tuesday morning 9:00 am - glexpo.com · quantitiesof-si-in-the-formof-silica gel-sio2.nh2o ......

Strawberry I

Tuesday morning 9:00 am

Where: Grand Gallery (main level) Room A & B

MI Recertification credits: 2 (1C, COMM CORE, PRIV CORE)

OH Recertification credits: 0.5 (presentations as marked)

CCA Credits: SW(0.5) PM(0.5) CM(1.5)

Moderator: Kevin Schooley, Ontario Berry Growers

9:00 am The Intricacies of Silicon Fertilization (OH: 2B, 0.5 hr)

Richard Belanger, Laval Univ., Quebec

9:45 am Emerging Technologies: How Can These Help Strawberry Growers

Pam Fisher, Ontario Ministry of Agriculture and Food

Kevin Schooley, Ontario Berry Growers

10:15 am Getting the Most out of Your Irrigation System

Jean Caron, Univ. of Laval, Quebec

11:00 am Home Grown Innovations - Show and Tell

Scott Thompson, Thompson Strawberry Farm, Bristol, WI, Panel

Moderator

12:00 noon Session Ends

The intricacies of silicon fertilization Richard Bélanger Département de phytologie, Université Laval, Quebec, Quebec G1V 0A6, Canada [email protected] While being classified as non-essential for plant growth, silicon (Si) has long been recognized for its prophylactic properties against a wide array of biotic and abiotic stresses. However, practical use of Si has been hampered by conflicting reports about its mode of action, application, and mostly about how and what plants can benefit from Si. The recent discovery of Si transporters in rice, along with new developments in genomics and sequencing data now make it possible to investigate with precision what plant species possess the molecular tools to uptake Si from the soil. In this context, strawberry remains enigmatic because it is considered a poor accumulator of Si and yet is the subject of several reports linking Si fertilization with benefits. Over the last few months, we have investigated the presence and expression of Si transporters in strawberry, along with Si accumulation in different cultivars and the effect of Si fertilization against strawberry powdery mildew. As will be discussed in the presentation, combining molecular approaches with field applications should lead to optimal recommendations for strawberry growers interested in exploiting the beneficial properties of Si. References

• Vivancos, J., R. Deshmukh, C. Grégoire, W. Rémus-Borel, F. Belzile, & R.R. Bélanger. (2016). Identification and characterization of silicon efflux transporters in horsetail (Equisetum arvense). J. Plant Physiol. In press

• Deshmukh, R.K., J. Vivancos, G. Ramakrishnan, V. Guérin, G. Carpentier, H. Sonah, C.

Labbé, P. Isenring, F. J. Belzile, & R.R. Bélanger. (2015). A precise spacing between the NPA domains of aquaporins is essential for silicon permeability in plants. The Plant Journal. 83:489-500.

• Deshmukh, R. and R.R. Bélanger. (2015). The functional role of silicon in plant biology-

Molecular evolution of aquaporins and silicon influx in plants. Functional Ecology. Doi: 10.1111/1365-2435.12570.

• Vivancos, J., C. Labbé, J. G. Menzies & R.R. Bélanger. (2015). Silicon-mediated

resistance of Arabidopsis against powdery mildew involves mechanisms other than the salicylic acid (SA)-dependent defence pathway. Mol. Plant Pathol. 16:572-582.

• Guérin, V., Cogliati, E.E., Hartley, S.E., Belzile, F., Menzies, J.G., & Bélanger, R.R.

(2014). A zoospore inoculation method with Phytophthora sojae to assess the prophylactic role of silicon on soybean cultivars. Plant Dis. 98: 1632-1638.

• Ma, J.F., Tamai, K., Yamaji, N., Mitani, N., Konishi, S., Katsuhara, M., Ishiguro, M.,

Murata, Y., and Yano, M. (2006). A silicon transporter in rice. Nature 440: 688-691.

• Mitani-Ueno, N., Yamaji, N., Zhao, F.-J., and Ma, J.F. (2011). The aromatic/arginine

selectivity filter of NIP aquaporins plays a critical role in substrate selectivity for silicon,

boron, and arsenic. J. Exp. Bot. 62: 4391-4398.

