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Yield Estimation in Chilli (Capsicum annuumL.) using RemoteSensing*

MALLESWARI SADHINENI1and V. C. PATIL2

Department of Agronomy, University of Agricultural Sciences, Dharwad

ABSTRACT

Chilli yield estimation in Hubli taluk of Dharwad district, Karnataka was carried out using IRS ID LISS

III imagery. The acreage estimation was done by supervised MXL classification and yield estimation by

developing yield model using the relationship between crop cutting experiments yield data, NDVI and LAI of

chilli crop. The average yield of chilli crop was estimated to be 419 kg ha -1and the total production of dry chillies

in Hubli taluk was 5,960 tonnes.

Reliable and timely forecast of crop production is of crucial economic importance in

any region. Among the various applications of space technology, agricultural applications

have received greater attention in India and in agricultural applications crop production

forecasting is the most challenging and economically important one. Space borne remotely

sensed data, being repetitive and multispectral in nature, is an ideal choice for use in forecasting

crop production. Intrinsic ability of spectral reflectance data is to identify and discriminate

crops and estimate their acreages resulting in possibility of relating reflectance data of crops

in specific wavelength regions to canopy growth or vigour. The yield, therefore has attractive

propositions. In the traditional method, the average yield is obtained on the basis of cropcutting experiments conducted on a number of randomly selected fields in a sample of

villages in a district. It is time consuming, requires more manpower and also may not be

accurate many times.

Chilli (Capsicum annuum L.) is an important spice cum vegetable crop of commercial

importance. Titillating pungency and fascinating natural colour of chillies form an indispensable

adjunct in every home all over the world. India is the leading country in the world in chilli

production with an area of 9, 08,400 ha and production of 9, 70,800 tonnes of dry chillies.

Recently, chilli is gaining greater importance in the global market because of its value-added

products and diverse uses. In this context, within season estimates of crop acreage, yield

and accurate forecast of most likely range of growth conditions help in organizing the inputslike fertilizers and pesticides. Further, pre-harvest estimates of crop production guide the

decision makers in framing and implementing the policies, price fixation, arrangement of

storage facilities and export-import strategies.

* Part of M.Sc (Ag.) Thesis submitted by former author to the University of Agricultural Sciences,Dharwad.

1. Professor and Head

J.Res. ANGRAU 35(3) 1 - 11, 2007


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Krishna Rao et al.(1997) estimated the chilli crop acreage by digital analysis of IRS

IC LISS III data covering five mandals of Guntur district of Andhra Pradesh. The studies on

yield and production estimation in indeterminate commercial crops like chilli are meagre.

Therefore, a study was conducted in Hubli taluk of Dharwad district, Karnataka to estimate

the yield and production of chilli crop.

Materials and Methods

The study area comprising Hubli taluk of Dharwad district, Karnataka lies between

150to 150 30' N latitude and 750to 750 30' E longitudes. The total geographical area of Hubli

taluk is 73,707 ha. The average rainfall of the region ranges from 626 to 727 mm per annum.

The main crops of the study area in kharifseason are chilli, cotton, redgram, groundnut and

onion. Chilli crop is mainly raised under rainfed conditions as a pure crop or a mixed crop

along with cotton. Chilli + cotton and chilli + cotton + onion mixed cropping are prevalent in

Hubli taluk.

A total of 26 ground truth sites for the collection of the observational data required

for the current investigations were selected after conducting a preliminary survey of the

study area and verification of the statistical data on the acreage under chilli crop. The GARMIN

12 GPS receiver in stand alone mode was used to collect the information regarding the

geographical location of the ground truth sites, which was used for marking of training sites.

The LAI 2000 plant canopy analyzer of LICOR was used to record the leaf area index in the

standing crop of chilli. Yield attributes and yield data were collected from the randomly

selected 10 m 10 m sampling unit from each ground truth site.

IRS ID LISS III digital data of Hubli taluk corresponding to path 97 and row 62

acquired on the 14thof November 2002, which coincides with the maximum vegetative growth

to fruit ripening stage of chilli crop was selected for the investigation.

