florida spodosols, however limpograss is increasingly stockpiled as standing hay for winter grazing. Pasture fertilization is one of the most expensive operating costs in the cow-calf business and N is usually the major limiting nutrient to pasture production in Florida.

Although extractable soil S is generally low (< 6 ppm) throughout the profile of most Florida spodosols, Mitchell and Blue (1981) showed that total S was highly correlated with organic C (r= 0.89) and total N (r= 0.95) in the surface horizons of these soils. Although S deficiencies in bahiagrass for these low-S soils are not common, high rates of N fertilization, use of refined fertilizers that are low in S, and intensive management of this crop for hay could deplete soil-available S and result in decreased yields or forage quality. Mitchell and Blue (1989) observed that at low N rate, a bahiagrass DMY response to

M.B. Adjei (deceased), Univ. of Florida Range Cattle Res. And Educ. Center, Ona, FL 33865 and J.E. Rechcigl, Univ. of Florida, Gulf Coast Res. and Educ. Center, Balm, FL 33598. This work was sponsored by Honeywell Fertilizer Company and the Univ. of Florida, Agric. Exp. Stn.

*Corresponding author ([email protected]). Contribution published in Soil Crop Sci. Soc. Florida Proc. 66:1-6 (2007).

S did not occur until the fourth year of the study when previously accumulated S in the stolon-root system became exhausted. Mitchell and Blue (1989) suggested a critical S concentration in bahiagrass tissue of 1.6 g kg-1 below which a yield response to applied S should be expected. Rechcigl (1991) compared ammonium nitrate with ammonium sulfate to bahiagrass providing 67 kg N ha-1 yr-1 over 3 yr and obtained a 10% greater yield from the ammonium sulfate (3360 vs. 3051 kg ha-1). The ammonium sulfate supplied 86 kg S ha-1 and raised bahiagrass tissue concentrations from 1.0 (for ammonium nitrate) to 2.2 g kg-1. Kalmbacher et al. (2005) evaluated a factorial combination of four levels of N (0-252 kg ha-1) and four levels of S (0-280 kg ha-1) and concluded that with the usual application of only 56 to 67 kg N ha-1 yr-1 on ranches, fertilization with S is unnecessary on older bahiagrass pasture if forage tissue S concentrations exceed 1.6 g kg-1. In contrast to bahiagrass, little is known about the response of limpograss to different nitrogen sources or sulfur application. Also claims of better forage yield response to other N sources such as calcium nitrate needed further investigation.

The primary objectives of the present study were to 1) compare the response of grazed bahiagrass pastures to available N fertilizer sources and 2) study the effect of N sources on limpograss (hemarthria) forage that was cut for hay.

MATERIALS AND METHODS

Each year (2003, 2004), four fertilizer treatments 1) ammonium nitrate (AN), 2) ammonium nitrate + elemental sulfur (AN + S), 3) ammonium sulfate (AS), and 4) calcium nitrate (CN) were applied once each year in May to supply 67 kg N ha-1 to Argentine bahiagrass pasture on Stokes Ranch in Lake Wales, FL (hereafter called Polk Co. site) and to a similar pasture on Butler Oak Dairy in Okeechobee, FL (hereafter called Okeechobee Co. site). A no-fertilizer control (Cont) was used as a check on each site and there were three replicates of each treatment per site arranged in a RCB design. Each plot was 6.08 by 6.08 m. The bahiagrass pasture on Stokes Ranch had a history of sludge application until 2 yr before the trial, and the pasture on Butler Oak Dairy was grazed by dairy replacement heifers supplemented with concentrates. These pastures were selected based on their initial low

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2 Soil and Crop Science Society of Florida

tissue S (<1.6 g S kg-1) status. Metal cages (1 m2) were used to protect forage regrowth on bahiagrass plots and cages were moved to a new cleaned (7.5 cm stubble) location on a plot after each of the six annual harvests. Bahiagrass forage regrowth was harvested repeatedly at approximately 30-d intervals. Harvest dates for bahiagrass in Polk Co. were 2 Jun., 1 Jul., 31 Jul., 2 Sep., 30 Sep., and 29 Oct. in 2003 and 16 Jun., 16 Jul., 12 Aug., 20 Sep., 15 Oct., and 29 Nov. in 2004. Harvest dates for bahiagrass in Okeechobee Co. were 18 Jun., 24 Jul., 22 Aug., 23 Sep., 22 Oct., and 21 Nov. in 2003 and 18 Jun., 19 Jul., 20 Aug., 24 Sep., and 4 Nov. in 2004.

The same four N-source treatments and a check were applied in May and September (67 kg N ha-1 per application) to non-grazed Floralta limpograss plots at the Range Cattle REC, Ona in Hardee Co. (hereafter called Hardee site) and at Butler Oak Dairy in Okeechobee Co (hereafter called Okeechobee site). Limpograss plots were initially harvested at ~ 30-d intervals in 2003 at both sites but this was modified to 35-45 d intervals after the third harvest in 2003 to improve stand recovery and persistence. In 2004, limpograss was harvested at irregular intervals due to interference from hurricanes. Limpograss harvest dates at the Hardee Co. site were 4 Jun., 2 Jul., 4 Aug., 1 Oct., and 18 Nov. in 2003 and 15 Jun., 21 Aug., and 2 Nov. in 2004. Limpograss harvest dates for the Okeechobee Co. site were 18 Jun., 24 Jul., 21 Aug., 2 Oct., and 8 Dec. in 2003 and 9 Jul., 6 Oct., and 9 Dec. in 2004.

Sub-samples of all harvested forage were weighed and dried at 60 oC to constant weight for DMY determination. Dried samples were ground and analyzed for CP (Gallaher et al., 1976; Hambleton, 1977), IVOMD (Moore and Mott, 1974) and tissue mineral composition.

Data for DMY, CP, IVOMD and tissue minerals were statistically analyzed by PROC MIXED procedure with treatment, year and harvest dates as main effect, split, and in time, respectively, and rep x treatment, rep x treatment x year and residual as random effects. Significant treatment means (P<0.05) were separated according to the P-diff option.

RESULTS AND DISCUSSION

Site Description

The initial soil pH ranged from 4.8 on the limpograss field at the Hardee Co. site to 6.9 on the bahiagrass field in Polk Co. (Table 1). Likewise, the initial P was high and K was medium at the Polk bahiagrass site. The initial high pH and nutrient status on Polk site was probably due to previous use of lime-stabilized biosolids for pasture fertilization. The decision to select sites, however, was based primarily on grass tissue S being near the deficiency range (<1.6 g S kg-1 DM) (Table 1).

Table 1. The initial soil pH, soil P and K, and grass tissue S concentrations at experimental sites. Location Grass Soil pH Soil P Soil K Tissue S (mg kg-1) (mg kg-1) (g kg-1)

Polk Bahiagrass 6.9 50 20 1.5 Okeechobee Bahiagrass 5.2 6 40 1.3 Hardee Limpograss 4.8 11 13 1.4 Okeechobee Limpograss 5.1 13 12 1.0

Following N-source application and repeated harvesting in 2003, the soil pH in Okeechobee and Hardee Co. fields declined below the target pH of 5.0, especially under the S containing fertilizer treatments (Table 2). Dolomitic lime was applied uniformly to all plots at those locations at the rate of 2.24 Mg ha-1 before the 2004 season.

Table 2. Changes in soil pH as influenced by fertilizer N source following 1 year of application.

Site

Bahiagrass Limpograss Polk Okeechobee Hardee Okeechobee

Initial 6.9 5.2 4.8 5.1 AN 6.9 a1 5.1 ab 4.5 abc 5.0 a AN + S 6.9 a 4.9 b 4.2 c 4.3 b AS 6.7 a 4.8 b 4.3 bc 4.7 ab CN 6.9 a 5.0 ab 4.7 ab 4.8 ab Cont 6.9 a 5.2 a 4.8 a 4.8 ab

Dry Matter Yield

Bahiagrass

There was no interaction (P > 0.12) between N fertilizer source and harvest date on bahiagrass DMY at any of the sites in either 2003 or 2004. In 2003, bahiagrass DMY was greatest for the AS and CN sources in Polk Co., but these yields were only greater than the DMY for the AN source (Fig. 1). For that same year, bahiagrass seasonal DMY from 6 harvests in Okeechobee Co. averaged 16 Mg ha-1 for all treatments except for the AN + S source which yielded ~ 20 Mg ha-1 (Fig. 1). In 2004, DMY was greater for the AN + S and AS treatments than the control in Polk Co. (Fig. 2), whereas seasonal yield from 5 harvests for bahiagrass in Okeechobee Co. was 10.5 Mg ha-1, regardless of treatment (including the control). Several factors could account for the lack of DMY response to N sources on grazed bahiagrass pastures. Due to storage of nutrients in the stolon-root system (Mitchell and Blue, 1989) the single dose of only 67 kg N ha-1 was probably inadequate to stimulate a synergistic response from the other nutrients such as Ca and S (Kalmbacher et al., 2005). Additionally, there was probably recycling of N from cattle manure at both locations and uniform redistribution of nutrients across plot boundaries from hurricane floods in 2004 which would confound the N treatment effects.


Figure 1. The effect of fertilizer N source on bahiagrass DMY at two sites in central Florida in 2003.

Figure 2. The effect of fertilizer N source on bahiagrass DMY in Polk County in 2004.

Limpograss

Unlike the situation for bahiagrass, the interaction between harvest date and N-source for limpograss DMY was highly significant (P < 0.001) in 2003. Treatments were applied in early May and September and DMY immediately following N-source application (June and October harvests) were significantly impacted by treatments at both locations. Limpograss DMY was always greatest for the AS treatment immediately after fertilization in 2003, regardless of site (Figs. 3 and 4). The yield from AS source was greater than all the other N-sources for the October 2003 harvest, regardless of site (Figs. 3 and 4) and greater than all the other N-sources except for the CN source in the June 2003 harvest. Additionally, the other N-source treatments produced more DMY than the control in the immediate post-application harvests. Each of the intervening harvests (harvests not preceded by fertilization) gave relatively lower yield as fertilizer effects waned and the sum for the two intervening

Figure 3. The interactive effect of N-source and harvest date on limpograss DMY in Hardee Co. in 2003.

Figure 4. The interactive effect of N-source and harvest date on limpograss DMY in Hardee Co. in 2004.

harvests showed little differences among N sources in 2003 (Figs. 3 and 4). The exceptionally low 2003 intervening yield for the AN+S treatment in Okeechobee (Fig. 4) could not be explained.

In 2004, the third harvest of limpograss was delayed till late November in Hardee Co. and early December in Okeechobee Co. due to interruptions from hurricanes. Notwithstanding the hurricanes, the interaction between N-source and harvest date was observed for the three limpograss harvests in Hardee Co. (Fig. 5) but not for the harvests from Okeechobee Co. (Fig. 6). In Hardee Co., the S-containing fertilizers produced more limpograss hay for the June and November 2004 harvests that followed N-fertilization, but all N-sources gave similar but greater yield than the control for the August harvest at that site (Fig. 5). Due to severe flooding at the Okeechobee Co. site, we observed differences in total limpograss yield between the N-sources and the control treatment in 2004 except with the AS treatment (Fig. 6).

Polk Okeechobee 4.0 Oct harvest Sum of 2 other harvests a a

~ 24

"' 22 .<= bl) 20 ~ 18 :!if 16 4) 14 ·;;. 12

a

b b b b ab a a

ab b

3.5 June harvest

" -= 3.0 b b b .. ~ b ab !!'

2.5 b b QI

2.0 ·;;. ... 10 4)

t: 8 "' 6 E > 4 c 2

0

.; 1.5 t:

"' E 1.0 ~

C 0.5

0.0 ~~~~{-, ~c, c~rf''- ~~ ~•', ~',(,,~ (,,O~\

~

N Source N Source

5.5 June harvest Oct harvest Sum of 2 other harvests 14 a a ~ 5.0

"' 13 a a .<= b ~ 4.5

bl) 12 -= b b b ~ .. 4.0 ab 11 ~ :!i ·ti

3.5 b 10 b b GI .; 3.0

'> 9 ·;;. 2.5 ~ ...

8 QI GI t: 2.0 t: "' "' 7 E 1.5 E > > 6 c 1.0 ... 5 0.5 0

\"'~ \"'~.,,':, l"'s cf ~o(''I. 0.0

~~ ~ ·', ~', (,,~(,,O~\ ~~~•', ~ (,,~ (,,O~\ ~~~•', ~',(,,~(,,O~\ ~ ~ ~

N Source N Source


Table 3. The interaction between harvest date and N-source on bahiagrass forage crude protein concentration at Okeechobee, FL site in 2004.

Figure 5. The interactive effect of N-source and harvest date on limpograss DMY in Okeechobee Co. in 2003.

Figure 6. The effect of N-source on total limpograss DMY in Okeechobee Co. in 2004.

Forage Quality

Bahiagrass

In 2003, crude protein concentration in bahiagrass forage changed (P < 0.001) from 162 g kg-1 in the harvest immediately following spring fertilization to 94 g kg-1 in

the late-summer harvest at the Polk Co. site and correspondingly from 141 to 89 g kg-1 at the Okeechobee Co. site, but there were no fertilizer treatment effects at either location. Seasonal mean 2003 forage CP for treatments was 125 and 107 g kg-1 for Polk Co. and Okeechobee Co. sites, respectively. In 2004, bahiagrass forage CP among harvests ranged from 191 to 90 g kg-1 at Polk Co. site with a treatment seasonal mean of 120 g kg-1. At the Okeechobee Co. site in 2004, bahiagrass forage CP declined from 155 g kg-1 in early summer to 97 g kg-1 in late-summer and increased to 134 g kg-1 in the fall. Nitrogen-fertilized bahiagrass forage had a greater mean forage CP than the control treatment (122 vs. 110 g kg-1) at the Okeechobee site in 2004 primarily because of differences recorded among treatments in the early-summer and fall seasons (Table 3). The control treatment also had a high forage CP in the fall because of reduced yield and DM dilution. Crude protein concentration and IVOMD reported for bahiagrass in this study are within normal range (Blue, 1970; Sumner et al., 1991) and the general lack of yield and quality response of Bahia grass response to sources and timing of N-fertilization is well known. This tendency in part could be attributed to its capacity to store nutrients in the stolon root system for latter use (Blue 1973). Mean 2003 bahiagrass tissue mineral concentrations including S were within normal range and not affected by N-source treatments (Table 4).

Limpograss

Crude protein concentration in limpograss forage was generally low ranging from 66 to 93 g kg-1 by harvest in Hardee Co. and 62 to 78 g kg-1 in Okeechobee Co. during the 2003 season. Corresponding CP ranges by harvest date for the 2004 season were 58 to 85 g kg-1 and 52 to 102 g kg-1, respectively. There was no treatment effect on limpograss CP at the Hardee Co. site in either year and seasonal limpograss CP concentration across treatments

N source

Harvest 1 (6-18-04)

Harvest 2 (7-19-04)

Harvest 3 (8-20-04)

Harvest 4 (9-24-04)

Harvest 5 (11-4-04)

Mean

----------------------------------- Crude protein, g kg-1 ------------------------------------ AN 152 b1 108 a 97 a 108 a 135 a 120 AN + S 162 b 102 a 94 a 104 a 142 a 121 AS 170 a 110 a 103 a 108 a 122 b 123 CN 174 a 110 a 96 a 103 a 126 b 122 Control 115 c 100 a 94 a 101 a 142 a 110 Mean 155 107 97 105 134 1Values in a column followed by the same letter are not different (P < 0.05) according to the P-diff mean separation. Table 4. Mean 2003 bahiagrass and limpograss tissue mineral concentrations following N-source application in central Florida. Site P K Ca Mg S Fe ------------------------------------------- g kg-1 ------------------------------------------- mg kg-1

Bahiagrass site Polk 3.4 9.4 6.6 3.3 3.2 156 Okeechobee 2.0 18.0 3.3 3.4 2.4 118 Limpograss site Hardee 1.5† 6.0 3.2 2.1 1.5 133 Okeechobee 1.5 6.1 9.3 2.9† 2.0† 96 † Significant treatment effects are shown in Table 6.

12 ~ 11 ,:;: a tl0 ~ 10 "O 9 ai '> 8 ... .,

7 t: "' E 6 > c 5

I>-~ 1--~"" 1--" (,~ e,o(:o.'I.

N Source

4 .0 June November a

3.5 b a 1, .r. 3.0 b ab .. ~

2.5 Augu$t :i!' ..

2.0 b a -► a - a d .. 1.5 Ii

E 1.0 C

~ C

0 .5

0.0 ~·\,:).,•" ~ c,,:).e,o~' ~t,:).•c, ~ c,,:). c,o~'- ~,:). ~ •" ~ <,,:). e,o~'-

N Source


Table 5. The effect of N-source treatments on limpograss forage crude protein and in vitro organic matter digestion in central Florida in 2003 and 2004 seasons. N source

Hardee Co. Okeechobee Co. 2003

IVOMD 2004

IVOMD Harvest 1 2003 CP

2004 CP

2004 IVOMD

----------------------------------------------------------------------- g kg-1 --------------------------------------------------------------- AN 534 ab1 588 ab 65 bc 79 a 572 a AN + S 526 abc 594 a 78 a 80 a 554 a AS 543 a 590 ab 74 ab 80 a 560 a CN 518 c 596 a 67 bc 72 a 562 a Control 505 c 548 b 60 c 59 b 519 b 1Values in a column followed by the same letter are not different (P < 0.05) according to the P-diff mean separation.

averaged 75 g kg-1 each year in Hardee Co (data not shown). In contrast, treatment differences were observed for seasonal forage CP in Okeechobee Co. in both years (Table 5). The S-containing fertilizer sources produced the greatest seasonal mean CP concentration in forage in both years which was always better than CP for the control treatment in Okeechobee Co. (Table 5). Our data showing that whole plant limpograss forage was low in CP concentration for cattle, especially during the summer and fall seasons; this concurs with findings of Ruelke and Quesenberry (1983), Sollenberger et al. (1987), Rusland et al. (1988), and Adjei et al. (1998, 2001), however, the differential yield and CP response to N-sources is new information.

In vitro organic matter digestion of limpograss forage was always good and ranged between 500 and 600 g kg-1

by harvest each year. Good forage digestibility of Hemarthria spp. is an inherent attribute of that species which led to its release in the first place (Quesenberry et al., 1978) and this has since been confirmed by several other studies (Quesenberry and Ocumpaugh, 1980; Adjei et al., 1988; Rusland et al., 1988). The application of N fertilizer tended to improve forage IVOMD over the unfertilized control (Table 5) except in 2003 at the Okeechobee Co. site where observed seasonal mean IVOMD was 548 g kg-1 for all treatments (including the control). In 2004, the effect of treatments on limpograss forage IVOMD at Hardee Co. site was significant only for the first harvest after early-summer fertilization (Table 5). The mean forage IVOMD for the remaining four harvests in Hardee Co. that year was 570 g kg-1.

Seasonal mean 2003 tissue P concentration in limpograss (Table 4), although improved by the application of AS fertilizer (Table 6), was still low (< 2.0 g kg-1). The increase in tissue S with the application of AS (Table 6) was below the cattle toxicity range. Table 6. The effect of N-source on limpograss tissue P, S and Mg concentrations in central Florida. Hardee Co. Okeechobee P S Mg N-Source ------------------------ g kg-1 ------------------------------- AN 1.4 b† 1.7 b 2.9 bc AN + S 1.6 a 2.3 a 3.4 a AS 1.5 ab 2.3 a 3.2 ab CN 1.5 ab 1.8 b 2.7 c Cont. 1.4 b 1.8 b 2.5 c †Values in a column followed by the same letter are not different (P < 0.05) according to the P-diff mean separation.

CONCLUSIONS

As expected, bahiagrass DMY under grazing conditions showed a general lack of or inconsistent response to N-sources and forage CP was improved with N application compared to the unfertilized control only in one out of the four trials on bahiagrass. Conversely, the DMY of hay and CP concentration in limpograss forage consistently was increased immediately following the application of S-containing, N-source fertilizers such as ammonium sulfate. However, ammonium nitrate and calcium nitrate were less acidifying N-source alternatives and may show less frequent need for lime application. The underlying factor behind the differential forage specie response to fertilizers appears to be variation in rooting system.

REFERENCES

Adjei, M.B., P. Mislevy, K.H. Quesenberry, and W.R. Ocumpaugh. 1988. Grazing frequency effects on forage production, quality, persistence and crown total nonstructural carbohydrate reserves of limpograsses. Soil Crop Sci. Soc. Florida Proc. 47:233-236.

Adjei, M.B., J.E. Rechcigl, and R.S. Kalmbacher. 1998. Fertilization effects on the yield and chemical composition of Limpograss pasture. Soil Crop Sci. Soc. Florida Proc. 57:66-73.

Adjei, M.B., R.S. Kalmbacher, and J.E. Rechcigl. 2001. Effect of P and K fertilizer on forage yield and nutritive value of Floralta limpograss. Soil Crop Sci. Soc. Florida Proc. 60:9-14.

Blue, W.G. 1970. Fertilizer nitrogen uptake by Pensacola bahiagrass from Leon fine sand, a Spodosol. p. 389-392. In Proc. XI Int. Grassland Congr. Surfers Paradise, Queensland Australia.

Blue, W.G. 1973. The role of Pensacola bahiagrass (Paspalum notatum Flugge) stolon-root system in fertilizer nitrogen utilization on Leon fine sand. Agron. J. 65-88-91.

Blue, W.G. 1974. Efficiency of five nitrogen sources for Pensacola bahiagrass on Leon fine sand as affected by lime treatments. Soil Crop Sci. Soc. Florida Proc.33:126-132.


Gallaher, R.N., G.O. Weldon, and F.C. Boswell. 1976. A semi-automated procedure for total nitrogen in plant and soil samples. Soil Sci. Soc. Am. Proc. 40:887-889.

Hambleton, L.G. 1977. Semiautomated method for simultaneous determination of phosphorus, calcium and crude protein in animal feeds. J. Assoc. Off. Anal. Chem. 60:845-854.

Kalmbacher, R.S, I.V. Ezenwa, J.D. Arthington, and F.G. Martin. 2005. Sulfur fertilization of bahiagrass with varying levels of nitrogen fertilization on a Florida spodosol. Agron. J. 97:661-667.

Mitchell, C.C., Jr., and W.G. Blue. 1981. The sulfur status of Florida soils I. Sulfur distribution in Spodosols, Entisols, and Ultisols. Soil Crop Sci. Soc. Florida Proc. 40:71-76.

Mitchell, C.C., Jr., and W.G. Blue. 1989. Bahiagrass response to sulfur on an Aeric Haplaquod. Agron. J. 81:53-57.

Moore, J.E., and G.O. Mott. 1974. Recovery of residual organic matter from in vitro digestion of forages. J. Dairy Sci. 57:1258-1259.

Quesenberry, K.H., L.S. Dunavin, E.M. Hodges, G.B. Killinger, A.E. Kretschmer, Jr., W.R. Ocumpaugh, R.D. Roush, O.C. Ruelke, S.C. Schank, D.C. Smith, G.H. Snyder, and R.L. Stanley. 1978. Redalta, Greenalta and Bigalta limpograss Hemarthria altissima, promising forages for Florida. Bull 802. Florida Agric. Exp. Stn., Univ. of Florida, Gainesville.

Quesenberry, K.H., and W.R. Ocumpaugh. 1980. Crude protein, IVOMD, and yield of stockpiled limpograss. Agron. J. 72:1021-1024.

Rechcigl, J.E. 1991. Sulfur fertilization improves bahiagrass pastures. Better Crops with Plant Food. 75 (4):22-24.

Ruelke, O.C., and K.H. Quesenberry. 1983. Effects of fertilization timing on the yields, seasonal distribution, and quality of limpograss forage. Soil Crop Sci. Soc. Florida Proc. 42:132-136.

Rusland, G.A., L.E. Sollenberger, K.A. Albrecht, C.S. Jones, Jr., and I.V. Crowder. 1988. Animal performance on limpograss-aeschynomene and nitrogen fertilized limpograss pastures. Agron. J. 80:957-962.

Sollenberger, L.E., K.H. Quesenberry, and J.E. Moore. 1987. Forage quality responses of an aeschynomene-limpograss association to grazing management. Agron J. 79:83-88.

Sumner, S., W. Wade, J. Selph, J. Southwell, V. Hoge, P. Hogue, E. Jennings, P. Miller, and T. Seawright. 1991. Fertilization of established bahiagrass pasture in Florida. Circ. 916. Florida Agric. Exp. Stn., Univ. of Florida, Gainesville.


Carbon Balance of Sugarcane Agriculture on Histosols of the Everglades Agricultural Area: Review, Analysis, and Global Energy Perspectives

Leon Hartwell Allen, Jr.*

ABSTRACT

Biofuels production from crops and cellulosic by-products has received much attention recently. Sugarcane (Saccharum spp.) derivatives supply about 16% of the energy for Brazil. Most sugarcane production in Florida is on drained Histosols (organic soils) of the Everglades Agricultural Area (EAA). Subsidence, due primarily to microbial oxidation, with release of carbon dioxide (CO2) to the atmosphere, has been occurring on these soils since drainage began in the early 1900s. The purpose of this paper is to analyze the carbon (C) balance of sugarcane production in the EAA, and to expand this C balance to some global perspectives. Several questions are addressed. How much C is released annually from microbial oxidation of drained EAA Histosols? How does the C content of sugarcane biomass yields compare with the C of oxidative subsidence? If utilized directly for fuel, how many days of global energy supply do the EAA Histosols represent? How does C released from oxidative subsidence in the EAA compare with global fossil fuel C releases to the atmosphere? Using selected soil properties and EAA subsidence rates of 2.54 cm y-1, the annual efflux would be 25,400 kg C ha-1 y-1, a plant biomass equivalent of 63,500 kg ha-1 y-1. An estimated EAA area of 240,000 ha gives 6.1 x 1012 g C y-1 released as CO2. The global release of C from fossil fuel burning during the 1990’s was about 6.4 x 1015 g C y-1. Hence, EAA oxidative subsidence represented about 0.095% of this rate. The volume of EAA Histosol required to supply 1-year’s global energy use would be 64 x 109 m3 or 64 km3, which would require a depth of 26.7 m. With an average Histosol depth of 0.84 m remaining, the EAA has enough organic soil, if burned as fuel, to supply global energy needs for only 11 ½ days. With EAA average sugar yields of 9,100 kg ha-1 y-1, subsidence C losses would be 7.0 times that of sugar yield C (63,500/9,100). Accounting for C fixed in bagasse, unharvested aboveground biomass, and belowground biomass increases biomass to 33,600 kg ha-1 y-1, and 63,500/33,600 = 1.9. However, implementing high watertable culture to decrease Histosol subsidence rates might make sugarcane production C-neutral or even provide a net gain of C. Carbon balance offers a way for determining if a production system represents a net loss or gain of C, which could be applied to any agricultural production system.

INTRODUCTION

High prices of gasoline at the pump during 2006-2008 have intensified awareness of the American public on the dependence of the USA on oil supplies from other nations. Alternative energy sources are possible such as wind, solar, tidal, nuclear fission, nuclear fusion (possibly), coal and coal gasification, methane hydrates, and biomass-derived energy that includes ethanol (including cellulosic ethanol), methanol, methane biogas, biodiesel, biomass gasification, catalytic metathesis of organic matter to n- alkanes, and direct burning. Hydrogen fuel is not a

L.H. Allen, Jr., Soil Scientist, USDA, ARS, South Atlantic Area, Center for Medical, Agricultural, and Veterinary Entomology (CMAVE), Chemistry Research Unit, 1700 SW 23rd Drive, Gainesville, FL 32608, and Courtesy Prof., Agronomy Department, University of Florida. This research was supported in part by the Florida Agricultural Experiment Station.

*Corresponding author ([email protected]). Peer reviewed and Refereed contribution published in Soil Crop Sci Soc. Florida Proc. 66:7-14 (2007).

primary source of energy, but it is a manufactured fuel that would require energy inputs from another source.

Proposed sources of bioenergy include biofuels (biodiesel, ethanol, methanol, biogases) from primary or secondary waste products, and from direct utilization (burning) of waste products. Sugarcane is one of a number of crops that has been proposed as a bioenergy--biofuel crop for Florida. In Brazil, ethanol production from sugarcane represents a large fraction (about 44% in 2007) of automotive fuels and about 16% of the total energy supply of that country (http://www.thebioenergysite.com/articles/118/brazil-biofuels-ethanol-annual-report-2008.). In 2007, petroleum and derivatives represented 36.7% of the total Petroleum Equivalents, and sugarcane derivatives represented 16.0% of the total Petroleum Equivalents.

Sugarcane in Florida is produced primarily in the Everglades Agricultural Area (EAA) on Histosols that are subject to subsidence (Stephens and Johnson, 1951; Stephens and Stewart, 1976; Stephens et al., 1984; Snyder, 2005). When Histosols are initially drained, subsidence may be due to in part to shrinkage and compaction. Later annual rates of subsidence are directly related mostly to depth to water table which exposes Histosols to microbial oxidation and to temperature which governs biological activity (Stephens and Stewart, 1976; Snyder, 2005). Sugarcane is also produced on mineral soils in Florida, but the area is smaller and yields have generally been lower (Obreza et al., 1998).

More than 55 years ago, Stephens and Johnson (1951), using linear extrapolations, predicted that the most of the organic soils of the EAA would have subsided by about 2000 to the point that agriculture would not be practical. Between 1924 and 1967, the average subsidence rates were 2.84 cm yr-1 based on soil elevations at the “subsidence post” at the University of Florida Research and Education Center at Belle Glade (Snyder 2005). Based on measurements in 1978, subsidence rates of soils of the EAA were about 2.54 cm per year (Shih et al., 1979). However, after 1978, subsidence rates have been about 1.45 cm per year (Shih et al., 1998). Also, Snyder (2005) reported that that the average subsidence rate at the “subsidence post” was 1.47 cm yr-1 during the period 1967-2003, and subsidence rates might be even lower now.

Subsidence of EAA Histosols is mainly related to microbial activity (Tate, 1979; Tate, 1980; Tate and Terry, 1980; Duxburry and Tate, 1981) which results in evolution of carbon dioxide (CO2) to the atmosphere (Knipling et al,


http://www.thebioenergysite.com/articles/118/brazil-biofuels-ethanol-annual-report-2008�

http://www.thebioenergysite.com/articles/118/brazil-biofuels-ethanol-annual-report-2008�


1971; Volk, 1973; Duxbury and Tate, 1981) depending on soil moisture and temperature. Thus, CO2 emissions due to microbial oxidative subsidence of Histosols have a contributing role in the global carbon cycle (Armentano, 1980).

The objectives of this review and analysis are to address several key questions. How much carbon is released annually from microbial oxidative subsidence of drained Histosols in the EAA? How does the carbon content of sugarcane yield in the EAA compare with the carbon of microbial oxidative subsidence? How do annual emissions of carbon to the atmosphere from the EAA compare with total global carbon emissions? If utilized for fuel, how many days of global energy supply does the EAA represent? Background information and calculations supporting the analyses are provided in Appendix 1.

METHODS

First, I computed the mass of carbon lost per year via oxidative subsidence of EAA Histosol, and then the plant production biomass equivalent of this amount of carbon. There are a number of assumptions and caveats, and potentially alternate methods of calculation. These calculations would be modified somewhat if other values were selected for rates of microbial oxidative subsidence, physical and organic properties of the Histosols, and sugarcane yields of sugar, bagasse, aboveground residues, and belowground biomass.

Soil properties of Histosols can vary widely with soil type, mineral content, and depth in the soil profile (Knipling et al., 1971; Volk, 1973; Duxbury and Tate, 1981; Armentano, 1980). Nevertheless, the following information of soil properties from various sources was used in subsequent calculations: EAA Histosol bulk density of 0.23 g cm-3, percent organic matter (OM) of 87%, and percent carbon (C) of Histosol OM as 50%, then the mass of C per unit volume of soil would be (0.23 g cm-

3 X 0.87 fraction OM X 0.50 fraction C in OM) = 0.100 g C cm-3. For each 1 cm y-1 of annual subsidence this would represent an annual efflux of 0.100 g C cm-2 y-1 or 10,000 kg C ha-1 y-1. This carbon emission rate is similar to the value of 11,000 kg C ha-1 y-1 for each 1 cm depth of Histosol subsidence calculated by Tate (1980) using similar parameters. Further, assuming EAA Histosol historical subsidence rates of 2.54 cm y-1, the annual efflux of carbon would be 0.254 g C cm-2 y-1 which translates to 25,400 kg C ha-1 y-1. Using an estimated area of 240,000 ha for the EAA in Palm Beach County derived from (Snyder, 2005), although other estimates of total EAA are as high as 300,000 ha (Stephens and Johnson, 1951), gives 6.1 x 1012 g C y-1 of carbon released to the atmosphere as CO2. The global release of carbon from fossil fuel burning during the 1990’s was about 6.4 x 1015 g C y-1 (IPCC, 2001) so the release of C by EAA microbial oxidative subsidence represents about 0.00095 times the amount (0.095%) of carbon released annually by fossil fuel

burning during this period. For an earlier time with lower fossil fuel usage and a slightly larger land area, Armentano (1980) estimated that the annual C release from the EAA was about 0.18% of the C released by fossil fuel combustion.

RESULTS

Biomass production resulting from the photosynthetic processes of the sugarcane plant consists of (1) sugar, i.e. sucrose, the commercially harvested product, (2) stem cellulosic fiber or bagasse, (3) field aboveground residues that are mostly leaves and tops sometimes called “trash” plus stubble), and (4) belowground components of roots, rhizomes, and buried stems. The biomass production of each of these components was estimated as follows:

Average Florida EAA sugar yield during 1980-2005 calculated from USDA-Economic Research Service data (www.ers.usda.gov/Briefing/Sugar/data/) was 9,100 kg ha-

1 y-1. Using a plant biomass organic matter CH2O-to-C molecular weight (MW) ratio (MW CH2O/MW C = 30/12) of 2.5, multiplied by 25,400 kg C ha-1 y-1, leads to 63,500 kg biomass ha-1 y-1, which is the plant biomass CH2O equivalent to carbon lost by subsidence per year at the 2.54 cm y-1 subsidence rate. The ratio of the plant biomass equivalent of carbon lost in annual oxidative subsidence to sugar yield would be 63,500 (biomass equivalent C)/9,100 (sugar) = 7.0. Thus, the carbon equivalent, or biomass equivalent, average oxidative subsidence losses of EAA Histosol of 2.54 cm y-1 would be about 7.0 times greater than average sugar yield. However, if current annual oxidative subsidence losses are less (e.g., 1.45 cm y-1) then the carbon equivalent would be less, only 4.0 times the annual sugar yield.

From data of Barry Glaz (personal communication, 2006), the estimated fiber yields are 7,900 kg ha-1 y-1, which when added to estimated sugar yields (9,100 kg ha-1 y-1) gives 17,000 kg ha-1 y-1 of “harvested” aboveground biomass. Inman-Bamber et al. (2002) reported that sucrose yield to dry stalk yield of sugarcane could be as high as 0.55 g sucrose g-1 dry stalk yield of sucrose plus bagasse. For a sucrose yield of 9,100 kg ha-1 y-1 this computes to a bagasse yield of 7,445 kg ha-1 y-1 which is similar to the estimates of Barry Glaz. Using 17,000 kg ha-1 y-1, the ratio of biomass equivalent (or carbon equivalent) of oxidative subsidence loss to harvested biomass is 63,500/17,000 = 3.7. Thus, subsidence losses of 2.54 cm y-1 would be 3.7 times harvested yield. However, with the most recently measured microbial oxidative subsidence rates of 1.45 cm y-1, the ratio of oxidative subsidence loss to harvested production would be 2.1.

Estimates of recoverable aboveground biomass residues (trash) information were provided by Barney Eiland (personal communication, 2006). Eiland’s data for recoverable aboveground biomass residues indicated


11,000 kg ha-1 y-1 after harvesting sugarcane without burning the sugarcane field beforehand. Adding this amount to the sugar plus bagasse gives a biomass total of 28,000 kg ha-1 y-1. Then the biomass equivalent oxidative subsidence to harvested biomass plus recoverable aboveground biomass ratio would be 63,500 /28,000 = 2.3. Thus, subsidence losses of 2.54 cm y-1 would represent 2.3 times (harvested biomass + recoverable aboveground biomass residues). If the oxidative subsidence were less at 1.45 cm y-1, the ratio of oxidative subsidence to (harvest + residues) would be 1.3.

For sugarcane not grown in high water-table conditions, the ratio of belowground biomass to aboveground shoot biomass was estimated to be 0.20 kg kg-1. For sugarcane cultivar CP80-1827, the data of Morris (2005) showed that the ratio of belowground biomass (root biomass plus belowground stem biomass) to aboveground shoot biomass was 0.129 kg kg-1 when the water-table was 15 cm and 0.192 kg kg-1 when the water-table was 30 cm. In a literature review, Smith et al. (2005) reported a peak root:shoot ratio of 0.42 kg kg-1 at about 50 days of age which decreased to about 0.17 kg kg-1 at 130 and 200 days after planting. Smith et al. (2005) also pointed out that living root biomass could seriously underestimate cumulative carbon allocation to roots. Multiplying 28,000 kg ha-1 y-1 by 0.20 gives an additional biomass of 5,600 g ha-1 y-1 or a total of 33,600 kg ha-1 y-1. On this basis, 63,500/33,600 = 1.9 in the case of an oxidative subsidence loss of 2.54 cm y-1, and 1.1 in the case of an oxidative subsidence loss of 1.45 cm y-1. The ratio of carbon lost by Histosol oxidative subsidence to carbon gained by sugarcane biomass components (sucrose only, sucrose plus bagasse, sucrose plus bagasse plus recoverable aboveground biomass, and sucrose plus bagasse plus recoverable aboveground biomass plus belowground biomass) are illustrated in Fig. 1.

DISCUSSION

In summary, based on sucrose production alone, the ratio of carbon lost to the atmosphere via microbial oxidative subsidence of EAA Histosols (at a rate of 2.54 cm y-1) to carbon gained via photosynthetic biomass production would be about 7.0. However, taking into account the harvested bagasse, the ratio of carbon lost to carbon gained would be lower, about 3.7. These conditions probably prevailed until the 1990s for sugarcane production in the EAA. However, recent production practices on higher water tables appear to have decreased the rates of subsidence to about 1.45 cm y-1 and probably have decreased the ratio of carbon lost to carbon harvested (sucrose plus bagasse for fuel) to a value of about 2.1. Furthermore, taking into account all sugarcane biomass production decreases the ratio of carbon lost to carbon gained to 1.9 or 1.1 for oxidative subsidence losses of 2.54 or 1.45 cm y-1, respectively.

0

1

2

3

4

5

6

7

8

SO

IL C

LO

SS

/BIO

MA

SS

C G

AIN

2.54 cm per year 1.45 cm per year

SUGAR + BAGASSE + RESIDUES + BELOWGROUND

Figure 1. Ratio of carbon lost by microbial oxidation of EAA Histosols to carbon gained by accumulations of sugarcane biomass components using historical rates (2.54 cm per year, red bars) and more recent rates (1.45 cm per year, blue bars) of annual soil subsidence. Ratios shown for biomass components are sugar only, sugar + bagasse, sugar + bagasse + aboveground residues, and sugar + bagasse + aboveground residues + belowground plant components.