• Fauteux, F., Rémus-Borel, W., Menzies, J.G., and Bélanger, R.R. (2005). Silicon and

plant disease resistance against pathogenic fungi. FEMS Microbiol. Lett. 249: 1-6.

16/11/2016

1

Richard Bélanger, Université LAVAL

The Intricacies of Silicon Fertilization

December 6, 2016

2016 North American Berry ConferenceGrand Rapids, Michigan

Silicon

Si14 28.086

What is Si in nature?

• Silicon: Pure Si; virtually absent in nature• Silica: SiO2 : quartz, sand, non soluble• Silicate: SiO2 mixed with sodium, calcium, aluminium and potassium• Low solubility ranging from 0.1 to 0.6 mM in soils• Silicic acid: soluble form of Si in the form Si0H4.Maximum solubility is1.7 mM at physiological pH (5-‐7). Only form that a plant can absorb

Von Sachs, 1860

Essential elements for plant growth

Macronutrients:

Micronutrients

N, P, K, S, Ca, Mg

Fe, Mn, Zn, B, Cu, Mo and Cl

« Si » is not among them…

XIXth Century…

E.g. Graminaceae

Rice and sugarcane accumulate large quantities of Si in the form of silica gel

SiO2.nH2O

Savant et al. 1999

And yet… Si content in plant tissues may varybetween 0.1 to 10%

0 50 100 150 200 250 300 350

Disease resistance

Abiotic stress tolerance

Yield and quality

Silicon as fertilizer

Pub lished repo rts

Silicon in agriculture in the literature

Over 1000 papers reporting beneficial effects…

16/11/2016

2

ü Consensus: prophylactic role

First reports in Chinese and Japanese literature in the 1920’s

First comprehensive report in USA by Wagner in 1940

ü Beneficial in many plant/pathogeninteractions

0 50 100 150 200 250 300 350

D isease re s istance

Ab io tic stre ss to le rance

Y ie ld and qua lity

S ilicon as fe rtilize r

Pub lished repo rtsHow does silicon protect

plants againstdiseases/stress?

The beneficial effects of Si appear to be correlated with the intrinsic ability of a plant to accumulate Si accumulate

ü How does silicon protectplants againstdiseases/stress?

How do plants absorb Si?

ü The beneficial effects of Si appear to be correlated with the intrinsic ability of a plant to accumulate Si


ü The beneficial effects of Si appear to be correlated with the intrinsic ability of a plant to accumulate Si

ü How do plants absorb Si?


Water flux

cortex

xylem

Silicic acid Lsi1 Lsi2

Silicon transport in plants

From the roots to the leaves: e.g. WHEAT

Only the soluble formmonosilicicacidSi(OH)4can beabsorbed by the plant

16/11/2016

3

The influx transporter Lsi1 is the essential filter for Si absorption in plants:

…plants absorb or not Si on the basis of presence of Lsi1 or not

Plants lacking Lsi1 and unable to absorb Si : • Arabidopsis • Canola • Rocket• Gerbera

Plants known to have Lsi1 and absorb Si: • Cucurbits• Rice• Sugarcane• Soybean• Others…


Lsi1

E.g.

Lsi1 proteins specifically belong to the nodulin 26-‐like intrinsic protein (NIPs) a sub-‐family of aquaporins


Lsi1

GB.C

extracellular

membrane

cytoplasmic

NPA domain

helix

water water

1

2

3

4 5

6

C N

Can we predict if a plant can absorb Si on the basis of the presence of NIP-‐III aquaporins?

Hypothesis

Identification of NIPs in 25 plant species through comparative genomics approach and phylogenetic analysis

All Known Si transporters grouped in NIP-‐III

16/11/2016

4

Maize

??

No report of significant Si accumulation in any of the species belonging to the Solanaceae

Can we predict if a plant can absorb Si on the basis of the presence of NIP-‐III aquaporins?