Digital analysis of satellite data was carried out for deriving information on spatial

extent of chilli crop grown in the study area. The IBM RS workstation with ERDAS IMAGINE

8.5 software at National Remote Sensing Agency, Hyderabad, was used for the analysis and

interpretation of remote sensing data. Geometric correction of the image was done using

SOI toposheets of 1:50,000 scale.

ESWARI and PATIL

Normalized Difference Vegetation Index (NDVI) proposed by Rouse et al.(1974)

was used in this study. This index is very sensitive to the presence of green vegetation. It

permits the prediction of agricultural crops and precipitation in semi arid areas. NDVI can

be defined by following equation


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The training windows were defined for various crops and other land use classes

based on the ground truth information. Multiple training sites for each class were identified in

order to represent the variability within the same class. The image was classified using

maximum likelihood algorithm. The red and near infrared channel data pertaining to the IRS

ID LISS image were transformed into NDVI image in ERDAS IMAGINE Modeler panel by

running the NDVI model. The resultant NDVI image of the chilli crop was used for yield

estimation.

The correlation coefficients were worked out between the yield and independent

variables affecting the yield like NDVI, LAI during the crop growth period. Polynomial regression

analysis was run between the yield and NDVI, LAI and the regression equation developed

was used for the yield predictions. The average yield of the taluk obtained from this equation

multiplied with the acreage under chilli crop was used to estimate the production of chilli

crop.

Results and Discussion

Acreage estimation of chilli crop in Hubli taluk was done using IRS ID LISS III data

with the help of ERDAS IMAGINE 8.5 software. The classification was done using supervised

approach with MXL algorithm. The acreage under pure chilli crop was found to be 11,032 ha

and the chilli+cotton mixed cropping system accounted for 3076 ha.

The False Colour Composite (FCC) and NDVI images of the Hubli taluk are shown in

Figures 1 and 2. The yield attributes, LAI and NDVI values of chilli crop are presented in

Table 1. The NDVI values of chilli crop in Hubli taluk ranged from 0.1132 to 0.4559.

In the present study, highly variable yield levels were observed in the ground truth

sites. The yield ranged from 111 to 1544 kg ha -1. The number of fruits per plant and fruit

weight also showed wide variation. The main season for low and variable yields at different

places was due to lack of sufficient rainfall immediately after transplanting and low erratic

distribution of rainfall during crop growth period, which exposed the crop to moisture stress

leading to reduced flowering and fruit set and dropping of the flowers and fruits.

The results of the linear regression analysis between NDVI and agronomic variables

like LAI, number of fruits per plant, fruit weight per and yield per hectare are presented in

Table 2. Among all the variables studied, highly significant correlation was found between

NDVI and number of fruits per plant (r=0.957) followed by fruit weight per plant and yield per

ha (r=0.896) and leaf area index (r=0.887).

YIELD ESTIMATION IN CHILLI

RNIR

RNIRNDVI

+

= where,

NIR and R are the reflectance in the near infrared and red regions, respectively.


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ESWARI and PATIL


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S.No. NDVI LAI No. of fruit

plant

Fruit weight(g/plant)

Dry chilliyield (kg/ha)

Table1: NDVI, LAI, Yeld attributes and Yield of Chilli crop in the selected ground truthsites of Hubli taluk of Dharwad district, Karnataka

1 0.3835 1.41 45 67.45 1140

2 0.4308 0.97 32 43.31 732

3 0.4559 1.80 57 91.36 1544

4 0.1385 0.33 9 11.53 195

5 0.2419 0.72 18 20.88 353

6 0.1296 0.28 10 10.47 177

7 0.2397 0.62 35 37.51 634

8 0.2154 0.57 23 30.47 515

9 0.1355 0.33 6 8.52 144

10 0.1970 0.27 13 17.28 292

11 0.2000 0.36 36 36.27 613

12 0.1818 0.26 8 15.62 264

13 0.1186 0.33 5 6.71 111

14 0.1429 0.53 9 11.71 198

15 0.1826 0.51 12 13.96 236

16 0.1846 0.58 14 15.85 268

17 0.1852 0.37 11 13.02 220

18 0.1739 0.56 12 15.68 265

19 0.2366 0.58 25 33.67 569

20 0.1966 0.43 18 21.65 366

21 0.1532 0.31 7 10.06 170

22 0.2522 0.58 24 31.60 534

23 0.3058 0.71 22 29.82 504

24 0.3000 0.57 25 29.11 492

25 0.1132 0.19 8 9.11 154

26 0.1429 0.21 9 11.36 192



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Table 2: Linear regression analysis between NDVI and agronomic variables of Chilli