Further improvement in the carbon lost-to-carbon gained ratio would depend on the following: (1) decreasing oxidative subsidence by maintaining higher water tables (e.g., Morris et al., 2004); (2) increasing yield and biomass productivity through improved management practices or improved cultivar selection (e.g., Glaz and Gilbert, 2006), especially under high water table conditions whereby new organic matter could accumulate in the soil (Morris, 2005); or (3) a combination of increasing, or maintaining, yield and biomass productivity while decreasing oxidative subsidence by maintaining higher water tables. Regarding subsidence per se, Snyder (2005) pointed out that subsidence rates could decrease based on: (1) more resistant humus remaining after a period of partial microbial oxidation; (2) greater fraction of mineral matter remaining in the soil profile after a period of microbial oxidation; and (3) applying Histosol-conserving agricultural practices which would include crop production with higher water tables.

PERSPECTIVES ON LOCAL CARBON BALANCE

Since soil subsidence in the EAA is directly related to water-table depth and uniquely modified by climate and temperature regimes (Stephens et al., 1984), producing crops with shallow water-tables is an option for decreasing the ratio of carbon lost to carbon fixed. Nevertheless, based strictly on energy balance (carbon balance) considerations, hypothetically, for fuel purposes, it would make more sense to mine the EAA Histosols and burn them for energy rather than to use them to produce biomass energy crops. Of course, mining the EAA Histosols makes no sense in ecological terms.

However, can an agricultural system that conserves Histosols make the EAA an overall carbon accumulator? Recent work suggests that further research may lead to successful production of sugarcane on periodically

■ ■


flooded, higher water table soils (Gilbert et al., 2007, 2008; Glaz et al., 2005; Glaz and Gilbert, 2006; Glaz and Morris, 2006; Glaz, 2007; Glaz et al., 2008; Morris et al., 2004; Morris, 2005). Sugarcane is already annually exposed to several floods of 1 to 7 day durations in the EAA due to use of best management practices to control P discharge.

There are few papers relevant to the question of actually restoring soil organic matter in the Histosols of the EAA (Morris, 2005). Lucas (1982) indicated that it would take sawgrass (Cladium jamaicence), a slow growing species prominent in the natural Florida Everglades, 179 years to produce a 15-cm layer of soil with a bulk density of 0.15 g cm-1, a rate equivalent to a depth of 0.084 cm y-1. Morris (2005) speculated that sugarcane, with much higher annual biomass productivity than sawgrass, might be able to accumulate 15 cm of peat in just 9 years, a rate of 1.67 cm y-1, if all biomass went to soil organic matter. However, since the above-ground parts are harvested, much less biomass would actually be available for carbon inputs to the soil. The soil would have to be largely flooded to prevent oxidative losses of the belowground parts of the sugarcane plant. In the non-farmed Everglades, cattail (Typha spp.) is displacing sawgrass where high-nutrient waters are pumped into Water Conservation Areas. Reddy et al. (1993) computed an accretion rate of peat in continuously flooded cattail in these nutrient-enriched waters to be 1.1 cm y-1. Although experimental information is limited, these findings suggest that biomass production in high water-table conditions in the EAA potentially could be managed so that the system as a whole might be carbon accreting. Since aboveground components would likely all be harvested, the soil carbon balance would depend largely on belowground biomass accumulation. Even though the soils might not be carbon accreting, they might still have the potential of being essentially carbon-flux neutral, that is, with no net loss of soil carbon.

These carbon balance calculations are based on carbon emissions and uptakes at the field, and do not account for additional emissions related to biomass production and biofuels conversion operations. Such additional energy inputs, with associated carbon emissions, include cultural and harvesting operations, production and transportation of fertilizers, pumping water for water-table management as seepage irrigation or drainage, transportation of harvested sugarcane to mills, and for sugar extraction/refining or ethanol production. For milling, extraction, and refining, much of the energy can, and currently does, come from use of bagasse to offset external sources of fossil fuel energy and carbon emissions. For ethanol production, cellulosic ethanol from bagasse can offset external sources of fossil fuel energy and carbon emissions.

PERSPECTIVES—GLOBAL ENERGY

Assuming 240,000 ha in the EAA and 2.54 cm y-1 of oxidative subsidence, it was shown that this would give 6.1

x 1012 g C y-1 released to the atmosphere as CO2. Furthermore, since the global release of carbon from fossil fuel burning during the 1990’s was 6.4 x 1015 g C y-1 (IPCC, 2001), the carbon released to the atmosphere by oxidative subsidence in the EAA was about 0.095% of carbon released from burning of fossil fuels. Furthermore, based on the soil properties, oxidation of a 26.7 m depth of EAA Histosol would be required to produce the carbon equivalent of annual global fossil fuel burning. However, the average remaining depth of the EAA organic soil is much less. The overall averages of organic soil remaining based on 30 sites measured in 1978 by Shih et al. (1979) was 1.02 m. The overall average measured depth to bedrock reported by Snyder (2005) for 1988 was 0.94 m, but the area-weighted average depth based on soil classification types was 0.84 m. Therefore, taking the average depth as 0.84 m of soil remaining, the EAA Histosols have enough equivalent carbon to supply global energy needs for only 11 ½ days.

Carbon equivalent calculations showed that the volume of EAA Histosol required for annual equivalent global energy use would be 64 x 109 m3 or 64 km3. Furthermore, the volume of relatively dense pure global fossil fuel extractions (coal, oil, natural gas at standard temperature and pressure) would be about 13 km3 annually, or about 3 cubic miles). Since the earth’s volume is about 1.28 x 1012 km3, the volume of fuel extracted world-wide annually is of the order of 10 x 10-12 of the volume of the earth (10-trillionths of the volume of the earth).

Based on a value of 1.65 X 1015 g C y-1 for carbon emitted by the USA for 2004 (Marland et al., 2004) and 11,200 kg ha-1 y-1 of biomass equivalent carbon that could be fixed by production of sugarcane as sugar plus bagasse plus aboveground residues, or other crops with equivalent annual biomass productivity of 28,000 kg ha-1 y-1, gives about 1.47 X 108 ha of land that would be required by a productive crop for biomass energy (Appendix 1). This represents a square block of land about 1,200 km by 1,200 km, or about 750 mi X 750 mi (562,500 mi2). In perspective, this is roughly the amount of land bounded by the perimeter from Washington, DC to Chicago, IL to New Orleans, LA to Jacksonville, FL to Washington, DC. To put this land area in another perspective, the USDA Crop Production 2007 Summary (2008) indicated that the 2007 USA land usage for crops was: corn = 94 X 106 acre; soybean = 64 X 106 acre; all hay = 62 X 106 acre; wheat = 60 X 106 acre. These acreages represent 87.5% of the total land area for all crops which was 320 X 106 acre. These crop acreages include all grains, hay, oilseeds, cotton, tobacco, sugar crops, dry bean, pea, lentil, potato, sweet potato, and several miscellaneous crops, but they do not include fresh vegetable, fruit, vine, and nut crops. The 320 X 106 acre, or 1.30 X 108 ha, is equal to 500,000 mi2 or 1.30 X 106 km2. This area represents a square of 707 mi by 707 mi or 1,140 km by 1,140 km. Thus, based on


carbon balance calculations, biomass energy production for all energy uses of the USA would require somewhat more than all of the land area currently used as cropland.

Clearly, the amount of biomass energy required for replacing all the current energy uses of the USA would displace a vast amount of the current food, feed, fiber, wood products, and ecosystems services of the landscape of the USA, another type of current inconvenient truth or inexorable reality. Furthermore, the production level of Florida sugarcane could not be attained over this area on an annual basis due mostly to seasonal climate (e.g., temperature) limitations. Since biomass-captured energy represents the most clear-cut method of harvesting solar energy over vast landscapes, the most pressing question for human civilization may not be “What do we do for energy independence and what do we do about carbon dioxide and other greenhouse gas emissions?” but “What do we do when the easily extractable fossil fuel energy sources become scarcer and harder to extract?” An eventual inconvenient truth or inexorable reality.

Other analyses have indicated the limited capability of bioenergy sources for supplanting current reliance on fossil fuel sources (The Rush to Ethanol: Not all Biofuels are created equal. Analysis and Recommendations for U.S. Biofuels Policy. Food & Water Watch and Network for New Energy Choices in collaboration with Institute for Energy and the Environment at Vermont Law School; http://www.newenergychoices.org/uploads/RushToEthanol-rep.pdf). For example, Hill et al. (2006) indicated that dedication of all current corn and soybean production of the USA for biofuels would supply only 12% of gasoline used and 6% of diesel used. Farrell et al. (2006) and Hammerschlag (2006) analyzed several reports of other authors on the energetics of ethanol production. However, none of these reports really addressed the ultimate limitations of biomass production as the feedstock for potential replacement of fossil fuel use with bioenergy sources. Although biomass production cannot supply all current or projected USA and global energy needs, it can be an important supplement especially where it does not displace food, feed, fiber, or wood product needs (such as cellulosic bioenergy), or jeopardize ecosystems or soil quality. Finally, carbon balance analyses offers a way for determining if a production system represents a net loss or gain of carbon, which could be applied to any agricultural production system. For planning bioenergy replacements for fossil fuel sources, if sufficient carbon be not there, then we must be aware.

ACKNOWLEDGMENTS

For providing recent background information and making various alternative suggestions including pointing out more recent subsidence measurements and high water-table adaptive research, I thank the following: Barney Eiland, George Snyder, Dolan Morris, Li-Tse Ou, John Thomas, Russ Gesch, and especially Barry Glaz. This

publication is related to work supported by the Agricultural Research Service under the ARS GRACEnet Project.

REFERENCES

Armentano, T.V. 1980. Drainage of organic soils as a factor in the world carbon cycle. BioScience 30:825-830.

Duxbury, J.M., and R.L. Tate III. 1981. The effects of soil depth and crop cover on enzymatic activities in Pahokee Muck. Soil Sci. Soc. Am. J. 45:322-328.

Farrell, A.E., R.J. Plevin, B.T. Turner, A.D. Jones, M. O’Hare, and D.M. Kammen. 2006. Ethanol can contribute to energy and environmental goals. Science 311:506-508.

Gilbert, R.A., C.R. Rainbolt, D.R. Morris, and A.C. Bennett. 2007. Morphological responses of sugarcane to long-term flooding. Agron. J. 99:1622-1628.

Gilbert, R.A., C.R. Rainbolt, D.R. Morris, and J.M. McCray. 2008. Sugarcane growth and yield responses to a 3-month summer flood. Agric. Water Manage. 95:383-291.

Glaz, B. 2007. Sugarcane response to month and duration of preharvest flood. J. Crop Improve. 20:137-152.

Glaz, B., J.C. Comstock, P.Y.P. Tai, S.J. Edme, R. Gilbert, J.D. Miller, and J.O. Davidson. 2005. Evaluation of new Canal Point sugarcane clones - 2003-2004 harvest season. USDA, ARS, ARS-165, 32 pp.

Glaz, B., and R.A. Gilbert. 2006. Sugarcane response to watertable, periodic flood, and foliar nitrogen on organic soil. Agron. J. 98:616-621.

Glaz, B., and D.R. Morris. 2006. Sugarcane morphological, photosynthetic, and growth responses to water-table depth. J. Sustainable Agric. 28:77-97.

Glaz, B., S.T. Reed, and J.P. Albano. 2008. Sugarcane response to nitrogen fertilization on a Histosol with shallow water table and periodic flooding. J. Agron. & Crop Sci. 194:369-379.

Hammerschlag, R. 2006. Ethanol’s energy return on investment: A survey of the literature 1990-present. Environ. Sci. Technol. 40:1744-1750.

Hill, J., E. Nelson, D. Tilman, S. Polasky, and D. Tiffany. 2006. Environmental, economic, and energetic costs and benefits of biodiesel and ethanol biofuels. Proc. National Acad. Sci. 103:11206-11210.

Inman-Bamber, N.G., R.C. Muchow, and M.J. Robertson. 2002. Dry matter partitioning of sugarcane in Australia and South Africa. Field Crops Res. 76:71-84.


IPCC. 2001. Climate Change 2001: The Scientific Basis. Cambridge University Press, UK.

Knipling, E.B, V.N. Schroder, and W.G. Duncan. 1971. CO2 evolution from Florida organic soils. Soil Crop Sci. Soc. Florida Proc. 30:320-326.

Lucas, R.E. 1982. Organic soils (Histosols) formation, distribution, physical and chemical properties and management for crop production. Res Rep. 435. University of Florida, Gainesville.

Marland, G., T.A. Boden, R. J. Andres. 2004. Global, Regional, and National CO2 Emissions. In Trends: A Compendium of Data on Global Change. Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tenn., U.S.A. (available online at http://cdiac.esd.ornl.gov/trends/emis/tre_coun.htm)

Morris, D.R. 2005. Dry matter allocation and root morphology of sugarcane, sawgrass, and St. Augustinegrass due to water-table depth. Soil Crop Sci. Soc. Florida Proc. 64:80-86.

Morris, D.R., B. Glaz, and S.H. Daroub. 2004. Organic soil oxidation potential due to periodic flood and drainage depth under sugarcane. Soil Sci. 169:600-608.

Obreza, T.A., D.L. Anderson, and D.J. Pitts. 1998. Water and nitrogen management of sugarcane grown on sandy, high water table soil. Soil Sci. Soc. Amer. J. 62:992-999.

Reddy. K.R., W.F. DeBusk, R.D. DeLaune, and M.S. Koch. 1993. Long-term nutrient accumulation rates in the Everglades. Soil Sci. Soc. Amer. J. 57:1147-1155.

Shih, S.F., E.H. Stewart, L.H. Allen, Jr., and J.W. Hilliard. 1979. Variability of depth to bedrock in Everglades organic soil. Soil Crop Sci. Soc. Florida Proc. 38:66-71.

Shih, S.F., B. Glaz, and R.E. Barnes, Jr. 1998. Subsidence of organic soils in the Everglades Agricultural Area during the past 19 years. Soil Crop Sci. Soc. Florida Proc. 57:20-29.

Smith, D.M., N.G. Inman-Bamber, and P.J. Thornton. 2005. Growth and function of the sugarcane root system. Field Crops Res. 92:169-183.

Snyder, G.H. 2005. Everglades Agricultural Area soil subsidence and land use projections. Soil Crop Sci. Soc. Florida Proc. 64:44-51.

Stephens, J.C., L.H. Allen, Jr., and E. Chen. 1984. Organic soil subsidence. pp. 107-122. In: T.L. Holzer (ed.). Reviews in Engineering Geology, v. VI. Geological Soc. of America.

Stephens, J.C., and L. Johnson. 1951. Subsidence of organic soils in the upper Everglades region of Florida. Soil Crop Sci. Soc. Florida Proc. 11:191-237.

Stephens, J.C., and E.H. Stewart. 1976. Effect of climate on organic soil subsidence. Proceedings of the Second International Symposium on Land Subsidence, Anaheim, CA, 13-17 December 1976. IAHS-AISH Pub. No. 121, pp. 647-655.

Tate, R.L. III. 1979. Microbial activity in organic soils as affected by soil depth and crop. Appl. Environ. Microbiol. 37:1085-1090.

Tate, R.L., III. 1980. Microbial oxidation of organic matter of Histosols. pp. 169-201. In: M. Alexander, (ed.) Advances in Microbial Ecology, vol. 4, Chap. 5. Plenum Publishing Corp.

Tate, R.L.III, and R.E. Terry. 1980. Variations in Microbial activity in Histosols and its relationship to soil moisture. Appl. Environ. Microbiol. 40:313-317.

USDA Crop Production 2007 Summary. 2008. Cr Pr 2-1 (08). National Agricultural statistics Service, U. S. Department of Agriculture, January 2008. Available on-line at: (http://usda.mannlib.cornell.edu/usda/current/CropProdSu/CropProdSu-01-11-2008.pdf) or (http://usda.mannlib.cornell.edu/MannUsda/viewDocumentInfo.do?documentID=1047).

Volk, B.G. 1973. Everglades Histosol subsidence: 1. CO2 evolution as affected by soil type, temperature and moisture. Soil Crop Sci. Soc. Florida Proc. 32:132-135.

http://cdiac.esd.ornl.gov/trends/emis/tre_coun.htm�

http://usda.mannlib.cornell.edu/usda/current/CropProdSu/CropProdSu-01-11-2008.pdf�

http://usda.mannlib.cornell.edu/usda/current/CropProdSu/CropProdSu-01-11-2008.pdf�


APPENDIX 1: BACKGROUND INFORMATION AND CALCULATIONS

Computing mass of carbon lost per year via oxidative subsidence, and the plant biomass equivalent of this amount of carbon.

Calculation Units Explanation

0.23 g cm-3 bulk density

x 0.87 fraction organic matter

x 0.50 fraction carbon

0.1000 g C cm-3

x 2.54 cm y-1 subsidence rate

0.2540 g C cm-2 y-1

x 10,000 cm2 m-2

2540 g C m-2 y-1

x 10,000 m2 ha-1

2540 x 104 g C ha-1y-1

x 0.001 kg g-1

25,400 kg C ha-1 y-1

x 2.5 CH2O / C mass ratio

63,500 kg ha-1 y-1 (biomass CH2O equivalent annual production required to balance the organic soil oxidative subsidence)

Computing the amount of carbon released to the atmosphere from the EAA annually:

240,000 ha area of EAA

x 25,400 kg C ha-1 y-1

6.1 x 1012 g C y-1 released to the atmosphere

Computing comparison with 1990’s global fossil fuel emissions of about 6.4 x 1015 g (C) y-1:

6.1 x 1012/6.4 x 1015

= 0.00095 or 0.095%

Computing depth of EAA Histosol equivalent to fossil fuel burning carbon emissions annually:

2.54/0.00095 = 2674 cm depth of EAA Histosol

26.7 m depth of EAA Histosol

Computing the number of days of fuel supply (carbon basis) available in the EAA, assuming 0.84 m (84 cm) soil depth remaining:

6.1 x 1012 g C y-1 carbon in 2.54 cm annual subsidence

x 84/2.54 cm/(cm y-1) weighted depth/annual loss

202 x 1012 g C mass of carbon in EAA

0.202 x 1015 /6.4 x 1015 g C g-1 C EAA carbon/annual global carbon emission

= 0.0315

0.0315

x 365 d y-1 days per year

11.5 d days of carbon in EAA equivalent to annual global fossil fuel burning


Calculation of approximate volume of extracted fuels that would release 6.4 x 1015 g (C) y-1, assuming a bulk density of 1.0 g cm-3 and 100% organic matter.

240,000 ha

x 1 x 104 m2 ha-1

x 26.7 m

= 64.1 x 109 m3

= 64.1 km3

64.1

x 0.23

x 0.87

= 12.8 km3 equivalent fossil fuel volume

1.28 x 1012 km3 volume of the earth

Calculation of land area required to supply all energy via biomass for the USA.

Using the aboveground biomass productivity of sugarcane (see text for sucrose plus bagasse plus recoverable aboveground biomass), the biomass productivity would be 28,000 kg ha-1 y-1.

Dividing by 2.5 (the CH2O/C mass ratio) gives 11,200 kg C ha-1 y-1, or 11.2 X 106 g C y-1.

Marland et al. (2004) reported that 2004 carbon emissions by the USA was 1.65 X 1015 g C y-1.

1.65 X 1015 g C y-1 divided by 11.2 X106 g C y-1 = 1.47 x 108 ha = 1.47 x 1012 m2.

1.47 x 1012 m2 x 10-6 (km)2 m-2 = 1.47 x 106 km2, a square of 1,210 km by 1,210 km, or a square of 750 mi by 750 mi. This would be an area roughly bounded by the perimeter from Washington, DC to Chicago, IL to New Orleans, LA to Jacksonville, FL back to Washington, DC. Actually, sugarcane productivity would be a relatively high estimate of biomass availability due to both climate and soils limitations within this circumscribed region.


Nutrient Composition of Tifton-9 Bahiagrass in the First Season of a Silvopastoral System with Boer x Spanish Goats

N. Gordon-Bradley* and O.U. Onokpise

ABSTRACT

‘Tifton-9’ bahiagrass (Paspalum notatum Flugge) is becoming widely used as forage in the southeastern United States for grazing and hay production. Its use in silvopastoral systems is only now being evaluated. In April 2005, Tifton-9 bahiagrass seeds were broadcast at a rate of 11 to 17 kg ha-1 between widely spaced tree rows of loblolly pine (Pinus taeda L) and in open pasture under full sun (main plot treatments). The experimental design was a split plot design in two replicates with Boer x Spanish crossbred goats randomly assigned to blocks at two stocking rates of 10 and 17 animals per hectare, respectively. In September 2005, 16-to 18-mo-old Boer x Spanish crossbred goats (Capra hircus) were introduced into fenced paddocks of established bahiagrass for grazing. Nutrient composition of Tifton-9 was determined prior to the animals grazing each paddock. Forage samples for nutrient analysis were collected by randomly selecting 15 hand grab samples and forming a composite sample from each paddock before each grazing cycle. Collected samples were dried, ground and analyzed for crude protein (CP), nutrient detergent fiber (NDF), acid detergent fiber (ADF) and total digestible nutrient (TDN). Results obtained showed significant differences for nutritive values of Tifton-9 at the different sampling dates. The results also showed that except for NDF, there were no significant differences for the nutritive values of Tifton-9 whether it was grown under loblolly pine trees or in open sunlight. This is particularly important for producers who want to manage silvopastoral systems for sustainable agriculture. It is probable that for Tifton-9 bahiagrass, limited amounts of shading will not significantly affect its nutrient composition.

INTRODUCTION

Grazing or harvesting of forage crops grown in association with planted trees represents a dominant form of silvopastoralism in many parts of the world (Payne, 1985). Although land use systems of this kind are thought to be highly productive owing to vertical stratification of the above and below ground components, they are extremely dynamic with available resources and environmental conditions changing over time (Kumar et al., 2001).

Silvopasture is being practiced more frequently in the southeastern United States where it is economical to graze a single species under a pine monoculture in a large silvopastoral operation (Harrison, 2002). Silvopastoral systems are important in that they provide forage for livestock, timber for industrial use and other uses as well as animal products (Nowak et al., 2002).

N. Gordon-Bradley and O.U. Onokpise, Forestry and Natural Resources Conservation, College of Engineering Science, Technology and Agriculture, Florida A & M University, Tallahassee, Florida 32307.


Bahiagrass has been shown to be productive when grown under loblolly pine trees in North Florida (Onokpise and Whilby, 2005). Bahiagrass is a very drought/flood tolerant grass that persists even under low fertilization and close grazing (Gates et al., 1999). This shade-tolerant grass species also lends itself very well to either improved open pastures or tree-covered pastures, allowing landowners to grow trees and grass simultaneously. Since the early 1950s many southern landowners have grown pine trees and bahiagrass on the same land (Tyree and Kunkle, 1995). Wood yields, in fact, are reported to be at their highest with bahiagrass compared to other grasses such as bermudagrass [Cynodon dactylon (L.) Pers.] or dallisgrass (P. dilitatum Poir.) (Tyree and Kunkle, 1995). Research also shows that on many sites, tree growth increases where fertilizer is applied for grass production (Tyree and Kunkle, 1995).

Bahiagrass is a warm season grass that provides abundant feed of adequate nutritional value for annual production in the southern United States (Gates et al., 2001). Tifton 9 Bahiagrass was developed in Tifton, GA, and is one of the newer cultivars of the bahiagrass (Baki et al., 1992). Tifton 9 has an increased spring herbage accumulation and yield advantages during the typical growing season compared to the older cultivars (Gates et al., 2001). One of the best attributes of Tifton 9 is that it has the potential to produce up to 40% more forage than the others under the right conditions with rain and fertilization (Gates et al., 2001).

Warm-season perennial grasses, especially bermudagrass and bahiagrass, are key to livestock operations in the Southeast. Evaluation of new cultivars under a range of climatic and grazing conditions allows development of optimal management for their use in the region (Pedreira and Brown, 1996; Gates et al., 2001). Research work by Onokpise and Whilby (2005) has shown that some forage species will grow better under shade than in full sunlight. The soil condition under the shaded area resulted in higher moisture content when compared to soil in open sunlight (Onokpise and Whilby, 2005). This increased soil moisture content could be the cause of the grass performing better under the shade (Onokpise and Whilby, 2005).

Ideally, forage produced under a silvopastoral system would be able to supply all the necessary nutrient requirements that are needed by the animal that it will be fed to. Being a relatively new cultivar, there is limited information on the effect of shade and stage of growth on



the forage quality of Tifton-9 bahiagrass. The objectives of this study were to evaluate the effect of time and shade on nutrient content of Tifton-9 bahiagrass grown in between rows of loblolly pine trees.

MATERIALS AND METHOD

Study Site

The research site for this study is located at Florida A & M Univ. Res. Ext. Ctr. Farm, Quincy, FL (30o36˝N and 84o33˝W; Clarke, 1999). The farm covers approximately 105 hectares and the soils are predominantly Orangeburg series (Fine-loamy, Kaolinitic, Thermic Typic Kandiudults). The major land cover includes pine, mixed hardwood/pine forests, agriculture and non-vegetative urban infrastructure (Darbyshire, 1993). The area that was used for this research consisted of loblolly pine plantation that was planted in 1979. This area was thinned in November 2001 from the original spacing of 1.2 x 2.4 m spacing to 1.2 x 12 m spacing (Onokpise and Whilby, 2005).

Experimental design

The experimental design was a split-plot design with two replications. Main plots were two levels of shade on Tifton 9 bahiagrass swards (an open pasture in full sunlight vs. natural shade conditions as existing under the established loblolly pine trees) and stocking rate (10 vs. 17 goats per hectare) was the subplot.

Land Preparation and Establishment of Grass Pastures between Loblolly Pine Tree Rows

The total hectarage used for the research was 1.62 hectares of land; 0.8 ha shaded and 0.8 ha unshaded. The research area was plowed and seeded with 16.5 kg ha-1

Tifton-9 seeds in April 2005. Fertilizer (10-10-10) was applied at a rate of 420 kg ha-1 in August 2005 to promote growth of grass, and the seeded area was fenced to establish pastures into paddocks for the grazing trial. Each of the main plots was divided into four subplots and each subplot was further subdivided into two 0.1 ha areas to allow rotational grazing.

Animal Introduction on Pasture

Animals averaging 23 kg were selected and dewormed with cydectin at rates of 1 cc per 9 kg animal weight one week before introduction into the pastures. Animals were assigned different stocking rates based on average weight of animals. The stocking rate used was 10 and 17 Boer x Spanish goats per hectare. Introduction of animals was done on 27 Sep 2005. A rotational method was used where the goats were placed in each 0.1 ha paddock of each subplot for 14 d (Figure1). Grazing was terminated on 25 Nov 2005 due to low forage availability. This resulted in three grazing cycles.

0.1ha 3 animals

0.1ha 3 animals

0.1ha

0.1ha

0.1ha 5 animals

0.1ha 5 animals

0.1ha

0.1ha

Figure 1. Field Plot layout. Key: Solid black lines represent experimental units (0.2 ha), small black lines represent paddock subdivision (0.1 ha), arrows represents grazing rotation. This layout was done for both shaded and unshaded areas

Grass Sampling and Analysis Procedure

Forage for nutrient analysis was sampled before each grazing cycle started within each paddock. Sampling dates were September 28, 2005, October 11, 2005 and October 25, 2005. Fifteen hand grab samples were taken using a randomized procedure. The herbage was clipped at a height of approximately 15 cm above ground level and composited for the paddock. Samples were dried to constant weight at 600 C for 4 d and the dried samples were then ground with a Wiley Mill equipped with a 0.2-mm mesh screen. Ground samples were stored in secured vials at room temperature until analyzed using Near Infrared Reflectance Spectroscopy (NIR) analysis at the Univ. of Georgia Forage Laboratory. Protein, acid detergent fiber (ADF), neutral detergent fiber (NDF) and total digestible nutrients (TDN) were determined for each sample.

Statistical Analysis

Data were analyzed by Analysis of Variance (SAS Institute, 2002) to determine significant treatment (date and shade) effects on the measured parameters. When significant treatment effects were identified, mean values were separated using Tukey’s Honestly Significant Difference (THSD). The 0.05 alpha level was chosen for this test.

RESULTS & DISCUSSION

The results obtained showed that time had significant effect (based on THSD) on the quality of Tifton-9 bahiagrass. Regardless of shade treatment, as the grass aged there was a general decreasing trend in the nutritive value concentration of the grass but there were some differences due to shade treatment. The grass grown under loblolly pine trees showed significant difference for NDF


concentration which showed a decline between the first (September 28, 2005) and the last sample date (October 25, 2005). Date had no effect for protein, ADF and TDN (Figure 2). The forage had a protein concentration of 86 g/kg, 79 g/kg and 84 g/kg for sampling dates September 28, 2005, October 11, 2005, and October 25, 2005, respectively. For the grass grown in open sunlight, NDF and ADF concentrations declined between the September and the two October collection dates (Figure 3). Total digestible nutrient concentration was lower at the first sampling date and there was a gradual increase at the second and third sampling dates for the TDN concentration of the forage (Figure 3). There was a decrease in the protein concentration by the last collection date in October (Figure 3). The protein concentration for the forage grown in open sunlight was 80 g/kg, 87 g/kg and 72 g/kg for sampling dates September 28, 2005, October 11, 2005, and October 25, 2005, respectively.

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Protein NDF ADF TDN

g/k

g

9/28/2005

10/11/2005

10/25/2005

Figure 2. Nutritive values (g/kg) for Tifton-9 bahiagrass grown under loblolly pine sampled on three different dates. Bars with the same letter are not significantly different, Tukey’s HSD, P = 0.05

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Figure 3. Nutritive values (g/kg) for Tifton-9 Bahiagrass Grown in Full Sunlight or open pastures. Bars with the same letter are not significantly different, Tukey’s HSD, P = 0.05

When comparison was done for the nutritive value of Tifton-9 using shade as treatment, results showed that except for NDF, there were no significant differences among the nutritive values of the grass whether it was grown under loblolly pine trees or in open pasture (Figure 4). This is very important because this showed that the trees did not significantly affect the protein and TDN concentration of the grass. The results also showed that the forage grown under loblolly pine trees produced an average TDN concentration of 503 g/kg and an average protein concentration of 83 g/kg, while the grass grown in open sunlight had a average TDN concentration of 503 g/kg and a protein concentration of 80 g/kg. Luginbuhl and Poore (1998) stated that the average TDN and protein requirements for meat goat yearlings are 65% and 12% respectively. Our findings indicate that the forage may have provided enough protein and TDN for 18 months old goats.

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g Shaded

Unshaded

Figure 4. Nutritive values (g/kg) for Tifton-9 bahiagrass for shaded and unshaded areas. Bars with the same letter are not significantly different, Tukey’s HSD, P = 0.05

CONCLUSION

One of the most important findings obtained from this study is that except for NDF, there was no significant difference between the nutritive values of Tifton-9 whether it is grown under loblolly pine trees or grown in the conventional open pasture method. From this data it can be concluded that the grass grown in a silvopastoral system will provide similar concentrations of nutrients as the grass grown in unshaded areas. The data obtained from this study will provide additional information to farmers who will practice silvopastoral systems as sustainable agricultural systems.

ACKNOWLEDGMENT

This research was supported in part by a grant from the USDA-CSREES-Initiative for Food and Agricultural Sciences (IFAFS) through the Center for Subtropical Agroforestry (CSTAF), University of Florida, Gainesville, Florida. Additional funds from FAMU Agricultural

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Research Program are gratefully acknowledged. Thanks are extended to Mr. Godfrey Nurse, Mr. Fitz Bradley and Dr. B. Macoon for field establishment and data collection. Thanks are also extended to the anonymous reviewer for critical editorial and review comments.

LITERATURE CITED

Baki, B.B., I.B. Ipon, and C.P. Chen. 1992. Paspalum notatum Fluegge. Mannetje, L. & Jones, R.M. (Editors): Plant Resources of South-East Asia No 4. Forages. Pudoc-DLO, Wageningen, the Netherlands. pp. 181-183.

Clarke, F.L.G. 1999. Investigating the spatial distribution of American beech and southern magnolia with remotely sensed data. M.S. Thesis, Florida A&M University, Tallahassee.

Darbyshire, J. 1993.Forestry management plan. F&W Forestry Services, Quincy, Fl.pp 8.

Gates, R.N., G.M. Hill, and G.W. Burton. 1999. Response of selected and unselected bahiagrass populations to defoliation. Agronomy Journal 91: 787-795.

Gates, R. N., P. Mislevy, and F. G. Martin, 2001.

Herbage accumulation of three bahiagrass populations during the cool season. Agronomy Journal, 93:112-117.

Harrison, V. 2002. Sustainable Agriculture and Silvopastoralism. Michigan Technological University Peace Corps. Article. pp 1 http://peacecorps.mtu.edu/resources/studentprojects/silvopasture.html

Kumar, B.M., S.J. George, and T.K. Suresh. 2001. Fodder grass productivity and soil fertility changes under four grass + tree associations in Kerala, India. Agroforestry Systems 52: 91-106.

Luginbuhl, J. M., and M.H. Poore. 1998. Nutrition of meat goats, (article), Department of Animal Science, North Carolina State University, Raleigh, NC.

Nowak, J., A. Blount, and S. Workman. 2002. Integrated Timber, Forage and Livestock Production - Benefits of Silvopasture. Circular 1430, Florida Cooperative Extension Service, Institute of Food and Agricultural Sciences, University of Florida.

Onokpise, O.U., and L. Whilby. 2005. Evaluating forage grass cultivars for a silvopastoral system in North Florida. Soil Crop Sci. Soc. Florida Proc. 64:86-89.

Payne, W.J.A. 1985. A review of the possibilities for integrating cattle and tree crop production in the tropics. Forest Ecology Management 12: 1-36.

Pedreira, C.G.S., and R.H. Brown. 1996. Yield of selected and unselected bahiagrass populations at two cutting heights. Crop Sci. 36:134–137.

SAS Institute. 2002. SAS procedures guide, version 9, SAS Inst., Inc., Cary, NC.

Tyree, A.B., and W. E. Kunkle. 1995. Managing pine trees and bahiagrass for timber and cattle production. University of Florida (circular 1154). Gainesville, Fl.

http://peacecorps.mtu.edu/resources/studentprojects/silvopasture.html�

http://peacecorps.mtu.edu/resources/studentprojects/silvopasture.html�


Spectral Changes Associated with Bacterial Wilt Stress in Tomato Leaves

G. Hacisalihoglu*, K. A. Milla, P. Ji, T. Mochena, S. Olson, and T. M. Momol

ABSTRACT

Spectral reflectance can be a valuable tool for detecting environmental stress, including plant disease damage over time. Ralstonia solanacearum is a systemic bacterium that causes bacterial wilt disease (BW) in several plant species. In this study, a series of experiments were carried out to collect wilt incidence and spectral properties of tomato (Lycopersicon esculentum L.) with reflectance spectroscopy and normalized difference vegetation index (NDVI). Healthy and inoculated plants were grown and kept well watered after inoculation with R. solanacearum. A field spectroradiometer was able to detect differences between healthy control and bacterial wilt damaged plants. The incidence of BW on inoculated plants decreased with application of Acibenzolar-S-methyl (a plant resistance inducer, ASM) at 25 µg/ml. Wilting reduced normalized difference vegetation index (NDVI) and reflectance at R325-1075

compared to healthy control plants. These results suggest that hyperspectral reflectance by a spectroradiometer has a potential application for on-time detecting bacterial wilt stress in tomato by distinguishing infected tomato plants from the healthy ones.

INTRODUCTION

Ralstonia solanacearum is a systemic bacterium that causes bacterial wilt disease in several plant species including tomato, eggplant and pepper (Hayward, 1991). Visible symptoms include wilting without yellowing and stunting of whole plant (Anith et al., 2004). In the southeastern U.S., fresh-market tomato production accounts for over 50% of harvested acres and 63% of yield nationally (Davis et al., 1998). However, tomato yield and quality are threatened by BW for which effective control measures are limited. Bacterial wilt is probably the most important bacterial disease of plants in tropical, subtropical and warm temperate zones of the world (Hayward, 1991). The Florida Tomato Committee and North Florida Tomato Growers have prioritized this disease as a high priority research area.

Actigard (Acibenzolar-S-methyl, ASM) is a systemic chemical used for control of diseases in different crops including tomatoes. It has been shown that ASM induces plant systemic resistance against bacterial pathogens (Anith et al., 2004; Louws et al., 2001; Pradhanang et al., 2005).

G. Hacisalihoglu, Florida A&M Univ., Biology Department., Tallahassee, FL 32307-3102; K. A. Milla, Florida A&M Univ., GIS/Remote Sensing Laboratory, Tallahassee, FL 32307-3102; P. Ji, Univ. of Florida/IFAS, North Florida Res. and Educ Ctr, Quincy, FL 32351-5677; T. Mochena, Florida A&M Univ., GIS/Remote Sensing Laboratory, Tallahassee, FL 32307-3102; S. Olson and M. T. Momol, District Directors Office, University of Florida/IFAS, Gainesville, FL 32611. This research was supported by Florida A&M Univ. & Univ. of Florida Ctr. for Coop. Agric. Programs.

*Corresponding author: G. Hacisalihoglu ([email protected]). Contribution published in Soil Crop Sci. Soc. Florida Proc. 67: 19-23 (2009).

Leaf spectral reflectance has been used to assess a number of stress agents in plants (Carter, 1994). Spectral measurements may provide an early measure of plant health status. For example, Ayala-Silva and Beyl (2005) showed that spectral reflectance measurements of wheat (Triticum aestivum L.) were useful for detecting macronutrient deficiencies such as P, K, and Ca. Nilsson (1995) found that healthy plants would show less reflectance in blue (R450-480nm) and red (R600-700nm) regions of the spectrum, while showing more reflectance in green (R500-550nm) region. Furthermore, in a field experiment, Zhang et al. (2003) used hyperspectral remote sensing to monitor late blight in tomato and was able to separate infected plants from healthy plants. These researchers concluded that remote sensing could be useful for plant disease identification.

The specific objectives of this study were to: 1) investigate spectral patterns of tomato foliage to determine if spectral reflectance can be used as an early indicator of pathogen stress and 2) assess early physiological changes of tomato plants associated with ASM application and different levels of disease stress.


Plant and Bacteria Growth

Tomato seeds (cv. FL 47) were sown in Terra-lite soil mix (Scott Sierra Hort Prod, Marysville, OH) in expanded polystyrene flats with 3.5- by 3.5-cm cells. The flats were placed in a greenhouse and watered daily by overhead watering.

Ralstonia solanacearum (race 1, biovar 1) tomato strain Rs5, isolated in Quincy, FL, was used in this study as described in Hacisalihoglu et al. (2007). The bacterial pathogen was grown at 28ºC on Casamino acid (casein hydrolysate)-Peptone-Glucose (CPG) medium for 48 h. Bacterial cells were harvested and suspended in sterile deionized water and the concentration of inoculum was estimated by measuring absorbance at 590 nm and adjusted to 5 x 107 colony-forming units (CFU)/ml.

The chemical resistance inducer ASM was applied as foliar spray and soil drench. The initial foliar application of ASM (0 and 25 µg/ml) was applied 14 days after seedling emergence, followed by a second foliar application with the same rates as mentioned and soil drench 5 d prior to plant inoculation with the pathogen. Plants were sprayed till run-off with ASM solution using a hand held garden sprayer. For soil drench, 5 ml of ASM


solution (0 and 12.5 µg/ml) was applied to each transplant cell.