Hypothesis

Inability may be because of

Structural variation in protein

Tomato known as poor accumulator has putative Si transporter (SlNIP2-‐1)!

GB.C

Lsi1 structure model

108 a.a. between the two NPA loops

Structural variation in protein?

Plant species Gene ID (Froger ’s residues, NPA-‐NPAdistance) Si accumulator (Reference)

Brachypodium distachyon BdNIP2-‐1 (LTAYF, 108), BdNIP2-‐2 (LTAYF, 108) Yes (present study)

Cajanus cajan CcNIP2-‐1 (FTAYF, 108), CcNIP2-‐1 (LTAYF, 108) Yes (Hodson et al., 2005)

Carica papaya CpNIP2-‐1 (LSAYF, 108) ?

Citrus sinensis CsNIP2-‐1 (LTAYL, 43) ?

Elaeis guineensis EgNIP2-‐1 (LTAYL, 108) Yes (Gowda et al., 2004)

Fragaria vesca FvNIP2-‐1 (LTAYM, 108), FvNIP2-‐5 (LTAYV, 108) Yes (Kanto et al., 2004)

Glycine max GmNIP2-‐1 (LTAYM, 108), GmNIP2-‐5 (LTAYV, 108) Yes (present study)

Musa acuminate MaNIP2-‐1 (LTAYF, 108), MaNIP2-‐2 (LTAYL, 108), MaNIP2-‐3 (LTAYF, 108), MaNIP2-‐4 (LTAYF, 108)

Yes (Henriet et al., 2006)

Oryza sativa OsNIP2-‐1 (ITAYF, 108), OsNIP2-‐2 (LTAYF, 108) Yes (Ma et al., 2006)

Prunus persica PpNIP2-‐1 (LTAYV, 108) Yes (LeBlond et al., 2011)

Populus trichocarpa PtNIP2-‐1 (LTAYL, 108) Yes (present study)

Ricinus communis RcNIP2-‐1 (LTAYI, 108) ?

Sorghum bicolor SbNIP2-‐1 (LTAYF, 108), SbNIP2-‐2 (LTAYF, 108) Yes (Lux et al., 2002)

Setaria italic SiNIP2-‐1 (LTAYF, 108), SiNIP2-‐2 (LTAYF, 108) Yes (Weichenthal et al., 2003)

Solanum lycopersicum SlNIP2-‐1 (LSAYI, 109) No (present study)

Vitis vinifera VvNIP2-‐1 (LTAYA, 108) Yes (Blaich and Grundhofer, 1997)

Zea mays ZmNIP2-‐1 (LTAYF, 108), ZmNIP2-‐2 (LTAYF, 108), ZmNIP2-‐3 (LTAYF, 108), ZmNIP2-‐4 (LTAYF, 108)

Yes (Morales et al., 2005)

Citrus sinensis CsNIP2-‐1 (LTAYL, 43) ?

Solanum lycopersicum SlNIP2-‐1 (LSAYI, 109) No (present study)

Structural variation in protein?

Does spacing between NPA domains regulate Si permeability?

Hypothesis

Functional evaluation of NIP2-‐1 genes with different NPA spacing was done by heterologous expression

16/11/2016

5

Functional evaluation of genes with different NPA spacings

o Species confirmed for Si uptake ability

o Candidate genes cloned from poplar and tomato: mutation and heterologous expression in Xenopus oocytes

Results

108

108

109 43

Functional evaluation of genes with different NPA spacings

o Species confirmed for Si uptake ability

o Candidate genes cloned from poplar and tomato: mutation and heterologous expression in Xenopus oocytes

Effect of NPA spacing changes in poplar

Spacing between NPA domains was changed from 108 to 107 and 109 either by adding or removing 1 a.a. in PtNIP2-‐1 of poplar Loss of function

Sl_wildtypeSl_mutant



N C

TM1 TM2 TM3 TM4 TM5 TM6LA LB LC LD LE

G S G R

NPA

NPAVal

Attempt to create functional protein in tomato

Si uptake in oocytes

Effect of NPA spacing changes in tomato

Gain of function

16/11/2016

6

In summary

Only and all plants possessing a NIPIIIaquaporin with a GSGR pore and a NPA-‐NPA distance of 108 amino acids can absorb Si in the form of silicic acid

In summary

ü Only and all plants possessing a NIPIII aquaporin with a GSGR pore and a NPA-‐NPA distance of 108 amino acids can absorb Si in the form of silicic acid It is now possible to easily predict what

plants can absorb Si with molecular tools

What about strawberry?