Agronomic variable Correlation coefficient values

Leaf area index 0.887*

No. of fruits per plant 0.957**

Fruit weight per plant 0.896**

Yield per 100 m2 0.896**

* - Significant at P = 0.05 ** - Significant at P = 0.01

Martin and Heilman (1986) and Sridevi (2002) also reported significant correlation between

NDVI and LAI, NDVI and yield components of rice crop. A simple regression analysis done

between yield and NDVI, LAI. NDVI has shown significant correlation with yield at 5 per cent

level (r=0.896). LAI was found to have highly significant correlation with yield at 1 per cent

level (r=0.920).

Yield prediction model

Y = -165.90 + 1333.5 NDVI + 532.99 LAI where,

NDVI : NDVI of chilli crop

LAI : LAI of chilli crop

R2 : 0.877 SEE : 120.28 F ratio : 81.93

The yield prediction model was found to be significant (r2=0.877), which explains 87

per cent of the variability in yield estimation. Using this yield model, the average yield of dry

chilli in Hubli taluk was estimated to be 419 kg ha-1-.

The total production of chilli crop in Hubli taluk was calculated by using the relationship,

Production = Acreage (ha) yield (kg/ha)

The estimated production of chilli in Hubli taluk was 5,960 tonnes.

The chilli yield and production estimation at taluk level was done satisfactorily using

IRS ID LISS III data. The estimated acreage under chilli crop in Hubli taluk was 14,224 ha.

The estimated yield and production of chilli were 419 kg ha-1-and 5,960 tonnes, respectively.

This study has shown that the yield estimation and production forecasting can be made in

ESWARI and PATIL


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indeterminate commercial crops like chilli through remote sensing technology with the

availability of high resolution data from IRS ID LISS III sensor.

References

KRISHNA RAO M V, HEBBAR K R and VENKATARATNAM L 1997 Chilli crop inventoryusing IRS-IC LISS-III data. Scientific Note, NRSA, Hyderabad.

MARTIN R D and HEILMAN J L 1986 Spectral reflectance patterns of flooded rice.Photogrammetric Engineering and Remote Sensing 52:1885-1890.

PARIHAR J S and NAVALGUND R R 1992 Crop production forecasting. In : Natural Resources

Management A New Perspective Ed. Karrle, R. L., NNRMS, Bangalore, pp. 91-107.

ROUSE J W, HAAS R W, SCHELL J A, DEERING D W and HARLAN J C 1974 Monitoringthe vernal advancement and retrogradation of natural vegetation. NASA/GSFCT Type IIIfinal report, Greenbelt,MD,USA.

SRIDEVI B 2002 Rice production modelling using remote sensing and GIS techniques.Ph. D. Thesissubmitted to Institute of Post Graduate Studies and Research, JawaharlalNehru Technological University, Hyderabad.



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J.Res. ANGRAU 35(3) 8 - 12 , 2007

Dissipation of Triazophos and Cypermethrin Residues on Chillies

(Capsicum annum L.)P.B. MAHALINGAPPA1, K. DHARMA REDDY2, K.NARASIMHA REDDY3and

G.V.SUBBARATNAM4

Department of Entomology College of Agriculture,Rajendranagar, Hyderabad 30

ABSTRACT

Dissipation of triazophos 0.08 and cypermethrin 0.0012 per cent residues on chillies were studied

by spraying at 15 days interval, initiating from 45 days after transplanting. A total of four sprays were given.

The initial deposit of triazophos and cypermethrin after fourth spray recorded 0.39 and 0.16 mg kg -1, respectively.