Five days after second ASM application, tomato seedlings with three to four expanded leaves were inoculated by applying 5 ml of R. solanacearum suspension (0 and 5 x 107 CFU/ml, respectively) into each transplant cell. Seedlings were transplanted into 10-cm pots three days after inoculation. Pots were placed in a saucer containing water to maintain high soil moisture in order to facilitate infection and wilt development. The plants were supplied with Peter’s Peat Lite Special (15:16:17 NPK) at 10-day intervals at a rate of 7.5 g /L of water. Tomato plants were maintained in the greenhouse. Starting 4 d after transplanting (one week after inoculation), ASM was sprayed onto tomato and at weekly intervals thereafter at above-mentioned concentrations. A total of four foliar applications of ASM were made in the greenhouse after transplanting.

Tomato plants were grown in the greenhouse. For growth analysis, treated and untreated tomato plants were analyzed at 4 stages: 7, 14, 21, and 28 d after inoculation for determination of wilt incidence.

Spectral Reflectance and Image Acquisition

The reflectance measurements were performed in the range from 325 to 1075 nm with a spectroradiometer (Field Spec HH, Analytical Spectral Devices, Denver, CO) with about 100 cm distance from the target leaf surface. Reflectance measurements were carried out during clear sky days between 1100h and 1300h (EST) in the greenhouse. A white plate was used to calculate the reference. Soil reflectance was measured and used to exclude the non-foliage background. Resulting data were analyzed by an Analytical Spectral Devices software package.

A two-band Agricultural Digital Camera (ADC, Dycam, Woodland Hills, CA) was used to collect images of plant foliage. The ADC captures images in red (635-667nm) and near-infrared (835-870nm) bands, which correspond with red and NIR Landsat TM bands. Using these bands, a Normalized Difference Vegetation Index (NDVI) can be calculated for each pixel in the image. This index is defined by reflectances in the red and NIR portions of the spectrum: (NIR-Red) / (NIR+Red) and is commonly used to evaluate biophysical properties of plant canopies. Images of inoculated plants and controls were captured and processed to mask off the foliage. Further image processing produced new images in which each pixel value represents the NDVI of the plant foliage at that point (Fig. 1E).

Experimental Design and Data Analysis

The experiments were set up in a complete randomized design with five replicates, and the variation within means is presented as the standard error (S.E.).

Experiments were replicated a minimum of two different times under greenhouse conditions with each replication spaced in time. Data were analyzed using analysis of variance and mean separations were performed using Scheffe Post hoc comparisons. Regression analysis was performed using Sigma Plot (SPSS Inc., Chicago, IL) as described in Hacisalihoglu et al. (2004). For determining bacterial wilt incidence, 20 plants were used for each treatment.

RESULTS

Plant Growth

Bacterial wilt symptoms, such as wilting of leaves and stunting of plants appeared as early as 10 to 15 d in the plants grown without ASM treatment. Inoculated and uninoculated plants showed marked differences in shoot height. Stunting of inoculated plants was reduced by ASM applied twice at 25 µg/ml compared with control in experiments 1 and 2. In uninoculated plants, reduction of shoot stunting by ASM was less pronounced (Fig. 1A-D).

Spectral Reflectance Features of Bacterial Wilt

Spectral reflectance was measured at leaf level in weekly intervals and typical curves are shown in Figure 2 for 10-d old tomato plants. The greatest reflectance (%) separation occurred in the green (R500) and red (R680) regions. In all measured wavelengths, bacterial wilt inoculation was associated with lower reflectance. Furthermore, there were significant differences in the slope of R680-720 region (Fig. 2). Inoculated plants showed the lowest slope (0.9) and non-inoculated control plants showed the highest slope (3.0).

Linear Regressions of Wilt Incidence, NDVI and Hyperspectral Reflectance

Linear regression was applied to determine the most significant wavelengths and NDVIs associated with BW damage and its control (Fig. 3). The best wavelengths associated with BW incidence in tomato was R500 (R2=-0.69***, Fig. 3B). Moreover, R680 was correlated (R2=-0.60**, Fig. 3C), while R732 was not correlated (R2=-0.25, Fig. 3D) with wilt incidence. Additionally, there was a strong vegetative relationship between wilt incidence and Normalized Difference Vegetation Index (NDVI, R2=-0.82***, Fig. 3A).

DISCUSSION

Bacterial wilt is one of the most important diseases of tomatoes in the southeastern United States due to its destructive nature and wide host range (Pradhanang et al., 2005). Spectral reflectance has been shown to be related to changes in physiological characteristics related to stress agents (Carter, 1994). Spectral reflectance of tomato leaves measured with a field spectroradiometer was able to detect differences between healthy and bacterial wilt damaged plants. Mean reflectance % in R500 region


Figure 1. Shoot height of tomato plants growing in greenhouse for 28 d after inoculation with Ralstonia solanacearum. A) uninoculated, B) uninoculated plus ASM, C) inoculated, D) inoculated plus ASM and E) a representative red / near-IR image of inoculated tomato plant in which each pixel value represents the NDVI of the plant foliage at that point.

Wavelength, nm400 450 500 550 600 650 700 750 800

Ref

lect

ance

, %

0.00

0.05

0.10

0.15

0.20

0.25

0.30control

inoculated

Figure 2. Comparison of average hyperspectral reflectance curves measured with a spectroradiometer of uninoculated and inoculated tomato plants at 10 d after inoculation.

,,,,,.------/ ---

I I

/


0 25 50 750.04

0.06

0.08

0.10

0.12

0 25 50 75

ND

VI

0.2

0.3

0.4

0.5

0.6

R2= -0.60**

Wilt incidence (%)0 25 50 75

0.04

0.06

0.08

0.10

0.12

A B

0 25 50 750.10

0.15

0.20

0.25

0.30R2= -0.25

R2= -0.69***R2= -0.82***

DC

Wilt incidence (%)

Ref

lect

ance

at

680

nm

Ref

lect

ance

at

732

nm

Ref

lect

ance

at

500

nm

Figure 3. Correlations between wilt incidence and Normalized Difference Vegetation Index (A); Reflectance at 500 nm (B); Reflectance at 680 nm (C); and Reflectance at 732 nm (D) of tomato plants grown for 28 days after inoculation with Ralstonia solanacearum. *, **, and *** statistically significant at P<0.05, P<0.01, and P<0.001 levels, respectively, as determined using simple linear regression.

contributed the most to tomato BW damage estimation (Fig. 3B). It was shown by Zhang et al. (2003) that average reflectance in R400-700nm for diseased plant was higher.

Acibenzolar-S-methyl, a systemic resistance enhancer, was found to reduce stunting of tomato plants due to BW compared with the untreated control plants. This suggests that ASM could significantly increase resistance of tomato plants against bacterial wilt. This is consistent with the findings of Pradhanag et al. (2005) that ASM enhanced resistance and increased yield of tomato cv. Neptune and cv. FL7514 in greenhouse and field studies.

Visible symptoms of BW disease were not evident until 10 to 15 d after inoculation. In contrast, leaf spectral reflectance was significantly different from control plants

7 days after inoculation (data not shown). Both spectral reflectance and NDVI of inoculated plants decreased significantly compared with uninoculated control plants (Fig. 3).

Acibenzolar-S-methyl has been shown to be an inducer of systemic acquired resistance in a number of

• ••• •

•

• • •

• • • • • •

• • •

• • • • •

• • • • • • • • • • • • • •

•


plant species including tomato (Anith et al., 2004; Louws et al., 2001; Pradhanang et al., 2005). We have demonstrated that ASM applied at a rate of 25 µg/ml reduced bacterial wilt incidence on tomato in two independent experiments. This is consistent with the observations of Pradhanang et al. (2005) that ASM significantly enhanced plant resistance against bacterial wilt in the field and greenhouse.

In summary, our present results indicate that R. solanacearum decreases NDVI and reflectance at R500 and this could be used as an early sign of bacterial wilt damage in tomato. There is a need for further research in the use of spectral reflectance as an indicator of bacterial wilt and technical improvements that are needed to extend this usage for practical application.

LITERATURE CITED

Anith, K.N., M. T. Momol, J.W. Kloepper, J. J. Marois, S. M. Olson, and J. B. Jones. 2004. Efficacy of rhizobacteria, acibenzolar-S-methyl, and soil amendment for integrated management of bacterial wilt on tomato. Plant Dis. 88:669-673.

Ayala-Silva, T., and G. A. Beyl. 2005. Changes in spectral reflectance of wheat leaves in response to specific macronutrient deficiency. Adv. In Space Res. 35: 305-17.

Carter, G.A. 1994. Ratios of reflectance in narrowbands as indicators of plant stress. Intl. J. Remote Sensing 15: 697-703.

Davis, R. M., W. T. Lanini, G. Hamilton, and C. Osteen. 1998. The importance of pesticides and other pest management practices in U.S. tomato production. USDA, Document No: 1-CA-98.

Hacisalihoglu, G., P. Ji, S. Olson, and T. M. Momol. 2007. Bacterial wilt induced changes in nutrient distribution and biomass and the effect of acibenzolar-S-methyl on bacterial wilt in tomato. Crop Protection 26: 978-982.

Hacisalihoglu, G., J. J. Hart, C. E. Vallejos, and L. V. Kochian. 2004. The role of shoot-localized processes in the mechanism of Zn efficiency in common bean. Planta 218:704-711.

Hayward, A.C. 1991. Biology and epidemiology of bacterial wilt caused by P. solanacearum. Annu. Rev. Phytopathol. 29: 65-87.

Louws, F.J., M. Wilson, H. L. Campbell, D. A. Cuppels, J. B. Jones, F. Sahin, and S. A. Miller. 2001. Field control of bacterial spot and bacterial speck of tomato using a plant activator. Plant Dis. 85:481-488.

Nilsson, H. E. 1995. Remote sensing and image analysis in plant pathology. Annu. Rev. Phytopathol. 15: 589-627.

Pradhanang, P.M., P. Ji, M. T. Momol, S. M. Olson, J. L. Mayfield, and J. B. Jones. 2005. Application of acibenzolar-S-methyl enhances host resistance in tomato against Ralstonia solanacearum. Plant Dis. 89:889-93.

Zhang, M., Z. Qin, Z. Liu, and S. L. Ustin. 2003. Detection of stress in tomatoes induced by late blight disease in California using hyperspectral remote sensing. Int. J. Appl. Earth Obs. 4: 295-310.


Fertilization, Aeration, and Sewage Biosolid Effects on Kikuyugrass Pasture Productivity

B.W. Mathews* and J.R. Carpenter

ABSTRACT

There are few data available for responses of old kikuyugrass (Pennisetum clandestinum Hochst. ex Chiov.) pastures to fertilization and aeration. The productivity of grazed kikuyugrass was evaluated for 2 yr in response to mechanical (spiked tine) soil aeration with and without fertilizer N (300 kg ha-1 yr-1 in five split applications) and fertilizer N + P (single 300 kg P ha-1 application). The pasture had not been fertilized in 36 yr, but the volcanic ash-derived silt loam soil (Acrudoxic Hydrudand) was of good fertility except for a low (12 mg kg-1) modified-Truog extractable P concentration. Forage production was increased only by N fertilization despite marginal kikuyugrass P concentrations for the treatments without P fertilization. A simultaneous 2-yr study was conducted on an adjacent long-term (30 yr) fertilized kikuyugrass pasture for the N alone and N + aeration treatments outlined above, an annual 300 kg N ha-1 yr-1 sewage biosolid application (B-A1N), and a single 600 kg N ha-1 sewage biosolid application at study initiation (B-S2N). During the first year B-S2N produced greater cumulative forage yield than B-A1N, which in turn produced more than the N + aeration and N alone treatments. In the first year, total annual N uptake mirrored forage DM production, but over half the annual N uptake for the biosolid treatments occurred during the first three defoliation harvests. There were no differences among the N and biosolid treatments in the second year for cumulative forage production or N uptake. Based on these studies, use of spiked tine aeration equipment on kikuyugrass pastures on Hawaiian Hydrudands can not be recommended and the potential of sewage biosolids as a slow release N source should be further investigated.

INTRODUCTION

Kikuyugrass has been estimated to account for about 85% of the pasture production in Hawaii and is common in tropical highland and subtropical environments throughout the world (Hanna et al., 2004). There is a large database to support kikuyugrass fertilization with N and P during stand establishment and in young pastures (Hanna et al., 2004; Mathews et al., 2004). However, there are limited data for responses to soil management practices such as fertilization and aeration in old kikuyugrass pastures (Theron et al., 1958; Morrison, 1966; Miles, 1997). Morrison (1966) found that kikuyugrass production on a pH 5.0 red clay loam (Ultisol) in Kenya that had not received fertilizer for 12 yr was increased by N and P fertilization. In contrast, while working with similar soils in South Africa, Miles (1997) found that provided the Ambic soil test (0.25 M NH4CO3 + 0.01 M NH4F +

0.05 g L-1 Superfloc at pH 8.0) P was greater than about 10 mg kg-1, only N fertilizer was essential in restoring unproductive 10- to 15-yr old kikuyugrass pastures. Miles (1997) also found that productive kikuyugrass pastures that had received 300 ± 50 kg N ha-1 yr-1 for over 5 yr continued to require similar annual N inputs in order to maintain productivity as there was little residual effect. The six-month study of Fukumoto and Yamasaki (2003) on an Andisol in Hawaii indicated that kikuyugrass production would be reduced by about 50% if N fertilization was discontinued after 30+ yr of urea applications (~250 kg N ha-1 yr-1).

Production declines in old kikuyugrass swards have also been attributed to soil compaction and a phenomenon referred to as mat- or root-bound (Theron et al., 1958; Morrison, 1966). It is common for a 2- to 4-cm thick compacted layer to form near the surface of fine-textured pasture soils (Vicente-Chandler and Silva, 1960; Greenwood and McKenzie, 2001). Aeration with spiked tine aerators is being utilized by some ranchers in Hawaii in an attempt to enhance productivity of old kikuyugrass pastures. Aeration of kikuyugrass pasture surface soil with a rotovator that penetrated to a depth of 5 cm and destroyed the mat was of little benefit in kikuyugrass pasture renovation in Kenya (Morrison, 1966). However, the work of Theron et al. (1958) in South Africa suggests that deeper disturbance of the topsoil for aeration could be beneficial.

Urea is the main N fertilizer used on established pastures because it is relatively inexpensive, but it is often inefficient in terms of N recovery even when applied in several split applications over the growing season (Prasertsak et al., 2001; Mathews et al., 2004). It is important to investigate alternative slower-release N sources that would have the added benefit of requiring less frequent applications and hence lower application cost in manpower, equipment, and fuel (Muchovej and Rechcigl, 1997, 1998). While working in Florida, Muchovej and Rechcigl (1997) found strong residual effects in the second year for bahiagrass (Paspalum notatum Flügge) yield and N concentration when a heat-dried, pelletized sewage biosolid was applied in a single dose of 400 or 800 kg N ha-1. Perhaps even greater residual effects would be observed in an environment like Hawaii where such warm-season perennial grasses can grow year round and thereby possibly minimize the concern of potential N losses to the environment during winter. However, data are not available to address this suggestion.

B.W. Mathews, College of Agric., Forestry, and Nat. Resour. Manage., Univ. of Hawaii at Hilo, HI 96720-4091; J.R. Carpenter, Dep. of Human Nutr., Food, and Animal Sci., College of Trop. Agric. and Human Resour., Univ. of Hawaii at Manoa, Honolulu, HI 96822. *Corresponding author ([email protected]). Contribution published in Soil Crop Sci. Soc. Florida Proc. 66:24-34 (2007).



Table 1. Selected chemical characteristics of the pasture soils (0- to- 15-cm depth). Experiment 1 was conducted on the unfertilized pasture while experiment 2 was conducted on the long-term (> 30 yr) N + P fertilized pasture.

Pasture pH† PMT† Exchangeable cations†

FeOX‡ OC† Ca2+ Mg2+ K+ Na+ Al3+

---------------------------------- mg kg-1 ------------------------------------ -------- g kg-1 ------ Unfertilized 5.8 12 3676 718 542 102 bd§ 116.0 172.4 Fertilized 5.2 68 2018 576 408 21 31 116.9 169.9 † Soil pH (saturated paste), modified-Truog extractable P (PMT), neutral 1 M NH4OAc exchangeable cations, and organic C (OC) determined by the methods outlined by Hue et al. (2000). ‡ Sodium oxalate (0.2 M, pH 3.0) extractable Fe (Mathews et al., 2005). § bd = below reliable detection limit.

The present study was conducted under grazing

conditions because kikuyugrass is not managed for mechanical harvesting in Hawaii. Furthermore, there is a tendency for clipped plot experiments to overestimate fertilizer requirements and underestimate productivity compared to grazing (Mathews et al., 2004). Specific objectives of the 2-yr study were: 1) to compare kikuyugrass productivity and plant and soil mineral status with and without aeration and three levels of fertilization (unfertilized control, N fertilized, and fertilized with N + P) on a long-term unfertilized pasture, and 2) to make similar comparisons on a long-term N- and P-fertilized pasture for the N alone and N + aeration treatments outlined above and additionally, an annual 1N (300 kg N ha-1 yr-1) biosolid application (B-A1N) applied each spring and a single 2N (600 kg N ha-1) biosolid application (B-S2N) applied at study initiation, both based on the total N amount applied to the N fertilized treatments during the study period.


Two simultaneous experiments were conducted during 2001-2003 in 0.2 ha portions of adjacent 1.2 ha kikuyugrass pastures that had been established in 1964 on a Maile silt loam soil (hydrous, ferrihydritic, isothermic Acrudoxic Hydrudands) at the University of Hawaii’s Mealani Experiment Station (elevation = 900 m) located in Waimea (20o01'N), Island of Hawaii. Experiment 1 was conducted in a nearly weed-free area of a sometimes over-grazed pasture that had received no fertilizer inputs since establishment (unfertilized). Experiment 2 was conducted on a pasture that received better grazing management and regularly received 250 ± 100 kg N ha-1 yr-1 as urea and periodic applications of P as treble superphosphate (Mathews et al., 2001). Selected chemical properties of these soils are presented in Table 1. The lower exchangeable base cation concentrations in the N- and P-fertilized pasture are probably due to leaching associated with N fertilization and the effects of lower pH on cation retention (Mathews et al., 2001). Soil bulk density measured in 3-cm increments to a depth of 15 cm averaged 0.54 ± 0.03 Mg m-3 except for a compacted layer at the 3- to 6-cm soil depth which has a bulk density of 0.66 ± 0.03 Mg m-3 (Mathews et al., 2001). Both experiments commenced on 3 Apr 2001 following pasture defoliation with a sickle bar mower to a stubble height of 5 cm. The monthly temperature variation and rainfall distribution during the study period is presented in Figs. 1 and 2.

Month

Jan May Sep Jan May Sep Jan

Tem

per

atu

re, o

C0

10

20

30

40 Mean Monthly Maximum, 2001-2002 Mean Monthly Minimum, 2001-2002Mean Monthly Maximum, 2002-2003Mean Monthly Minimum, 2002-2003

Figure 1. Mean monthly temperature variation during the study.

Month


Rai

nfa

ll, m

m

0

100

200

300

400

500

600

2001-2002, Total = 1975 mm2002-2003, Total = 1459 mm

Figure 2. Monthly rainfall distribution during the study.

Experiment 1

In experiment,1 a factorial treatment arrangement consisting of all combinations of three fertilizer managements (unfertilized control, N fertilized, and fertilized with N + P) and two aeration managements (undisturbed and aerated) was imposed for 2 yr in a randomized block design (six treatments total). There were two blocks with each treatment replicated twice in each block for a total of four replications per treatment. Each treatment plot was 4.6 by 6.1 m with a 1 m border between plots. One block had good internal drainage and

IL.:::.....:...; . _______ I '

'

0

0


occurred at the top of a pasture knoll. The other block was located in a flatter area between two knolls with somewhat restricted internal drainage, particularly following heavy rains. Mottling was readily apparent at a soil depth of 15 to 30 cm in the block with restricted drainage.

Aerated treatments received two parallel aeration passes at initiation of the study with an AerWay® spiked tine aerator (Model AW118, Holland Equipment Ltd., Norwich, ON, Canada) that was mounted on the three-point-hitch of a • 41-MW (55-HP) tractor. An additional 225 kg of weight was added to the aerator per the manufacturer’s suggestion. The 20-cm tines arranged in a spiral pattern around the shaft penetrated to a soil depth of 10 to12 cm and created 2-cm wide slits that were about 10 cm in length at the soil surface.

The N-fertilized treatments received applications equivalent to 60 kg N ha-1 at study initiation and after every other defoliation (once every 12 wks) for a total of 300 kg N ha-1 yr-1. In addition to N fertilization as described above, the N + P fertilized treatments received a single 300 kg P ha-1 application as treble superphosphate at study initiation.

Experiment 2

Drainage in the pasture area selected for experiment 2 was intermediate between that of the blocks in experiment 1. Experiment 2 consisted of four treatments arranged in a completely randomized design with four replications. Each treatment plot was 4.6 by 3.1 m with a 1 m border between plots. Treatments consisted of the N alone and N + aeration treatments outlined above for experiment 1, an annual 1N (300 kg N ha-1 yr-1) biosolid application (B-A1N) surface applied each spring based on the annual N application equivalent of the N fertilized treatments, and a single 2N (600 kg N ha-1) biosolid application (B-S2N) surface applied at study initiation based on the total N amount applied to the N fertilized treatments during the 2-yr study period. An anaerobically digested, heat-dried, granulated sewage biosolid marketed as Milorganite® (Milwaukee Sewage Commission, Milwaukee, WI) was selected for this experiment because it is fairly representative of a low heavy metal type of product (Table 2) that could be produced in Hawaii (Hue and Ranjith, 1994).

Forage Sampling, Chemical Analysis, and Defoliation by Mob Grazing

Every 6 wk a 1 m by 1.54 m strip of forage was collected from each plot by clipping to a stubble height of 5 cm immediately prior to defoliation by grazing. The harvested forage was weighed fresh and a 1 kg subsample used for DM determination and subsequent chemical analysis. Samples were dried for 1 wk at 55oC using a mechanical convection oven and DM production calculated. The dried samples were then ground to pass a 1-mm stainless steel screen using a Wiley Mill (Arthur H.

Table 2. The pH and elemental concentration of the anaerobically digested, heat-dried granulated sewage biosolid (Waters Agricultural Laboratories, Camilla, GA).

pH 5.9 S (g kg-1) 8.5 Total solids (g kg-1) 970 Na (g kg-1) 2.6 C (g kg-1) 340.5 Fe (g kg-1) 52.6 N (g kg-1) 62.2 Al (g kg-1) 10.2 C/N (ratio) 5.5 Zn (mg kg-1) 530 NH4-N (g kg-1) 1.0 Mn (mg kg-1) 390 P (g kg-1) 21.4 Cu (mg kg-1) 250 Citrate-extractable P (g kg-1) 20.0 B (mg kg-1) 40 Water-extractable P (g kg-1) 0.1 Mo (mg kg-1) 20 K (g kg-1) 7.5 Ni (mg kg-1) 30 Ca (g kg-1) 19.5 Pb (mg kg-1) 90 Mg (g kg-1) 5.9 Cd (mg kg-1) 10

Thomas Company, Philadelphia, PA). Nitrogen and neutral detergent fiber (NDF) were estimated by near infrared reflectance spectroscopy (Herrero et al., 1996) in experiment 1, while a LECO CNS 2000 combustion analyzer (LECO Corp., St. Joseph, MI) was used to measure N in Experiment 2. Tissue concentrations of P, K, Ca, Mg, S, Na, Fe, Mn, Zn, Cu, and B were determined by inductively coupled plasma emission spectroscopy (ICPES) following digestion in nitric acid and hydrogen peroxide as outlined by Jones and Case (1990). Concentrations of Al, Cd, Ni, and Pb were also determined by ICPES in experiment 2.

Forage N uptake was estimated as the product of forage DM production and N concentration. Apparent fertilizer N recovery was calculated for the N and N + P fertility managements in experiment 1 by subtracting the total N uptake from the control fertility management from that of the respective fertilized management and dividing by the quantity of N applied, the result being expressed on a percentage basis (Mathews et al., 2004).

Following forage sampling, mixed breed mature cows (Bos spp., 250 head ha-1) were allowed to mob graze (Mislevy et al., 1981) the paddock containing the experimental plots and consume the forage down to a 5-cm stubble height within a 1-d period. Any clumps of forage not grazed by the cattle were clipped and discarded outside the plots.

Soil Sampling and Analysis

Immediately following the last defoliation of the experiment, soils were sampled at the 0- to 15-cm depth for experiment 1 and the 0- to 15- and 15- to 30-cm depths for experiment 2. The samples were obtained by collecting a well-mixed composite of 12 cores (2-cm diam) from each plot. The composited samples for each plot were sieved through a 4-mm screen. The soil samples were maintained field moist for analysis and results are reported on an oven-dry (100oC) soil equivalent basis. All samples were analyzed for pH (saturated paste), modified Truog (0.01 M H2SO4 + 0.02 M [NH4]2SO4) extractable P (PMT) by the molybdenum-blue colorimetric method; neutral 1 M NH4OAc exchangeable Ca, Mg, and K by ICPES; and KCl extractable NH4-N and NO3-N by the phenate and Cd-


reduction colorimetric methods (Hue et al., 2000). In order to determine the short-term effect of P fertilization on PMT the treatments receiving P applications in experiment 1 were also sampled 3 mo after the study started.

Statistical Analyses

Data were analyzed by using Proc GLM of the Statistical Analysis System (SAS Inst., 1999) using the appropriate models for a randomized block design with treatment replication within each block (generalized randomized block design) in experiment 1, and a completely randomized design in experiment 2 (Hinkelmann and Kempthorne, 1994). Year was considered a sub-plot. Treatment by sampling date interactions and comparisons of responses among sampling dates within a year were determined using repeated measures analysis of variance procedures and associated contrasts (Hinkelmann and Kempthorne, 1994). Season-long averages for forage nutrient concentration were calculated as weighted means using the DM production data for all sampling dates within each of the two years. Treatment mean comparisons were made by Fisher’s F-test protected LSD test at the 0.05 level of significance unless otherwise noted.


Experiment 1

There were no interactions for aeration or fertility management by year (P > 0.35), aeration by fertility management (P > 0.29), block by aeration management (P > 0.19) or block by fertility management (P > 0.18) for the plant responses measured. Aeration management had no effect on kikuyugrass DM production (P > 0.49) or chemical composition (P > 0.14). Apparently, the narrow zone of compaction at the 3- to 6-cm soil depth was not severe enough for kikuyugrass to respond to aeration. Previous work with sugarcane (interspecific hybrids of Saccharum spp.) growing on Hydrudands in Hawaii has demonstrated that reductions in root growth and yield may be observed from compaction similar to that observed for the pastures in the present study, but serious reductions may not be observed until the soil bulk density is 0.75 g cm-3 (Trouse and Humbert, 1961; Uehara et al., 1981). When yield is reduced from compaction in Hydrudands, it is presumably the result of low macroporosity because total porosity is obviously very high (Gavenda et al., 1996).

Fertility management responses (P < 0.05) were observed for DM production and forage N, P, K, Ca, Mg, and Fe concentration. There were also fertility management by defoliation date interactions for DM production (P < 0.06) in both years and for N (P < 0.002) in the second year. However, examination of the data by date indicated that these interactions resulted from differences in magnitude of response rather than changes

in direction of response (data not shown). Therefore, the fertility management responses for cumulative DM production and forage N and minerals are presented together as study-long means (Table 3). Defoliation date effects on DM production averaged across managements are presented in Fig.3. They followed the pattern typically observed in the subtropics, of lower production during the short-photoperiod winter months (Dec. - April) (Sinclair et al., 2001; Mathews et al., 2004).

Month


Mea

n D

M p

rod

uct

ion

(M

g h

a-1 )

0

1

2

3

4

5

2001-2002, SE = 0.12002-2003, SE = 0.1

Figure 3. . Effect of defoliation date on mean kikuyugrass DM production in experiment 1. Differences of > 0.3 Mg ha-1 within a year are different at P < 0.05.

There were also defoliation date effects (P < 0.001) for NDF (Fig 4). In general, these data showed the expected trend towards reduced fiber concentrations during late winter/early spring (March-April) and increased concentrations during mid summer (July-August) (Carpenter et al., 1998; Hanna et al., 2004). Some producers in Hawaii attempt to better balance forage nutritive value and demand by grazing kikuyugrass

Month


ND

F (

g k

g-1

)

500

550

600

650

700

750

2001-2002, SE = 6.42002-2003, SE = 8.8

Figure 4. Effect of defoliation date on mean kikuyugrass neutral detergent fiber (NDF) concentration in experiment 1. Differences of > 18 and 26 g kg-1 are different at P < 0.05 in 2001-2002 and 2002-2003.

0

0


Table 3. Influence of fertility management on mean annual cumulative DM production; concentrations of N, P, K, Ca, Mg, and Fe; unit DM production increase per unit N fertilizer applied, and the Ca:P ratio for kikuyugrass herbage during 2001-2003 in experiment 1.

Fertility Management

DM Production

Nutrient Concentrations† Unit DM/unit N Ca/P

N P K Ca Mg Fe Mg ha-1 ------------------------------------ g kg-1 ----------------------------------- mg kg-1 Control 11.87b‡ 22.3b 1.9b 22.8b§ 5.3a 2.0b 1008a ------ 2.8a N 16.84a 23.7a 1.8b 25.2a 4.6b 2.0b 835b 16.6a 2.6a N + P 18.38a 23.9a 2.9a 26.5a 4.9ab 2.2a 621b¶ 21.7a 1.7b SE# 1.36 0.4 0.05 1.1 0.2 0.04 64 5.0 0.1 † Concentrations are weighted experiment-long means. ‡ Fertility management means in the same column not followed by the same letter are different at P < 0.05 using Fisher’s F-test protected LSD test unless otherwise noted. § Management means for K not followed by the same letter are different at P < 0.10. ¶ Differs from the N fertility management at P < 0.10. # Standard error of a fertility management mean.

pastures every 4 rather than every 6 wk during the summer (Hanna et al., 2004). This management strategy can improve animal performance by decreasing forage fiber concentrations and thereby increasing animal intake of digestible organic matter (Hanna et al., 2004).

Defoliation date effects on kikuyugrass mineral composition were relatively minor (data not shown) compared to those observed for forage DM production and NDF as previously noted for the study site (Carpenter et al., 1998). The reader interested in seasonal effects on kikuyugrass mineral composition at the study site is referred to Humphreys et al. (2005). They examined all mineral data collected from kikuyugrass pasture trials conducted at the Mealani Experiment Station between 1988 and 2003, including the present study.

Kikuyugrass DM production responded to both the N and N + P managements, but the trend towards greater DM production with N + P than N alone was not significant (Table 3). This occurred despite the possibility of marginal plant P deficiency for N alone (mean P = 1.8 g kg-1) in addition to the control (Table 3). The critical P concentration for whole shoots of 6-wk old kikuyugrass is thought to be about 2.1 ± 0.1 g kg-1 while grazing ruminants require approximately 2.5 g kg-1 (Mathews et al., 2004). Both N and N + P fertilization increased kikuyugrass N and K (Table 3), but these managements did not differ from each other. It is well-known that N fertilization can stimulate increases in forage grass N and K concentrations (Tamimi et al., 1981; Mathews et al., 2004). Nitrogen fertilization can increase K concentration if adequate soil K is available for uptake, but N fertilization of low soil K pastures will result in decreased grass K concentration due to the dilution effects associated with greater DM production (Tamimi et al., 1981). The unit DM production increase per unit N applied (Table 3) was in the lower end of the expected (13 to 48) range, as was apparent N recovery (Miles, 1997; Hanna et al., 2004; Mathews et al., 2004). Apparent N recovery was 45 and 58% for the N and N + P fertility managements (SE = 13). These types of responses may reflect gaseous losses of N from the system, particularly in the block with restricted drainage where there may have been substantial denitrification (Prasertsak et al., 2001; Mathews et al.,

2004). Regardless, a major factor influencing N recovery was the 40% lower average DM production observed (P < 0.001) for the block with restricted drainage (mean = 11.74 Mg ha-1 yr-1 ) compared to the well-drained block (mean = 19.65 Mg ha-1 yr-1). It also should be noted that an estimate of N in the roots was not obtained and would account for some of the “missing” N.

Nitrogen fertilization alone slightly decreased forage Ca compared to the control while the N + P fertility management did not differ from either of the other fertility managements (Table 3). The wide (> 2:1) Ca/P ratios (Table 3) for the control and N alone managements are unusual for kikuyugrass (Hanna et al., 2004; Mathews et al., 2005) and can be attributed in part to the relatively high soil Ca coupled with low soil test P for the long-term unfertilized pasture used in this experiment (Table 1). In addition, the block with restricted drainage also produced forage with greater (P < 0.001) average Ca (mean = 5.8 g kg-1) than the well-drained block (mean = 4.0 g kg-1). It is well established that the solubility of exchangeable Ca often increases under the higher soil moisture conditions of restricted drainage (Patrick et al., 1985). Fertilization with P slightly increased forage Mg (Table 3). If plants have adequate P, one model suggests that Mg uptake is enhanced by phosphorylation of Mg transport proteins on the root plasmalemma (Reinbott and Blevins, 1994). Both N and particularly N + P fertilization decreased forage Fe relative to the control (Table 3). The effect of N on forage Fe concentration can be attributed to dilution resulting from greater DM production while the P effect is probably due in part to the precipitation of amorphous Fe-phosphates (Mathews et al., 2005). Humphreys et al. (2005) previously observed that pastures at the Mealani Experiment Station with a history of P fertilization had much lower forage Fe concentrations than unfertilized pastures with soil P concentrations similar to the control fertility management in the present study. The overall high forage Fe concentrations can be attributed in part to the high concentrations of extractable Fe in the ferrihydritic Maile soil (Table 1). Examination of the University of Hawaii’s kikuyugrass forage data base indicated that it is not uncommon to observe Fe concentrations in the 500 to 1000 mg kg-1 range for forage grown on ferrihydritic


Table 4. Influence of treatment and defoliation date on kikuyugrass DM production in experiment 2. Treatment

Defoliation Total

1 2 3 4 5 6 7 8 9 10 -------------------------------------------------------------------------------- Mg ha-1 --------------------------------------------------------------------------------- 2001-2002 15 May 26 June 7 Aug. 18 Sep. 30 Oct. 11 Dec. 22 Jan. 5 March 16 April 29 May N 1.43b† 1.17c 1.76b 1.73a 1.76c 1.07a 0.17b 0.52a 0.54c 0.69b 10.84c N + aeration 1.88b 1.80bc 1.88b 1.80a 1.60c 0.85a 0.27b 0.40a 0.75c 1.06b 12.30c B-A1N 3.54a 2.62ab 1.85b 1.72a 2.33b 1.03a 0.46ab 0.31a 2.17b 0.97b 16.98b B-S2N 4.23a 3.29a 3.15a 1.90a 3.04a 1.54a 0.74a 0.40a 2.98a 1.69a 22.96a SE‡ 0.37 0.34 0.29 0.18 0.17 0.22 0.10 0.06 0.24 0.15 1.10 2002-2003 8 July 20 Aug. 1 Oct 13 Nov. 23 Dec. 3 Feb. 17 Mar. 28 April 10 June 21 July N 1.63ab 1.38a 2.20a§ 0.85a 1.29a§ 0.40a 0.81a 1.23a 3.56ab§ 2.18b§ 15.52a N + aeration 1.36bc 1.73a 2.28a 0.70a 0.93ab 0.55a 0.86a 1.20a 3.83a 2.35ab 15.80a B-A1N 2.17a 1.99a 2.24a 1.11a 0.68b 0.60a 0.31b 1.07a 2.68c 2.13b 14.98a B-S2N 0.81c 1.48a 1.52b 1.11a 0.85b 0.60a 0.53ab 2.10a 2.82bc 2.77a 14.59a SE‡ 0.21 0.28 0.20 0.23 0.15 0.10 0.11 0.44 0.31 0.16 0.90 † Treatment means in the same defoliation date column not followed by the same letter are different at P < 0.05 using Fisher’s F-test protected LSD test unless otherwise noted. ‡ Standard error of a treatment mean. § 2002-2003 treatment means for 1 Oct., 23 Dec., 10 June, and 21 July not followed by the same letter are different at P < 0.10.

Udands, while concentrations for kikuyugrass grown on other upland soils typically range from 100 to 400 mg kg-1. In addition, the block with restricted drainage produced forage with greater (P = 0.004) Fe concentration (mean = 943 mg kg-1) than the well-drained block (mean = 683 mg kg-1), probably due to increased solubility of Fe2+ resulting from reducing conditions in the subsoil (Patrick et al., 1985). According to NRC (2005), dietary Fe levels of 500 mg kg-1 or more can result in reduced ruminant performance depending on the bioavailability of Fe in the feed.

There were no significant management effects (P > 0.11) for plant S (mean = 2.0 g kg-1; SE = 0.05), Na (mean = 2180 mg kg-1; SE = 176), B (mean = 9 mg kg-1; SE = 0.3), Mn (mean = 124 mg kg-1; SE = 17), Zn (mean = 33 mg kg-1; SE = 1), and Cu (mean = 10 mg kg-1; SE = 0.2). These concentrations were all within the expected ranges for normal growth of kikuyugrass and grazing ruminants (Tamimi et al., 1981; Mathews et al., 2004) and similar to the long-term study of Humphreys et al. (2005).

While soil PMT increased as expected from the initial concentration of 12 mg kg-1 for the aerated and non-aerated managements receiving N + P, there were no differences between these treatments 12 wk after P fertilization (P = 0.35, mean PMT = 38 mg kg-1; SE =1). At the end of the study there were fertility responses (P < 0.001; SE =1) only for soil NO3-N and PMT but not soil pH or the other soil nutrients measured. Nitrate-N was greater for the N (mean = 20 mg kg-1) and N + P (mean = 18 mg kg-1) managements than the control (mean = 11 mg kg-1). For PMT, the N + P management had a greater concentration (24 mg kg-1) compared to the N alone (14 mg kg-1) and control (15 mg kg-1) managements. The decline in PMT for the N + P management since the sampling that occurred 12 wk after P fertilization can be attributed in part to the continuing slow reactions of fertilizer P with the pasture soil (Burkitt et al., 2002). The PMT concentrations for the control and N alone managements did not change during the study period. As

previously noted for a long-term grazing study at the Mealani Experiment Station (Mathews et al., 2001), P mineralization and P recycling via the cattle dung were apparently able to maintain the relatively stable but low PMT concentration for the control and N alone managements. The present study also indicates that old established kikuyugrass pasture responds fairly well to N fertilization alone at nearly half the 25 mg kg-1 PMT concentration recommended during kikuyugrass stand establishment on Hawaiian Andisols (Tamimi, 1972). Mean soil pH was 5.7 and the means for extractable NH4-N (SE = 1), exchangeable K (SE = 51), Ca (SE = 98), and Mg (SE = 40) were 7, 411, 3335, and 578 mg kg-1, respectively.