Pictures of strawberry

Literature

Literature

o Ma (2004): Strawberry is a non accumulator of Silicon

Literature

o Kanto et al. (2006): 0,5% more under Si treatment

o Miyake and Takahashi (1986): 1,22% Si

o Liang et al. (2006): Strawberry uptakes Si passively

16/11/2016

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Full aquaporin analysis in

Fragaria vescaSr. No

Manually assigned features based on protein sequence alignment

NPA-‐NPA Distance

NPA (LB) NPA (LE)Ar/R filters

H2 H5 LE1 LE2 TM

FvNIP1-1 NPA NPA W V A R 6 109FvNIP1-2 NPA NPA W V A R 6 126FvNIP1-3 NPA NPA W A A R 6 110FvNIP1-4 NPA NPA W V A R 6 109FvNIP1-5 NPA NPA W V A R 6 109FvNIP2-1 --- NPA G S G R 3FvNIP2-2 NPA NPA G S G R 6 109FvNIP2-3 NPA --- G S - - 3

FvNIP2-4 NPA NPA G S G R 6 108FvNIP2-5 NPA NPA G S G R 6 108FvNIP3-1 NPA NPA A V G R 6 108FvNIP3-2 NPA NPV T I A R 6 108FvNIP3-3 NPS NPV A I G R 6 108FvNIP5-1 NPS NPA S I A R 6 108

Genomic search for Lsi1 candidate proteins

FvNIP2-4 NPA NPA G S G R 6 108FvNIP2-5 NPA NPA G S G R 6 108

>FAN_iscf00233045.1.g00001.1_(+1)GGLIVTVMIYAVGHISGAHMNPAVTIAFATFRHFPWKQIGELAGIAVGSAVCITSIFAGPISGGSMNPARTIGPALASAYYNGVWIYMVGPVIGALLGAWSYSFIRVNDKPVQASSPRSLSLQLRRIKSDVNVQAVSICKDPLDFA*

>FAN_iscf00346118.1.g00002.1_(+1)MARTELVSVENPIVEHPFYPPGFLKKVVAEIIATFLLVFVTCGSSALSASDERKVSKLGASMTGGLIVTVMIYAVGHISGAHMNPAVTIAFATFRHFPWKMSKSSESNSDGRVHVCPRDVPDCVDHHRHYKPSGGSMNPARTIGPALASAYYNGIWIYMVGPVIGALLGAWSYSFIRVNDKPVQASPPRSLSLQLRRIKSDVNVQAVSICKDPLDFA*

Homologous genes found in

Fragaria ananassa ALIGNMENT

In theory , strawberry has the proper genetic tools to absorbsilicic acid from the soil…

The role of silicon in the suppression of strawberry powdery mildew

16/11/2016

8

Experimental designSeascapeCharlotteMontereyAlbionAmandineVerity

Ø Day neutral cultivars

Ø Silicon amendment: Liquid potassium silicate (Kasil©) at a concentration of 1.7 mM

Analyses:

Yield and fruit quality

Silicon content

Powdery mildew incidence

Natural powdery mildew infectionØ Disease: Silicon content analysis

Powdery mildew incidence Yield and fruit quality

In conclusion

Strawberry has the proper genetic tools (aquaporins) to absorb Si

During the course of a season, strawberry plants can absorb as much as 3% Si

Silicon feeding had an excellent prophylactic role againstpowdery mildew on strawberry, which led to a better yield

Constant supply of Si in the form of silicic acid is preferable to maximize absorption