The level of residues at 1,3,5,10, 15, 20 and 30 days after last spray in green chillies were 0.35, 0.26, 0.21,

0.18, 0.13, 0.09 and 0.04 mg kg -1for triazophos and 0.12, 0.08, 0.05, 0.03 mg kg-1for cypermethrin which was

observed below detectable (BDL) from 20 thday onwards. The half life (RL50

) values of 9.70 and 6.54 days and

waiting period (Ttol

) of 8.03 and one day was found for triazophos and cypermethrin respectively. The

residues in shade dried red chillies at 90 days after last spray was 0.06 and 0.01 mg kg -1, respectively for

triazophos and cypermethrin.

Chilli (Capsicum annum L.) is one of the important condiments having immense

commercial and therapeutic value. India contributes about one fourth of worlds production

of chillies. Andhra Pradesh alone accounts for 45 to 50 per cent production of chillies and

meets one third demand of the countrys need.

There is ample scope to export chillies to other countries and earn foreign exchange

provided that the produce is free of pesticide residues. The chilli farmers suffer due to

rejection of chilli consignments exported, due to presence of pesticide residues in it . Hence,

there is every need to prescribe the waiting period for safe consumption of the produce.

Keeping this in view, a study was under taken to test the dissipation pattern of triazophos

and cypermethrin residues in chilli fruits.

Materials and methods

An experiment was conducted in the field during 2004-05 with triazophos 0.08 and

cypermethrin 0.0012 per cent for controlling chilli pests. Each treatment was replicated thrice

in a randomized block design. Spraying was given at 15 days interval with hand compression

sprayer. Initiating from 45 days after transplanting, a total of four sprays were given. Composite

* Part of M.Sc. (Ag.) Thesis submitted by the first author to Acharya N.G. Agricultural University,Rajendranagar, Hyderabad.

2. Associate Professor

3. Scientist, AINP on Pesticide Residue, College of Agriculture, Rajendranagar, Hyderabad.

4. Professor & University Head.


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fruit samples were collected at 0 hours, 1,3,5,10, 15, 20 and 30 days after last spray and

analysed at All India Net Work Project on Pesticide Residues, Rajendranagar, Hyderabad.

Triazophos residues were analysed by following the method of Getz and Watts (1964) modified

by Jain et al. (1974). The composite chilli fruit sample (500 g) was cut into small pieces. A

representative portion of 50 g chopped sample was blended thrice with 100, 50, 50 ml of

acetone in a high speed blender, filtered and the extracts combined and concentrated to

about 50 ml using a Kunderna Danish Evaporator and then transferred to a one litre capacity

separatory funnel. The extract was diluted with 5 per cent aqueous sodium chloride solution

and partitioned thrice into 100, 50 and 50 ml of dichloromethane. The dichloromethane layer

was passed through anhydrous sodium sulphate. The combined dichloromethane fractionswere evaporated to near dryness. The complete removal of dichloromethane was ensured

by repeatedly adding acetone to the residues followed by evaporation under vacuum. The

residues thus obtained were dissolved in 5 ml of acetone (Luke et al.,1975 and Honda,

1994). The extracts were taken in Getz tube and solvent evaporated off under vacuum or by

dry air. To the residues 0.2 ml of 2 per cent 4 (p-nitrobenzyl)pyridine and 0.2 ml of 2 per cent

cyclohexylamine solution in acetone was added. The tube was fitted with an air condenser

and heated in an oil bath at 175 to 1800C for three minutes. After cooling the tube in an ice

bath, 3 ml of ethyl acetate was added and the absorbance recorded at 540 nm. The residues

of triazophos was extracted with acetone. Five ml of triazophos extract was taken in a glass

column containing adsorbent mixture of charcoal, celite and magnesium oxide (2:2:1). The

concentrated extract in the column was diluted with 150 ml of chloroform. The dilute was

finally dissolved in chloroform (20 ml) for determination of residues. Recovery of 89 per cent

with limit of detection of micro gram/gram was ensured.