Experiment 2

There were treatment (P < 0.001), treatment by year interaction (P < 0.001), and treatment by defoliation date interaction (P < 0.06) effects for kikuyugrass DM production, N concentration, and N uptake. Over the 2-yr study period, B-S2N produced more (P < 0.05) total forage (mean = 37.55 Mg ha-1) than B-A1N (mean = 31.96 Mg ha-1) which in turn produced more (P < 0.10) forage than N + aeration (28.10 Mg ha-1) and (P < 0.05) N alone (mean = 26.36 Mg ha-1). There were dramatic DM production responses to B-A1N and B-S2N compared to the N and N + aeration treatments for the first two defoliation dates in 2001-2002 (Table 4). Responses were inconsistent the remainder of the first year, particularly for the B-A1N treatment. There were no treatment effects for DM production on 18 September, 11 December, and 5 March. Regardless, cumulative DM production for B-A1N and B-S2N in 2001-2002 was 1.5 ± 0.1 and 2.0 ± 0.1 fold greater than the N and N + aeration treatments, which did not differ. These first year responses are tremendous compared to the observations of Cogger et al. (2004) with established plots of tall fescue (Festuca arundinacea Schreb.) in Washington, with a six-mo growing season, and using the same heat-dried biosolid source used in the present study. Cogger et al. (2004) found that a single 488


Table 5. . Influence of treatment and defoliation date on kikuyugrass N concentration in experiment 2.

Treatment Defoliation

Total 1 2 3 4 5 6 7 8 9 10

-------------------------------------------------------------------------------- g kg-1 ------------------------------------------------------------------------------------- 2001-2002 15 May 26 June 7 Aug. 18 Sep. 30 Oct. 11 Dec. 22 Jan. 5 March 16 April 29 May N 33.0bc‡§ 28.1c 27.2b 24.7bc 25.7c 28.0b 28.2c 25.9a 23.1a 20.0a 26.9c N + aeration 30.1c 27.7c 27.2b 23.0c 25.8c 29.3b 31.1bc 27.1a 22.9a 20.4a 26.5c B-A1N 36.3ab 32.4b 29.2b 26.3b 30.1b 29.4b 34.0b 26.9a 21.0a 21.4a 29.6b B-S2N 39.2a 36.4a 35.3a 33.2a 37.2a 35.2a 39.9a 31.0a 23.8a 22.9a 33.9a SE¶ 2.4 0.7 0.9 0.9 1.1 1.2 1.3 1.6 0.8 0.9 0.7 2002-2003 8 July 20 Aug. 1 Oct 13 Nov. 23 Dec. 3 Feb. 17 Mar. 28 April 10 June 21 July N 30.6ab 27.1a 26.6a 24.3a 32.7a 29.9a 31.3ab 25.5a 25.6a 27.8a 27.6a N + aeration 28.1b 25.2a 26.0a 24.7a 33.9a 30.6a 31.7a 27.2a 24.7a 30.1a 27.5a B-A1N 34.6a 28.8a 28.7a 25.8a 34.5a 26.2a 25.1c 26.5a 27.8a 28.4a 28.8a B-S2N 26.2b 26.7a 25.8a 25.7a 35.5a 28.4a 27.7bc 28.6a 26.0a 28.9a 27.6a SE¶ 1.6 1.3 1.9 1.4 2.1 2.0 1.3 0.9 2.0 1.4 0.7 † Weighted season-long means. ‡ Treatment means in the same defoliation date column not followed by the same letter are different at P < 0.05 using Fisher’s F-test protected LSD test unless otherwise noted. § Treatment means for 15 May not followed by the same letter are different at P < 0.10. ¶ Standard error of a treatment mean.

kg N ha-1 application of the biosolid produced a total first year yield equivalent to that obtained with 200 kg N ha-1 applied as ammonium nitrate in three split applications. The relative efficacy of sewage biosolids compared to split applications of soluble ammoniacal fertilizers in producing forage varies with the source material, soil and environmental conditions, defoliation management, and their impact on mineralization and N losses (Muchovej and Rechcigl, 1997; Epstein, 2003; Corrêa et al., 2005). Considering the large first-year responses to the biosolid treatments in the present study, the possibility of a stimulatory (priming) effect of biosolid application on the mineralization of extra soil organic N for plant growth should be further explored with high organic C soils such as the Maile soil (Sastre et al., 1996; Stevenson and Cole, 1999).

During 2002-2003, DM production responses in the present study were inconsistent and cumulative DM production did not differ among treatments (Table 4). With the exception of the first defoliation date (8 July) of 2002-2003, the lack of greater response to the second application of biosolids for B-A1N may have been due to leaching and denitrification of readily mineralized N (Mathews et al., 2004). This could have resulted from the moderately heavy July rainfall (220 mm, Fig. 2) coupled with existing high moisture soil conditions due to the unusually heavy rainfall near the end of the first year (Jan.- March 2001-2002) (Fig. 2). In contrast rainfall was light (< 80 mm mo-1) for the first four months (April-July) following biosolid application during 2001-2002.

In general, the kikuyugrass N concentration and N uptake data mirrored the DM production response except that the responses to B-S2N persisted through most of 2001-2002 (Tables 5 and 6). The cumulative N uptake for B-A1N and B-S2N during 2001-2002 was 1.6 ± 0.1 and 2.5 ± 0.2 fold greater than the N and N + aeration treatments, which did not differ. About 52 ± 1% of the 2001-2002 cumulative N uptake for B-A1N and B-S2N

was obtained from the first three defoliation harvests. Muchovej and Rechcigl (1997) and Cogger et al. (2004) made similar observations for the first few harvests while studying bahiagrass and tall fescue responses to heat-dried biosolids. Sartain et al. (2004) conducted a 6-mo laboratory incubation experiment with the equivalent of 1000 kg N ha-1 of the sewage biosolid used in the present study. They found that 33% of the applied N was released during the first 12 wk with only an additional 7% of the applied N being released during the last 14 wk of incubation. The observations of these investigators coupled with the observations in the present study indicate that after an initial period of rapid N release, subsequent N release from heat-dried biosolids is slow. Mean annual N concentration and cumulative N uptake did not differ among treatments in 2002-2003. As aforementioned for DM production, the lack of greater N concentration and N uptake response to the second application of biosolids for B-A1N may have been due to losses of readily mineralized N during the moderately heavy July rainfall. Over the 2-yr study period, however, B-S2N had a greater (P < 0.05) total N uptake (mean = 1185 kg ha-1) than B-A1N (mean = 932 kg ha-1) which in turn had a greater (P < 0.05) total N uptake than the N + aeration (761 kg ha-1) and N alone (mean = 722 kg ha-1) treatments.

As observed by Waddington et al. (1994) while working with perennial ryegrass (Lolium perenne L.) growing on a Typic Hapludalf in Pennsylvania, the biosolid material used in the present study slightly increased (P < 0.05) forage S and Zn. There were no treatment by year interactions (P > 0.89) for these nutrients. Mean S concentration (SE =0.1) was greater for B-A1N and B-S2N (2.6 g kg-1 for both) than the N alone and N + aeration treatments (2.4 g kg-1 for both). Likewise, mean Zn concentration (SE = 1) was greater for B-A1N and B-S2N (39 mg kg-1 for both) than for N + aeration (34 mg kg-1) and N alone (33 mg kg-1). There were no treatment effects (P > 0.14) for forage Ca (mean = 3.0 g kg-1; SE = 0.1), Mg (mean = 3.2 g kg-1; SE = 0.2), P


Table 6. Influence of treatment and defoliation date on kikuyugrass N uptake in experiment 2.

Treatment Defoliation

Total 1 2 3 4 5 6 7 8 9 10

-------------------------------------------------------------------------------- kg ha-1 ----------------------------------------------------------------------------------- 2001-2002 15 May 26 June 7 Aug. 18 Sep. 30 Oct. 11 Dec. 22 Jan. 5 March 16 April 29 May N 51b† 33c 48b 42b 45c 29b 5b 13a 12c 14b 293c N + aeration 57b 50c 52b 41b 42c 26b 9b 11a 17c 22b 326c B-A1N 127a 85b 54b 45b 70b 30b 16b 8a 45b 21b 502b B-S2N 166a 120a 111a 63a 113a 54a 30a 12a 71a 38a 778a SE‡ 16 11 10 4 6 7 4 2 6 3 34 2002-2003 8 July 20 Aug. 1 Oct 13 Nov. 23 Dec. 3 Feb. 17 Mar. 28 April 10 June 21 July N 51b 36a 58a 21a 41a 12a 25ab 32a 92a 60b 428a N + aeration 38bc 43a 60a 17a 32a 18a 27a 33a 97a 70ab 435a B-A1N 74a 57a 64a 29a 24a 15a 8c 28a 73a 60b 430a B-S2N 22c 39a 40a 30a 30a 17a 15bc 61a 74a 81a 407a SE‡ 7 7 7 7 5 3 3 13 12 5 32 †Treatment means in the same defoliation date column not followed by the same letter are different at P < 0.05 using Fisher’s F-test protected LSD test. ‡Standard error of a treatment mean.

(mean = 3.6 g kg-1; SE = 0.1), Ca/P ratio (mean = 0.83; SE = 0.02), K (mean = 31.6 g kg-1; SE = 2.4), B (mean = 4 mg kg-1; SE = 1), Cu (mean = 9 mg kg-1; SE = 0.1), Fe (mean = 240 mg kg-1; SE = 28), Mn (mean = 105 mg kg-1; SE = 3), Na (mean = 316 mg kg-1; SE = 5) or Al (mean = 113 mg kg-1; SE = 18) concentration. There were also no treatment effects (P > 0.47) for Ni (mean = 0.67 mg kg-1; SE = 0.07), Pb (mean = 0.16 mg kg-1; SE = 0.02), or Cd (mean = 0.05 mg kg-1; SE = 0.01). The lack of heavy metal effects was expected considering the low concentrations in the biosolid (Epstein, 2003). Furthermore, Hydrudand soils strongly sorb heavy metals with their considerable concentrations of amorphous minerals and organic C (Hue et al., 1988).

The only forage mineral of concern from the plant nutrition standpoint was the low B concentration, which can be corrected through application of borax (Mathews et al., 2004). From the ruminant health standpoint, the major forage mineral concerns were a narrow Ca/P ratio < 1.0, a Na concentration that was half the sufficiency level, and a marginal Cu concentration (Mathews et al., 2004). These concerns are readily addressed through mineral supplementation (Mathews et al., 2004). The low Na concentration can be attributed to the low exchangeable Na level in this pasture soil compared to the pasture in experiment 1 (Table 1). The reader interested in the generally minor defoliation date effects (data not shown) on forage mineral composition is referred to Carpenter and Mathews (2006).

There were no treatment effects (P > 0.15) for soil pH (mean = 5.0); exchangeable Ca (mean = 1930 mg kg-1; SE = 99), Mg (mean = 547 mg kg-1; SE = 44), and K (mean = 351 mg kg-1; SE = 56); or extractable NO3-N (mean = 22 mg kg-1; SE = 4) and NH4-N (mean = 15 mg kg-1; SE = 1) at the 0- to 15-cm depth. The only soil nutrient response that occurred at the 0- to 15-cm depth was for PMT. Both B-A1N (mean = 117 mg kg-1) and B-S2N (mean = 107 mg kg-1) had greater (P < 0.05; SE = 7) PMT concentrations compared to the N (mean = 72 mg kg-1) and N + aeration (mean = 73 mg kg-1) treatments. The biosolid treatments resulted in the application of 205 kg P ha-1; excess P

delivered to soils is an inherent consequence of sewage biosolids applied at agronomic N rates (Epstein, 2003). Sewage biosolids have narrow N:P ratios (3:1 in the present study) but plants require 7 to 15 times less P than N. This soil P buildup occurs particularly quickly in grazed pastures because most of the P is recycled via dung rather than removed from the system in marketed products (Mathews et al., 2004). Phosphorus buildup in pasture soils is primarily an environmental concern for soils with a limited capacity to sorb P because of the increased possibility that runoff losses could contribute to eutrophication of surface waters (Mathews et al., 2005). This is not a major concern for the Maile soil (Mathews et al., 2005). At the 15- to 30-cm depth, there were no treatment effects (P > 0.27) for soil pH (mean = 5.5); extractable PMT (mean = 24 mg kg-1; SE = 2), exchangeable Ca (mean = 2225 mg kg-1; SE = 111), Mg (mean = 320 mg kg-1; SE = 25), and K (mean = 161 mg kg-

1; SE = 29); or extractable NO3-N (mean = 15 mg kg-1; SE = 2) and NH4-N (mean = 9 mg kg-1; SE = 2).

CONCLUSIONS

Aeration did not significantly affect productivity of grazed kikuyugrass. Forage DM production on a pasture soil with a low PMT concentration was increased by N fertilization. Phosphorus fertilization, however, did not significantly increase N response despite marginal forage P concentration. A simultaneous study conducted on a pasture soil with a high PMT concentration indicated that a heat-dried biosolid was more effective than N applied as urea in terms of cumulative forage production and N uptake during the first year. There were no treatment differences in the second year for cumulative DM production or N uptake. However, a single 2N application of biosolids applied in the first year showed a residual effect in the following year for forage production and N uptake that was equivalent to 300 kg N ha-1 applied as urea in five split applications. Moderately heavy rainfall in the second month after the year 2 biosolid application may have reduced response to the B-A1N treatment through N leaching and denitrification losses from the rapidly released N pool. In the first year, N uptake mirrored forage DM production but over half the annual N uptake


for the biosolid treatments occurred during the first three defoliation harvests. These results suggest that after an initial period of rapid N release, subsequent N release was slow for the biosolid studied.

Based on these studies, use of spiked tine aeration equipment on kikuyugrass pastures on Hawaiian Andisols can not be recommended, and the potential of sewage biosolids as a slow release N source should be further investigated. The influence of heavy rainfall on N losses from freshly applied biosolids is of particular interest. Phosphorus fertilization of established kikuyugrass pastures with low soil PMT concentration may not lead to a significant increase in DM production at an annual N fertilizer rate of 300 kg N ha-1, but can increase forage P.

ACKNOWLEDGEMENTS

Funding for this research was provided by the County of Hawaii, Department of Research and Development; and the University of Hawaii at Hilo’s Hutchinson Fund for Applied Agricultural Research. Thanks are extended to Ms. Mary Kaheiki for her assistance in forage sample drying, grinding, and analysis.

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Population Abundance and within Plant Distribution of Frankliniella thrips in Cotton

E.A. Osekre*, D.L. Wright, and J.J. Marois

ABSTRACT

Population dynamics and within-plant distribution of Frankliniella spp. thrips in cotton were determined during summer 2005 at Quincy, FL. Frankliniella tritici (Fitch) accounted for more than 98% of the adult thrips in the samples. The adults of F. bispinosa (Morgan), F. occidentalis (Pergande), and F. fusca (Hinds) were also collected. Populations of F. fusca inhabited the cotton leaves prior to flowering. The other species were highly anthophilic, primarily inhabiting cotton during its reproductive growth stages. Thrips densities peaked during mid-season which also coincided with peak bloom. Adult F. tritici and the larvae were more aggregated in the flowers than other plant parts. No F. fusca, F. bispinosa or F. occidentalis were found on cotton squares. Mean densities of adult F. tritici per square per week were less than one and that of adult F. occidentalis and F. bispinosa per leaf or flower never exceeded 0.1 throughout the study period. Larval thrips densities were less than one per leaf or square or flower for most part of the study. This is the first report of population dynamics and within-plant distribution of individual thrips species determined for cotton in the southern USA.

Key words Cotton, Frankliniella tritici, population dynamics, thrips, Thysanoptera

INTRODUCTION

Frankliniella thrips (Thysanoptera: Thripidae) are ubiquitous, polyphagous pests of vegetables, fruits and ornamental crops (Hansen et al., 2003) and are able to feed in different microhabitats within a particular host plant (Kirk, 1997; Mound, 1997). A complex of Frankliniella spp. occurs throughout north Florida and the southeastern USA (Chellemi et al., 1994; Puche et al., 1995; Eckel et al., 1996). These species are highly anthophilic (Cho et al., 2000) and inhabit flowers of a variety of cultivated and uncultivated plants (Chellemi et al., 1994).

Several studies on the ecology and chemical response behavior of thrips are documented (Salguero Navas et al., 1991; Michelakis and Amri, 1997; Pearsall and Myers 2000; Ramachandran et al., 2001; Hansen et al., 2003; Whittaker and Kirk, 2004). Despite the similarity in appearance and overlapping host ranges of thrips species, they display different population dynamics (Cho et al., 2000; Ramachandran et al., 2001; Baez, 2002; Reitz, 2002). The reasons underlying these variations are unclear and appear to vary with the Frankliniella spp. and the host plant. These behavioral variations in thrips on different host plants emphasize the need to study the population

E.A. Osekre, D.L. Wright, and J. J. Marois, University of Florida, North Florida Research and Education Center, 155 Research Road, Quincy, FL 32351-5677, USA. This research was supported by Cerexagri and Cotton Inc. *Corresponding author: Email: [email protected] Contribution published in Soil Crop Sci. Soc. Florida Proc. 66:35-38 (2007).

dynamics of thrips on various crops to help determine how host plant architecture and plant phenology impact the within-plant distribution of thrips. Additionally, quantifying the within-plant distribution of Frankliniella thrips is important for the development of reliable and cost effective sampling protocols (Atakan et al., 1996) that will allow accurate estimation of the abundance and subsequent control of thrips in the crop. There is little published research on the population dynamics and within plant distribution of thrips species in cotton in the southeastern part of the USA; even though, thrips damage the leaves of vegetative-stage cotton (Bauer and Roof, 2004). The objectives of this study were to determine the population dynamics and within plant distribution of Frankliniella spp. thrips in cotton in north Florida.


Research plots were established at the North Florida Research and Education Center, University of Florida, Quincy (84O 33' W, 30O 36' N) in 2005. Cotton cultivar ‘DPL-445 Bt/RR’ (Delta Pine and Land Co., Scott, MS) was planted using a Monosem pneumatic planter (ATI Inc., Lenexa, KS) at 144,000 seeds ha-1 during the summer and the plots were maintained according to recommended production practices (Wright et al., 2007), unless otherwise stated. The experiment was four 100 m by 15 m blocks with 0.9 m row spacing. Plots were planted on 3 May, 2005. A broadcast application of 5-10-15 (N-P-K) at 225 kg ha-1 was made three days prior to planting. No fungicides or insecticides were applied to these plots.

Sampling of thrips

Samples were taken between 1100 and 1300 h Eastern Daylight Time. The above-ground parts of 40 plants (10 plants from each block) from each plot were randomly collected weekly for four consecutive weeks into separate 1.9-L plastic containers containing 70% ethyl alcohol and taken to the laboratory for processing. From the fifth week onward, four leaves from each of 40 plants (10 plants from each block) from each plot were sampled and subjected to the same laboratory procedure stated previously. Weekly samples of the reproductive parts of the plants began when 50% of the plants were flowering. Random samples of ten cotton squares or white flowers per block were placed individually in 60-ml bottles containing 70% ethyl alcohol. (Upland cotton cultivars are white on the first day of flowering, and they turn pink on the second day after pollination). Random samples of ten cotton bolls per block



were also collected and treated as described previously. Thrips were extracted and adult species and their sexes were determined and counted under a stereomicroscope at 40x based on their taxonomic features (body color, antennae, pigmentation, and ornamentation) (Mound and Kibby, 1998). The number of adult thrips of each species and the total number of larval thrips was determined for each sample. The larvae were grouped together since they could not be identified to species.

The data were subjected to analysis of variance of data pooled over date, and the treatment (plant parts) by block interaction was used as error term. Tukey’s procedure was used for means separations.

RESULTS

Population Dynamics of Frankliniella Thrips

Frankliniella tritici accounted for more than 98% of the adult thrips in the samples. The other thrips adults collected were F. bispinosa, F. fusca and F. occidentalis. F. fusca were the most abundant species found on the leaves during the first three weeks and declined greatly thereafter (Fig. 1). Low densities of F. bispinosa and F. occidentalis were recorded and no adult F. fusca, F. bispinosa and F. occidentalis were collected on cotton squares. Adult thrips species densities were less than one per square per week throughout the sampling period (Fig. 2). Likewise, weekly mean densities of F. occidentalis or F. bispinosa per leaf or flower were less than 0.1. The numbers of thrips larvae were less than one per leaf or per flower on nearly all sample dates (Figs. 1 and 3). The mean densities of adult F. tritici per leaf did not exceed 0.5. Adult thrips were highly anthophilic, with thrips population increasing rapidly on the plants with the onset of bloom, peaking around mid-season which also coincided with peak bloom, around late July (Fig. 3). Only adult F. tritici and larval thrips were collected on the bolls, and their respective densities per boll per week were less than 0.2 (Fig. 4).

Within-Plant Distribution of Frankliniella Thrips

There were significant (P < 0.0001) differences in the mean densities of F. tritici on the various parts of the plant. Only adult F. tritici and larval thrips were found on all parts of the plants. The majority (>90%) of the adult thrips were found in the flowers (data not shown). More larval thrips inhabited the leaves at the initial stages of bloom but this proportion declined in favor of the flowers with time.

DISCUSSION

Thrips species populations fluctuate throughout the year, influenced mainly by competition, availability of natural enemies and reproductive plant hosts. Frankliniella tritici appears to be the most abundant Frankliniella spp. on cotton during the summer in north Florida; with

May 18May 25

June 2June 9

June 15June 21

June 28July 5

July 12July 19

July 26Aug 1

Aug 8Aug 15

Aug 22

Thr

ips

per

leaf

0

2

4

6

8

F. tritici F. fusca Larval thrips

Figure 1. Mean densities (±SEM) of Frankliniella thrips on cotton leaves for weekly samples taken from 18 May through 22 August of 2005 at Quincy, FL.

June 28July 5

July 12July 19

July 26Aug 1

Aug 8Aug 15

Aug 22Sept 3

Sept 16

Thr

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0.00

0.02

0.04

0.06

0.08

0.10

0.12

0.14

0.16

0.18

F. tritici Larval thrips

Figure 2. Mean densities (±SEM) of Frankliniella thrips in cotton squares for weekly samples taken from 28 June through 16 September of 2005 at Quincy, FL.

July 12 July 19 July 26 Aug 1 Aug 8 Aug 15 Aug 22 Aug 29

Thr

ips

per

flow

er

0

10

20

30

40

50 F. tritici Larval thrips

Figure 3. Mean densities (±SEM) of Frankliniella thrips in cotton flowers for weekly samples taken from 12 July through 29 August of 2005 at Quincy, FL.

Aug 1 Aug 8 Aug 15 Aug 22 Aug 29

Thr

ips

per

boll

0.00

0.05

0.10

0.15

0.20

0.25

F. tritici Larval thrips

Figure 4. Mean densities (±SEM) of Frankliniella thrips on cotton bolls for weekly samples taken from 1 August through 29 August of 2005 at Quincy, FL.

I :

1-:- I


populations of the other species greatly reduced, possibly due to the effect of natural enemies on thrips spp. abundance (Chellemi et al., 1994). In their studies on tomato in north Florida, Salguero Navas et al. (1991) found large populations of F. occidentalis, F. tritici, and F. fusca between late April and early June, with greatest densities during May. Reitz (2002) found F. tritici was the predominant species in fall, with thrips population increasing rapidly on tomato plants soon after the onset of flowering in early September. Stavisky et al. (2002) found that thrips increased in early May on tomato, peaked in mid-May, and declined in early June in north Florida. It is unclear why low densities of F. bispinosa were recorded in our study; probably competition or other factors that regulate thrips populations affected it more.

Crop plants present changes in microhabitat as they grow in space and time and these changes impact the behavioral patterns and within-plant distribution of Frankliniella thrips. Thrips aggregate on leaves as the only source of food available in the initial stage of the plant growth but shift their aggregation to the more nutritious flowers when blooming begins. Adult thrips are more mobile and, therefore, traverse plants more rapidly than the larvae. Our findings that more than 90% of adult F. tritici population inhabited cotton flowers confirms the attractiveness of blooms to thrips, corroborating Teulon and Penman (1991) that pollen and nectar are important food sources for egg productivity of thrips. Heavy concentrations of adult thrips in flowers have been reported in pepper (Tavella et al., 1996; Funderburk et al., 2000; Hansen et al., 2003; Reitz et al., 2003). Higgins (1992) found more adult F. occidentalis in the flowers of greenhouse-grown pepper and cucumber (Cucumis sativa [L.]), but found more larvae on the leaves, in contrast to the consistently lower concentration of larval thrips found on cotton leaves in our studies when blooming began. Variations in the aggregation of adult Frankliniella spp. thrips and larvae on host plant parts may have resulted from differences in species behavior, mobility or predatory pressures. Plant host phenology may be an important factor in thrips abundance. Even though thrips may be more exposed to predation on the leaves than the squares and bolls, the leaves are preferred. The leaves serve as a more stable plant part for survival in terms of food (Funderburk et al., 2002), and as receptacle for eggs deposited by the females. Young leaves are exploited by adults when flowers are scarce (Toapanta et al., 1996). Predation may have contributed to the low populations of the larvae in our study. Previous studies (Ramachandran et al., 2001; Reitz et al., 2003) had shown greater predation of larval Frankliniella thrips than the adults by a predator of thrips, Orius insidiosus (Say), due possibly to low mobility of the larvae. Understanding thrips distribution within the cotton plant is a first step in developing sampling methods that will allow accurate estimation of the abundance of thrips in the crop.

REFERENCES

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Baez, I. 2002. Population dynamics of flower thrips (Thysanoptera: Thripidae). Frankliniella and predator Orius insidiosus (Say) in tomato and pepper crops. MSc. Thesis, Florida A & M University, Tallahassee, FL, 94 pp.

Bauer, P.J., and M.E. Roof. 2004. Nitrogen, aldicarb, and cover crop effect on cotton yield and fiber properties. Agron. J. 96:369-376.

Chellemi, D.O., J.E. Funderburk, and D.W. Hall. 1994. Seasonal abundance of flower-inhabiting Frankliniella species (Thysanoptera: Thripidae) on wild plant species. Environ. Entomol. 23: 337-342.

Cho, K., J.F. Walgenbach, and G.G. Kennedy. 2000. Daily and temporal occurrence of Frankliniella spp. on tomato. Appl. Entomol. and Zool. 35: 207-214.

Eckel, C.S., K. Cho, J.F. Walgenbach, G.G. Kennedy, and J.W. Moyer. 1996. Variation in thrips species composition in field crops and implications for tomato spotted wilt epidemiology in North Carolina. Entomologia Experimentalis et Applicata 78: 19-29.

Funderburk, J., J. Stavisky, and S. Olson. 2000. Predation of Frankliniella occidentalis (Thysanoptera: Thripidae) in field pepper by Orius insidiosus (Hemiptera: Anthocoridae). Environ. Entomol. 29: 376-382.

Funderburk, J.E., J. Stavisky, C. Tipping, D. Gorbet, T. Momol, and R. Berger. 2002. Infection of Frankliniella fusca (Thysanoptera: Thripidae) in peanut by the parasitic nematode Thripinema fuscum (Tylenchidae: Allantonemetidae). Environ. Entomol. 31: 558-563.

Hansen, E.A., J.E. Funderburk, R.R. Stuart, S. Ramachandran, J.E. Eger, and H. Mcauslane. 2003. Within-Plant distribution of Frankliniella species (Thysanoptera: Thripidae) and Orius insidiosus (Heteropera: Anthocoridae) in field pepper. Population Ecology 32: 1035-1044.

Higgins, C.J., 1992. Western flower thrips ( Thysanoptera: Thripidae) in greenhouses: Population dynamics, distribution on plants and association with predators. J. Econ. Entomol. 85: 1891-1903.

Kirk, W.D.J. 1997. Thrips feeding. p. 21-29. In T. Lewis (ed) Thrips as crop pests. CAB International. New York.


Michelakis, S.E., and A. Amri, 1997. Integrated control of Frankliniella occidentalis in Crete-Greece. Bull. OILB/SROP 20: 169-176.

Mound, L.A. 1997. Biological Diversity. p. 197-216. In T. Lewis (ed) Thrips as Crop Pests. CAB International, New York.

Mound, L. A., and G. Kibby. 1998. Thysanoptera: an identification guide. 2nd ed. CABI, UK.

Nicoli, G. 1997. Biological control of exotic pests in Italy: Recent experiences and perspectives. Bull. OEPP 27: 68-75.

Pearsall, I.A., and J.H. Myers. 2000. Population dynamics of western flower thrips (Thysanoptera: Thripidae) in nectarine orchards in British Columbia. J. Econ. Entomol. 93: 264-275.

Puche, H., R.D. Berger, and J.E. Funderburk. 1995. Population dynamics of Frankliniella species (Thysanoptera: Thripidae) thrips and progress of spotted wilt in tomato fields. Crop Prot. 14: 577-583.

Ramachandran, S., J.E. Funderburk, J. Stavisky, and S. Olson. 2001. Population abundance and movement of Frankliniella species and Orius insidiosus in field pepper. Agric. and Forest. Entomol. 3: 129-137.

Reitz, S.R. 2002. Seasonal and within plant distribution of Frankliniella thrips (Thysanoptera: Thripidae) in northern Florida tomatoes. Fla. Entomol. 85: 431-439.

Reitz, S.R., E.L. Yearby, J.E. Funderburk, J. Stavisky, M.T. Momol, and S.M. Olson. 2003. Integrated management tactics for Frankliniella thrips (Thysanoptera: Thripidae) in field-grown pepper. J. Econ. Entomol. 96: 1201-1214.

Salguero Navas, V.N., J.E. Funderburk, R.J. Beshear, S.M. Olson, and T.P. Mack. 1991. Seasonal patterns of Frankliniella spp. (Thysanoptera: Thripidae) in tomato flowers. J. Econ. Entomol. 84: 1818-1822

Stavisky, J., J.E. Funderburk, B.V. Brodbeck, S.M. Olson, and P.C. Andersen. 2002. Population dynamics of Frankliniella spp. and tomato spotted wilt incidence as influenced by cultural management tactics in tomato. J. Econ. Entomol. 95: 1216-1221.

Tavella, L., A. Arzone, and A. Alma. 1996. Researches on Orius Laevigatus ( Fieb), a predator of Frankliniella occidentalis (Perg.) in greenhouse. A preliminary note. IOBC/WPRS Bull. 14: 65-72.

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http://edis.ifas.ufl.edu/AG200�


Modeling Shallow Groundwater Flow and Nitrate Discharge into River from an Agricultural Land

Ying Ouyang*

ABSTRACT

While surface loading of nutrients into the lower St. Johns River (LSJR), Florida, USA has been intensively examined, the groundwater discharge of nitrate into the river has not yet been thoroughly quantified. This study investigates the shallow groundwater nitrate transport in the Tri-County Agricultural Area and estimates its potential discharge into the adjacent LSJR using MODFLOW and MT3DMS models. Three simulation scenarios were performed: the first one was chosen to evaluate groundwater nitrate transport for a simulation period of 3 years with agricultural pumpage; the second one was identical to the first except without agricultural pumpage; and the third was the same as the second with addition of two hypothetical areal nitrate sources, one near (about 1200 m) to LSJR and the other relatively far (about 6300 m) from the LSJR. Comparisons of groundwater head distribution with and without pumpage simulations shows that the use of agricultural pumpage decreased groundwater level locally. The average migration velocity of the nitrate plumes with perimeter concentration contour of 2 mg L-1 was about 43 m y-1 near the observation wells and the rate of groundwater nitrate discharge into river was about 1.2 x 104 mg m-2 d-1.

Keywords: Contamination; Groundwater flow; Nitrate discharge; Simulation

INTRODUCTION

Pollution of groundwater and surface water with excess nutrients due to leaching from vadose zone, groundwater discharge, storm water runoff, surface loading, and atmospheric deposition is an environmental concern. Among these, groundwater nitrate contamination is a particular concern for its potential adverse impact on ground and surface water quality. Nitrate may cause methemoglobinemia (blue baby syndrome) in infants when it exceeds EPA’s 10 mg L-1 drinking water standard (US-EPA, 1992). Nitrate concentrations of 19-29 mg L-1 in rural domestic wells in Indiana, USA were reported to cause some health problems during 1991-1994 (CDCP, 1996). Nitrate in drinking water also might increase cancer risk through production of N-nitroso compounds in the body, which are highly carcinogenic. Additionally, nitrate interaction with other dietary substances may cause health problems in humans (Madison and Brunett, 1985). It has been reported that elevated concentrations of nitrate (> 2 mg L-1) in drinking water are associated with adverse health effects (Nolan et al., 2002). In general, shallow groundwater unaffected by human activities commonly contains less than 2 mg L-1 nitrate (Mueller and Helsel, 1996). Environmental consequences of nitrate routing into

Department of Water Resources, St. Johns River Water Management District, P.O. Box 1429, Palatka, FL 32178, USA.


surface waters include increased water acidification and nitrogen-based downstream eutrophication (Stoddard, 1994).

Nitrate in groundwater primarily originates from non-point sources such as fields on which inorganic fertilizers and animal manures are applied. Although typically associated with agriculture and forestry, inorganic fertilizers also are applied to lawns and golf courses in urban areas. Puckett (1995) reported that about 11.5 million tons of nitrogen are applied annually as fertilizer in agricultural areas and about 6.5 million tons of nitrogen are produced annually by farm animals in USA. Other non-agricultural and forestry sources of nitrogen, such as septic tank leachate and leaking sewers, generally are less significant regionally and nationally but can affect groundwater and surface water quality locally (Canter and Knox, 1988).

Excessive nutrient leaching and loading from the Tri-County Agricultural Area (TCAA) into the adjacent lower St. Johns River (LSJR) is a major environmental concern. Pollution of the LSJR with nitrogen comes mainly from surface runoff generated from urban, rural, and agricultural lands; discharges from ditches serving agricultural croplands; contaminated groundwater seepage from malfunctioning septic tank systems; aquatic weed control; and naturally-occurring organic inputs; and atmospheric deposition (Campbell et al., 1993). The degradation of water quality due to nitrogen and other nutrients has resulted in altered species composition and decreased overall health of aquatic communities within the area. High levels of these constituents in surface water bodies have contributed to conditions of severe algal blooms, elevated bacterial levels, and increased biochemical oxygen demand (BOD). Increased BOD levels can lower oxygen concentrations to the point where fish kills occur.

Despite a need to understand nutrient flux dynamics in the TCAA and its potential adverse environmental impacts upon surface water quality, there are few data sets that have comprehensively summarized the shallow groundwater nitrate status. Boniol (1996) reported that the maximum concentrations of nitrate were 16.1 and 11.1 mg L-1, respectively, in the deep and surficial aquifers of the St. Johns River Water Management District (SJRWMD), Florida, USA. These maximum concentrations were found in a fern agricultural area and a cow pasture. Boniol (1996) further argued that although only a couple of wells in the aquifer systems had nitrate concentrations exceeding the EPA drinking water standard (10 mg L-1), the low



nitrate levels in the sampled wells did not mean that there were no nitrate contamination problems in the groundwater systems of the SJRWMD. Nitrate contamination is a localized problem. In a recent TCAA best management practice project, a shallow groundwater well was found to have a nitrate concentration of 38.6 mg L-1 (SJRWMD, personal communication). Such a high concentration indicates potential contamination of groundwater with nitrate in the area. Although these studies have provided good insights into the nitrate contamination status in groundwater, the spatial distribution and potential environmental impacts of groundwater nitrate on river water quality are still poorly understood.

A variety of mathematical models have been introduced in the literature to describe the movement of nitrate through the vadose zone soils and groundwater systems (Addiscott 1977; Jarvis et al., 1991; Hutson and Wagenet 1992; Khakural and Robert 1993; Navulur and Engel, 1998; Oenema et al., 1998; Stone et al., 1998; Bakhsh et al., 1999; Harrison et al., 1999). Currently, the most commonly used model to estimate nitrate leaching through the vadose zone of experimental plots is the LEACHN (Jabro et al., 1995) and the most commonly used models for surface runoff and loading in agricultural watershed are HSPF (Bicknell et al., 1996) and SWAT (Neitsch et al., 2002). The most widely used combination of models for dissolved groundwater contaminant transport in industrial practices is MODFLOW (McDonald and Harbaugh, 1988) with MT3DMS (Zheng and Wang, 1999). Several modeling studies have also been directed towards addressing nitrogen uptake by plant roots (Khakural and Robert, 1993; Jemison et al., 1994; Benjamin et al., 1996; Buysse et. al, 1996). More recently, the Watershed-Nutrient Transport and Transformation Model (NTT-Watershed) has been developed to simulate non-point source nitrogen pollution at the watershed scale (Heng and Nikolaidis, 1998). These modeling studies have improved our understanding of nitrate loading and leaching in surface and subsurface environments and nitrogen uptake within the root zone. However, little effort has been devoted to estimating groundwater nitrate discharge into rivers through the ground and surface water interface and its potential adverse environmental impact upon river water quality.

The objective of this study was to investigate shallow groundwater flow and nitrate transport in the TCAA and estimate their discharges into the adjacent LSJR, using numerical models in conjunction with field measurements. The three-dimensional groundwater flow model Visual MODFLOW and the three-dimensional contaminant transport model MT3DMS were employed for the purpose of this study. The specific objectives were to: (i) predict groundwater flow in the TCAA under conditions with and without agricultural pumpage, (ii) estimate the travel time when a nitrate plume with an outer concentration contour of 2 mg L-1 reaches the adjacent LSJR for conditions with

two hypothetical areal nitrate sources, one being near and the other being far from the river, and (iii) evaluate the rates of groundwater and nitrate discharge into the river through the ground and surface water interface.


Site Description

Figure 1. A. Location of the Tri-county Agricultural Area. B. Location of the modeled area showing an active modeled domain (inside the general head boundary) and groundwater observation and agricultural pumping wells.

The TCAA, located in the coastal plain ecoregion, Florida (Fig. 1A), is comprised of portions of St. Johns, Putnam and Flagler counties and is dominated by nearly level flatwood soils. These poorly drained, sandy and loamy soils typically contain an underlying impermeable layer within approximately 12 to 20 inches of the soil surface. Flatwoods are scattered throughout the area with obscure drainage patterns and depressional areas, which are ponded for long periods of time. Agricultural row crop fields are situated primarily on the low broad flats and

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around floodplains. Networks of manmade drainage canals are used to maintain water tables and convey runoff from agricultural production areas. (Livingston-Way, 1997).

The climate of the TCAA is classified as humid subtropical, and it is characterized by warm, normally wet summer and mild, relatively dry winter. The average temperature is about 22.7 oC (Miller, 1986). In the winter and early spring, precipitation is widespread and usually associated with frontal activity, while in the summer most of the rainfall is in the form of isolated showers and thunderstorms (Tibbals, 1990). Rainfall represents the largest input of water to the hydrologic system, and it is unevenly distributed throughout time and space. Approximately 60% of the annual rainfall occurs from June through October (Rao et al., 1997). Most of this rainfall results from local thunderstorms that cover a relatively small area although large-scale tropical storms or hurricanes occasionally pass through the region.

Although evapotranspiration (ET) represents the largest water loss from the hydrologic system, there are few data available that represent direct ET measurements. Estimates of the upper and lower limits of average annual ET rates in some regions of north Florida have been made by Tibbals (1990). The upper limit is approximately equal to the rate at which water can evaporate from an open body of water. This limit ranges from 117 cm y-1 in the northeastern part of the east-central Florida region to 125 cm y-1 in the southwestern part (Tibbals, 1990). Estimates of the minimum annual ET rate range from 64 cm y-1 to 89 cm y-1 (Tibbals, 1990; Sumner, 1996).