2016‐11‐22

1

Getting the Most out of Your Irrigation System in Strawberry

Jean Caron, Lelia Anderson, Guillaume Sauvageau and Laurence GendronUniversité Laval, Département des Sols et de Génie AgroalimentaireCorresponding author: [email protected]

Great Lakes Fruit, Vegetable & Farm Market EXPO Michigan Greenhouse Growers EXPO December 6 ‐ 8, 2016

DeVos Place Convention Center, Grand Rapids, MI

Introduction

86% of the strawberry of North America grown in California, along with Florida (7%) and Québec (3.5%) and Ontario (3.5%)

Water is becoming increasingly scarce in California, and under increasing controlled use elsewhere.

Introduction

Cuts may be imposed to strawberry growers to save water, with

limited information on the impact on crop yield.

This also increases pressure to get more crop per drop

A new approach was recently proposed to manage irrigation and

offers the opportunity to maximize yield and generate water savings

without affecting yield, getting the most of your irrigation system

Daily or Weekly estimates of past eventsto estimate water use (ET)Newer

Real time water use(flux –tension based)

Two commonly used approaches to run irrigation: water flux from soil to the plant or estimated uptake from

weather conditions or from change in soil weight

Evapotranspiration (ETo):Evapotranspiration (ETo):

• ETo is the loss of water by evaporation (from soil and plant surfaces) and transpiration (from plant tissues)

• Estimates of Et for a specific crop and area are used for irrigation scheduling:

Crop Et = ETo x Kc

Daily or Weekly estimates of past eventsto estimate water use (ET)Newer

Real time water use(flux –tension based)

Two commonly used approaches to run irrigation: water flux from soil to the plant or estimated uptake from

weather conditions or from change in soil weight

2016‐11‐22

2

Complementing ET in managing irrigation• ET: For a runner, adjusting your diet based on your weekly weight basis

or your past calorie consumption: risk of reducing your efforts due to underfeeding if rate of feeding does not feed enough

• Tension real time: heart and calorie monitor: you will adjust your food uptake based on your real time consumption and your feeding rate hence optimizing your efforts. Irrigation initiated at a tension threshold hc to provide adequate soil water flux to the plant. It considers actual ET (s0 +q0) to make sure the plant is properly supplied during peak activity (in real time)

hc

Part 1: Comparing grower managed (Crop ET and visual assessment) with a real time

tensiometer approach

Using tension or suction forces to drive irrigation decisions

Using tension or suction forces to drive irrigation decisions

Stopping irrigation: tension drops

Initiating irrigation: threshold reached

Observed tension fluctuations at two depths under manual assessment

Saving water

Stay within the blue: initiate irrigation

before being out of the blue zone with the

top tensiometer: likely avoid prewetting and

risk of slaking

Stop it before the lower tensiometer hits

low values: avoid water logging and

leaching

Newer approach to maintain the crop in a non limiting flux situation (below hc) with two tensiometers

Slow run track

Fast run track

hc

2016‐11‐22

3

Irrigation treatments applied though the growth cycle

(CRBD with 5 replicates)

Comparing irrigation threshold to initiate irrigation (top of the blue band)

Determine hc to get top yield irrespective of water use (2011-2014)

Establishment small roots & low ETC deep rooting & large canopy

‐35 kPa

Parameters Measured

Yield in sub‐sampling sites

Size of the fruits (caliber)

Fruit quality using Brix index

Plant size (canopy area)

Leaf Water Potential (SWP) using

pressure chamber

Leaf temperature with infrared thermometer

Plant performance and hydric stress measurements (Weekly measurements from January to June)

Plant performance and hydric stress measurements (Weekly measurements from January to June)

Parameters Measured

Soil sampling and soil analysis (3 soil samples/plot)Initial properties

Texture Saturated Hydraulic Conductivity (Ksat) Soil Water Retention Curves Salinity (Electrical Conductivity (EC)) and pH

Weekly determination Soil salinity from SSE method (1: 1 suspension) Soil salinity (EC) using suction lysimeter Amount of water/ha using flowmeters (non replicated though)