Extraction and cleanup of cypermethrin was done as per the procedure suggested

by Awasthi (1994). Chilli fruit samples were chopped and blended. A representative sample

of 50 g was extracted with a solvent mixture of 100 ml of acetone : hexane (1:1 v/v). The

extracted solvent mixture was transferred to hexane layer by solvent partitioning in separatory

funnel and diluted with water to remove acetone. The upper hexane phase was collected

through anhydrous sodium sulphate and concentrated to about 5 ml . The concentrated

extract of cypermethrin was passed through a glass column containing 5 g of florisil, 5 g of

neutral alumina grade III overlaid with a 20 mm layer of anhydrous sodium sulphate. The

column was then diluted with solvent mixtures of n-hexane: acetone (9:1v/v) and the dilute

was concentrated to 5 ml for GC analysis. The residues of cypermethrin were determined

using Varian cp 3800 gas chromatograph with following parameters.

Detector : ECD (Ni63) (Electron capture detector)

Column : Factor four Varian 0.25 ID, 10 m.

DISSIPATION OF TRIAZOPHOS


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Injector temperature (0C) : 270

Detector temperature (0C) : 300

Column (over) temperature (0C) : 240

Carrier gas flow (ml/min.) : 1.5 ml

Retention time (min.) :5.881 minutes

With above conditions, the recovery obtained was 94.5 per cent and limit of detection

was 0.01 ng. Based on the data, half life (RL50) and waiting period (Ttol) were calculated

(Gunther and Blimn, 1955 and Hoskin, 1961).

Results and Discussions

The initial deposit of 0.39 mg kg-1of triazophos 0.08 per cent was obtained on green

chillies. The subsequent residues at 1, 3, 5, 10, 15, 20 and 30 days after fourth spray was

found to be 0.35, 0.26, 0.21, 0.18, 0.13, 0.09 and 0.04 mg kg-1(Table 1). The corresponding

dissipation was 10.25, 33.33, 46.15, 53.84, 66.66, 76.92 and 89.74 per cent respectively.

The half life of triazophos was found to be 9.70 days and waiting period of 8.03 days. Hence,

it was suggested to give the last spray of triazophos (0.08 %) nine days before harvest, from

consumer safety point of view. The present findings are in accordance with the reports of

Narasimha Reddy et al.(1997) and Phani kumar et al.(2000a). Residues of triazophos (0.08%)

in shade dried red chillies at 30, 60, and 90 days after the last spray were found to be 0.20(48.71%), 0.14 (64.10%) and 0.06 mg kg-1(84.61%), respectively (Table 1).

Cypermethrin 0.0012 per cent after fourth spray left the initial deposit of

0.16 mg kg-1which was found to be far below maximum residue level (MRL) of 0.50 mg kg-

1(G.O.I.Gazette, 1990). The residues degraded to an extent of 0.14, 0.12, 0.08l, 0.05 and

0.03 mg kg-1at 1, 3, 5, 10 and 15 days respectively. However, residues were below detectable

level (BDL) at 20 and 30 days (Table 2) after the fourth spraying. The corresponding dissipation

percentage was found to be 12.5, 25, 50.0, 68.75, 81.25, 100 and 100 respectively. The

residues recorded at zero hour were far below MRL of 0.5 mg kg-1. Hence, waiting period and

half life were worked out to be one and 6.54 days, respectively. The present dissipation

pattern concurred with the findings of Bhupinder Singh and Udeaan(1989) and Phanikumar et

al.(2000b). In shade dried red chillies, the residues recorded were 0.13 (18.75%), 0.02

(87.50%), and 0.01 mg kg-1(93.75%) at 30, 60 and 90 days after last spray, respectively

(Table 2).

MAHALINGAPPA et al.


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DISSIPATION OF TRIAZOPHOS

Table 1: Dissipation of triazophos 0.08 per cent in chillies

Days after treatment Residues (mg/kg) Dissipation (%)Green Chillies

0 hours 0.39 -

1 0.35 10.25

3 0.26 33.33

5 0.21 46.15

10 0.18 53.84

15 0.13 66.6620 0.09 76.92

30 0.04 89.74

Red Chillies

30 0.20 48.71

60 0.14 64.10

90 0.06 84.61

Table 2: Dissipation of cypermethrin 0.0012 per cent in chillies

Days after treatment Residues (mg/kg) Dissipation (%)