Model Development

A conceptual diagram of the modeled area is given in Fig. 1B. This modeled area comprises only the surficial aquifer since the aim of this study is to investigate the shallow groundwater nitrate transport and potential discharge into the adjacent LSJR. A numerical model for this modeled area was developed using the Visual MODFLOW (Waterloo Hydrogeologic Inc., 2000) and MT3DMS (Zheng and Wang, 1999) models. The Visual MODFLOW is the most complete and easy-to-use modeling environment for practical applications in three-dimensional groundwater flow. The model utilizes the generic U.S. Geological Survey (USGS) three-dimensional finite difference flow simulation program, MODFLOW (McDonald and Harbaugh, 1988). MT3DMS is a new version of the Modular 3-D Transport model, where MS denotes the Multi-Species structure for accommodating add-on reaction packages. It has a comprehensive set of options and capabilities for simulating advection, dispersion/diffusion, and chemical reactions of contaminants in groundwater flow systems under general hydrogeological conditions (Zheng and Wang, 1999).

A fixed finite difference grid (Fig. 2) covers the entire model area. The basic fixed mesh consists of 80 rows

(running east-west), 80 columns (running north-south) and one layer as only the shallow aquifer was considered in this study. The modeled grid has 6400 equal cells, each 500 m x 500 m in size. The choice of the grid interval is based upon the computation efficiency of the Visual MODFLOW and MT3DMS (Zheng and Wang, 1999).

Figure 2. Model grids and initial groundwater head distribution used for Scenario 1.

In order to simulate groundwater flow for the model developed in Fig. 1B, the numerical boundary and initial conditions must be defined. In this study, the surficial groundwater aquifer in the TCAA is a regionally extensive aquifer that does not have physical boundaries or limits that result in constant-head or no-flow boundaries. Thus, it is more realistic to allow for the effects of pumping and other stress to extend beyond the boundaries represented in the model without creating unrealistically large flows near the boundaries (Motz et al., 1995). Therefore, the general head boundary (GHB) or head dependent flux boundary condition was selected for this study. The GHB allows groundwater flow into or out of the modeled domain, depending on the head difference between the boundary cell and assigned head at a certain point outside of the model domain as well as the conductance of the aquifer between the boundary cell and the location of the assigned head. In this study, the GHB condition was assigned around the peripheries of the east, west, south, and north faces of the modeled domain. A no-flow boundary condition was assigned at the bottom face of the modeled domain, whereas the top boundary conditions included recharge, evapotranspiration, and river flow.

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Model Calibration

Model calibration is the process of adjusting hydraulic parameters, boundary conditions, and initial conditions within a reasonable range to obtain a match between observed and simulated groundwater levels. In this study, the model was calibrated for groundwater flow conditions using the groundwater observation well head measurements collected at three shallow groundwater-monitoring wells located at Bakersville, Treaty Park, and San Mateo (Fig. 2) for a three-year time period from January 1999 to November 2002. The temporal nature of inflows and outflows, including river flows, water applied for irrigated agriculture and pumpage, and groundwater drawdown in the TCAA, dictated the need to simulate groundwater flow. A river boundary with an average river stage was assigned to the top face of the modeled domain where the LSJR situates. The river stage value was estimated based on daily measurements obtained from the Racy Point and Palatka monitoring stations along the LSJR over a time period from 1995 to 2002. Other input parameters for the simulations including hydraulic conductivities, storage coefficients, specific yields, and effective porosities, were obtained from SJRWMD groundwater modeling reports (Motz et al., 1995; McGurk and Presley, 2002).

The primary input parameters calibrated during simulations were the general head boundary (GHB) conditions and the net areal recharge. This was accomplished by adjusting the values of GHB and recharge to match the groundwater heads between observations and predictions. The recharge calibration was accomplished using the non-linear parameter estimation and predictive analysis program WinPEST. WinPEST is a numerical tool used to assist in data interpretation and in model calibration. It can adjust model parameters until the fit between model outputs and laboratory or field observations is optimized. A detailed description of WinPEST can be found in the User's Manual for WinPEST (Waterloo Hydrogeologic Inc., 2000). Table 1 shows the final model input parameters after calibration.

Comparisons of the observed and simulated groundwater heads for the three observation wells from January 1999 to November 2002 are shown in Fig. 3. The goodness of the fit is estimated by simple statistical analysis. The values of root mean square and standard estimate error are, respectively, 0.4615 m and 0.3083 m, whereas the correlation coefficient (R2) is 0.9831. Therefore, a reasonable agreement was obtained between the observed and the predicted groundwater heads.


To evaluate groundwater flow and nitrate discharge into the LSJR from the TCAA, three simulation scenarios were performed in this study. The first scenario was chosen to evaluate the shallow groundwater flow for a

Figure 3. Comparison of the predicted and observed groundwater heads during model calibrations.

simulation period of three years using the initial and boundary conditions obtained from the model calibration processes. These initial and boundary conditions were assumed to represent current field conditions in the TCAA. The second scenario was identical to the first one except without agricultural pumpage. Comparison of simulation results with and without pumpage was performed to improve our current understanding of the impacts of agricultural pumpage on the groundwater system in the TCAA. The third scenario was the same as the second except that the groundwater nitrate transport for a simulation period of 30 years was included, using two hypothetical areal nitrate sources: one being near (about 1200 m) and the other being relatively far (about 6300 m) from the river (LSJR) (Fig. 8). Each source area was 1800 m x 1680 m. This scenario was chosen to estimate the potential discharge of shallow groundwater nitrate from the TCAA into the LSJR. Currently, detailed information on shallow groundwater nitrate contamination in the TCAA is largely unavailable although a sample from one study well had a nitrate concentration of 38.6 mg L-1. All of the input parameters used for these simulation scenarios are given in Table 1.

Groundwater Flow with Pumpage (Scenario 1)

The spatial distribution of groundwater head contours at 1, 2, and 3 years is shown in Fig. 4. In general, the groundwater level decreased slightly from the beginning of the simulation to 1 year and then reached its equilibrium condition from 1 year to the end of the simulation at 3 years in the intensive pumping areas. For example, the initial groundwater head contour was 6 m at x = 30000 m and y = 28000 m, but was about 5.5 m at 1 year at the same location (Fig. 4A). The lowering of head was about 0.5 m and occurred because of the agricultural pumpage. Then, from 1 year to the end of the simulation (i.e., 3

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years) the groundwater head contour was almost constant (about 5.3 m). This occurred because an equilibrium condition was reached. It should be pointed out that the rates of agricultural pumpage used in this study were obtained from the SJRWMD. These daily average rates were estimated based on the field measured data over a ten-year period from 1991 to 2000 for the TCAA (Table 1).

The relationship between groundwater head contour and flow direction (velocity vector) at the end of the three-year simulation is shown in Fig. 5. Results show that the groundwater flow direction was always perpendicular to the groundwater head contours. This occurred because the groundwater flow direction was determined mainly by the hydraulic gradient-driven force in this study. It is assumed that the density-driven groundwater flow due to salt water intrusion in the TCAA is not significant.

Figure 5. Relationship between groundwater head contour and flow velocity vector (flow direction) at the end of the simulation in Scenario 1.

Overall, the shallow groundwater flow direction is from the southeast toward the northwest and into the LSJR. However, this may not be always true locally, especially in the intensive agricultural pumping areas. As shown in Fig. 5, there is a groundwater sink, which occurred apparently due to the intensive agricultural groundwater withdrawals (Fig 1B).

Groundwater Flow without Pumpage (Scenario 2)

Comparison of groundwater head distribution with and without pumpage at the end of the simulation is given in Fig. 6. The groundwater head measurements at a pumping area with x = 24000 m and y = 28000 m for conditions with and without pumpage were 4.8 and 5.2 m, respectively. This demonstrates that agricultural pumpage decreased groundwater level due to the groundwater withdrawal, and thereby the groundwater level in the TCAA appeared to be controlled locally by pumpage.

Rates of groundwater discharge from the TCAA into the LSJR with and without agricultural pumpage as a function of time are given in Fig. 7. These rates were the cell flux values at the interfaces between the groundwater and river water, which were the outputs from the MODFLOW simulations. The rate was about the same with and without agricultural pumpage from 0 to 150 days. Then, from 150 days to the end of the simulation, differences in groundwater discharge rate started to develop. The rate was about 0.0047 m3 m-2 d-1 at the end of the simulation in the no pumpage simulation and was 0.0039 m3 m-2 d-1 at the same time in the pumpage simulation; a difference of about 21%. The difference is

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Table 1. Input parameters for simulation Scenarios 1 through 3. Parameter Scenario Remark/Reference 1 2 3

Modeled domain Modeled area length (m) 25000 25000 25000 Assumed Modeled area width (m) 44000 44000 44000 Assumed Delta X (m) 500 500 500 Assumed Delta Y (m) 500 500 500 Assumed Time control parameters

Simulation time step (day) 1 1 1 Assumed Max. simulation time (year) 3 3 30 Assumed

Hydrologic properties

Conductance (m d-1) 1.0 x 10-5 1.0 x 10-5 1.0 x 10-5 Motz et al., 1995 Effective porosity (m3 m-3) 0.3 0.3 0.3 USGS, 1984 Hydraulic conductivity (m d-1) 9.5 9.5 9.5 Motz et al., 1995 Net areal recharge (m d-1) 0.0015 0.0015 0.0015 Calibrated Specific yield 0.0004 0.0004 0.0004 Motz et al., 1995 Total porosity (m3 m-3) 0.35 0.35 0.35 USGS, 1984 Evapotranspiration (m d-1) 0.0032 0.0032 0.0032 Mao et al., 2002 Dispersivity (m) 10 10 10 Motz et al., 1995 Average pumping rates in TCAA (m3 d-1 well-1) St. Johns County 310 0 0 Measured Flagler County 331 0 0 Measured Putnam County 550 0 0 Measured

Chemical Parameters

Chemical -- -- Nitrate Assumed Initial NO3

-1 conc. (mg L-1) -- -- Area sources* Assumed *The initial nitrate concentrations are 10 mg L-1 for the two hypothetical source areas around the BS and DF observation wells and 0.003 mg L-1 elsewhere.

attributed to the groundwater withdrawal associated with agricultural usage in the pumpage simulation.

Currently, there are no published investigations of the rate of groundwater discharge from the TCAA into the LSJR. In the past, a couple of studies were performed to quantify groundwater discharge into the Indian River lagoon (Pandit and El-Khazen, 1990; Belanger and Walker, 1990). Using a finite element model of head difference between the lagoon and surficial aquifer, Pandit and El-Khazen (1990) found that the rate of annual groundwater discharge to the lagoon from the vicinity of Port St. Lucie, Florida is in the order of 3.4 x 107 m3. Direct measurements using seepage flow meters by Belanger and Walker (1990) showed a high heterogeneity of groundwater discharge rates in the vicinity of Jensen Beach, Florida with an average rate of 0.0095 m3 m-2 day-1. This average rate is in the same order of magnitude obtained by our study.

Nitrate Transport with Hypothetical Areal Sources (Scenario 3)

This scenario was chosen to estimate the potential discharge of shallow groundwater nitrate from the TCAA into the LSJR under various conditions. The simulation started with an initial nitrate concentration of 10 mg L-1 at the two source areas and 0.003 mg L-1 elsewhere. These two source areas are, respectively, located near the BS and DF observation wells (Fig. 8).

Spatial distribution of groundwater nitrate concentrations for the simulation conditions with two hypothetical areal sources at times of 10, 20, and 30 years is given in Fig. 9. In general, the migration distances of the nitrate plumes from the source areas toward the river

were very short over a 30-year simulation period. For example, the migration distances of the nitrate plume with an outer concentration contour of 2 mg L-1 near the BS monitoring well were about 500, 700, and 1100 m, respectively, at 10, 20, and 30 years. A similar result was observed near the DF observation well. That is, the migration distances of the nitrate plume with an outer concentration contour of 2 mg L-1 near this well were 480, 860, and 1200 m, respectively, at 10, 20, and 30 years. In other words, the average migration velocities of the nitrate plumes with an outer concentration contour of 2 mg L-1

were about 41 and 44 m y-1, respectively, near the BS and DF observation wells. It should be kept in mind that the migration velocity of the nitrate plume also depends on the selected nitrate concentration contour levels. The nitrate contour level of 2 mg L-1 was chosen here for analysis because this concentration could adversely affect aquatic life.

Figure 9B shows that it took about 20 years for the DF observation well area nitrate plume with an outer concentration contour of 2 mg L-1 to reach the LSJR. This was equivalent to a longitudinal migration distance of about 900 m in 20 years. Results suggest that nitrate enrichment in the LSJR due to the shallow groundwater discharge is minimal unless the contaminated sites are near the river. It further confirms that nitrate contamination in the shallow groundwater system of the TCAA is a localized problem since nitrate plume movement is very slow due to the low groundwater gradient. It should be pointed out that interactions of nitrate (such as denitrification) in the hyporheic zone (i.e., a transition zone between groundwater and surface water) were not included in this numerical experiment partially because the MODFLOW/MT3D models lack capabilities for such


Figure 6. Comparison of simulated head with and without pumpage in 3 years.

simulations and partially because we do not have any data for such investigation. The focus of this study was to simulate how much nitrate was potentially discharged to this zone and not the fate of nitrate at this zone.

Groundwater Nitrate Discharge into the LSJR

Based on the average groundwater discharge rate obtained from the simulations, the rate of groundwater nitrate discharge into the adjacent LSJR can be obtained using the following equation:

33 NOGWNO CRR = (1)

Figure 7. Comparison of groundwater discharge rate into the LSJR for conditions with and without pumpages.

Figure 8. The hypothetical source areas used in simulation Scenario 2. These areas are located, respectively, near the BS and DF observation wells.

where 3NOR is the rate of groundwater nitrate discharge

(mg m-2 day-1), GWR is the rate of groundwater discharge

(m3 m-2 day-1), and 3NOC is the groundwater nitrate

concentration (mg cm-3). For instance, if the groundwater nitrate concentration is 2 mg L-1 at the interface of the river near the DF well (Fig. 9C), the rate of groundwater nitrate discharge from this well into the river after 20 years is then given as:

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This rate is very important for estimating nitrate load from the shallow groundwater into the LSJR.

CONCLUSIONS

This study was designed to investigate shallow groundwater flow and nitrate transport in the TCAA and their potential discharges into the LSJR using Visual MODFLOW and MT3DMS models. The groundwater flow model was calibrated prior to its application using three observation wells with daily groundwater levels collected from January 1999 to November 2002. The calibration was conducted by adjusting input parameters, namely the net areal recharge and general head boundary conditions, to match the simulated groundwater head values with the observed ones. Mathematically, the calibration was accomplished using the input parameter optimization program WinPEST. With the values of standard estimate error and correlation coefficient (R2) equal to 0.3083 m and 0.9831 respectively, we concluded that a good agreement was obtained between the observed and simulated groundwater head values.

To evaluate TCAA groundwater flow and discharge into the LSJR and the potential influence of agricultural

pumpage, two basic simulation scenarios were performed. The first scenario was chosen to evaluate the shallow groundwater flow and discharge for a simulation period of three years for conditions with agricultural pumpage using the initial and boundary conditions obtained from the model calibration process, which were assumed to represent the current field conditions in the TCAA. The second scenario was identical to the first scenario except without the agricultural pumpage. The pumpage simulation shows that in general, the groundwater level decreased slightly from the beginning of the simulation to 1 year and then reached its equilibrium condition from 1 year to the end of the simulation at 3 years in the pumping area. Such a decrease occurred because of the groundwater withdrawal resulting from agricultural pumpage. Comparison of groundwater head distributions between pumpage and no pumpage simulations demonstrates that the use of agricultural pumpage decreased groundwater level locally.

A third scenario was performed to evaluate potential discharge of nitrate from the shallow groundwater in the TCAA into the LSJR. Simulations show that in general, the longitudinal migration of the nitrate plume in the shallow groundwater was very slow. The average migration velocity of the nitrate plumes with an outer concentration contour of 2 mg L-1 was about 43 m y-1 near the observation wells although this value could vary with the selected nitrate concentration contour levels. Simulations further reveal that it took about 20 years for a nitrate plume with an outer concentration contour of 2 mg L-1 to reach the LSJR from an observation well area, a migration distance of about 900 m. Results suggest that nitrate enrichment in the LSJR from the shallow groundwater discharge in the modeled area under average field conditions is somewhat minimal unless the contaminated sites are near the river. Therefore, further study performing field investigations on shallow groundwater nitrate contamination near and along the LSJR areas is warranted.

It should be noted that although the input values of ET, net areal recharge, and pumping rate are constant, these conditions act as continuous sources and sinks of groundwater. These continuous sources/sinks of groundwater plus the use of the general head boundary conditions did not generate a steady state condition. Therefore, the simulations in this study are not in a steady state condition.

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39588 ----"'!'

~"JR .._...,...,....,..,._....,,.....,....., ......... ...,...,...,.m,..,."""""....,i.., 395ll8 Tl"l-"l'l'!"l'l'!"I"

5S38 +l.l...i-U.1..1..1.a1,,1,,1...i.u.i...,.u.i.u.i.i..:.:.1.11-...i.u.i.u.i.i....t

10383 2-IOOO 37365

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Use of Soil Amendments to Reduce Leaching of Nitrogen and Other Nutrients in Sandy Soil of Florida

J. Y. Yang1, Z. L. He*1,2, , Y. G. Yang1,3, and P. J. Stoffella1

ABSTRACT

Nitrogen is a nutrient often associated with accelerated eutrophication of surface water. Amending sandy soils is considered one of the best management practices (BMPs) to reduce N loss. The effectiveness of soil amendments (CaCl2, CaCO3, cellulose, Al(OH)3, and mill mud) in reducing leaching of N and other nutrients from a typical acidic sandy soil (Ankona sand: sandy , siliceous, hyperthermic, ortstein Arenic Haplaquods) in Florida was determined by laboratory column leaching. Amendments were applied at the rate of 15 g kg-1 for a single amendment and 7.5 g kg-1 each if two amendments were combined. Leaching (250 ml of deionized water, equivalent to 90 mm rainfall or two pore volume of the soil column) of 1 kg soil mixture (20 cm deep, in a 6.6cm column) was conducted every four days for 32 days. With different soil amendments, the cumulative losses of NO3

--N and NH4+-N ranged from 41-82% and 13-

33%, respectively, of total applied N. Reduction in total inorganic N loss was most significant when the soil was amended with cellulose, CaCl2, or CaCl2 + CaCO3, which reduced N loss by 43, 32, and 33%, respectively. The effects of mill mud, Al(OH)3, and mill mud + Al(OH)3 on reduced total inorganic N leaching were moderate (23, 22, and 21%, respectively). Calcium carbonate was not effective in reducing total inorganic N leaching. Application of CaCl2 or CaCl2+CaCO3 significantly decreased K, Mg, and Cu, but increased Zn concentration in leachate. These results indicate that amendment of CaCl2, or CaCl2 + CaCO3 were effective in reducing leaching losses of N, K, Mg, and Cu and therefore can be considered in the development of BMPs for the sandy soil regions.

INTRODUCTION

Water quality throughout South Florida has been a major concern for many years (Chamberlain and Hayward, 1996). The St. Lucie watershed is a major citrus production area in Florida where citrus crops are grown on flatwood soils. These soils are characterized by low moisture and nutrient holding capacities and a shallow hardpan or argillic horizon, which acts as a confining layer to reduce the downward migration of pollutants and increase lateral movement of nutrients to surface drainage (He et al., 2000b). Most of the citrus acreage in Florida is on extremely sandy soils characterized by sand content often in excess of 90% (Hoogeweg and Hornsby, 1997). Frequent applications of fertilizers are made to assure high yields. More than 50% of applied N fertilizer is subject to potential leaching or runoff losses. Therefore, excess nutrients that are not utilized by the crop are a potential source of surface water and/or ground water contamination.

1. Univ. Florida, Inst. Food Agric. Sci., Indian River Res. Educ. Ctr. , 2199 South Rock Road, Fort Pierce, FL34945-3138, USA; 2 College of Environ. and Resource Sci., Huajiachi Campus, Zhejiang Univ., Hangzhou 310029, China; and 3 Institute of Geochemistry, Chinese Acad. of Sci., Guiyang 550002, China.

* Corresponding author ([email protected]). Contribution published in Soil Crop Sci. Soc. Florida Proc. 66:49-57 (2007).

Leaching is the physical process of the downward movement of dissolved constituents in soil solution. As the soil solution is displaced through soil profile by rainfall or irrigation in excess of the water-holding capacity of the soil, the dissolved ions move with the wetting front. The study of NO3

- movement, which is both a nutrient and possible contaminant, has intensified in recent years (Spalding and Exner, 1993) and remains a growing concern due to application of N fertilizers (Tan et al., 2002) and climatic conditions (Di and Cameron, 2002). Being an anion, NO3

- is not adsorbed by most soils (Nikolla et al., 2000); whereas ammonium leaching occurs in soils amended with sewage and other sludge (Medalie et al., 1994).

Copper is commonly used as a major component of fungicides for vegetable and citrus crops. On annual basis, the removal of accumulated Cu in soils by harvested portion of the citrus trees is insignificant. Copper is one of the least mobile trace elements in soils; however, transport of Cu through surface runoff into surface water could be considerable (Zhang et al., 2003). Management actions should be taken to reduce N and other nutrient (such as Cu) losses from soils. Adding soil amendments is considered one of the promising ways to reduce N loss. The effectiveness of amendments is influenced by soil and watershed characteristics. Practical considerations such as amendment availability, optimal rate, and cost must also be accounted for. Loss of other nutrients such as Mg, K, Cu, and Zn must be also considered to ensure that solving the N problem does not lead to loss of other nutrients or other water quality problems (O’Connor et al., 2005). Liming acid soils improves citrus yield and quality due to improved soil environment for root development. Liming also decreases losses of nutrients and metals in surface runoff by increasing soil holding capacity for these elements. Lime has been used as soil amendment to increase soil pH. Many other amendments [such as CaCl2, Al(OH)3, etc.] and industry byproducts (such as sugarcane mill mud) have been suggested to reduce N, P, and metal leaching in sandy soils. However, no systematic studies have been conducted in the Indian River area to demonstrate the effectiveness of these materials in reducing N and other nutrient losses into surface waters. The objective of this study was to evaluate the effectiveness of some commonly used organic and inorganic amendments in reducing leaching losses of N and other nutrients in typical sandy soils in the Indian River area.



Table 1. Relevant properties of the Ankona sand soil. KCl extractable N

Soil Depth pH (H2O) Electrical Conductivity Organic Matter Mehlich 3-P NO3--N NH4

+-N - cm - µS cm-1 g kg-1 -------------------------------------- mg kg-1 -------------------------------- 0-15 6.3 326 4.0 95.7 26.5 23.7 15-30 6.5 405 2.4 98.5 25.8 28.0

Table 2. Relevant properties of the tested sugarcane mill mud.

Element Na K Ca Mg B Cd Cr Cu Fe Mn Mo NH4-N Ni NO3-N P Pb Zn mg kg-1 295 2472 78600 5042 11.3 <1.00 10.5 138 5302 445 <1.00 56.0 8.20 286 9280 <5.00 235

MATERIAL AND METHODS

Soil and Amendments

Soil samples were collected at 0- to 15-cm and 15- to 30-cm depths from a representative commercial farm (Ankona sand: sandy, siliceous, hyperthermic, ortstein Arenic Haplaquods) in the Indian River area. The soil samples were air dried and ground to < 2 mm prior to physical and chemical analysis. Some properties of the soil are presented in Table 1. Total organic carbon in the soil samples was determined by combustion using a Macro Elemental Analyzer (Vario MAX CN, Elementar Analysensysteme GmbH,Germany). Electrical conductivity (EC) and pH of the soil samples were measured in slurry with deionized water at a soil: water ratio of 1:2 and 1:1, respectively, using a pH/ion/conductivity meter (Model 220, Denver Instrument, Denver, CO). Labile N (NH4

+-N and NO3--N)

was determined by shaking a 2.5 g air-dried sample in 25 ml of 2 M KCl for 1 h and the concentrations of NH4

+-N and NO3

--N in the filtrate were analyzed using a N/P Discrete Autoanalyzer (EasyChem, Systea Scientific LLC, Oak Brook, IL). Available P was determined by extracting the samples with Mehlich III solution and measuring the concentration by inductively coupled plasma atomic emission spectrometry (ICPAES, Ultima, J Y Horiba, Edison, NJ).

The soil amendments tested in this study included CaCl2, CaCO3, cellulose, Al(OH)3, and mill mud. They were all commercial products except for mill mud (pH 6.88), which was provided by the USDA, Sugarcane Field Experiment Station, Canal Point, FL. This material is an organic waste from sugar industry, containing approximately 24% organic C, 1% N, 0.9% P, 0.02% K, and trace amounts of metals (Table 2).

Column Leaching Study

Air-dried soil (1.0 kg) was thoroughly mixed with chemical fertilizer and one or two of the amendments, depending on treatment. There were two levels of P, N, and K (0 and 100 mg kg-1 P as KH2PO4 and 0 and 200 mg kg -1 N and K as KNO3/NH4NO3) and three replicates for each treatment. Fertilizer levels were equivalent to 112.5 kg ha-1 for P and 225 kg ha-1 for N and K, which were close to the field application rate for major crops in south Florida. There were seven amendment treatments: (1)

CaCl2, (2) CaCO3, (3) CaCl2 + CaCO3, (4) cellulose, (5) Al(OH)3, (6) mill mud, and (7) mill mud plus Al(OH)3. Soil samples receiving neither amendment nor inorganic fertilizer were used as the control. The application rate of soil amendment was 15 g kg-1 for a single amendment and 7.5 g kg-1 each if two amendments were applied together. Deionized water was added to maintain soil moisture at 70% field-holding capacity. The mixtures were then incubated at 25 ºC for 10 d, prior to being placed in a column leaching study, to ensure adequate equilibrium of chemical reactions between soil and the amendment.

Column leaching study was conducted using 6.6-cm inner diameter and 30.5–cm-long plastic columns (soil depth for 1 kg soil was approximately 20 cm) with leaching solution delivered by a peristaltic pump (Pump- Pro MPL, Watson-Marlow, Inc., Wilmington MA, UK). After incubation, the soil was packed into each column and two disks of filter paper (Whatman # 42) were placed on the top of each soil column to prevent disturbance by water droplets during leaching. The soil columns were slowly saturated by placing the bottom of each column in a shallow pan containing deionized water and maintained at room temperature for 3 d to allow the soil to compact naturally and allow equilibrium of chemical and biological reactions to occur prior to leaching. Leaching (250 ml of deionized water, equivalent to 90 mm of rainfall or two pore volume of the soil column) was conducted every four days for 32 d. A total of 2000 ml of water was leached, which was equivalent to a half year’s rainfall (720 mm) in the Indian River area. Leachate samples were filtered through a Whatman # 42 filter paper, and pH and EC of the leachates were measured within 8 h after sample collection using the pH/ion/conductivity meter. Filtration of leachates with 0.45-µm membrane was performed on the same day. The concentrations of dissolved macro- and micro-elements in leachate were determined using the ICPAES following EPA method 200.7. Concentrations of NH4

+-N and NO3--N

in the leachate samples were measured using the Discrete Autoanalyzer following EPA method 350.1 and 353.2, respectively.

Statistical Analyses

Separation of means for leachate concentrations of Mg, K, Cu, Fe and Zn among different treatments was conducted by the Duncan multiple range test procedure of the Statistical Analysis System release 8.2 (SAS Institute,


Figure 1. Effect of different soil amendments on leachate pH of the eight successive leaching events. Error bars indicate standard deviation.

2001). Each variable of pH, electrical conductivity, leachate concentrations of NO3-N and NH4-N was expressed as means plus standard error.


Effects on Leachate pH and EC

Fertilization affects the mobility of ions by changing the ionic strength of soil solution and input of cations to replace sorbed metals on exchange sites and by changing soil pH. In this study, addition of fertilizer alone decreased leachate pH. Compared with application of fertilizer alone, application of soil amendment together with fertilizer generally increased leachate pH except that a decrease in leachate pH (0.39 units) of the first leaching event occurred in the columns amended with CaCl2 or cellulose

(Fig. 1). Application of CaCO3 and mill mud increased leachate pH by 0.53 units. Leachate pH values from the first two leaching events were generally lower and then increased gradually with leachings except that leachate pH

values did not change significantly for the cellulose-amended column. The effect of soil amendments on leachate pH diminished with further leaching events and leveled off at 6.2 to 6.9 in later leaching events, probably due to depletion of H+ and/or Al3+.

The variation of leachate EC with different amendments was similar to pH (Fig. 2). The EC values in leachates of the control soil were lower than those receiving chemical fertilizer alone. The increase in leachate EC was most with CaCl2 among the seven treatments, which was 9.2 times greater than that of the control. For all the leachate water samples, leachate EC of the amended soils was high in the first leaching event, but rapidly declined from the second and third leaching events. By the fourth leaching event, EC values were similar among the different treatments and similar to the control level. Leachate EC of the third leaching was only 4.6% to 15.6% of the first leaching, indicating that soluble salts are readily leached out from the sandy soils. There were no differences in leachate EC among the samples from the

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Leaching events


Figure 2. Effect of different soil amendments on leachate electrical conductivity (EC) of the eight successive leaching events. Error bars indicate standard deviation.

third to eighth leaching event. The elevated EC value from the addition of chemical fertilizer alone or application of soil amendment together with chemical fertilizer was caused by the input of soluble salts from the fertilizer or amendments.

Effects on Nitrogen Leaching

The total amount of leached NO3--N from the control

soil was 7.86 mg kg-1. Application of chemical fertilizer alone markedly increased the leaching of NO3

--N by 20.9 times. The variation curves of NO3

--N in leachate as a function of leaching events were similar for different amendment treatments (Fig. 3). The concentration of leachate NO3

--N decreased markedly in the first three leaching events and dropped to a minimal level afterwards, which implied that most of the leachable NO3

--N was released from the soil during the first 12 days. Nitrate concentration in the first two leaching events greatly exceeded the drinking water standard (10 mg L-1)

(USEPA, 1994) indicating that leachate NO3--N in a

fertilized soil can be a potential source of non-point pollution. The high rate of leaching is undoubtedly due to the input of N fertilizer and the sandy nature of the tested soil. In the third leaching event, the concentration of NO3

--N in leachate decreased to lower than 10 mg L-1 except for those applied with chemical fertilizer alone or chemical fertilizer plus CaCO3 amendment. After the initial rapid declines, the concentration of NO3

--N in leachate was similar for all the treatments by the fourth leaching event, which was 0.06% (CaCl2 treatment) to 0.82% (chemical fertilizer alone) of the first leaching. The leachate NO3

--N concentrations decreased to below the surface water limit (1.5 mg L-1) after the fifth leaching event. This indicates that the release of NO3

--N is a fast process. With different soil amendments, the concentration of NO3

--N released in the second leaching event ranged from 5.9 to 75.4 mg L-1. The corresponding values for the third, fourth, and 8th (last) leaching events were 0.8 to 9.4 mg L -1, 0.1 to 2.3 mg L-1, and 0.0 to 1.2 mg L -1, respectively, except for the

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Leachi ng event s

8


Figure 3. Effect of different soil amendments on NO3

--N concentrations in leachate from the eight successive leaching events. Error bars indicate standard deviation.

columns with CaCO3 amendment which showed no considerable effect of time on NO3

--N leaching. Leachate NO3

--N concentration of the control columns remained relatively low for the entire leaching period except for the first leaching event. In the first leachate, NO3

--N concentration was 20.9 mg L-1, which exceeded the drinking water standard. These results indicate that fertilization practices in the Indian River Area may cause potential N contamination to ground water. Leaching loss of NO3

--N was reduced by 50%, 47%, 41%, and 21%, respectively, by CaCl2, CaCl2 + CaCO3, cellulose, or Al(OH)3 amendment, all which were significantly less than with chemical fertilizer alone. The mechanisms of reduced NO3

--N leaching by above amendments are not fully understood. The inputs of CaCl2 or Al(OH)3 reduce the negative charges on soil surface by Ca2+, Al3+ sorption, thus decreasing NO3-N leaching, whereas the addition of cellulose enhanced microbial incorporation of NO3

--N into organic fractions (He et al., 2002). Mill mud and mill mud + Al(OH)3 did not have significant effects on NO3

--N leaching loss, and the high NO3

--N background in the mill mud could be a factor. The cumulative losses of NO3

--N decreased among the different amendments in the order of

chemical fertilizer alone = CaCO3 = Mill mud = Mill mud + Al(OH)3 > Al(OH)3 > cellulose > CaCl2 + CaCO3 > CaCl2. With soil amendments, the cumulative losses of NO3

--N ranged from 83 to 164 mg kg-1 which was 41-82% of total applied N. This result agrees with the previous report that NO3

- is not adsorbed by soil components and therefore, readily moves downward or laterally (Nikolla, 2000). The high concentration of NO3

--N in surface water often causes suffocation disease (Panichsakpatana, 1997) or eutrophication if other factors (such as phosphorus and potassium) are adequate (Sukreeyapongse et al., 2001).

The mean NH4+-N concentration in leachate varied

among the leaching events. The cumulative loss of NH4+-N

from the control soil was 2.34 mg kg-1. Application of chemical fertilizer alone increased the amount of NH4

+-N in leachate by 25.5 times (Fig. 4). With soil amendments, the cumulative losses of NH4

+-N in leachate ranged from 25.5 to 69.5 mg kg-1, which was much lower than those of NO3

--N leaching. Leaching N in the form of NH4+-N was

13-33% of total applied N. After the first leaching event, the NH4

+-N concentration decreased markedly until the third leaching event and thereafter the NH4

+-N concentration was close to zero for all the treatments. The

600. 0 · · ·· • -0 • · · .. · Control

I 500. 0 • --

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Leachi ng event s


Figure 4. Effect of different soil amendments on NH4

+-N concentrations in leachate from the eight successive leaching events. Error bars indicate standard deviation.

highest NH4+-N concentration in leachate generally

occurred in the first leaching event, which accounted for 80% to 89% of the total leached NH4

+-N. In the second leaching event, NH4

+-N concentration of all the leachate samples was below 29.4 mg L-1 except for soils amended with CaCO3 (38.3 mg L-1) or chemical fertilizer alone (32.9 mg L-1). It has been reported that high concentration of NH4

+-N (≧29.4 mg L-1) can cause fish kills (Ghosh and Bhat, 1998). Cellulose, mill mud, and mill mud + Al(OH)3 decreased NH4

+-N leaching from the soil, but CaCl2, CaCO3, and CaCl2 + CaCO3 had no significant effect on NH4

+-N leaching. Application of cellulose increases the microbial biomass, which probably was responsible for immobilization of inorganic N (He et al., 2002), thus decreasing leaching loss of NH4

+-N. With the different amendments, N loss by leaching in the form of NO3

--N was 1.2-5.8 times more than that of NH4

+-N. Nitrate with its negative charge can easily move through the root zone and transport to deep soil or groundwater. Ammonium, in contrast, has a positive charge and can be retained by

negatively charged surfaces of the soil. This may explain why the average N leaching in the form of NO3

--N was greater than NH4

+-N (Sukreeyapongse et al. 2001). This finding is in agreement with previous studies, which indicated that N in leachate was mostly in the form of nitrate (Cabrera, 1997; Sukreeyapongse, 2001). Total inorganic N (NO3-N + NH4-N) losses by leaching were 57-96% of the total N applied in chemical fertilizer. Reduction in total inorganic N leaching was most significant when the soil was amended with cellulose, CaCl2, or CaCl2 + CaCO3, which reduced N leaching by 43, 32, and 33% respectively. The effects of mill mud, Al(OH)3, and mill mud + Al(OH)3 on N leaching were moderate (23, 22, and 21%, respectively), whereas CaCO3 had no effect.

Effects on Other Nutrients Leaching

Trace metals were analyzed because they can be transported to water by leaching or surface runoff if they are accumulated in soils due to repeated application. The concentrations of macro-elements and micro-elements in

250.0

200.0

C 0 150. 0

:.;:::::

~ ..... C Cl) (.) C 0 100. 0 ()

z I

+ st

I z 50. 0

0.0

~

♦\ :1 ..

0 1 2 3 4

• • .... o .. · · · · Control -··-··~-.. - ··- NPK _,._ .. _., ____ ,._ CaCl

2·2H

2O

--♦-- CaCl2·2H2O+CaCO1

-----b-- Cellulose --0-- Al(OH)3·nHp ··· ··· ... * ... ··· ··· Mill Mud ---0--- Mill Mud+Al(OH)1·nH2O --- --♦-- --- CaCO3

5 6 7

Leachi ng event s

8


the leacheate decreased with leaching events, and most leaching loss occurred in the first two leaching events (Tables 3-4). The effects of soil amendments on the leaching of K, Mg, and heavy metals including Cu, Zn, and Fe were different. Application of CaCl2 and CaCl2+CaCO3 significantly decreased K, Mg, Cu, and Fe concentrations, but increased Zn concentration in leachate, though the extent of decrease varied with individual elements.

The leaching of Mg decreased in the soils amended with CaCl2 and CaCl2+CaCO3, as compared to the control. Magnesium concentration was high at the beginning of leaching, but decreased quickly and was minimal at the end of leaching. In the first leaching event, Mg concentration in leachate from the CaCl2 and CaCl2 + CaCO3 amended soils were 55.6 and 65.1 mg L-1, respectively, but it decreased to 4.7 and 2.8 mg L-1, respectively, in the second leaching event. Thereafter, Mg concentration remained below 1.0 mg L-1. Cumulative Mg loss by the eight leaching events in columns amended with CaCl2 and CaCl2 + CaCO3 were 71% and 81%, respectively, of the columns amended with chemical fertilizer alone. There were no significant differences in Mg loss between columns with chemical fertilizer alone and chemical fertilizer combined with CaCO3 or Al(OH)3. Cellulose, mill mud, and mill mud + Al(OH)3 increased total leachate Mg by 24%, 120%, and 60%, probably due to mill mud containing considerable amount of Mg. Leaching pattern of K was similar to that of Mg.

The concentrations of leached K were very high in the first leaching event for all the treatments, but decreased sharply in the second event, especially in the CaCl2 and CaCl2 + CaCO3 treatments, which were only 11% and 9% of the first leaching event. Leachate-K concentrations declined with time, but were higher than the unamended soil at the end of the experiment except for the CaCl2 and CaCl2 + CaCO3 treatments, which were similar to the unamended soil. Reduction in leachate-K concentration was most significant when the soil was amended with CaCl2, or CaCl2 + CaCO3. Total amount of K loss from the tested soils during the entire experiment period was 174, 133, and 128 mg kg-1, respectively, for chemical fertilizer alone, CaCl2 or CaCl2 + CaCO3 amendments. The effects of cellulose and Al(OH)3 on reduced K leaching were moderate, and the amount of K loss were 155.9 and 152.2 mg kg-1, respectively. Total amount of K loss from mill mud and mill mud + Al(OH)3 treatment were much higher compared to the chemical fertilizer alone and the unamended soil (6.1 mg kg-1), likely due to the input of K from the amendment. Theoretically, Mg and K leaching can be increased by amendment of CaCl2 or CaCl2 + CaCO3, due to the replacement of Ca2+. In this case, the large amount of Ca from these two Ca-containing amendments would precipitate water-soluble P, and therefore, during the formation of less water-soluble

The effect of fertilization on the transport of trace metals varied among the different individual elements. Copper is one of the least mobile trace elements in soils. However, transport of Cu through surface runoff has been reported as a major pathway of Cu from land to surface water and has caused increasing concern in South Florida (Zhang et al., 2003). In this study, among all the 72 leaching water samples, 5.6% of the samples exceeded the highest value (280 µg L-1) of Cu observed in a published assessment of natural surface waters of the USA (Manahan, 1991), while 56.9% of the samples had dissolved Cu < 100 µg L-1, a limit value for Cu in surface water (USEPA, 1994). Mean dissolved Cu concentration of leaching water samples during the whole leaching process were 83 µg L-1 (control), 120 µg L-1 (chemical fertilizer alone), 70 µg L-1 (CaCl2+CaCO3), 82 µg L-1

(CaCl2), 91 µg L-1 (CaCO3), 138 µg L-1 (mill mud), 143 µg L-1 (Al(OH)3), 147 µg L-1 (mill mud + Al(OH)3 ), and 150 µg L-1 (cellulose). All these values were higher than the average (15 µg Cu L-1) for natural surface waters in the USA (Manahan, 1991). Among the seven treatments, CaCl2+CaCO3 had the greatest effect on reduced Cu leaching from soil, which reduced 42% of Cu loss, as compared with chemical fertilizer alone. Calcium chloride or CaCO3 alone reduced Cu leaching by 32% and 24%, respectively. The effects of these amendments on reduced Cu2+ leaching are likely related to flocculation of dissolved organic matter at elevated salt concentration as evidenced by the increased EC value and raised pH by CaCO3. The transport of Cu from soil to water is realized mainly through chelation with dissolved organic matter (He et al., 2006).