Initial properties

Texture Saturated Hydraulic Conductivity (Ksat) Soil Water Retention Curves Salinity (Electrical Conductivity (EC)) and pH

Weekly determination Soil salinity from SSE method (1: 1 suspension) Soil salinity (EC) using suction lysimeter Amount of water/ha using flowmeters (non replicated though)

Results for 2012 to 2015 in California and Québec

Plant performance and water used(Weekly measurements from January to June)

15 minute real time soil water potential at 15 cm and 30 cm(3 reps) using wireless Hortau tensiometers

Irrigation initiated by the irrigator (2012,13, 14) or automated (2015)

Plant performance and water used(Weekly measurements from January to June)

15 minute real time soil water potential at 15 cm and 30 cm(3 reps) using wireless Hortau tensiometers

Irrigation initiated by the irrigator (2012,13, 14) or automated (2015)

Watsonville Salinas Oxnard

Soil seriesClear Lake clay

Salinas Clay and

Mocho silty loam

Hueneme sandy

loamYield difference

from optimum thresholds

16% (8,000 pounds

per acre)17% 14%

Optimum tension

cbars (top of blueband)

10 13 8

Acre foot/Acre

difference betweentreatments

0.30 0.15 0.15

Percentage of crop

ET for top yield 75 49 114

Effects of real time irrigation management on strawberry production:

Real-time irrigation: summarizingReal-time irrigation: summarizingReal time management:

Irrigation triggered

Irrigation stopped before leachingFast leaching = 0 kPa

Etc management:

Irrigation triggered too late

Too long irrigation = leachingand waterlogging

2016‐11‐22

4

Yield IncreaseRelative to Grower

Year Soil Type Region Grower ‐10 kPa (%)

2011 Clay CA 100 93 0

Wastonville 2013 Clay CA 144 84 0

2014 Clay CA 83 83 26

2012 Silty Clay Loam CA 163 68 17

2012 Silty Clay Loam CA 100 114 14

2013 Sandy Loam CA 93 128 6

2014 Sandy Loam CA 100 154 7

2012 Gravelly Clay Loam QC 35 42 20



112 103 10CA: California; QC: Québec

Water Used% of crop ET

Average Water Use in Percentage of Crop ET (CA only):

Salinas

Oxnard

Île d'Orléans

Flux is important to be maintained non limiting through irrigation

Analyse statistique

Fig. 2. Predicted total fresh market yield (1 kgha-1 = 0.89 lbac-1) from average soil matric potential reached before irrigations using data from seven experimental sites (centered regression line).

Soil Matric Potential (kPa)

Fre

sh M

arke

t Yie

ld (

kgha

-1)

R2adj = 0.86

Analyse statistique

Fig. 3. Frequency distribution of average soil matric potentials reached before irrigations considering eight treatments under conventional irrigation management. Treatments consisted of the grower standard procedure, which aimed at applying 100% of crop ET, and of the treatment based on 100% of crop ET.

0

1

2

3

0-10 11-20 21-30 31-40 41-50

Fre

quen

cy D

istr

ibut

ion

of

Soi

l Mat

ric

Pot

enti

als

Intervals of Soil Matric Potential (-kPa)

Field Number

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17

App

lied

Wat

er (

% o

f cro

p E

T )

0

20

40

60

80

100

120

140

160

Average = 94% Crop ET

Field Number

1 2 3 4 5 6 7 8 9 10 11 12 13 14

Ap

plie

d W

ate

r (%

Cro

p E

T)

0

50

100

150

200

250

January - October

Avg = 146%

Percentage of crop ET applied by growers in 2010 and 2011 in the Watsonville area (drawn from Cahn, 2012)

2010 2011

LOSSES GAINSREDUCED INCOMES INCREASED INCOMES

Yield Gain lbac -1 lb supp. $lb -1 ($)1 290 64 500 1.00 64 500

INCREASED COSTS REDUCED COSTSIncreased Variable Costs Reduced Variable Costs

$lb -1 ($) acftac -1 Tot. Water $acft -1 ($)Operating Costs 0.50 32 250 Water Savings 0.20 10 150 1 500