Green Chillies

0 hour 0.16

1 0.14 12.50

3 0.12 25.00

5 0.08 50.00

10 0.05 68.75

15 0.03 81.25

20 BDL 100.00

30 BDL 100.00

Red chillies

30 0.13 18.75

60 0.02 87.50

90 0.01 93.75

BDL = Below detectable level


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References

AWASTHI M D 1994 Studies on dissipation and persistence of pyrethroid residues on chillifruit for safety constants. Pesticide Research Journal 6: 80 83

BHUPINDER SINGH and UDEAAN A S 1989 Estimation of cypermethrin residues in thefruits of okra Abelmoschusesculentus (Linn.) Moench. Journal of insect science 2: 49 52.

GETZ M E and WATTS R R 1964 Application of $ (p-nitrobenzyl) pyridine as a rapidquantitative reagent for organophosphate pesticides. Association of official analyticalchemists journal 4: 1094 1096.

GUNTHER F A and BLIMN R C 1955 Analysis of insecticides and acaricides. Inter SciencePublishers, New York, pp: 696.

HONDA S K 1994 Protocol on residues of triazophos. All India Coordinated Research Projecton Pesticide Residues, New Delhi.

HOSKINS W M 1961 Mathematical treatments of loss of pesticide residues. Plant ProtectionBulletin, FAO, 9:163 168.

JAIN H K, PANDEY S Y, AGNIHOTRI N P and DEWAN R S 1974 : Rapid estimation oforganophosphorus insecticides. Indian Journal of Entomology 36:145 148.

LUKE A MILTORN, JERRY E FROBERG and HERBERT T MASUMOTO 1975 Extractionand clean up of organochlorine, organophosphate, organonitrogen and hydrocarbon pesticidesin produce for determination by Gas Liquid Chromatography: Association of Official Analytical

Chemists Journal 58:1020 1026.

NARASIMHA REDDY K, MIR AZAM SULTAN, JAGADISHWAR REDDY D and RAMESHBABU T 1997 Dissipation and decontamination of triazophos and lindane in brinjal. NationalSeminar on Plant Protection towards Sustainability, pp: 15

PHANIKUMAR K, JAGDISHWAR REDDY D, NARASIMHA REDDY K, RAMESH BABU Tand NARENDRANATH VV 2000 a Dissipation of cypermethrin residues in chilli. PesticideResearch Journal 12:130 132.

PHANIKUMAR K, JAGDISHWAAR REDDY D, NARASIMHA REDDY K, RAMESH BABU Tand NARENDRANATH V V 2000 of Dissipation and decontamination of triazophos andacephate residues in chilli (Capsicum annuum Linn.). Pesticide Research Journal12:26 29.

MAHALINGAPPA et al.


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Combining Ability Studies for Important Physico-Chemical Quality

Characteristics in Aromatic Rice

B. KRISHNA VENI1and N. SHOBHA RANI2

Division of Genetics and Plant Breeding, Directorate of Rice Research,

Rajendranagar, Hyderabad

ABSTRACT

Combining ability studies were undertaken for seven important physico-chemical quality traits in 25

hybrids derived from ten parents involving eight scented and two non-scented rice varieties/lines. The resultsrevealed that IR 62874-88-2-1, HBC 85 and PGB possessed desirable GCA for all three physical kernel

characters. For cooked kernel length and elongation ratio, PR 109, PK 1379-9-1-1 and PGB were the best

general combiners. Among crosses, PR 109/Basmati 6129 and IR62874-88-2-1/ Basmati 6129 were the best

specific combiners for all the three physical kernel quality traits studied while PK1379-9-1-1/PGB was the best

combiner for kernel length after cooking. Most of the crosses which showed high SCA effects for various

characters involved at least one parent with desirable GCA suggesting the major role of non-additive gene

action in association with additive gene effects in the expression of these traits.

The importance of rice grain quality is now instrumental and has become a valuable

tool for the acceptance of varieties to be released. Therefore in recent years, emphasis in

rice improvement programmes has been laid on selection of genotypes combining desirable

traits, particularly grain quality characters. Quality in rice is described by a combination of

many physico-chemical properties which show a complex nature of inheritance. Information

on the gene action for important quality traits is scanty. Combining ability studies are frequently

used to test the performance of parents in various cross combinations, besides elucidating

the nature and magnitude of gene action involved in the expression of quantitative traits.