The mean concentrations of Zn in leaching water for all samples except that from columns amended with CaCl2

and CaCl2+CaCO3 were below 45 µg L-1. This mean value is below the average (64 µg L-1) of natural surface waters in the USA (Manahan, 1991). All samples had Zn < 5000 µg L-1, the maximum permissible value for Zn in U.S. drinking water (United States Public Health Service, 1962). Addition of CaCl2 and CaCl2+CaCO3 significantly increased Zn concentration in the first leaching event, which were 32 and 8 times, respectively, greater than that of the chemical fertilizer treatment. After the first leaching event, Zn concentration in those treatments decreased from the second to third event and was similar to the level of all the other treatments. The increased leaching of Zn might be attributable to the replacement of retained Zn by the fertilizer cations such as Ca2+, K+, and NH4

+.

The effect of different amendments on Fe was very similar to that of Cu. The CaCl2+CaCO3 treatment had the greatest effect on reducing Fe leaching from soil, which reduced Fe loss by 76% as compared with chemical fertilizer alone. Amendment of CaCl2 or CaCO3 reduced Fe leaching by 71% and 46%, respectively. It was reported that in the Riviera fine sand, Fe is in the amorphous oxides forms (Zhang et al., 1997) and the dissolution of the


Table 3. Concentrations of total dissolved Mg and K in leachate from the eight successive leaching events (L1 to L8).

Treatments Concentrations, mg L-1

L1 L2 L3 L4 L5 L6 L7 L8

Mg

Control 11.0e† 6.33c 6.07cd 5.74d 5.00cde 5.58c 5.34c 5.31c N P K 36.5d 19.6ab 7.95bc 4.89de 4.32def 5.11c 5.30c 5.16c N P K +CaCl2 55.6c 4.74c 0.74e 0.48f 0.35f 0.32e 0.31e 0.28e N P K +CaCO3 43.0d 19.9ab 6.24cd 3.86e 3.09ef 3.12d 3.45d 3.24d N P K +CaCl2 + CaCO3 65.1b 2.78c 0.83e 0.86f 0.68ef 0.63e 0.57e 0.47e N P K +Cellulose 38.9d 11.4bc 13.0a 11.8b 9.67b 9.02b 8.25b 8.01b N P K +Al(OH)3 38.2d 11.4bc 4.64d 4.51de 7.72bcd 5.15c 5.42c 5.18c N P K +Mill Mud 89.4a 25.2a 14.6a 13.6a 17.1a 12.6a 12.0a 11.3a N P K +Mill Mud + Al(OH)3 70.7b 20.1ab 10.3b 8.92c 8.95bc 7.87b 7.72b 7.25b

K

Control 7.37c 4.76e 3.66e 2.47c 2.00c 1.70c 1.43c 1.13c N P K 413b 164abc 61.0abc 26.1b 14.0b 9.17b 6.05b 4.50b N P K +CaCl2 462b 50.7de 10.6e 4.14c 2.57c 1.54c 1.16c 1.02c N P K +CaCO3 435b 213a 64.6ab 25.7b 14.0b 7.31b 5.85b 4.51b N P K +CaCl2 + CaCO3 447b 40.3de 10.6e 4.15c 2.59c 1.77c 1.71c 1.52c N P K +Cellulose 399b 121bc 47.0cd 22.4b 13.5b 8.69b 6.81b 5.28b N P K +Al(OH)3 413b 98.6cd 39.9d 21.9b 14.2b 9.58b 6.58b 5.12b N P K +Mill Mud 615a 174ab 69.5a 35.3a 21.0a 13.8a 9.28a 7.40a N P K +Mill Mud + Al(OH)3 541a 130bc 48.8bcd 24.1b 14.3b 9.31b 6.57b 4.96b

† Values within a column with the same letter(s) are not significantly different at P<0.05 based on Duncan’s Multiple Range Test.

Table 4. . Concentrations of total dissolved Cu, Fe, and Zn in leachate from the eight successive leaching events (L1 to L8). Treatments

Concentrations (mg L-1) L1 L2 L3 L4 L5 L6 L7 L8

Cu

Control 0.15cd† 0.11b 0.07c 0.07b 0.06cd 0.07bc 0.06bc 0.08abc N P K 0.27b 0.19a 0.11abc 0.11ab 0.08bcd 0.08bc 0.07abc 0.07abc N P K +CaCl2 0.18c 0.10b 0.07c 0.08b 0.07bcd 0.05c 0.04c 0.06bc N P K +CaCO3 0.17cd 0.14ab 0.09bc 0.09b 0.06bcd 0.05c 0.06bc 0.06bc N P K +CaCl2 + CaCO3 0.11d 0.10b 0.08c 0.08b 0.06d 0.04c 0.05c 0.05c N P K +Cellulose 0.34a 0.20a 0.16a 0.16a 0.08bcd 0.09bc 0.10a 0.07abc N P K +Al(OH)3 0.29ab 0.21a 0.13abc 0.09ab 0.11a 0.11ab 0.09ab 0.10a N P K +Mill Mud 0.34a 0.18a 0.11abc 0.09ab 0.09b 0.11ab 0.09ab 0.09ab N P K +Mill Mud + Al(OH)3 0.31ab 0.18a 0.15ab 0.10ab 0.09bc 0.16a 0.09ab 0.10a

Fe

Control 0.03a 0.04b 0.04bc 0.05b 0.04b 0.02b 0.03b 0.02b N P K 0.02a 0.03b 0.02bc 0.03b 0.05b 0.07b 0.03b 0.04b N P K +CaCl2 0.00b 0.00b 0.00c 0.01b 0.02b 0.02b 0.01b 0.02b N P K +CaCO3 0.01b 0.01b 0.03bc 0.03a 0.03b 0.02b 0.01b 0.01b N P K +CaCl2 + CaCO3 0.00b 0.01b 0.01c 0.02b 0.02b 0.01b 0.01b 0.00b N P K +Cellulose 0.03a 0.48a 0.16a 0.67a 0.92a 0.69a 0.51a 0.69a N P K +Al(OH)3 0.03a 0.18b 0.11ab 0.05b 0.07b 0.04b 0.03b 0.03b N P K +Mill Mud 0.04a 0.04b 0.04bc 0.02b 0.03b 0.03b 0.06b 0.07b N P K +Mill Mud + Al(OH)3 0.03a 0.08b 0.03bc 0.03b 0.03b 0.10b 0.04b 0.06b

Zn

Control 0.03c 0.01b 0.01c 0.00a 0.01b 0.02ab 0.03b 0.02bc N P K 0.09c 0.06ab 0.04a 0.01a 0.01b 0.01b 0.03b 0.02bc N P K +CaCl2 2.75a 0.11a 0.03ab 0.01a 0.01b 0.02ab 0.02b 0.02bc N P K +CaCO3 0.07c 0.04b 0.02abc 0.00a 0.00b 0.01b 0.03b 0.03bc N P K +CaCl2 + CaCO3 0.69b 0.03b 0.02bc 0.01a 0.01b 0.01b 0.02b 0.01c N P K +Cellulose 0.08c 0.02b 0.02abc 0.02a 0.02ab 0.04a 0.05a 0.05a N P K +Al(OH)3 0.10c 0.07ab 0.03ab 0.01a 0.04a 0.02ab 0.04ab 0.02bc N P K +Mill Mud 0.06c 0.02b 0.02bc 0.01a 0.02b 0.02ab 0.03b 0.04ab N P K +Mill Mud + Al(OH)3 0.06c 0.03b 0.02abc 0.01a 0.02ab 0.04a 0.03b 0.02bc

† Values within a column with the same letter(s) are not significantly different at P<0.05 based on Duncan’s Multiple Range Test.

amorphous Fe oxides was lower in the leaching solution containing high salt concentration (He et al., 2000a). In this study, Fe concentration was low in the leachate with high EC value. The mean EC value in the leachate of CaCl2, CaCO3, CaCl2 + CaCO3 amended, and chemical fertilizer treated columns was 1352, 805, 1194, and 772 • S cm-1, respectively. Cellulose, Al(OH)3, mill mud, and Al(OH)3 + mill mud significantly increased Fe leaching from soils. But the control columns leached as much Fe as those that were amended with chemical fertilizer alone. All of the samples had dissolved Fe < 1000 µg L-1, a limit

value for Fe in surface water (USEPA, 1994). Further work is needed to understand the mechanisms of interactions between the applied macronutrients and the micronutrients present in the soil in relation to the potential leaching of the latter.

CONCLUSIONS

The Ankona soil in South Florida is sandy with minimal holding capacities for moisture and nutrients. Repeated application of fertilizers for sustaining high yield of vegetable crops has caused potential contamination to


surface and ground water. The benefits and effectiveness of soil amendments in reducing N losses from vegetable cropping systems while sustaining desired vegetable yield need to be demonstrated. Results from this study indicated that CaCl2 and CaCl2 + CaCO3 are most effective in reducing N leaching from sandy soil and decrease the concentrations of K, Mg, Cu, and Fe in leachate. Amendment of CaCl2 and CaCl2+CaCO3 should be more closely studied for their contribution to nutrient cycling within soil-water ecosystem, especially where soil pH is low, before use of these amendments is put into practice and considered in the development of BMPs for the sandy soil regions.

ACKNOWLEDGMENTS

This study was, in part, supported by a grant (Contract #OT050703) from the South Florida Water Management District.

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Ghosh, B.C., and R. Bhat. 1998. Environmental hazards of nitrogen loading in wetland rice fields. Environmental Pollution. 102:123–126.

He, Z.L., A.K. Alva, D.V. Calvert, and D.J. Banks. 2000a. Effects of leaching solution properties and volume on transport of metals and cations from a Riviera fine sand. J. Environ. Sci. Health A. 35:981-998.

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He, Z.L., D.V. Calvert, A.K. Alva, Y.C. Li, and D.J. Banks. 2002. Clinoptilolite zeolite and cellulose amendments to reduce ammonia volatilization in a calcareous sandy soil. Plant and Soil. 247:253-260.

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GRADUATE STUDENT FORUM ABSTRACTS - CROPS

Enhancing Turf Quality in Bahiagrass by Over-Expression of a Gibberellin Catabolizing Enzyme

M. Agharkar*1, F. Altpeter 1,2,3, H. Zhang 1, M. Gallo1,2,3, K. Quesenberry1, D.S. Wofford1, and G.L. Miller4

1Agronomy Dept., Univ. of Florida Gainesville, FL 32611 2Plant Molecular and Cellular Biology, Univ. of Florida, Gainesville, FL 32611

3Genetics Institute, Univ. of Florida, Gainesville, FL 32611 4Dept. of Environmental Horticulture, Univ. of Florida, Gainesville, FL 32611

Bahiagrass (Paspalum notatum Flügge) is a low input, drought tolerant, and disease resistant warm season turfgrass used for residential lawns and along highways in the Southeastern US. Turf quality of bahiagrass is compromised by prolific seedhead production, open growth habit, and light green color. The objective of this study was to improve the turf quality of bahiagrass by over-expression of a gibberellin catabolizing enzyme, gibberellin 2-oxidase (GA2ox). Gibberellin 2-oxidase1 and GA2ox8 ORF’s were isolated from Arabidopsis and sub-cloned under the control of the constitutive ubiquitin or 35S promoters. Co-transfer of constitutive nptII and GA-2 oxidase expression cassettes into seed derived callus cultures from turf-type bahiagrass (cv. Argentine) was carried out. Transgenic plants were confirmed by NPTII ELISA (Agdia), PCR, and RT-PCR. Phenotypic data were generated under controlled environment conditions of soil or hydroponics grown plants and allowed to identify transgenic bahiagrass lines with a superior phenotype. Turf quality and persistence of the transgenic bahiagrass will be determined under field conditions at the University of Florida, Plant Science Res. and Educ. Unit near Citra, FL.

*M. Agharkar, [email protected]

Growth and Phenology of Native Legumes in Two Light Environments S.E. Cathey* and T.R. Sinclair

Agronomy Dept., Univ. of Florida, Gainesville, FL 32611

In the fire-maintained longleaf pine- (Pinus palustris) wiregrass (Aristida stricta) ecosystem, legumes are important for replacing nitrogen lost from frequent burning. Restoration of understory nitrogen-fixing legumes is important for prescribed fire practices and wildlife habitat improvement. The objectives of this study were to document the influence of shading on growth habits and biomass accumulation on native legumes and to observe subsequent effects of shading on phenological development and nodule number and morphology. Initial observations of growth responses to shade, phenological development through a season, and nodule morphology for eight species of native legumes were made. The group of species in this study represented all three major subfamilies of Fabaceae and two distinctly different growth forms: vining/spreading and erect herbs. Biomass accumulation was not significantly reduced by shade for any of the species. Although stem elongation responses to shade were only significant for three species, Clitoria mariana, Crotalaria rotundifolia, and Lespedeza hirta, a general pattern of vining/spreading plant etiolation under shaded conditions and a lesser effect on more upright plants was evident. Weekly measurements of plant height, plant canopy expansion, and notations regarding phenological phase were used to describe changes in each species over a single growing season. Nodules varied from spheroid to elongate to coralloid.

*S.E. Cathey, [email protected]




Extended Daylength and Fertilization Effects on Above- and Below-Ground Bahiagrass Mass and Chemical Composition

S.M. Interrante*1, L.E. Sollenberger1, A.R. Blount1, T.R. Sinclair1, J.C.B. Dubeux2, and J.M.B. Vendramini3

1Agronomy Dept., Univ. of Florida, Gainesville, FL 32611

2UFRPE- Depto. de Zootecnia, Recife, PE, Brazil 3Soil and Crop Sci. Dept., Texas A&M Univ.

Bahiagrass is the primary pasture grass in Florida, and pastures are productive from April to November in northern Florida. The reduction in bahiagrass growth during winter months may be attributed to short daylengths. Research has been aimed at increasing bahiagrass productivity during short-daylength months through genetic selection and development of cultivars that are insensitive to photoperiod. There are concerns that increasing above-ground growth may negatively affect the partitioning of organic matter to storage structures, possibly resulting in reduced tolerance to defoliation and potential stand loss. An extended daylength field study was conducted to evaluate a cold tolerant, less daylength sensitive bahiagrass type against existing bahiagrass cultivars. Treatments were the factorial combinations of two daylength treatments, two fertilizer treatments, and three bahiagrass genotypes in four replications of a split-plot arrangement of a completely randomized design. Dry matter yields were determined by regular harvests to an 8-cm stubble height. Destructive samples were collected three times per season, and plants were divided into shoot, rhizome, and root fractions for subsequent analyses. There were no differences in total season DM yields for the extended daylength treatment (P>0.05). For the November harvest, DM yields for genotypes under extended daylengths were generally greater than those under normal daylengths (P<0.05). However, April normal daylength DM yields and above-: below-ground ratios were greater than those under extended daylengths (P<0.05). In April, Pensacola and Tifton 9 root and rhizome DM yields were greater than PICA C4 (P<0.1). Fraction N content will also be measured.

*S.M. Interrante, [email protected]

Predicting Tomato Fruit Growth Dynamics in Terms of Fresh Weight and Size: A Review and Modeling Approach

M.R. Rybak*1, K.J. Boote1, J.M.S. Scholberg1, C.H. Porter2, and J.W. Jones2

1Agronomy Dept., Univ. of Florida, Gainesville, FL 32611-0500

2Agric. and Biol. Engineering Dept., Univ. of Florida, Gainesville, FL 32611-0570

A number of tomato (Lycopersicon esculentum Mill.) crop models have been developed which simulate fruit yield based in cumulative dry matter. Tomato growers, however, would be more interested in models that could predict the weekly pattern of yield on fresh weight basis including variation in marketable size. Such models could assist growers in planning their management and commercialization strategies especially relative to harvest timing and fruit quality. Tomato production varies week to week and accurate predictions are hard to achieve. The developmental stage and growth rate of individual fruits are influenced by environmental, cultural and genetic traits. Therefore, functional relationships need to be understood in order to build useful simulations. This paper reviews the literature concerning the factors that regulate single fruit growth patterns and increases in size for fresh market tomato. The paper analyzes the use of this information to support improving tomato crop models. A conceptual model is presented for predicting fresh weight and size of fruits over time, starting with crop-model-predicted dry mass per fruit and fruit thermal age.

*M.R. Rybak, [email protected]




Enhancing Biosafety of Transgenic Bahiagrass by Engineering Inducible Cell Death S. Sandhu*1, F. Altpeter1,2,3 , A.S. Blount4, K. Quesenberry1, M. Gallo1,2,3, and M. Singh5

1Agronomy Dept., Univ. of Florida, Gainesville, FL 32611

2Plant Molecular and Cellular Biology, Univ. of Florida, Gainesville, FL 32611 3Genetics Institute, Univ. of Florida, Gainesville, FL 32611

4North Florida Res. and Educ. Center, Univ. of Florida, Quincy, FL 32351 5Citrus Res. and Educ. Center, Univ. of Florida, Lake Alfred, FL 33850

Bahiagrass (Paspalum notatum Flügge) is the most important forage grass in Florida and, in addition, it is used widely as low-input turf. We recently developed an efficient genetic transformation protocol for bahiagrass. Transgenes with the potential to enhance turf and forage quality as well as stress tolerance were introduced into bahiagrass. Risk assessment and risk management research are integral components of this grass biotechnology program. ‘Argentine’ bahiagrass is a tetraploid apomict which reproduces by producing seeds and vegetatively by stolons. We are investigating the targeted, selective elimination of transgenic plants by engineering inducible cell death. Inducible cell death with the ArgE/ N-acetyl phosphinothricin system could be used for selective control of transgenic plants and for monitoring vegetative and sexual reproduction of transgenic plants. N-acetyl phosphinothricin is a non-toxic herbicide precursor which is converted to toxic herbicide phosphinothricin (glufosinate) by the ArgE gene product. Transgenic plants expressing the ArgE gene have been generated by biolostic transformation with the ArgE gene under the control of a constitutive ubiquitin promoter. Gene expression in the transgenic lines was confirmed with RT-PCR analysis and real-time RT-PCR was used to identify lines with high expression of the ArgE gene. Following subcloning of the transgenic plants we will apply N-acetyl phosphinothricin to determine the functionality of the proposed system.

*S. Sandhu, [email protected]

Plant Regeneration of Lotononis through Cotyledon Culture M.L. Vidoz* and K.H. Quesenberry

Agronomy Dept., Univ of Florida, Gainesville, FL 32611-0500

Lotononis (Lotononis bainesii Baker) is a subtropical forage legume, which prefers sandy soils and exhibits some frost tolerance. The objective of this research was to evaluate the effect of different plant growth regulators (PGR) on the in vitro response of cotyledons of 50 genotypes of lotononis. Seeds were scarified with concentrated sulphuric acid for five minutes, rinsed with running water for 10 minutes, surface disinfected in 70% ethanol for 30 seconds followed by 0.6% NaOCl plus one drop Tween 20® for 10 minutes, and rinsed 3x with sterile distilled water. Disinfected seeds were placed onto half strength Murashige and Skoog (1962) basal medium (MS) with 1.5% sucrose and 0.7% agar for germination. Cotyledons from one-week-old seedlings were cut longitudinally into two pieces, so that four pieces were obtained per genotype and placed onto MS without PGRs, MS + 1mg L-1 thidiazuron (TDZ), MS + 1mg L-1 2,4-dichlorophenoxyacetic acid (2,4-D), and MS + 1mg L-1 picloram (PIC), respectively. Cultures were incubated at 25±2 ºC, with 14-h photoperiod. After two weeks, 54% of the genotypes developed adventitious buds from small callus produced on explants on medium containing TDZ. Explants placed on the medium devoid of PGRs remained irresponsive, whereas those cultured on media containing either 2,4-D or PIC produced callus but no organogenesis. After 60 d, buds were transferred to MS + 0.01 mg/L benzyladenine + 0.01mg/L indolebutyric acid, where they elongated and rooted. Plants were placed onto MS without PGRs for further development. Regenerated plants were successfully acclimatized ex vitro.

*M.L. Vidoz, [email protected]




Preliminary Studies on the Effect of Chitosan on the Germination of Cabbage Seeds Inoculated with Xanthomonas campestris pv campestris (Pammel)

Camille Webster*1, Kome U. Onokpise2, Michael Abazinge1, and James Muchovej2

1Environmental Sci. Inst., Florida A&M University, Tallahassee, Florida 32307 2Division of Agric. Sci., Florida A&M University, Tallahassee, Florida 32307

Black rot in cabbage (Brassica oleracea var capitata L.) can cause significant reductions in yield. Black rot is caused by the bacterium, Xanthomonas campestris pv campestris (Pammel) Dowson, and is a destructive disease of worldwide importance. X. campestris pv campestris is dependent on type III protein secretion system, which relies on transport proteins, secreting several hypersensitive reaction proteins and outer proteins, causing an interaction with the plant. Chitosan is a hydrophilic polyelectrolyte and an insoluble biopolymer that is widely distributed in nature. It has been exploited as a seed treatment and pesticide. The objective of the present study was to investigate the effect of chitosan on the germination of cabbage seeds inoculated with X. campestris pv campestris. Inoculated seeds were treated with 1 g, 3 g and 5 g of different concentrations of chitosan and sown in trays containing washed construction sand in a greenhouse for 14 d. During this period, the average daily temperature was recorded. Moisture content (%) and pH of the soil as well as percent seed germination were determined. Germination decreased in inoculated seeds with an increase in the concentration of chitosan. Soil of inoculated seeds had a higher pH compared to that of the non inoculated seeds. Soil pH was extremely high with increasing concentration chitosan. The results suggest that X. campestris pv campestris and chitosan per se contribute to high soil pH and subsequently to reduced seed germination. Further studies are underway to determine the effect of chitosan on X. campestris pv campestris.

*Camille Webster, [email protected]

Cool-season Forage Production in Silvopastoral Systems in North Florida

S.K. Bambo*1, J. Nowak1, A.R. Blount2, A.J. Long1, and R.O. Myer2

1School of Forest Resources and Cons., Univ. of Florida, Gainesville, FL 32611-0410 2North Florida Res. and Educ. Center, Univ. of Florida, Marianna, FL 32446 -7906

Little information is available about winter forage production in silvopastoral systems in the southeastern U.S. The objectives of this research were to evaluate the quantity and quality of winter forage combinations under silvopastoral versus open pasture systems in north Florida. Ryegrass (Lolium multiflorum Lam.) (R), crimson clover (Trifolium incarnatum L.) (C), and red clover (Trifolium pretense L.) (D) in combinations of R, RC, and RCD forage treatments were overseeded into an ‘Argentine’ bahiagrass (Paspalum notatum Flügge.) sod under a thinned 18-year old (200 trees ha-1) loblolly pine (Pinus taeda L.) stand, composed of two tree configurations (scattered and double-row), and in a pasture (no tree cover) in November 2003 and 2004. Forage treatments were replicated four times in a randomized complete block design. Samples were clipped in the spring of 2004 and 2005. Dry matter (DM), crude protein (CP), and in vitro organic matter digestibility (IVOMD) were determined on oven-dried samples. Overall, pasture (7,417 kg ha-1) produced 20% and 34% more DM than double-row (5,924 kg ha-1) and scattered (4,866 kg ha-1) tree configurations, respectively. Double-row produced 18% more DM than scattered tree configuration. Forage from the pasture treatment had approximately 3% greater IVOMD (77.4%), but similar CP (19%) compared to silvopasture. Both RC (6,238 kg ha-1) and RCD (6,177 kg ha-1) had increased DM production compared to R (5,792 kg ha-1), but IVOMD (75.5%) and CP (19.5%) were similar. Based on forage yield and quality, a mid-rotation loblolly pine stand can be converted to productive silvopasture.

*S.K. Bambo, [email protected]




GRADUATE STUDENT FORUM ABSTRACTS - SOILS AND

ENVIRONMENTAL QUALITY Soil Properties in Traffic and No-Traffic Areas in Golf Courses and Relationship

with Goosegrass Growth

Claudia Arrieta*1, Philip Busey1, and Samira Daroub2

1Fort Lauderdale Res. and Educ. Center, Univ. of Florida, Fort Lauderdale, FL 33314 2Everglades Res. and Educ. Center, Univ. of Florida, Belle Glade, FL 33430-8003

Goosegrass (Eleusine indica) is a serious weed in golf and sports bermudagrass turf. Growth of goosegrass on traffic areas has been considered an indicator of compacted soil. The objectives of this study were to investigate the relationship between compaction and goosegrass occurrence and compare soil properties in traffic and no-traffic areas of golf tees on three courses in South Florida. Soil penetrometer resistance (SPR), water and organic matter content, and goosegrass cover and plants numbers were measured for each side of the tee on five tees in each golf course. Four relatively undisturbed soil cores were taken from traffic and no-traffic sides and analyzed for saturated hydraulic conductivity, pore space content, distribution (macro, micro), bulk density, and water holding capacity. Number of goosegrass plants and cover differed between sides of the tees and showed higher values on the traffic sides. The SPR was analyzed by depth at in 2.5-cm increments from 2.5 to 12.5 cm. Soil penetrometer resistance was marginally related to traffic across all three golf courses at 2.5-cm depth. The effect was attributable to one golf course in which traffic affected penetrometer resistance at all depths. There was no effect of traffic on any soil parameter. However, organic matter was associated with both bulk density and volumetric water content; and SPR with water holding capacity by volume and micropore percentage (P<.05). We conclude that goosegrass infests trafficked areas more than non-trafficked areas, but it is not related to compacted soil.

*Claudia Arrieta, [email protected]

Soil Carbon Pools in Slash Pine-Based Silvopastoral Systems of Florida

Solomon G. Haile*1, P.K. Ramachandran Nair1, and Vimala D. Nair2

1School of Forest Resources and Cons., Univ. of Florida, Gainesville, FL 32611 2Soil and Water Sci. Dept., Univ. of Florida, Gainesville, FL 32611

Compared to most agricultural systems, tree-based land-use systems such as silvopasture, that integrate trees in pasture production systems, are likely to enhance soil C sequestration in deeper zones of the soil profile. The total soil C at six depths (0-5, 5-15, 15-30, 30-50, 50-75, and 75-125 cm) were determined in a silvopasture of slash pine (Pinus elliottii) + bahiagrass (Paspalum notatum), and on an adjacent treeless pastures at two sites, representative of Spodosols and Ultisols in Florida. The C contents within three fraction-size classes (<53, 53-250, and 250-2000 µm) of each soil profile were determined. Using stable C isotope signatures, the plant sources (C3 vs C4 plant) of C fractions were determined and traced at both sites. Compared with the treeless pasture, the Spodosol profile between trees in a row in the silvopasture contained more C in the fraction <53µm at and below the spodic horizon (40-cm deep). In both soil types, the C3 plant (slash pine) contributed more C in the smallest soil fraction (<53µm) than the C4 plant (bahiagrass) at all soil depths, particularly at the lower depth. The results support the hypothesis that under similar ecological settings, silvopastoral systems retain more stable C fraction in the soil profile than under treeless pasture.

*Solomon G. Haile, [email protected]




Manure Components Affecting Phosphorus Stability of Dairy Manure-Amended Soils

M.S. Josan*, V.D. Nair, and W.G. Harris

Soil and Water Sci. Dept., Univ. of Florida, Gainesville, FL 32611

Manure applications to soils not only elevate P concentrations, but also result in a build-up of manure-derived components such as Mg, Ca, Si, and dissolved organic carbon (DOC). Despite high pH and abundant Ca in manure, stable forms of Ca and P such as apatite, do not form and high levels of P continue to be released from manure-amended soils. In this study we evaluated the inhibitory effects of Mg, Si, and manure-derived DOC on Ca-P crystallization in the presence and absence of solids (clay-sized fractions). Solutions containing Mg, Si or DOC were prepared in a medium containing the average leachate concentrations of the other major chemical species found in manure-amended soils. These solutions, including a control, were incubated with and without clay fractions obtained from these soils for 20 wk. The median equilibrium concentrations of Ca and P after incubation were significantly less in solutions without solids, with the exception of the DOC-solution. In the presence of solids, the control and Si-solution had lower median P concentrations (28 mg/L) than the Mg-solution (34 mg/L). The presence and absence of solids did not affect the behavior of P in the DOC-solution (50 mg/L); however Ca concentrations declined from 266 to 144 mg/L possibly due to organic complexation. Formation of hydroxyapatite in both the control and Si-solution and the more soluble brushite in the Mg-solution were confirmed by x-ray diffraction. Therefore, Mg in manure-amended soils can inhibit the formation of stable forms of calcium phosphates.

*M.S. Josan, [email protected]

Reducing Phosphorus Loss from Pastureland through Silvopasture

G.-A. Michel*12, V.D. Nair2, P.K.R. Nair1

1School of Forest Resources and Cons., Univ. of Florida, Gainesville, FL 32611

2Soil and Water Sci. Dept., Univ. of Florida, Gainesville, FL 32611

Phosphorus loss from sandy soils that predominates the 1.4 million ha of pastureland in Florida is a major cause of nutrient pollution of water bodies. We hypothesize that the loss of P to surface and ground water could be less from silvopastoral systems than from treeless pastures because the trees would remove the nutrient from the soil. An on-farm research was conducted in 2004 on two slash pine (Pinus elliottii)–bahiagrass (Paspalum notanum) silvopastoral systems located in Manatee (270 13' N, 820 8' W) and Suwannee (300 24' N, 830 0' W) counties. The soils in Manatee and Suwannee are respectively Spodosols and Ultisols. Soil samples were collected by depth (0–5, 5–15, 15–30, 30–50, 50–75, and 75–100 cm.) The soil P storage capacity (SPSC), the maximum amount of P that can safely be applied to a soil before it becomes an environmental concern, was used as the environmental soil P indicator. Water-soluble P concentrations at 0- to 5-cm depth were 4 and 10 mg kg-1 respectively, in the silvopasture and treeless pasture in Suwannee and 11 to 23 mg kg-1 in Manatee. Total SPSC to one meter depth were 337 and -59 kg ha-1, respectively, in the silvopasture and treeless pasture in Suwannee and 329 and 191 kg ha-1, respectively, in Manatee, suggesting that P buildup within the soil profile was less in the silvopastoral systems than in the treeless pastures.

*G.-A. Michel, [email protected]

Basis for Estimating P Source Coefficients for the Florida P Index

Olawale O. Oladeji*, George A. O’Connor, and Jerry B. Sartain


Realization that different P sources can result in varying P losses prompted inclusion of a P-source coefficient in Florida P index. However, three P-source coefficients (PSC) in the drafted P index (0.05 for fertilizer and manure, 0.015 for biosolids, and 0.10 for waste water) may be insufficient. We investigated impacts of P sources on P losses, and identified basis for PSC determination that could account for the varying P losses. Four P sources [poultry manure, Boca Raton biosolids (high water soluble P), Pompano biosolids (low water soluble P), and triple super phosphate (TSP)] were surface applied to a Florida




sand at two rates (56 and 224 kg P ha-1) to represent low and high soil P loads typical of P-based and N-based rates. Simulated rainfall was applied at 71 mm h-1 on amended soils in boxes constructed to national protocol specifications but modified to collect leachates. Masses of bioavailable P (BAP) lost from various P sources followed similar trends with source percentage water extractable P (PWEP; values in parentheses): TSP (84%) > manure (18%) > Boca Raton biosolids (12%) > Pompano biosolids (4%). Regression of BAP loss with application rate (r2=0.36) was improved by accounting for P source differences with Florida P index coefficients (r2=0.54) and Pennsylvania PSC values (r2=0.70), but better with PWEP (r2=0.83). The result agreed with another leaching study with two Florida soils amended with eight biosolids, chicken manure, and TSP. Use of coefficients based on PWEP of source is suggested for the Florida P index.

*O.O. Oladeji, [email protected]

Controlling Phosphorus Loss from a Manure-Impacted Soil with Aluminum Water Treatment Residuals

T.J. Rew*, D.A. Graetz, Vimala D. Nair, and George O'Connor


Dairy and beef operations in the Lake Okeechobee watershed in Florida and across the nation are receiving attention as a result of their contribution of P to surficial water bodies. Prior research has shown that water treatment residuals (WTR) are capable of sequestering soluble P thereby reducing P loss through runoff and leaching. The objective of this research was to evaluate an Al-WTR for controlling P loss from a manure-impacted soil obtained from a dairy sprayfield. Soil samples were removed as 0 to 10 cm and 10 to 20 cm layers and packed in boxes (100 cm x 30 cm x 20 cm) designed to collect runoff, subsurface flow, and leachate. Water treatment residual at a rate of 2.5% of soil dry weight was either surface applied or incorporated to 10 or 20 cm depths. The soil was then sprigged with stargrass (Cynodon nlemfuensis). Water was applied with a rainfall simulator following a nationally recommended protocol. Subsurface flow and leachate were collected after runoff ceased from a depth of 10 and 20 cm, respectively. Surface application of WTR reduced soluble P (SP) in surface runoff by 75% but did not affect SP in subsurface drainage and leachate. Incorporation of WTR reduced runoff SP by approximately 45%. However, SP in subsurface flow and leachate was reduced by approximately 90 and 95%, respectively, when the WTR was incorporated into the 20 cm of soil. These results show that Al-WTR can be effective in reducing P losses from manure-contaminated soils.

*T.J. Rew, [email protected]




GENERAL SESSION ABSTRACTS - SOILS Sugarcane Plant Crop Response to Phosphorus Fertilizer in Two Locations on

Organic Soils in Florida

J.M. McCray*1, Y. Luo1, R.W. Rice2, and I.V. Ezenwa3

1Everglades Res. and Educ. Center, Univ. of Florida, Belle Glade, FL 33430 2Palm Beach County Extension Service, Univ. of Florida, Belle Glade, FL 33430

3Southwest Florida Res. and Educ. Center, Univ. of Florida, Immokalee, FL 34142

Phosphorus concentration in water draining to the Everglades is a primary environmental concern in south Florida. Of the 283,500 ha of cropland in the Everglades Agricultural Area (EAA), over 162,000 ha are in sugarcane production. This study is being conducted to update the UF/IFAS soil test calibration used for P fertilizer recommendations for sugarcane on organic soils in the EAA. Two small-plot studies (Everglades Res. and Educ. Ctr, EREC, and a grower’s field) were established in fall 2004 to investigate the effects of P fertilizer rate (0, 9.2, 18.4, 36.6, 73.4, and 146.7 kg P ha-1) and placement (band and broadcast) on sugarcane production. Pre-application acetic acid extractable P index was 50 at the EREC site and 25 at the grower site and the soil type at each location is Dania (Euic, hyperthermic, shallow Lithic Medisaprist). At the grower site there were increases in stalk population at the higher P rates. However, there were no differences in sugar production (Mg ha-

1) between rates. At the EREC site there were no responses to P fertilizer application. Fertilizer placement was not a significant factor in sugar production in the first year at either location. Previous work has shown more responses in the ratoon crops than with plant cane, so following these tests for two more years will be important. Results will then be combined with previous research to update UF/IFAS recommendations.

*J.M. McCray, [email protected]

Application Rate of Water Treatment Residuals Based on Agro-Environmental Thresholds

Olawale O. Oladeji*, Jerry B. Sartain, and George A. O’Connor


Studies have shown water treatment residuals (WTR) are useful soil amendments to control excessive soluble P in soils. Applying WTR without considering its chemical composition (Al, P, and Fe contents) however, could result in inadequate or excessive immobilization of soil soluble P. This study evaluated the influence of application rates of WTR and P sources on soil P solubility, plant yields, and P concentrations and attempted to identify basis for application rates of the residuals. Bahiagrass (Paspalum notatum Fluggae), ryegrass (Lolium perenne L.) and a second bahiagrass cropping were grown in that sequence in a P-deficient soil amended with four P sources at two application levels (N and P-based rates) and 3 WTR rates (0, 1, and 2.5% oven dry basis) in a glasshouse pot experiment. Soil P storage capacity (SPSC) increased following application of WTR, and the increase varied with P sources and application rates. Soil soluble P increased with reduction in SPSC with a change point at 0 mg kg-1 SPSC. A change point was also identified in plant yield at bahiagrass P concentration of 2.0 g kg-1 equivalent to 0 mg kg-1 SPSC. Similar result was obtained from a 2-yr field experiment with similar treatments surface applied to established bahiagrass. The 0 mg kg-1 SPSC was shown to be an agronomic threshold, and applying P sources at N-based rate along with WTR sufficient to give 0 mg kg-1 SPSC reduced environmental hazards of P without negative agronomic impacts.

*O.O. Oladeji, [email protected]




Loading of Heavy Metals in Runoff Water from Citrus Groves and Vegetable Fields in the Indian River Area

Z.L. He*1, P.J. Stoffella1, X.E. Yang2, D.V. Calvert1, and Y.C. Li1

1Indian River Res. and Educ. Center, Univ. of Florida, Fort Pierce, FL34945-3138

2Ministry of Educ. Key Laboratory of Environ. Remediation and Ecol. Health, Zhejiang Univ., Hangzhou, China

Water quality throughout South Florida has been a major concern for many years. The input of heavy metals into surface water through runoff water from agricultural area is also a potential problem. The objective of this study was to monitor and assess heavy metals in surface runoff from agricultural production systems in the Indian River area. Five citrus groves and two vegetable fields on commercial farms in the Indian River area were selected for this monitoring study. Autosamplers were installed in the field to collect surface runoff water samples and record rainfall and surface water discharge data. Runoff water samples were collected and analyzed for the concentrations and loadings of Cu, Zn, Ni, Pb, Cd, and Co. The concentrations of Cd, Ni, and Pb in runoff water from the fields were minimal, but those of Cu and Zn water were relatively high. The annual mean concentrations of Cu from the seven field sites ranged from 0.01 to 513 mg L-1, with a mean (2000-2005) of 64.4 mg L-1, and Zn from 0.02 to 179 mg L-1, with a mean of 21.0 mg L-1. The annual loads of Cd ranged from 0 to 2.34 g ha-1 y-1, with a mean of 0.22 g ha-1 y-1; Cu from 0.004 to 664 g ha-1 y-1, with a mean of 104 g ha-1 y-1; Ni from 0 to 8.21 g ha-1 y-1, with a mean of 1.42 g ha-1 y-1, Pb from 0 to 7.79 g ha-1 y-1, with a mean of 0.65 g ha-1 y-1, and Zn from 0.002 to 281 g ha-1 y-1, with a mean of 45.9 g ha-1 y-1. Runoff water discharge rate and concentrations in runoff water were the controlling factors for transport of heavy metals from agricultural fields.