Increased Fixed Costs Reduced Fixed CostsWireless Tensiometer Technology ($) ᴑ Depreciation (0% intesrest) 4 896 24 480 $ / 5 years ᴑ Annual Service Fees 3 000 ᴑ Initial Costs (Shipping & Installation) 195 975 $ / 5 years

($) ($)Total 40 341 Total 66 000

Payback Period: 0.8 year

ø

Net Change in Profit : 25 659 $

ø

→

Cost-benefit Analysis –Case study of a 50-acre farm

Assumption: conventional management triggers irrigation at -15 kPa, on average. We are looking at the gains and losses associated with the management based on tension at -10 kPa compared to conventional management at -15 kPa, for a 50 acre-farm.

Part 2: Using a real time tensiometer approach to manage deficit irrigation

2016‐11‐22

5

hc is expected to vary during the season because rooting depth (L) and crop ET

(So) vary

Software and controllers could allow adjustment for increasing root and

increasing ET and implement them for managing irrigation

Alternatively, a simpler approach could maintain a lower (‐35 kPa) threshold

when the roots and the plants are small and move to a higher (‐10 kPa

threshold) when the plants gets bigger to save water

Adjusting critical irrigation threshold

0

5

10

15

20

25

30

35

40

Jan‐14 Feb‐14 Mar‐14 Apr‐14 May‐14

hc(‐kPa)

Daily critical threshold (hc) calculated with Forecast of ET and with actual threshold using monitoring data of ET (Oxnard 2014)

hc Forecast

hc Real

Constant hc

0

5

10

15

20

25

30

35

1‐Jan 21‐Jan 10‐Feb 2‐Mar 22‐Mar 11‐Apr 1‐May 21‐May 10‐Jun 30‐Jun

hc (‐kPa)

Daily critical threshold (hc) calculated with Forecast of ET and with actual threshold using monitoring data of ET (Oxnard 2015)

hc forcasted

hc real

Constant hc

Irrigation treatments applied though the growth cycle

(CRBD with 5 replicates)

Main objective

Determine if adjusting the irrigation threshold hc could increase water productivity without

affecting yield

Establishment small roots & low ETC deep rooting & large canopy

1.37

1.51

1.78

1.94

2.12

1.38

0.00

0.50

1.00

1.50

2.00

2.50

2014

Control (Grower) Dry (‐35 kPa)

Variable (*) Roots (**)

Wet (‐10 kPa) Etc

1.44

1.08

1.36

1.03

1.191.08

0.00

0.50

1.00

1.50

2.00

2.50

2015

Control (Grower) Dry (‐35 kPa)

Wet (‐10 kPa) Roots (**)

Variable (*) ETc

Cumulative total water use for the 2 seasons of experiment in ac‐ft/aca) Year 2015: from January 9th to June 11th 2015b) Year 2014: from November 26th 2013 to June 12th 2014

Weighted Yields for 2014a) Weighted Total Yield during the whole season from January 02th to June 05th 2014 (lbs/ac);b) Weighted Marketable Yield (Fresh Market) from January 02th to April 18nd 2014 (lbs/ac);c) Relative Marketable Yield (Wet = 100% ) from January 02th to April 18nd 2014.

57287 59633

61195

61141

60783

30000

35000

40000

45000

50000

55000

60000

65000

Cumulative

yield (lbs/ac)

Total Yield

92

91

96

94

100

80

82

84

86

88

90

92

94

96

98

100

Cumulative

yield (% of ‐10 kPa)

Relative MarketableYield

36728

36127

37948

37355 39718

30000

35000

40000

45000

50000

55000

60000

65000

Marketable Yield (fresh)

2016‐11‐22

6

54611

54258

56121

56225

57589

31000

36000

41000

46000

51000

56000

61000

Weigther 2015 Yields in lbs/ac

Total Yield (fresh + freezer)

34721

32923

34280

36123

36560

31000

36000

41000

46000

51000

56000

61000

Marketable Yield (fresh)

0.95

0.90

0.94

0.99

1.00

0.8

0.9

0.9

0.9

0.9

0.9

1.0

1.0

1.0

1.0

Relative Yield (Wet = 1.00)

Relative Marketable Yield (fresh)

Weighted Yields for 2015a) Weighted Total Yield (Fresh Market = Freezer) during the whole season (January 9th to June 11th 2015);b) Weighted Marketable Yield (Fresh Market) from January 9th to April 2nd 2015;c) Relative Marketable Yield (Wet = 1.00) from January 9th to April 2nd .