Such information is required to design effective breeding programme for rapid improvement.

The ultimate objective of this analysis is to spot out best parents for general combining

ability and best hybrids for specific combining ability effects. In the present study, an

attempt was made to assess the combining ability for seven important physico-chemical

quality traits in 25 hybrids and their ten parents involving basmati and non basmati varieties.


Two non-scented popular high yielding rice varieties (IR64 and PR109) and three

aromatic rice lines viz.,Gaurav, IR 62874-88-2-1 and PK 1379-9-1-1 were used as lines and

crossed with five basmati testers (HBC 85, Karnal local, Basmati 410, Basmati 6129 and

J.Res. ANGRAU 35(3) 13 - 20 , 2007

1. Scientist, Regional Agricultural Research Station, Lam Guntur

2. Principal Scientist and Head.


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PGB) in a line x tester mating design to obtain 25 crosses. All these F1s along with their ten

parents were evaluated in a randomized block design with two replications during 1999 wet

season at Directorate of Rice Research farm, Hyderabad. Each replication consisted of

three rows of 3.6 m length with 30 cm inter and intra row spacing. Standard agronomic

practices and need based plant protection measures were undertaken to raise the crop.

From each replication, ten randomly selected plants were harvested and threshed separately.

After six months of ageing, the seed samples were analysed for seven important physico-

chemical quality traits on individual plant basis. Hulling was done in a lab husker (THU005)

and small Kett polisher was used for milling the seed samples. Kernel length and kernel

breadth were determined by using dial micrometer as indicated by Murthy and Govindaswamy(1967). Length/breadth ratio was calculated as the ratio of mean kernel length to mean kernel

breadth. Standard cooking procedure described by Juliano et al.(1965) was used for cooking

the sample and estimating kernel length after cooking. Elongation ratio was computed by

dividing the mean cooked kernel length by mean uncooked milled kernel length. Alkali

spreading value and amylose content were estimated by following the methods delineated

by Little et al.(1958) and Juliano (1971) respectively. The mean data was utilized for estimating

combining ability in line x tester model as per Kempthrone (1957).


The analysis of variance results for line x tester design indicated that the lines differed

significantly for kernel length, kernel breadth, length/breadth ratio, kernel length after cooking,

elongation ratio, alkali spreading value and amylose content (Table1). Among testers,

significant variation was observed for all traits except for elongation ratio and alkali spreading

value. The variance due to interaction between lines x testers was highly significant for all

seven physico-chemical quality traits indicating the presence of adequate variability in the

experimental material. The GCA to SCA variance ratio was less than unity for all the

characteristics studied suggesting the preponderance of non-additive gene action in the

expression of these traits. These results are in confirmation with the findings of Srivastava

et al. (1978), Sarathe et al.(1986), Paramasivan et al.(1996) and Sharma and Mani (1997).

The study of GCA effects revealed that Gaurav, IR 62874-88-2-1 among lines and

HBC 85 among testers possessed desirable GCA effects for kernel length and length/breadthratio indicating the possibility of simultaneous improvement in both the traits (Table 2).

Except the former line, all others also recorded significant negative GCA for kernel breadth

which was desirable. For kernel length after cooking and elongation ratio, PR 109, PK 1379-

9-1-1 and PGB manifested high GCA effects in the desirable directions. IR 64 was the best

general combiner for alkali spreading value while four parents viz., IR 64, PR 109, Karnal

VENI and RANI


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Local and Basmati 410 exhibited favourable effects for amylose content. IR62874-88-2-

1and HBC85 were the best general combiners for all three physical kernel quality traits while

IR 64, showed positive GCA effects for both alkali spreading value and amylose content.