*Z.L. He, [email protected]

Soil-Test Phosphorus Trends in Everglades Agricultural Area Histosol Profiles

Y. Luo*1, G. Kingston2, R.W. Rice3, and J.M. Shine, Jr.4

1Everglades Res. and Educ. Center, Univ. of Florida, Belle Glade, FL 33430

2BSES Limited, Bundaberg DC, QLD 4670, Australia 3Palm Beach County Extension Service, Univ. of Florida, Belle Glade, FL 33430

4Sugar Cane Growers Cooperative of Florida, Belle Glade, FL 33430

Over time, soil profiles in the Everglades Agricultural Area have changed as a consequence of soil subsidence. Our objective was to characterize soil test P (STP) with depth in six different Histosol soil series (euic, hyperthermic Haplosaprists). Soil profiles were sampled at 25-cm increments, air-dried, and extracted using four STP methods including water (Pw), acetic acid (Pa), Mehlich-1 (M1), and Mehlich-3 (M3). For a deep (90-152 cm) Torry soil series with relatively low (43%) organic matter (OM), Pw declined from 2.2 to 0.7 mg kg-1 (32%), Pa from 49.9 to 34.4 mg kg-1(69%), M1 from 43.6 to 30.7 mg kg-1 (70%), and M3 from 24.1 to 5.2 mg kg-1 (22%) for the 0- to 25-cm and the 75- to 100-cm increments, respectively. For the Terra Ceia, another deep (186-226 cm) soil series with greater (69%) OM, Pw decreased from 109 to 4.5 mg kg-1 (5%), Pa from 2455 to 100 mg kg-1 (4%), M1 from 1474 to 69.4 mg kg-1 (5%), and M3 from 1982 to 36.1 mg kg-1 (2%), respectively. A similar trend occurred for two medium depth soil series, Pahokee and Lauderhill, with all P measurements declining (6-7% Pw; 10-16% Pa; 15-60% M1-P; and 4-5% M3-P) from the 0- to 25-cm to the 75- to 100-cm increments. For the two shallow soils, Dania (11-56 cm) and unclassified “Villa Lago” (16-26 cm), Pw, Pa, M1-P, and M3-P ranged between 8.4 to 26.2, 138 to 420, 65.4 to 211, and 74.3 to 374 mg kg-1 for the 0- to 25-cm increment, respectively. In general, STP concentrations across methods were greatest at the soil surface and declined rapidly with depth.

*Y. Luo, [email protected]




Utility of Mehlich 1 and Mehlich 3 Soil Tests to Predict Citrus Tree Nutritional Status

T.A. Obreza*1, R.E. Rouse2, and K.T. Morgan2

1Soil and Water Sci. Dept., Univ. of Florida, Gainesville, FL 32611

2Southwest Florida Res. and Educ. Center, Univ. of Florida, Immokalee, FL 34142

Florida citrus growers want to use soil testing to guide fertilization, but UF-IFAS soil test P, K, and Mg interpretations for citrus were not established using a rigorous, standard calibration method. The objective of this experiment was to determine if Mehlich 1 or Mehlich 3 soil tests are suitable for predicting citrus tree nutritional status. In November 1998, we planted ‘Flame’ grapefruit (Citrus paradisi) trees on previously non-cultivated Immokalee fine sand. In subsequent years, dolomitic lime and varying rates of P/K fertilizer were applied to establish a range of soil test values. The recommended N fertilizer rate was applied each year. Soil and leaf tissue samples were taken each August to track soil test changes and tree nutrition. Leaf tissue nutrients for a given year were correlated with soil test values from the previous year. The two extracting solutions provided roughly equal values of soil test P and K, but Mehlich 1 extracted substantially more Mg compared with Mehlich 3. Soil test K did not increase with K fertilizer application so correlation between leaf and soil K could not be attempted, but tree nutrition did respond positively to K-fertilizer rate. A relationship between leaf P and soil test P emerged in 2002 and became stronger in subsequent years. Leaf tissue P concentration below 1.2 g/kg (considered “low” nutrition) occurred only where soil test P was less than 10 mg/kg (a “very low” soil test). Leaf and soil test Mg were not sufficiently correlated to allow estimation of a critical value.

*T.A. Obreza, [email protected]

GENERAL SESSION ABSTRACTS - CROPS Effect of Topsin M and Karate on Square Abortion and Incidence of Hardlock

Disease in Cotton

E.A. Osekre*1, D.L. Wright2, and J. Marois2

1Agronomy Dept., Univ. of Florida, Gainesville, FL 32611-0500 2North Florida Res. and Educ. Center, Univ. of Florida, Quincy, FL 32351-5677

Hardlock disease, caused by Fusarium verticillioides, is a serious disease that reduced cotton yields in the Florida panhandle by 50-60% in 2002. It was estimated to have caused over $20 million in lost yield in that year. High plant density, high temperature, and high humidity during the growing season have been associated with the incidence of the disease. It is believed that thrips can help spread Fusarium verticillioides. Cotton variety trials conducted showed that the disease affects all varieties currently being grown. The disease is also believed to cause increased abortion of cotton squares, leading to reduced boll set. Field studies were conducted at North Florida Research and Education Center at Quincy to: 1) evaluate the effectiveness of a fungicide (Topsin-M), an insecticide (Karate), and a combination of the two pesticides for the control of the disease; and 2) determine the effects of environmental factors on the abortion of cotton squares. Results showed that there were no significant differences in the number of aborted squares and yield of the pesticide-treated cotton plants and the control. There were also no significant differences in hardlock incidence in the Karate or Topsin plus Karate treated plants and the control. Hardlock incidence in the Topsin-M treated plants was, however; significantly higher than in the untreated control. Relative humidity appeared to be the single most important environmental factor affecting cotton square abortion.

*E.A. Osekre, [email protected]




Chemical Composition of Soils Under Forages Grown Between Tree Rows of Loblolly Pine Trees

O.U. Onokpise*, L. Whilby, and N.G. Bradley

Agronomy, Forestry and Natural Res. Conservation Program.

Florida A&M Univ., Tallahassee, Florida 32307 In 2001 and 2002, 18 to 20 year-old loblolly pine (Pinus taeda L.) trees at the Florida A&M University Research and Community Development Center were systematically thinned for the establishment of an agrosilvopastoral system with Boer x Spanish crossbred goats (Capra hircus). Prior to seeding tree rows with either bahiagrass (Paspalum notatum Flügge) or bermudagrass [Cynodon dactylon (L) Pers.], soil samples were randomly collected at a depth of 15 cm. Thirty-three soil samples per hectare were collected from three separate blocks (2, 3 and 7) before, and 28 and 52 weeks after planting (WAP) using a soil probe. The soil samples were analyzed for macro- and micronutrients to evaluate the impact of tree and forage growth on soil nutrients compared to a parallel unshaded site. Overall, there was a significant decline in soil chemical composition over the 52 weeks of sampling in the shaded area for total Kjeldahl nitrogen (TKN), P, K, Zn, Ca, Mg, and S. However, in the unshaded areas, the reduction in TKN, Zn, Ca and P was non-significant. The implication of the results is that the agrosilvopastoral fields will have to be managed by individual blocks in order to ensure the effective utilization of nutrients not only among trees but also for the pasture grasses.

*O.U. Onokpise, [email protected]

Energy Fluxes and Land Surface Parameters in Grassland Ecosystems: Remote Sensing Prospective

Assefa M. Melesse*1, Al Frank2, Jon Hanson2, Mark Liebig2, and Vijay Nangia3

1Dept. of Environ. Studies, Florida International Univ.

2USDA, ARS, Northern Great Plains Research Laboratory,Mandan, ND 3Upper Midwest Consortium, Univ. of North Dakota

Characterization of land surface and estimation of energy flux values are required in many environmental studies including hydrology, agronomy, and meteorology. The continuous micro-scale energy exchange between the land surface and the near-surface atmospheric layer can be simulated using surface energy budget models. Spatial variability of energy fluxes in larger areas limits point measurements and necessitates remote sensing for spatial mapping of energy fluxes. A remote sensing-based land surface characterization and flux estimation study was conducted using data from 1997 to 2004 on two grazing land experimental sites located at the USDA, ARS Northern Great Plains Res. Lab., Mandan, ND. Spatially distributed surface energy fluxes (net radiation [Rn], soil heat flux [G], sensible heat [H], latent heat [LE], emissivity [•], albedo [• ], normalized difference vegetation index [NDVI] and surface temperature [Tsur] were estimated. These estimates were then mapped at a pixel level from Landsat Thematic Mapper and Enhanced Thematic Mapper images and weather information using the Surface Energy Balance Algorithm for Land (SEBAL) procedure as a function of grazing land management (heavily grazed, HGP, and moderately grazed pastures, MGP). Energy fluxes and land surface parameters were mapped and comparisons were made between the two sites. Over the study period, H, • and Tsur from HGP was higher by 6.7%, 18.2% and 2.9% than in MGP. The study also showed G, LE and NDVI were higher by 1.3%, 1.6% and 7.4% for MGP than in HGP. The results show remote sensing approach to characterize grassland sites was an effective technique.

*Assefa M. Melesse, [email protected]

Importance of Soil Organic Matter in Florida Citrus Production A.W. Schumann*, Q.U. Zaman, and K.H. Hostler

Citrus Res. and Educ. Center, Lake Alfred, FL 33850-2299

Florida citrus production is strongly affected by soil properties which are not always delineated by soil series. The objective of this study was to investigate the roles of soil organic matter (SOM) and mineral nutrients affecting production of selected




citrus groves. Five grid or transect soil surveys were conducted to collect soil samples for analysis from 4- to 6-profile-depth intervals (0-15, 15-30, 30-60, 60-90, 90-120, 120-150 cm). From a sixth site, soil samples from the same depth intervals were collected as pairs, comparing citrus grove soils with adjacent unplanted soils. Soil organic matter, pH, EC, density and color were measured for all samples, and exchangeable acidity, DTPA-extractable Fe, extractable P, K, Ca, Mg, and CEC were analyzed for selected samples. Tree vigor and size were estimated from color-NIR aerial photographs using the Normalized Difference Vegetation Index (NDVI). Stepwise multiple regression analysis revealed that SOM was correlated with tree performance across all sites. Comparison of citrus with non-citrus soils showed that after more than 40 years of grove monoculture, SOM was significantly depleted by 36.5 Mg/ha in the upper 15 cm of the sampled soil profile. The importance of SOM in Florida’s sandy citrus soils was demonstrated, and growers should implement options to conserve this important soil property.

*A.W. Schumann, [email protected]

Soil Conditions Affect Sweet Corn and Sunnhemp Initial Growth and Root Proliferation

B.R.Morton*, J.C. Linares, J.M.S. Scholberg, and K.J. Boote

Agronomy Dept., University of Florida, Gainesville, FL 32611-0500

Roots are critical for the interception of nutrients before nutrient loss can adversely impact the environment. A study was conducted to determine the effect of soil conditions (dry, moist, compacted, and nutrient addition) on root growth, root proliferation patterns, and shoot growth of sweet corn (Zea mays L.) and sunnhemp (Crotalaria juncea L.). Acrylic growth tubes were filled with potting soil and root growth was monitored at 2 to 3 day intervals. The soil compaction treatments greatly reduced root elongation and rooting depth for both species. Soil water deficit increased root elongation for sweet corn at 2 wk after planting but subsequently rate of root growth slowed, possibly due to reduced assimilate supply. Sweet corn, being a C4 species, grew faster and had much higher root length intensity. Sunnhemp, a C3 species, grew slower but was less affected by adverse soil conditions. While sweet corn had an exponential decrease in root length intensity with depth, sunnhemp had a relatively more even root distribution throughout the upper 60 cm of the soil profile. Water use efficiency (WUE) for sweet corn was enhanced by either water stress or supplemental nutrients and values were twice as high as those for sunnhemp. Growth and WUE for sunnhemp were not affected greatly by adverse soil conditions, probably related to the smaller plant size of sunnhemp at this stage of growth.

*B.R.Morton, [email protected]

Fertilization of Grazed Bahiagrass Pastures in South Florida M.B. Adjei1 and J.E. Rechcigl*2

1Range Cattle Res. and Educ. Center, Univ. of Florida, Ona, FL 33865

2Gulf Coast Res. and Educ. Center, Univ. of Florida, Wimauma, FL 33598

The objective of this 8-yr study was to test the UF/IFAS hypothesis that P or K fertilization was not needed on grazed bahiagrass (Paspalum notatum) pastures in south Florida. Sub-plot, fertilizer treatments: 1) 67 kg N ha-1 (N); 2) 67-12-56 kg N-P-K ha-1 (NPK); 3) 67-12-56 kg N-P-K ha-1 plus 22 kg ha-1 of micronutrients mix (NPKM); and 4) control (no fertilizer) were superimposed annually on lime (pH > 5.0) vs no-lime (pH<4.5) treatments from 1998 to 2005 on two grazed pastures (71A and 81). The 8-yr mean forage dry matter yield (11.9 Mg ha-1) was not different due to treatment on pasture 71A but was improved with lime vs no-lime treatment (9.4 vs 7.4 Mg ha-1) and with the NPK treatment over the other fertilizer treatments under liming (10.5 vs 9.9 Mg ha-1) on pasture 87. Plant tissue P averaged 2.6 g kg-1 for the NPK and NPKM treatments regardless of pasture or liming treatment, but declined progressively from 2.5 to 1.8 g kg-1 for the N and no-fertilizer treatments during 8 years. Similarly, tissue K averaged 12.5 g kg-1 for the NPK and NPKM treatments on both pastures and liming situations but declined to 8.1 g kg-1 for the N and no-fertilizer treatments during the same period. These results generally validate the need for little additional K or P on grazed bahiagrass for yield improvement but the huge decline in tissue P and K concentrations over time for the N-only treatment could weaken the sod.

J.E. Rechcigl, [email protected]





Preliminary Observations on Growth and Yield of Kenaf in Florida J.J. Ferguson*1, G.W. Feaster2, and J.J. Sifontes 3

1Horticultural Sci. Dept., Univ. of Florida, Gainesville, Fl 32611-0690 2Kenaf USA, LLC., St. Augustine, Fl 32080 3 Sigarca, Inc., Gainesville, Fl 32605-1468

Two kenaf (Hibiscus cannabinus L) cultivars Guatemala-4 and India were planted near Citra, FL, on 24 June 2004 using a grain drill and an air planter at plant densities ranging from 143,000 to 334,000 seeds ha-1 based on 4.5 m 2 samples for both cultivars. All plots were fertilized with 447 kg ha-1 of a 20-16.6- 8.8 fertilizer before planting and 261 kg ha-1 of ammonium nitrate (33.5% N) on 10 Aug. 2004. Seedlings emerged approximately 7 d after planting. By 70 d after planting, height and dry weight of Guatemala-4 plants were generally greater than that of India plants. Ninety days after planting, yield of India plants mowed at 15- and 30-cm height ranged from 353 to 314 Mg ha-1 fresh weight, respectively, based on plants harvested from 0.02 ha samples. Comparisons of growth and yield of cultivars planted at different densities with different planting methods were not possible because of severe root knot nematode damage.

*J.J. Ferguson, [email protected]

Efficacy of Jack Frost Foam® for Frost Protection on Vegetable and Strawberry Transplants

R.J. McGovern*1, C.R. Semer IV1, and Lajos Pecsenka2

1Plant Pathology Dept. and Plant Medicine Program, Univ. of Florida, Gainesville, FL 32611-0500

2American Ag. Foam LLC, Casper, Florida 34667

This research evaluated Jack Frost Foam® (American Ag Foam LLC, Casper Fl.) applied to pepper, tomato, squash, watermelon and strawberry transplants for frost protection Two experiments were conducted (2005 and 2006) at Univ. of Florida, Plant Sci. Res. and Educ. Unit, at Citra, FL. Transplants were planted in 16 December and 17 January into fumigated beds covered with plastic mulch. The experiment a complete randomized split plot design with six replications consisting of 6 to 20 plants per replication. Watch Dog Model 425 data loggers positioned 14 cm above the soil line were used to record the temperatures in one protected plot and one control plot. The foam was hand applied to a height of 35 cm above the bed. Two frost events occurred in December and one frost event occurred in January. The results of both tests were similar; the foam provided a 6.2 to 10.7 º C temperature increase at the meristem of the treated transplants versus the unprotected transplants. Transplants not protected with the foam died within 24 to 48 hr after the frost event due to freeze injury. The treated plots showed some plant loss in areas where the foam was blown off the plots.

*R.J. McGovern, [email protected]

Influence of Grazing Frequency on Cynodon Grasses Grown in Peninsular Florida P. Mislevy*

Agronomy Dept., Range Cattle Res. and Educ. Center,

Univ of Florida, Ona, FL 33865

Bermudagrass (Cynodon doctylon L. Pers.) and stargrass (C. nlemfuensis Vanderyst var. nlemfuensis) are among the most important of the warm-season perennial grasses used in warmer regions of the world. The purpose of this experiment was to test four lines each of stargrass and bermudagrass at different grazing frequencies (GF) for dry biomass (DB) yield, nutrient value, and persistence. A split-plot arrangement of a RCB with three replicates with GF (2, 4, 5, and 7 wk) as the main plot and grass entries/cultivars (Stargrass 2000, Florona, Okeechobee, and Ona Pasture No. 2 stargrass; Bermudagrass 2000, Jiggs, World Feeder, and Tifton 85 bermudagrass) as subplots was used. Dry biomass yield was monitored during the warm (May - December) and cool (December - March) seasons over a 3-yr period. Crude protein (CP) and in vitro organic matter digestion (IVOMD) was monitored June to November 2002 and April to October 2003. Warm season annual fertilization (four split N applications) consisted of 224-15-56 kg ha-1 N-P-K + micros. At the beginning of the cool season 56 kg ha-1 N




was applied. Warm season DB yield of grass entries interacted with GF. Decreasing GF from 2 to 7 wk resulted in a linear increase in DB yield. Bermudagrass 2000 and Jiggs bermudagrass were among the two highest yielding entries between 7.6 and 6.9 Mg ha-1, respectively, at 2 wk GF, and 20.8 and 18.4 Mg ha-1, respectively, at 7 wk GF. Winter forage production after 12 wk regrowth averaged 2.5 and 2.4 Mg ha-1, respectively, for these same two entries.

*P. Mislevy, [email protected]

A Model for Sustainable Production of Habanero Peppers G.L. Queeley*, C.S. Gardner, and T.A. Hylton

Coop. Ext. Service, College of Engineering Sci., Technology, and Agriculture,

Florida A & M Univ., Tallahassee, FL 32307

America’s fascination with spices has resulted in a diverse array of hot pepper (Capsicum spp.) name brands and differentiated spicy condiments on the shelves of grocery stores and restaurants throughout the United States. A market that was historically dominated by Tabasco products, is now overrun with scores of new brand items ranging from jellies and cheeses to various intensities of the more popular salsa. As the demand for spicy products escalate throughout the U.S., hot peppers will no doubt play a leading role in the success of the spicy condiment industry. The demand for fresh hot peppers and their value-added by-products will no doubt lead to expansive land clearage for production. This will further translate into an increased demand for inputs such as fertilizers and pesticides in an effort to maximize profits. Extensive land clearage combined with non discretional use of agricultural chemicals traditionally have been known to have adverse effects on the environment. Published examples include eutrophication of streams, groundwater contamination and ecological imbalance. It is therefore imperative that as we strive to satisfy our cravings for spicy condiments, we develop sustainable models using low cost production inputs that jointly alleviate environmental concerns and at the same time minimize costs and maximize profits.

*G.L. Queeley, [email protected]

Response of Scotch Bonnet Hot Pepper to Incremental Phosphorous Levels on a Sandy Loam Soil

C.S. Gardner and G.L. Queeley*

College of Engineering Sci., Technology, and Agriculture, Florida A& M Univ., Tallahassee, FL 32307

Phosphorous is an essential element for plants and is not always readily available for uptake on most soils. In crop production systems, low availability has been addressed by application of P fertilizers or lime. However, even when adequate amounts of P exist in soils, farmers tend to apply incremental amounts of fertilizers to their crops to ensure profitable yields. The efficiency of this process may be affected by factors such as P immobilization in the soil and the cost of fertilizer acquisition and application. Furthermore, intensive P fertilization may lead to runoff and pollution of surface water resources. Therefore, application of phosphorous fertilizer, plant P uptake and use, and soil phosphorous are of considerable interest in agro-ecosystems. A one year study was conducted to determine the threshold application rate of P fertilizer for growth and yield of Scotch Bonnet hot pepper (Capsicum chinense Jacq.), a crop being developed to benefit small-scale farmers. The experiment was arranged as a RCB design with six replicates. Six levels of P (TSP 0-46-0) were applied in equally spaced amounts of 0, 56, 112, 168, 224, and 280 kg ha-1. Soil type at the site was an Orangeburg sandy loam with a baseline P level of 21 ppm. Data were collected on parameters such as fruits per plant, fruit size, and marketable fruit yield (kg ha-1). Results showed significant increases in fruit size for applied P over baseline P level. The study suggests that baseline P level is adequate to sustain plant growth and yields.

*G.L. Queeley, [email protected]





SOCIETY AFFAIRS

2006 PROGRAM SOIL AND CROP SCIENCE SOCIETY OF FLORIDA

AND FLORIDA NEMATOLOGY FORUM

SIXTY-SIXTH ANNUAL MEETING

4 – 6 June 2006

Tampa Marriott Westshore Tampa, FL

SOCIETY OFFICERS

President……………………………………………………………………………………... Ken Boote

President–Elect and Program Chairman…………..................................................................Martin Adjei Past President……………………..…………………………………………………….Bill Thomas Secretary–Treasurer………………………………………………………………………Thomas Obreza Director…………………………………….…………..………………………………..…..Lena Ma Director……………………………………..…………………………………………...Greg McDonald Director……………………………………………………………………………….....Samira Daroub Proceedings Editor……………………………………………………………………...Ken Boote

2006 PROGRAM SUMMARY

Sunday, 04 June 2006

Time Event Room 12:00 Noon Registration begins Foyer 5:00 PM Board Meeting Boardroom 6:00-7:00 PM Welcome Reception Salons D & E

Monday, 05 June 2006

Time Event Room 7:00 AM Registration continues Foyer 7:00-8:00 AM Continental Breakfast Foyer 8:30-9:45 AM Joint General Session Salons A & B 10:00-12:00 Noon Graduate Student Forum – Crops Cotillion/Terrace 10:00-12:00 Noon Graduate Student Forum – Soils and Environmental Quality Salon E 1:30-3:15 PM General Session I – Soils Salon E 3:30-5:00 PM General Session II – Crops Salon E

Tuesday, 06 June 2006

Time Event Room 8:30-9:45 AM Business Meeting Salon E 10:00-12:00 Noon General Session III – Assorted Topics Salon E


2006 SESSIONS

Monday AM, 05 June 2006

2006 GRADUATE STUDENT FORUM PAPER SESSIONS

Crops

Enhancing Turf Quality in Bahiagrass by Over-Expression of Gibberellin Catabolizing Enzyme – M.A. Agharkar*, F. Altpeter, H. Zhang, M. Gallow, K. Quesenberry, S. Wofford, and G.L Miller

Nutrient Composition of Tifton-9 Bahiagrass in the First Season of a Silvopastoral System with Boer x Spanish Goat Crossbreeds – N. Bradley* and O.U. Onokpise

Growth and Phenological Reponse of Legumes Native to the Longleaf-Wiregrass Ecosystem in Two Light Environments – S.E. Cathey*, T.R. Sinclair, and L.R. Boring

Extended Daylength and Fertilization Effects on Above- and Below-ground Bahiagrass Mass and Chemical Composition – S.M. Interrante*, L.E. Sollenberger, A.R. Blount, T.R. Sinclair, J.C.B. Dubeux, and J.M.B. Vendramini

Population Dynamics and within Plant Distribution of Frankliniella spp and Orius insidiosus in Cotton – E.A. Osekre*, D.L. Wright, and J. Marois

Predicting Tomato Fruit Growth Dynamics in Terms of Fresh Weight and Size: A Review and Modeling Approach – M.R. Rybak*, K.J. Boote, J.M.S. Scholberg, C.H. Porter, and J.W. Jones

Enhancing Biosafety of Transgenic Bahiagrass by Engineering Inducible Cell Death – S. Sandhu*, F. Altpeter, A.S. Blount, K.H. Quesenberry, M. Gallo, and M. Singh

Plant Regeneration of Lotononis bainesii (Leguminosae) through Cotyledon Culture – M.L. Vidoz* and K.H. Quesenberry

Preliminary Studies on the Effect of Chitosan on the Germination of Cabbage Seeds and Sweet Corn Grains – C. Webster* O. Onokpise, and M. Abazinge

Soils and Environmental Quality

Soil Physical Properties in Traffic and No Traffic Areas in Golf Courses, and Relationship with Goosegrass Growth – C. Arrieta*, P. Busey, and S. Daroub

Soil Carbon Pools in Slash Pine-based Silvopastoral Systems of North Florida – S.G. Haile*, P.K.R. Nair, and V.D. Nair

Manure Components Affecting P Stability of Dairy Manure-amended Soils – M.S. Josan*, V.D. Nair, and W.G. Harris

Evaluation of a Controlled-release Fertilizer Program on Florida Orange Production – C. Medina*, T. Obreza, J. Sartain, F.M. Roka, and R.E. Rouse

Reducing Nutrient Loss from Pastureland Through Silvopasture – G-A. Michel*, P.K.R. Nair, and V.D. Nair

Basis for Estimating P-source Coefficients for the Florida P Index – O.O. Oladeji*, G.A. O’Connor, and J.B. Sartain

Controlling Phosphorus Loss from a Manure-impacted Soil with Aluminum Water Treatment Residuals – T.J. Rew*, D.A. Graetz, V.D. Nair, and G.A. O’Connor

GENERAL PAPER SESSIONS

Session I - Soils

Spatial and Seasonal Variations of Shallow Groundwater Nutrients in the Lower St. Johns River Basin – Y. Ouyang

Soil-test Phosphorus Trends in Everglades Agricultural Area Histosol Profiles – Y. Luo*, G. Kingston, R.W. Rice, and J.M. Shine, Jr.

Application Rate of Water Treatment Residuals (WTR) Based on Agro-Environmental Thresholds – O.O. Oladeji*, G.A. O’Connor, and J.B. Sartain

Sugarcane Plant Crop Response to Phosphorus Fertilizer in Two Locations on Organic Soils in Florida – J.M. McCray*, Y. Luo, R.W. Rice, and I.V. Ezenwa


Session I -- Soils (continued)

Utility of Mehlich 1 and Mehlich 3 Soil Tests to Predict Citrus Tree Nutritional Status – T.A. Obreza*, R.E. Rouse, and K.T. Morgan

Loading of Heavy Metals in Surface Runoff Water from Citrus Groves and Vegetable Fields in the Indian River Area – Z.L. He*, P.J. Stoffella, X.E. Yang, and Y.C. Li

A New Approach for Phosphorus Risk Assessment – M. Chrysostome*, V.D. Nair, and W.G. Harris Session II – Crops

Cool-season Forage Production in Silvopastoral Systems in North Florida – S. Bambo*, J. Nowak, A. Long, A.R.S. Blount, and B. Myer

Chemical Composition of Soils Under Forages Grown Between Tree Rows of Loblolly Pine Trees – O.U. Onokpise*, L.A. Whilby, and N.G. Bradley

Effect of Topsin M and Karate on Square Abortion and the Incidence of Hardlock Disease in Cotton – E.A. Osekre*, D.L. Wright, and J. Marois

Observations of Growth and Yield of Kenaf in Florida – J. Ferguson*, J. Feaster, and J. Sifontes

Influence of Grazing Frequency on Cynodon Grasses Grown in Peninsular Florida – P. Mislevy Session III – Assorted

Soil and Subsoil K and S Fertility Effects on Bermudagrass – C.L. Mackowiak*, A.R.S. Blount, and P. Mislevy Developing a Sweet Corn Simulation Model to Predict Fresh Market Yield and Quality of Ears – J.I. Lizaso*, K.J.

Boote, J.J. Casanova, C.M. Cherr, J. Judge, J.M. Scholberg, J.W. Jones, A. Garcia, and G. Hoogenboom

Detection of Environmental Stress via Spectral Reflectance of Leaves in Crop Plants – G. Hacisalihoglu* and K. Milla

Soil Conditions Affect Sweet Corn and Sunnhemp Initial Growth and Root Proliferation – B.R. Morton*, J.C. Linares, J.M.S. Scholberg, and K.J. Boote

Energy Fluxes and Land Surface Parameters in Grassland Ecosystem: Remote Sensing Perspective – A.M. Melesse*, A. Frank, J. Hanson, M.A. Liebig, and V. Nangia

Importance of Soil Organic Matter in Florida Citrus Production – A.W. Schumann*, Q.U. Zaman, and K.H. Hostler

Fertilization of Grazed Bahigrass pastures in South Florida – M.B. Adjei* and J.E. Rechcigl


MINUTES

Soil and Crop Science Society of Florida Business Meeting Tampa Marriott Westshore, Tampa

06 Jun 2006

Kenneth Boote, President

Ken Boote called the meeting to order at 8:40 AM.

Attendees: Ken Boote, Greg Means, Paul Mislevy, Bill Thomas, Hartwell Allen, Martin Adjei, Mabry McCray, Jerry Sartain, Jerry Bennett, Bruce Mathews, Ike Ezenwa, Dave and Mrs. Calvert, Yuncong Li, Samira Daroub, and Yigang Luo.

Minutes from the last meeting on 19 May 2005. Comments were made congratulating Rob Kalmbacher for the job he did as editor before passing the job to the new editor, Mimi Williams. Necrology report recognized David Jones and Carroll Chambliss. Dedication was to Brian McNeal. Three honorary lifetime members were Fred Rhoads, Dave Calvert and Grover Smart. Bill Thomas moved to approve the minutes, seconded by Dave Calvert. The motion passed.

Treasurer’s Report. Audit committee (Rao Mylavarapu, Larry Duncan, and Ken Quesenberry) reviewed the last 2 years financial reports and said they were acceptable. Assets have been going down, approximately $3500 decrease over the last year or two. Printing charges are

higher than page charges plus sale of Proceedings. This will get worse because the IFAS Deans are no longer picking up page charges so we will have to bill individual authors. Graduate student awards and hotel rooms are also a large expense. This year the cost of student awards will be higher because of two categories of winners. Paul Mislevy stated that the amount of dues listed seems low. There has been a trend of declining payment of dues. Greg Means was requested to send reminders to members who haven’t paid their dues.

Graduate students’ attendance at the meetings has been, and should be encouraged, but is difficult to pay for. Discussion of ways to help cover the cost ensued. Jerry Sartain mentioned that there are two sources of money (IFAS and Graduate Student Council) that students can apply for up to $200 as travel grants. Raising money for student endowments was also suggested. Dave Calvert mistakenly paid a registration fee to both FSHS and to SCSSF. He moved to use the $100 from his extra registration fee to start an endowment fund to help cover the cost of student expenses to attend the meetings. The motion was seconded by Hartwell Allen. The motion passed.

Paul Mislevy mentioned the possibility of getting sponsors such as fertilizer companies to help cover the costs. Jerry Sartain moved that SCSSF encourage the students’ major professors to cover their expenses. If they can’t, then SCSSF will pay for their room for one night only. A suggested way to handle this, was to ask on the form at the time of title submission, whether the major professor can cover the student’s hotel expense. The motion was seconded by Jerry Bennett. The motion passed, with Hartwell Allen opposed.

Jerry Bennett heard from some FSHS people who felt that SCSSF wasn’t meeting its financial responsibilities for the combined meetings, and would like to know if there was any basis for their complaints. Ken Boote stated that the Soil and Water Science and Agronomy Departments each put in $400 toward the cost of the meeting receptions, but that the amount was much less than what the FSHS was routinely obtaining from various industry sponsors. He will meet with FSHS to try to resolve this issue. Dave Calvert moved to approve the treasurer’s report. The motion was seconded by Jerry Bennett. The motion passed.

Graduate student contest report. Gilbert Sigua chaired one session and Ike Ezenwa chaired the other. Crops section judges were Jerry Bennett, Hartwell Allen, Ike Ezenwa, Paul Mislevy, and Martin Adjei. Soils section judges were Cassell Gardner, Samira Daroub, Jon Lizaso,


Mabry McCray and Mark Clark. Student winners in the crops section were: 1st place – Sandhu Sukhpreet, and 2nd place tie – Sarah Cathey and Sindy Interrante. Soils and environmental quality winners were: 1st place – Olawale Oladeji, 2nd place – Manohardeep Josan, and 3rd place tie – T.J. Rew and Carolina Medina.

Necrology Report. David Wright is chair. One former member, Vincent Schroder, passed away during the past year. Vincent Schroder was a faculty member of the Agronomy Department. He was a crop physiologist /crop nutritionist who retired in 1986. There was a moment of silence to honor him.

Dedication of Proceedings Report. Hartwell Allen reported that the committee recommended nominating Carroll Gene Chambliss for the dedication of Volume 66 of the Proceedings. There are no current vacancies for honorary life members so no one was nominated.

Membership and Promotion Committee Report. Martin Adjei is chair. He sent email requests to department chairs including Ag and Bio Engineering, and Plant Medicine to encourage them to participate in the Society. He also contacted FAMU to encourage their students to participate. He noted that there is a bit of an increase in student participation including two or three who presented papers to FSHS sections. He mentioned a suggestion that we get in touch with the Caribbean (T-STAR) program to involve Caribbean scientists. There might be some interest on their part in meeting with our Society. It was pointed out that we had a Hawaiian (Bruce Mathews) in attendance. Samira Daroub asked if we knew the number of registrants for this year’s meeting. We would have to get that from FSHS since they handled registration.

Program Planning. Martin Adjei reported that there were 41 papers submitted, although one had to be withdrawn. Nineteen of them were student papers. The paper deadline was in March. Two or three email reminders were sent. It was suggested that Greg Means add the students to the membership role. Email addresses need to be kept up to date. It was suggested that email addresses should be included on the form or abstract when a paper is submitted. Next year if we join again with FSHS, we should sit in on their meeting planning sessions, to be more involved.

Decision to join with FSHS for the next two years. They will be meeting next year in West Palm Beach at the PGA Golf Resort and the following year in Ft. Lauderdale. They will always be meeting toward the south if we join with them. We need to resolve some issues FSHS has concerning financial and planning issues if we are going to continue joint meetings. Suggestion was made that we continue joint meetings for the next couple years before a long term decision is made. Chair, Sec-Treas, and Program committee chair should sit in on FSHS planning sessions. Provided we resolve perceived problems from this year, Jerry Sartain moved that SCSSF continue to

meet jointly with FSHS for 2007 and 2008. The motion was seconded by Dave Calvert. The motion passed.

Separate society identities should be maintained. The possibility to move papers back and forth between the two societies would be good. Bill Thomas stated that there is interest in bringing the Nematology Forum back to the meetings. That would have to be worked into the joint meetings. Discussions need to be held with the Nematology group to see how they would fit into the joint meeting. Bill Thomas will communicate with them to get their thoughts. We would like them to be included.

Editor’s report. Mimi Williams was absent but her statement is, for this current year there are 6 non-refereed and 2 refereed publications, plus 27 abstracts. SCSSF and FSHS will continue to have separate publications. For publications, there is a committee made up of Tom Obreza, Mimi Williams and Lena Ma that has and will be looking into alternative options for publication. EBSCO was mentioned as an option as an electronic service. We can’t continue to publish at the current rate. It’s too expensive. It was recommended that this committee get back by the next meeting with a more definite decision, possibly making this next copy (due out this fall) the last hard copy published. Some discussion of refereed vs non-refereed publications continued.

Nominating Committee report. New incoming director – Billy Crow; Secretary-Treasurer (for 2 years) – Ken Boote; President Elect – Tom Obreza; President – Martin Adjei. It was moved the nominees be elected as recommended. The motion was seconded and passed.

Other notes. By-laws are getting dated because they talk about fall meetings, but probably should hold off updating them until a more permanent decision is made concerning the joint meetings with FSHS. Page charges must be covered by the individual faculty member. Gavel was passed to Martin Adjei. Accolades were given to Ken Boote as out-going president.

Meeting adjourned.

Soil and Crop Science Society of Florida Executive Board Meeting

203 Newell Hall, University of Florida

15 March 2006

Individuals present. At Gainesville: Ken Boote, Mimi Williams, Greg McDonald, Tom Obreza, Martin Adjei, Lena Ma. At Belle Glade via Polycom: Samira Daroub.


Ken Boote called the meeting to order at 10:49 AM and handed out the agenda.

Program planning for annual meeting. Program Chair Martin Adjei has received 26 paper titles; 8 are from graduate students entering the paper contest. We need to send one more reminder to grad students to get titles in by March 17th. We need to find out how many sessions will we have and how many 15-min slots there will be in order to determine how many papers we can fit using only one meeting room. Right now we have 6.5 hours worth of papers, which does not approach the estimated limit. We need to find out the deadline date when FSHS needs information from SCSSF in order to print the program. Tom Obreza will e-mail Steve Sargent with this question. Since we have separated our dues and meeting registration this year (dues notices have already been sent out), we need to find out how and when FSHS will release their registration information. Tom will also ask Steve this question, and the answer will determine how we alert our members. Martin Adjei will send a reminder about the hotel room reservation deadline (which was later found out to be May 9th).

Meeting program structure. During the general session on first day, there is an opportunity for the Presidents of both FSHS and SCSSF to address the joint membership. Ken Boote will say a few words following FSHS president Jackie Burns. The keynote speaker will finish out the general session. We need to determine when we will have our business meeting. After some discussion, it was decided to position it as the last item on Monday, between the paper sessions and the Industry Reception. Following the business meeting, right before the reception, we can present our graduate student awards, dedicate the Proceedings, and name new life members.

Papers. Graduate student abstracts should be checked for formatting as they come in. Everyone who presents at the meeting is required to submit an abstract that will be published unless a full paper is submitted. Papers should go through departmental review before being submitted to Editor Mimi Williams.

A discussion ensued about how future issues of the Proceedings should be published, e.g. compact disc or electronic (web) vs. conventional hard copy. Tom Obreza indicated that we have lost more than $2000 per year the last 2 years due to the difference between hard copy publication cost ($6000+) and page charges received ($4000). This situation will become even more aggravated with Volume 65 since the Dean for Research office will not pay directly any more. Since authors will receive direct page charge billing for the first time this year, Mimi Williams suggested that we warn them in advance. Samira Daroub suggested that we approach the deans about how to handle this situation and possible alternatives. An ad hoc committee of Tom Obreza, Mimi Williams, and Lena Ma was appointed to investigate what it would take and how

much it would cost to convert from a hard copy Proceedings to an electronic version that would be available, indexable, and searchable on the web. A report on the findings will be presented to the membership at the upcoming business meeting. Lena Ma asked if there was a way to determine how much the Proceedings has been cited in the past, but nobody had a sufficient answer.