Summary of the performances for both years

Irrigation treatments Relative yield1 Water used

% acre‐foot per acre

Grower 91 1.41

‐10 kPa 100 1.74

‐35 kPa 93 1.30

Partial deficit

Roots 94 1.51

Variable 98 1.49

Reference ET ‐ 1.23

1Main effects significant at p=0.05

Treatments

Water use efficiency and relative yield

Statistical analyses were performed using proc mixed and proc GLM in SAS (p<0,05).

Step Wet 50% ET 100% ET Grower

Yield (% of 100% ET) 95 ab 105 a 76 c 100 a 83 bc

Water use efficiency (kg/ha.cm) 1539 a 1407 a 1531 a 1109 b 1208 b

Clay loam

Sandy loam

Statistical analyses were performed using proc mixed and proc GLM in SAS (p<0,05).

Step Dry Variable Wet Grower

Yield (% of Grower) 104 a 105 a 110 a 111 a 100 a

Water use efficiency (kg/ha.cm) 1229 a 1187 a 1118 a 996 b 846 c

Analyse statistique

Fig. 1. Effect of (1) average soil matric potential reached before irrigations and (2) irrigation management method on predicted total WU (1 acft.ac-1 = 3047 m3ha-1) using data from eight experimental sites (centered regression line).

Soil Matric Potential (kPa)

° Conventional Management + Ѱ-based Management

Wat

er U

se (

m3 h

a-1)

R2adj = 0.91

2016‐11‐22

7

0.12 0.28 0.41 0.81 4.05150 350 500 1000 5000

Deficit ѱ-based management

-kPa lbac -1 % acftac -1 %

-15 -1290 -4 -0.13 -7 (625) (598) (578) (511) 25-20 -2580 -7 -0.27 -11 (1 250) (1 196) (1 156) (1 022) 50-30 -5150 -16 -0.54 -23 (2 495) (2 387) (2 307) (2 039) 105

Yield decrease (relative to -10 kPa)

Water savings (relative to -10 kPa)

Net Gain (Loss)

($ac-1)

Operation Costs ($kg-1) ($lb -1 )

1.10 (0.50)

Annual Fresh Strawberry Price ($kg-1) ($lb -1 )

2.20 (1.00)

Water Price ($m-3) ($acpi -1 )

Deficit Irrigation –using wireless tensiometers

Impact on profit of a deficit irrigation (-15, -20, -30 kPa) relative to a wet management based on tension (-10 kPa)

Conclusions

• Real time management at ‐10 kPa is important for more crop per drop and higher revenues

• Target is ‐10 kpa to initiate irrigation, any stress even early in the season has generated yield decreases and revenue losses.

• Water savings do not compensate for yield losses but at a cost of 1000‐5000$ per acre‐foot

Ito bros Inc

Colleagues, students, research assistants: Carole Boily, Amélie Picard, Julien Cormier, Valérie Bernier, Guillaume Létourneau, Benjamin Parys, Laurence Gendron.

Hortau and technical support :Sébastien Rochette, Jocelyn Boudreau, Shirley McClish, Derek Gagne, Omar Flores,TravisWilson, Philippe Sylvestre.

Growers and their teams : Henri Ito, Emily Paddock, Allison VandenHout, Lina, Agustin, Ruben, Lalo, Pascual Bruno.

University of California cooperative Extension : Oleg Daugovish and Michael Cahn

tuesday morning 9:00 am - glexpo.com · quantitiesof-si-in-the-formof-silica gel-sio2.nh2o ......

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