Committees. Ken Boote sent mission statements and charges to our various committees. The Necrology, Nominating, and Dedication committee duties are routine. Regarding future meetings with FSHS, we were offered the opportunity to visit potential hotel sites, but nobody from the Site Selection committee was able to go. We will talk about continuing our meetings with FSHS at the business meeting. Hopefully we will know the location of the 2007 FSHS meeting at that time so we can tell the membership.

The audit committee needs to get their job done before we meet in Tampa. Tom Obreza will contact them with the financial reports.

The role and duties of the Membership committee were discussed. It was suggested that DPM students should be prime candidates to become members. The membership committee (Martin Adjei) will ask Bob McGovern if he can help recruit graduated DPM students to become members. Mimi Williams asked if a statement of the benefits of belonging to SCSSF exists. Nobody present knew of such a statement. Mimi suggested that the Membership committee derive such a statement, and Ken Boote indicated that it should be keyed to the state of Florida.

We need to send a reminder to Soil/Water, Agronomy, and Ag Engineering grad students about the paper competition. Tom Obreza will send the score sheet that has been used in the past to Mimi Williams.

Other items. We need to scan the bylaws of SCSSF and put them on the web site.

It was suggested that Audit committee may be the appropriate group to suggest higher dues, since we have been losing money of late.

The next board meeting was tentatively scheduled for 3:00 PM on Sunday, June 4th at the Tampa Marriott hotel.

The meeting was adjourned at 12:20 PM.


SOIL AND CROP SCIENCE SOCIETY OF FLORIDA FINANCIAL REPORT July 1, 2005 through June 30, 2006

ASSETS IN BANK (July 01, 2005) Checking Account - Bank of America ........................................................................................................................................................ 6515.25 Certificate of Deposit - Bank of America (XXX XXX XXXX 2783) ....................................................................................................... 12364.99 Total in Bank ......................................................................................................................................................................... 18880.24 RECEIPTS Dues ............................................................................................................................................................................................................ 2340.00 Sale of Proceedings ..................................................................................................................................................................................... 1495.00 Page Charges, Volume 64 ........................................................................................................................................................................... 3993.75 Gifts Received .............................................................................................................................................................................................. 100.00 Annual Meetings ........................................................................................................................................................................................... 790.00 Registration ……………………………………..……….790.00 Interest .......................................................................................................................................................................................................... 245.49 Certificate of Deposit (300 000 7062 2783)………....... 239.31 Checking Account Interest.…………………..…………...6.18 Total Receipts ............................................................................................................................................................................................. 8964.24 DISBURSEMENTS Printing SCSSF Proceedings Vol 64 ........................................................................................................................................................... 5990.84 Postage.......................................................................................................................................................................................................... 429.84 Checking account service charge .................................................................................................................................................................... 66.00 Annual Meeting Expenses Grad student awards ................................................................................................................................................................... 950.00 Grad student hotel rooms ......................................................................................................................................................... 1489.54 Student Registration ................................................................................................................................................................... 160.00 Office Supplies ............................................................................................................................................................................ 55.53 Annual license fee to Florida Dept of State ..................................................................................................................................................... 61.25 Total disbursements .................................................................................................................................................................................... 9203.00 UNCLEARED DISBURSEMENTS (as of June 30, 2006) Grad student awards...................................................................................................................................................................................... 250.00 Student Registration ........................................................................................................................................................................................ 10.00 Total uncleared disbursements ...................................................................................................................................................................... 260.00 ASSETS IN BANK (June 30, 2006) Checking Account - Bank of America ........................................................................................................................................................ 6037.18 Certificate of Deposit - Bank of America (XXX XXX XXXX 2783) ....................................................................................................... 12604.30 Total in Bank ............................................................................................................................................................................................ 18641.48

2006-2007 COMMITTEES

(Date in parenthesis indicates year each member rotates-off after the annual meeting.)

Audit Rao Mylavarapu (2006) Ken Quesenberry (2007) Larry Duncan (2008)

Nominating

Craig Stanley (2006) Ken Quesenberry (2007) Bill Thomas (2008)

Necrology

David Wright (2006) Jerry Bennett (2007) Ed Hanlon (2008)

Dedication of Proceedings and Honorary Lifetime Member Selection

Hartwell Allen (2006) George O'Connor (2007) Lynn Sollenberger (2008)

Membership Martin Adjei (2006)

William Crow (2006) Robert McGovern (2007) Oghenekome Onokpise (2007) Ken Quesenberry (2008) Peter Nkedi-Kizza (2008)

Graduate Student Presentation Contest

Gilbert Siqua (2006) Mimi Williams (2006) Anne Blount (2007) Craig Stanley (2007) Mark Clark (2008) Vimala Nair (2008)

Site Selection- Local Arrangements

Jerry Sartain (2006) Paul Mislevy (2007) Jack Rechcigl (2008)


MEMBERSHIP LISTS

Regular Members 2006

MARTIN B. ADJEI RANGE CATTLE REC-ONA 3401 EXPERIMENT STATION ONA, FL 33865-9706

KENNETH L. CAMPBELL UNIVERSITY OF FLORIDA P.O. BOX 110570 GAINESVILLE, FL 32611-0570

MARIA GALLO-MEAGHER UNIVERSITY OF FLORIDA P.O. BOX 110300 GAINESVILLE, FL 32611-0300

L. H. ALLEN UNIVERSITY OF FLORIDA P.O. BOX 110965 GAINESVILLE, FL 32611-0965

MING CHEN EVERGLADES REC P.O. BOX 8003 BELLE GLADE, FL 33430

CASSEL S. GARDNER FLORIDA A&M UNIVERSITY AGRON PROG & CEN FOR WATER QUAL PERRY-PAIGE BLDG SOUTH, RM 202J TALLAHASSEE, FL 32307

D. D. BALTENSPERGER UNIVERSITY OF NEBRASKA 4502 AVE. I SCOTTSBLUFF, NE 69361-4939

WILLIAM CROW UNIVERSITY OF FLORIDA P.O. BOX 110620 GAINESVILLE, FL 32611-0620

ROBERT GILBERT EVERGLADES REC P.O. BOX 8003 BELLE GLADE, FL 33430

IIAN BAR NETAFIM USA 116 BEUFORT DR. LONGWOOD, FL 32779

A. A. CSIZINSKY GULF COAST REC 5007 60 STREET EAST BRADENTON, FL 34203-9324

BARRY GLAZ USDA-ARS 12990 US HIGHWAY 441 CANAL POINT, FL 33438

RAY BASSETT AGLIME SALES, INC. 1375 THORNBURG ROAD BABSON PARK, FL 33827

SAMIRA DAROUB EVERGLADES REC 3200 E. PALM BEACH RD BELLE GLADE, FL 33430

D. W. GORBET NORTH FLORIDA REC 3925 HIGHWAY 71 MARIANNA, FL 32446

JERRY M. BENNETT UNIVERSITY OF FLORIDA P.O. BOX 110500 GAINESVILLE, FL 32611-0500

DONALD W. DICKSON UNIVERSITY OF FLORIDA P.O. BOX 110630 GAINESVILLE, FL 32611-0630

EDWARD A. HANLON SOUTHWEST FLORIDA REC 2686 SR 29 NORTH IMMOKALEE, FL 33438

D. A. BERGER NORTH FLORIDA REC 55 RESEARCH RD. QUINCY, FL 32351-5677

SPENCER G. DOUGLASS DOUGLASS FERTILIZER 1180 SPRING CENTER BLVD. ALTAMONTE SPRINGS, FL 32714

ZHENLI HE INDIAN RIVER REC 2199 SOUTH ROCK ROAD FT. PIERCE, FL 34945

KENNETH J. BOOTE UNIVERSITY OF FLORIDA P.O. BOX 110500 GAINESVILLE, FL 32611-0500

MICHAEL DUKES UNIVERSITY OF FLORIDA P.O. BOX 110570 GAINESVILLE, FL 32611-070

GEORGE J. HOCHMUTH NORTH FLORIDA REC 155 RESEARCH ROAD QUINCY, FL 32351-5677

BARRYJ. BRECKE WEST FLORIDA REC 5988 HWY 90, BLDG 4900 MILTON, FL 32583

LARRY DUNCAN CITRUS REC 700 EXPERIMENT STATION ROAD LAKE ALFRED, FL 33850-2299

EDWARD W. HOPWOOD, JR. 5200 NW 62ND COURT GAINESVILLE, FL 32653

JACQUE W. BREMAN ROUTE 3, BOX 299 LAKE BUTLER, FL 32054

JOE EGER DOW AGRO SCIENCES 2606 S. DUNDEE BLVD. TAMPA, FL 33629

R. N. INSERRA UNIVERSITY OF FLORIDA P.O. BOX 147100 GAINESVILLE, FL 32614-7100

ERIC C. BREVIK VALDOSTA STATE UNIVERSITY DEPT OF PHYSICS, ASTRON & GEOSCIENCE VALDOSTA, GA 31698-0055

IKE EZENWA RANGE CATTLE REC 3401 EXPERIMENT STATION ONA, FL 33865-9706

JENNIFER M. JACOBS UNIVERSITY OF FLORIDA P.O. BOX 116580 GAINESVILLE, FL 32611-6580

J. B. BROLMANN 2914 FOREST TERRACE FT. PIERCE, FL 34982

JAMES FERGUSON UNIVERSITY OF FLORIDA P.O. BOX 110690 GAINESVILLE, FL 32611-0690

JAY JAYACHANDRAN FLORIDA INTERNATIONAL UNIV. ENVIRONMENTAL STUDIES DEPT. MIAMI, FL 33199

ROBIN BRYANT TROPICANA INC. 1001 13TH AVE. EAST BRADENTON, FL 34208

CLYDE W. FRAISSE UNIVERSITY OF FLORIDA PO BOX 110570 GAINESVILLE, FL 32611-0570

JONATHAN D. JORDAN UNIVERSITY OF FLORIDA P.O. BOX 110570 GAINESVILLE, FL 32611-0570

DAVID V. CALVERT INDIAN RIVER REC 2199 S. ROCK ROAD FT. PIERCE, FL 34945-3138

RAYMOND GALLAHER UNIVERSITY OF FLORIDA P.O. BOX 110730 GAINESVILLE, FL 32611-0730

ROBERT S. KALMBACHER RANGE CATTLE REC – ONA 3401 EXPERIMENT STATION ONA, FL 33865-9706


TAWAINGA KATSVAIRO NORTH FLORIDA REC-QUINCY 155 RESEARCH ROAD QUINCY, FL 32351

ROBERT MCSORLEY UNIVERSITY OF FLORIDA P.O. BOX 110620 GAINESVILLE, FL 32611-0620

OGHENEKOME U. ONOKPISE FLORIDA A & M UNIVERSITY RM 203, SOUTH PERRY-PAIGE BLDG TALLAHASSEE, FL 32307

NANCY KOKALIS-BURELLE USDA-HORT. RES. LAB 2001 S ROCK RD. FT. PIERCE, FL 34945

MARIA DE LOURDES MENDES UNIVERSITY OF FLORIDA PO BOX 110620 GAINESVILLE, FL 32611-0620

YING OUYANG ST. JOHNS RIVER WMD P.O. BOX 1429 PALATKA, FL 32178-1429

THOMAS A. KUCHAREK UNIVERSITY OF FLORIDA P.O. BOX 110680 GAINESVILLE, FL 32611-0680

JOHN MENHENNETT OKEELANTA CORPORATION PO BOX 86 SOUTH BAY, FL 33493

HUGH L. POPENOE UNIVERSITY OF FLORIDA P.O. BOX 110286 GAINESVILLE, FL 32611-0286

ORIE N. LEE 5005 LILLIAN LEE ROAD ST. CLOUD, FL 34771

J. D. MILLER SUGARCANE FIELD STATION STAR ROUTE BOX 8 CANAL POINT, FL 33438

DAVID POWELSON 616 LOTHIAN DR. TALLAHASSEE, FL 32312-2832

PAUL S. LEHMAN DPI/FDACS P.O. BOX 147100 GAINEVILLE, FL 32614-7100

PAUL MISLEVY RANGE CATTLE REC-ONA 3401 EXPERIMENT STATION ONA, FL 33865-9706

KENNETH H. QUESENBERRY UNIVERSITY OF FLORIDA P.O. BOX 110500 GAINESVILLE, FL 32611-0500

YUNCONG LI TROPICAL REC 18905 SW 280 STREET HOMESTEAD, FL 33031

OSCAR MONJE DYNAMAC CORPORATION MAIL CODE DYN-3 KENNEDY SPACE CENTER, FL 32980

JACK RECHCIGL GULF COAST REC 5007 60 STREET E BRADENTON, FL 34203-9324

SALVADORE J. LOCASCIO UNIVERSITY OF FLORIDA P.O. BOX 110690 GAINESVILLE, FL 32611-0690

KELLY MORGAN SOUTHWEST FLORIDA REC 2686 SR 29 N IMMOKALEE, FL 34142-9515

PAUL REITH UNIVERSITY OF FLORIDA P.O. BOX 110500 GAINESVILLE, FL 32611-0500

YIGANG LUO EVERGLADES REC 3200 E PALM ROAD BELLE GLADE, FL 33430

DOLEN MORRIS USDA, SUGARCANE FIELD STATION 12990 HWY 441 CANAL POINT, FL 33438

JERRY B. SARTAIN UNIVERSITY OF FLORIDA P.O. BOX 110510 GAINESVILLE, FL 32611-0510

LENA Q. MA UNIVERSITY OF FLORIDA P.O. BOX 110290 GAINESVILLE, FL 32611-0290

ROSA M. MUCHOVEJ SOUTHWEST FLORIDA REC 2686 SR 29 NORTH IMMOKALEE, FL 34142-9515

LIESBETH M. SCHMIDT ROUTE 3, BOX 224-10 LAKE CITY, FL 32025

GREG MACDONALD UNIVERSITY OF FLORIDA PO BOX 110500 GAINESVILLE, FL 32611-0500

KENNETH R. MUZYK GOWAN CO 408 LARRIE ELLEN WAY BRANDON, FL 33511

ARNOLD SCHUMANN CITRUS REC 700 EXPERIMENT STATION ROAD LAKE ALFRED, FL 33850-2299

ROBERT MANSELL UNIVERSITY OF FLORIDA P.O. BOX 110290 GAINESVILLE, FL 32611-0290

RAO MYLAVARAPU UNIVERSITY OF FLORIDA P.O. BOX 110290 GAINESVILLE, FL 32611

LARRY SCHWANDES 1805 NW 38 TERRACE GAINESVILLE, FL 32605

BRUCE MATHEWS UNIVERSITY OF HAWAII-HILO COLLEGE OF AGRICULTURE 200 W. KAWILI ST HILO, HI 96720-4091

SHAD D. NELSON TEXAS A&M UNIV. – KINGSVILLE MSC 228 KINGSVILLE, TX 78363

CHARLES SEMER UNIVERSITY OF FLORIDA P.O. BOX 110680 GAINESVILLE, FL 32611-0680

V. V. MATICHENKOV INDIAN RIVER REC 2199 SOUTH ROCK ROAD FT. PIERCE, FL 34945

PETER NKEDI-KIZZA UNIVERSITY OF FLORIDA P.O. BOX 110290 GAINESVILLE, FL 32611-0290

JAMES M. SHINE, JR. SUGAR CANE GROWERS COOP P.O. BOX 666 BELLE GLADE, FL 33430

MABRY MCCRAY EVERGLADES REC 3200 E PALM BEACH ROAD BELLE GLADE, FL 33430

THOMAS A. OBREZA UNIVERSITY OF FLORIDA P.O. BOX 110290 GAINESVILLE, FL 32611-0290

AZIZ SHIRALIPOUR UNIVERSITY OF FLORIDA P.O. BOX 110500 GAINESVILLE, FL 32611-0500

ROBERT MCGOVERN UNIVERSITY OF FLORIDA PLANT MEDICINE PROGRAM P.O. BOX 110680 GAINESVILLE, FL 32611-0680

GEORGE O'CONNOR UNIVERSITY OF FLORIDA P.O. BOX 110510 GAINESVILLE, FL 32611-0510

KENNETH SHULER 12657 158 STREET NORTH JUPITER, FL 33478


GILBERT SIGUA USDA-ARS 22271 CHINSEGUT HILL ROAD BROOKSVILLE, FL 34601

JEAN M.G. THOMAS UNIVERSITY OF FLORIDA P.O. BOX 110300 GAINESVILLE, FL 32611-0300

E. B. WHITTY UNIVERSITY OF FLORIDA P.O. BOX 110500 GAINESVILLE, FL 32611-0500

GROVER C. SMART, JR. UNIVERSITY OF FLORIDA P.O. BOX 110620 GAINESVILLE, FL 32611-0620

WILLIAM THOMAS COLUMBIA COUNTY EXTENSION RT 18, BOX 720 LAKE CITY, FL 32025

M. J. WILLIAMS USDA-NRCS 2614 NW 43RD STREET GAINESVILLE, FL 34606-6611

GEORGE H. SNYDER EVERGLADES REC P.O. BOX 8003 BELLE GLADE, FL 33430

PAULETTE TOMLINSON BRADFORD COUNTY EXTENSION 2266 NORTH TEMPLE AVE. STARKE, FL 32091-1028

P. J. WIATRAK NORTH FLORIDA REC 155 RESEARCH RD. QUINCY, FL 32351

RAYMOND SNYDER 3101 GULFSTREAM ROAD LAKE WORTH, FL 33461

NOBLE USHERWOOD 1661 APALACHEE RIVER RD. MADISON, GA 30650

ANN C. WILKIE UNIVERSITY OF FLORIDA P.O. BOX 110960 GAINESVILLE, FL 32611-0960

A. R. SOFFES-BLOUNT NORTH FLORIDA REC 3925 HWY 71 MARIANNA, FL 32446-7906

MARK WADE INDIAN RIVER REC 2199 S. ROCK ROAD FT. PIERCE, FL 34945

BOB WILLIAMS DUPONT 10918 BULLRUSH TERR BRADENTON, FL 34202

LYNN E. SOLLENBERGER UNIVERSITY OF FLORIDA P.O. BOX 110300 GAINESVILLE, FL 32611-0300

KOON-HUI WANG UNIVERSITY OF FLORIDA P.O. BOX 110620 GAINESVILLE, FL 32611-0620

T. W. WINSBERG GREEN CAY FARM 12750 HAGEN RANCH RD BOYNTON BEACH, FL 33437

GERADO SOTO 4801 HAMPDEN LANE #704 BETHESDA, MD 208142949

DAVID P. WEINGARTNER HASTINGS REC P.O. BOX 728 HASTINGS, FL 32145-0728

GEORGE WINSLOW GULF CITRUS MANAGEMENT, INC P.O. BOX 512116 PUNTA GORDA, FL 33951-2116

CRAIG D. STANLEY GULF COAST REC 5007 60 STREET EAST BRADENTON, FL 34203-9324

RALPH W. WHITE 11227 DEAD RIVER ROAD TAVARES, FL 32778

D. L. WRIGHT NORTH FLORIDA REC 30 RESEARCH ROAD QUINCY, FL 32351

JAMES A. STRICKER P.O. BOX 9005 DRAWER HS03 BARTOW, FL 33831-9005

Honorary Life Members

WILLIAM G. BLUE 1501 NW 31 ST. GAINESVILLE, FL 32605

CARROLL M. GERALDSON GULF COAST REC 5007 60 ST. EAST BRADENTON, FL 34203-9324

AMEGDA OVERMAN GULF COAST REC 5007 60 STREET E BRADENTON, FL 34203-9324

DAVID V. CALVERT INDIAN RIVER REC 1007 GRANDVIEW BLVD FT. PIERCE, FL 34982

LUTHER HAMMOND 1018 SW 25th PLACE GAINESVILLE, FL 32601

PAUL L. PFAHLER UNIVERSITY OF FLORIDA P.O. BOX 110500 GAINESVILLE, FL 32611-0500

VICTOR W. CARLISLE UNIVERSITY OF FLORIDA P.O. BOX 110290 GAINESVILLE, FL 32611-0290

ELVER M. HODGES 1510 HIGHWAY 64 WEST WAUCHULA, FL 33873

GORDON M. PRINE UNIVERSITY OF FLORIDA P.O. BOX 110500 GAINESVILLE, FL 32611-0500

R. P. ESSER P.O. BOX 147100 GAINESVILLE, FL 32614-7100

EARL S. HORNER UNIVERSITY OF FLORIDA P.O. BOX 110500 GAINESVILLE, FL 32611-0500

FRED M. RHOADS NORTH FLORIDA REC 30 RESEARCH ROAD QUINCY, FL 32351

PAUL H. EVERETT 3731 NW 104 DR. GAINESVILLE, FL 32606

ALBERT E. KRETSCHMER 1028 ANTILLES AVE. FT. PIERCE, FL 34982-3325

DONALD ROTHWELL 4041 NW 33RD PLACE GAINESVILLE, FL 32606

NATHAN GAMMON, JR. 1403 NW 11TH ROAD GAINESVILLE, FL 32605

DARREL E. MCCLOUD UNIVERSITY OF FLORIDA P.O. BOX 110500 GAINESVILLE, FL 32611-0500

GROVER C. SMART JR. UNIVERSITY OF FLORIDA PO BOX 110620 GAINESVILLE, FL 32611-0620

DONALD L. MYHRE 2280 NW 21st PLACE GAINESVILLE, FL 32605


Emeritus Member

WALTER T. SCUDDER 4001 SOUTH SANFORD AVE. SANFORD, FL 32773-6007

Subscribing Members 2005

ALBERT R MANN LIBRARY CORNELL UNIVERSITY SERIALS UNIT / ACQ DIVISION ITHACA, NY 14853

INSTITUTE FOR SCIENTIFIC INFO 3501 MARKET STREET PHILADELPHIA, PA 19104

SMI SCHWEITZER MEDIA INTL 35-23 UTOPIA PARKWAY FLUSHING, NY 11358

ACQUISITIONS/SERIALS S*01****101PSS MISSISSIPPI STATE UNIVERSITY LIBRARY P.O. BOX 5408 MISSISSIPPI STATE, MS 39762

JEFFERSON COUNTY LIBRARY 1315 SOUTH JEFFERSON STREET MONTICELLO, FL 32344

SUNCOAST HIGH SCHOOL CHARGER BOULEVARD RIVIERA BEACH, FL 33404

BIBLIOGRAPHIC DATABASES P.O. BOX 830470 BIRMINGHAM, AL 35283

KIT INFORMATION SERVICES 2783 POSTBUS 95001 1090 HA AMSTERDAM, NETHERLANDS

SUWANNEE RIVER REGIONAL LIBRARY 207 PINE AVE. LIVE OAK, FL 32060

BIBLIOTECA WILSON POPENOE ESCUELA AGRICOLA PANAMERICANA ZAMORANO P.O. BOX 93 TEGUCIGALPA, HONDURAS

LIBRARY OF CONGRESS EXCHANGE AND GIFT DIVISION WASHINGTON, DC 20540

SWETS BLACKWELL, INC. 440 CREAMERY WAY, SUITE A EXTON, PA 19341

BIOSIS SOURCE LOG-IN TWO COMMERCE SQUARE 2001 MARKET STREET, SUITE 700 PHILADELPHIA, PA 19103-7095

MAGRATH LIBRARY SERIALS DEPT. UNIVERSITY OF MINNESOTA 1984 BUFORD AVE. SAINT PAUL, MN 55108-1012

THE BOOK HOUSE, INC. 216 W. CHICAGO STREET JONESVILLE, MI 49250-0125

BLACKWELL'S BOOK SERVICES NEW TITLE DEPARTMENT 100 UNIVERSITY COURT BLACKWOOD, NJ 08012

MARSTON SCIENCE LIBRARY SERIALS DEPARTMENT, L306 MSL P.O. BOX 117011 GAINESVILLE, FL 32611-7011

THE LIBRARIAN CSIRO 8800005615 LAND AND WATER PRIVATE BAG 2 GLEN OSMOND SA 5064, AUSTRALIA

CHEMICAL ABSTRACTS SERV. LIBRARY P.O. BOX 3012 COLUMBUS, OH 43210

NORTH BREVARD PUBLIC LIBRARY 2121 SOUTH HOPKINS AVE. TITUSVILLE, FL 32780

THE LIBRARIAN CSIRO 8800005615 LIVESTOCK INDUSTRIES OLD BIOSCIENCE PRECINCT 306 CARMODY ROAD ST. LUCIA QLD 4067

DEWITT TAYLORJR-SR HIGH SCHOOL EAST WASHINGTON AVE. PIERSON, FL 32080

PKYONGE LIBRARY OF FLORIDA P.O. BOX 117001 GAINESVILLE, FL 32611-7001

TITUSVILLE HIGH SCHOOL LIBRARY TITUSVILLE, FL 32780

DIVISION OF PLANT INDUSTRY/LIBRARY ATTENTION: ALICE SANDERS P.O. BOX 147100 GAINESVILLE, FL 32614-7100

POLYSPRINGS ENTERPRISES CO., LTD PERIODICALS DEPARTMENT P.O. BOX 33905 SHEUNG WAN POST OFFICE HONG KONG

TOKYO DAIGAKU NOGAKU-BU LIBRARY 1-1-1 YAYOI BUNKO-KU TOKYO 113-0032, JAPAN

EVERGLADES REC LIBRARY 3200 EAST PALM BEACH ROAD BELLE GLADE, FL 33430-4702

POMPANO BEACH CITY LIBRARY 1213 EAST ATLANTIC BOULEVARD POMPANO BEACH, FL 33060

TROPICAL RES & EDUC CENTER 18905 SW 280 STREET HOMESTEAD, FL 33030

FLORIDA A&M UNIVERSITY LIBRARY ACQ DEPT-SERIALS UNIT 1500 S MARTIN LUTHER KING BLVD. TALLAHASSEE, FL 32307

SERIALS DEPT DUPRE LIBRARY UNIV OF LOUISIANA AT LAFAYETTE 302 E SAINT MARY BLVD. LAFAYETTE, LA 70503-2038

UNIV DEL ZULIA-SERBILUZ BIBL CENTRAL NUCLEO HUMANISTICO AV 16 GOAJIRA-CIUDAD UNIV. MARACAIBO EDO ZULIA VENEZUELA

FL DEPT OF AG & CONSUMER SERV. DIVISION OF PLANT INDUSTRY P.O. BOX 147100 GAINESVILLE, FL 32614-7100

SERIALS SECTION CENTRAL LIBRARY ST. LUCIA CAMPUS THE UNIVERSITY OF QUEENSLAND QUEENSLAND 4072 AUSTRALIA

UPR MAYAGUEZ GENERAL LIBRARY P.O. BOX 9022/ADQUISITIONS MAYAGUEZ, PR 00681-9022 USA

FRANCES LEWIS CONTINUATIONS BIBLIOGRAPHER YANKEE BOOK PEDDLER 999 MAPLE STREET CONTOOCOOK, NH 03229-3374

SERIALS UNIT PURDUE UNIVERSITY LIBRARY TSS 504 W STATE STREET WEST LAFAYETTE, IN 47907-2058

USDA NATIONAL AGRIC LIBRARY CURRENT SERIAL RECORDS, RM 202 10301 BALTIMORE AVE. BELTSVILLE, MD 20705


WAGENINGEN UR BIBLIOTHEEK 60020 POSTBUS 9100 6700 HA WAGENINGEN, NETHERLANDS

WEST PALM BEACH PUBLIC LIBRARY 100 CLEMATIC STREET WEST PALM BEACH, FL 33401

YOUNG LIBRARY SERIALS-AG IABZ1263 UNIVERSITY OF KENTUCKY 500 S LIMESTONE LEXINGTON, KY 40506-0001

WINTER HAVEN SR. HIGH SCHOOL MEDIA CENTER 600 SIXTH STREET SE WINTER HAVEN, FL 33880


Historical Record of Society Officers

Year

President

President Elect

Secretary-Treasurer

Board Directors†

2007 2006 2005 2004 2003 2002 2001 2000 1999 1998 1997 1996 1995 1994 1993 1992 1991 1990 1989 1988 1987 1986 1985 1984 1983 1982 1981 1980 1979 1978 1977 1976 1975 1974 1973 1972 1971 1970 1969 1968 1967 1966 1965 1964 1963 1962 1961 1960 1959 1958 1957 1956 1955 1954 1953 1952 1951 1950 1949 1948 1947 1946 1945 1944 1943 1942 1941 1940

M. B. Adjei K. J. Boote W. D. Thomas C. G. Chambliss C. D. Stanley D. W. Dickson R. N. Gallaher D. V. Calvert T. A. Kucharek K. H. Quesenberry R. S. Mansell J. W. Noling D. L. Wright E. E. Albregts G. H. Snyder G. C. Smart, Jr. R. S. Kalmbacher R. D. Barnett J. B. Sartain P. Mislevy D. F. Rothwell E. B. Whitty J. G. A. Fiskell G. M. Prine F. M. Rhoads O. C. Ruelke A. J. Overman V. W. Carlisle D. W. Jones W. L. Pritchett K Hinson H. L. Breland A. E. Kretschmer, Jr. L. C. Hammond F. T. Boyd C. E. Hutton E. M. Hodges W. K Robertson E. S. Horner C. M. Geraldson G. B. Killinger C. F. Eno V. E. Green, Jr. D. O. Spinks H. C. Harris W. G. Blue W. H. Chapman J. R. Henderson P. H. Senn G. D. Thornton D. E. McCloud R. W. Ruprecht F. H. Hull E. L. Spencer N. Gammon, Jr. I. W. Wander R. A. Carrigan W. T. Forsee, Jr. W. T. Forsee, Jr. H. A. Bestor H. A. Bestor H. Gunter W. E. Stokes G. M. Volk H. I. Mossbarger J. R. Neller F. B. Smith M. Peech

T. A. Obreza M. B. Adjei K. J. Boote W. D. Thomas C. G. Chambliss C. D. Stanley D. W. Dickson R. N. Gallaher D. V. Calvert T. A. Kucharek K. H. Quesenberry R. S. Mansell J. W. Noling D. L. Wright E. E. Albregts G. H. Snyder G. C. Smart, Jr. R. S. Kalmbacher R. D. Barnett J. B. Sartain P. Mislevy D. F. Rothwell E. B. Whiny J. G. A. Fiskell G. M. Prine F. M. Rhoads O. C. Ruelke A. J. Overman V. W. Carlisle D. W. Jones W. L. Pritchett K. Hinson H. L. Breland A. E. Kretschmer, Jr. L. C. Hammond F. T. Boyd C. E. Hutton E. M. Hodges W. K Robertson E. S. Horner C. M. Geraldson G. B. Killinger C. F. Eno V. E. Green, Jr. D. O. Spinks H. C. Harris W. G. Blue W. H. Chapman J. R. Henderson P. H. Senn G. D. Thornton D. E. McCloud W. Reuther F. H. Hull E. L. Spencer N. Gammon, Jr. I. W. Wander R. A. Carrigan R. A. Carrigan L. H. Rogers L. H. Rogers H. A. Bestor H. Gunter W. E. Stokes G. M. Volk H. I. Mossbarger J. R. Neller F. B. Smith

K. J. Boote T. A. Obreza T. A. Obreza T. A. Obreza T. A. Obreza T. A. Obreza T. A. Obreza T. A. Obreza T. A. Obreza T. A. Obreza C. D. Stanley C. D. Stanley C. D. Stanley C. G. Chambliss C. G. Chambliss C. G. Chambliss C. G. Chambliss C. G. Chambliss D. D. Baltensperger/C. G. Chambliss G. Kidder G. Kidder G. Kidder G. Kidder G. Kidder G. Kidder J. B. Sartain J. B. Sartain J. B. Sartain J. B. Sartain D. W. Jones D. W. Jones D. W. Jones D. W. Jones D. W. Jones D. F. Rothwell D. F. Rothwell J. NeSmith J. NeSmith J. NeSmith J. NeSmith J. NeSmith R. V. Allison R. V. Allison R. V. Allison R. V. Allison R. V. Allison R. V. Allison R. V. Allison R. V. Allison R. V. Allison R. V. Allison R. V. Allison R. V. Allison R. V. Allison R. V. Allison R. V. Allison R. V. Allison R. V. Allison R. V. Allison R. V. Allison R. V. Allison R. V. Allison R. V. Allison R. V. Allison R. V. Allison R. V Allison R. A. Carrigan R. A. Carrigan

G. E. MacDonald L. Ma M. B. Adjei W. D. Thomas (R. McSorley) P. Nkedi-Kizza R. M. Muchovej Robert Kinloch J. E. Rechcigl E. C. French III S. C. Schank/J. R. Rich E. A. Hanlon M. J. Williams L. E. Sollenberger D. A. Graetz J. M. Bennett F. M. Rhoads N. R. Usherwood G. C. Smart, Jr. R. W. Johnson J. W. Prevatt/J. B. Sartain/B. L. McNeal E. E. Albregts D. R. Hensel P. Mislevy D. V. Calvert G. M. Prine T. W. Winsberg F. M. Rhoads P. H. Everett O. C. Ruelke A. J. Overman R. L. Smith A. L. Taylor A. E. Kretschmer, Jr./G. L. Gascho H. L. Breland J. T. Russell †Board of Directors established in 1972 with 1, 2, and 3 year terms for the first three members. The year for each Director is when they rotate-off.


Honorary Lifetime Members Editors*

1950 1954 1956 1959 1960 1961 1962 1963 1964 1965 1966 1970 1971 1973 1974

Selman A. Waksman Charles Franklin Kettering Sir Edward John Russell Merritt Finley Miller Frederick James Alway Sergei Nikolaevitch Winogradsky Walter Pearson Kelley Oswald Schreiner David Jacobus Hissink Charles Ernest Millar John Gordon DuPuis, M.D. Lyman James Briggs Hardrada Harold Hume Firmin Edward Bear Wilson Popenoe Pettis Holmes Senn Knowles A. Ryerson James A. McMurtrey, Jr. Herbert Kendall Hayes Harold Gray Clayton Thomas Ray Stanton Gotthold Steiner Emil Truog John William Turrentine George Dewey Scarseth Joseph R. Neller Howard E. Middleton Frank L. Holland Herman Gunter Frank E. Boyd Henry Agard Wallace Robert Verrill Allison Richard Bradfield William A. Carver William Gordon Kirk Frederick Buren Smith Marvin U. Mounts William Thomas Forsee, Jr. R. A. Carrigan Henry Clayton Harris Michael Peech Joseph Russell Henderson Ernest Leavitt Spencer Jesse Roy Christie Willard M. Fifield Joseph Riley Beckenbach

1975 1978 1979 1980 1981 1982 1984 1986 1988 1989 1990 1991 1992 1993 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006

J. Cooper Morecock, Jr. George Daniel Thornton Gaylord M. Volk Gordon Beverly Killinger Roy Albert Bair Frederick Tilghman Boyd Darell Edison McCloud Nathan Gammon, Jr. Ralph Wyman Kidder Lester T. Kurtz David Wilson Jones Paul Harrison Everett Elver Myron Hodges John G. A. Fiskell Otto Charles Ruelke Victor E. Green, Jr. William Guard Blue Earl Stewart Horner Victor Walter Carlisle Donald-L. Myhre Carroll M. Geraldson Donald F. Rothwell Luther C. Hammond Amegda J. Overman Charles F. Eno Albert E. Kretschmer. Jr. Robert P. Esser Gordon M. Prine None elected None elected Paul Pfahler None elected Fred Rhoads David Calvert Grover Smart, Jr. None elected

1953 1954 1955 1956 1957-1973 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006

C. F. Eno C. F. Eno I. W. Wander Walter Reuther G. D. Thornton E. S. Horner E. S. Horner E. S. Horner E. S. Horner E. S. Horner E. S. Horner E. S. Horner E. S. Horner E. S. Horner E. S. Horner W. G. Blue V. E. Green, Jr. V. E. Green, Jr. V. E. Green/E. S. Horner W. G. Blue W. G. Blue W. G. Blue W. G. Blue P. L. Pfahler P. L. Pfahler P. L. Pfahler B. L. McNeal B. L. McNeal B. L. McNeal B. L. McNeal B. L. McNeal/ R. S. Kalmbacher R. S. Kalmbacher R. S. Kalmbacher R. S. Kalmbacher R. S. Kalmbacher R. S. Kalmbacher R. S. Kalmbacher R. S. Kalmbacher M. J. Williams

*Prior to 1953, the minutes printed in the Proceedings do not name the Editor, although a publication report is printed and an Editor is mentioned. The minutes imply, but do not explicitly state, that for the first several years there was an Editorial Committee with the Chairman of the Committee serving as Editor.

The Soil Science Society of Florida was formed on 18 April 1939 under the leadership of Drs. R. V. Allison, R. A. Carrigan, F. B. Smith, Michael Peech, and Mr. W. L. Tait. In 1955 the name was changed to the Soil and Crop Science Society of Florida. The Society was incorporated as a non profit organization of 6 June 1975. The articles of incorporation were published in Volume 35 of the Proceedings, and the By-Laws in Volume 41.

Volumes 31 and 44 of the Proceedings listed the previous officers of the Society. The information listed above draws heavily upon those two volumes and the minutes of the Society published in each volume. I discovered a few errors, especially in the Board of Directors, and all have beencorrected to the best of my knowledge.

Grover C. Smart, Jr., President, SCSSF, 1991-92.


Dedication of Proceedings

Year Volume Person Year Volume Person

1939 1940 1941 1942 1942 1943 1943 1944 1945 1946-47 1948-49 1950 1951 1952 1953 1954 1955 1956 1957 1958 1959 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 1970 1971-72 1973

1 2 3 4-A 4-B 5-A 5-B 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32

Robert M. Barnette H. H. Bennett & Selman A. Waksman Harry R. Leach Spessard L. Holland H. Harold Hume Nathan Mayo Wilmon Newell Herman Gunter Lewis Ralph Jones Millard F. Caldweld Willis E. Teal, Col. USA The First 11 Honorary Lifetime Members Charles R. Short Robert M. Salter J. Hillis Miller Lyman James Briggs Lorenzo A. Richards T. L. Collins & Fla. Water Resource Study Commission Firmin E. Bear Harold Mowry Work & Workers in the Fla. Agr. Ext. Serv. 1939-59 Roger W. Bledsoe Doyle Conner R. V. Allison J. G. Tigert J. R. Neller Active Charter Members of the SCSSF Fred Harold Hull Frederick Buren Smith William Thomas Forsee, Jr. Henry Clayton Harris William G. Kirk Alvin Thomas Wallace Curtis E. Hutton

1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007

33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66

E. Travis York, Jr. George Daniel Thornton Marshall O. Watkins Frederick T. Boyd Gaylord M. Volk Gordon Beverly Killinger Nathan Gammon, Jr. Fred Clark John W. Sites William K. Robertson Charles F. Eno Theodore (Ted) W. Winsberg Gerald O. Mott J. G. A. Fiskell Francis Aloysius Wood Victor E. Green, Jr. Earl S. Horner Amegda J. Overman William Guard Blue Charles E. Dean Luther C. Hammond Allan J. Norden Knell Hinson Noble R. Usherwood Earl E. Albregts James M. Davidson William Pritchett E. C. French A. Smajstrla S. F. Shih Shirlie West Fred M. Rhoads Grover Smart George Snyder Brian McNeal Carroll Chambliss

*In the earlier years, the Proceedings bear a date which coincides with the year of the annual meeting. During the years of World War II, publication was irregular and at least some of the volumes were published after the war. Also, the actual year that a publication is available becomes the "legal" date of a issue, not the year the meeting was held. Thus, volumes 32 and after bear a date one year after the annual meetings.

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