The cross combinations, PR 109/Basmati 6129, and IR 62874-88-2-1/Basmati 6129

exhibited significant SCA effects for all three physical kernel characteristics in the desirable

direction (Table3). These two crosses involved at least one parent with high/moderate GCA

for the above said traits. Bansal et al(2000) reported similar results in a combining ability

study. Four hybrids viz., PK 1379-9-1-1/PGB, IR 64/HBC 85, IR 64/Karnal Local and IR 64/

Basmati 410, were the best specific combiners for kernel length after cooking while Gaurav/

Basmati 6129, IR 62874-88-2-1/HBC 85 manifested positive and significant SCA effects for

elongation ratio in that order. None of the hybrids exhibited significant SCA effect for alkali

spreading value, while three crosses viz., Gaurav/Karnal Local, PR 109/PGB, IR 62874-88-

2-1/PGB manifested positive and significant SCA effects for amylose content. The cross

PK1379-9-1-1/PGB was the best specific combiner for kernel length after cooking which is

the most important quality characteristic of basmati rice. This cross was derived from both

GCA parents for kernel length after cooking. Earlier Sood et al.(1983) reported that crosses

involving high x low or high x moderate GCA exhibited significant SCA effects for kernel

length after cooking. The cross Gaurav/Karnal local exhibited best combining ability for

amylose content as well as alkali spreading value.

The mean values and SCA effects for seven physico-chemical quality traits in hybrids

revealed that every character required different combination of parents for their expression

in the desirable direction. No correspondence between per seperformance and GCA/SCA

effects could be observed making it difficult to generalize the trend. When we consider both

the mean values and GCA/SCA ratio at a time, some parents/crosses were common, but

occupied different positions. Srivastava et al. (1978) and Sharma and Mani (1997) also

observed same results and suggested that selection of crosses should be made on the

basis of per seperformance as well as SCA effects. It would be more useful if the crosses

showing high SCA effects involved parents with high GCA effects. Most of the promising

crosses giving high SCA effects for different characters involved at least one good general

combiner which suggests that direct selection could be made on the basis of per seperformance (Table 4). The per seperformance of F

1s indicate that either one or both the

parents were good combiners which demanded inclusion of at least one good combining

parent in producing superior hybrids.

COMBINING ABILITY STUDIES


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VENI and RANI


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The present investigation suggested the predominance of non-additive gene action

in addition to additive gene effects. In such cases, where non-additive gene effects played

a vital role in association with additive components, maximum gain could be attained by

maintaining considerable heterozygosity coupled with selection in early segregating

generations to provide opportunity to disassociate unworthy linkages, enhance the frequency

of genetic recombinants, provide transgressive segregants and create a broad genetic base

so that maximum number of potentially functional genes may be accumulated, reassembled

and expressed leading to isolation of stable and widely adapted genotypes.

References

BANSAL U K, SAINI R G and RANI N S 2000 Heterosis and combining ability for yield, itscomponents and quality traits in some scented rices (Oryza sativaL.). Tropical Agriculture(Trinidad) 77:180-187.

JULIANO B O 1971 A simplified assay for milled rice amylose.Cereal science today16: 334-340.

JULIANO B O, ONATE L U and DELMUDO A M 1965 Relation of starch composition,protein content and gelatinization temperature to cooking and eating qualities of milled rice.Food Technology 19:1006-1011.

KEMPTHORNE O 1957 An Introduction to Genetic Statistics. John Wiley and Sons inc.New York.

LITTLE R R HILDER G B and DAWSON E H 1958 Differential effect of dilute alkali on 25varieties of milled white rice Cereal chemistry 35:111-126.

MURTHY P S N and GOVINDASWAMI 1967. Inheritance of grain size and its correlationwith the hulling and cooking qualities. Oryza. 4:12-21.

PARAMASIVAN K S GIRIDHARAN A P SOUNDARRAJ M K and PARTHASARATHY P1996 Heterosis and combining ability for grain characters in rice. Madras Agricultural Journal83: 110-114.

SARATHE M L , SINGH S P and PERARAJU P 1986 Heterosis and combining ability forquality characters in rice. Indian Journal of Research in Agricultural Sciences 56: 749-753.

SHARMA R K and MANI S C 1997 Combining ability for cooking quality characters in

basmati rices. Crop Improvement 24: 93-96.SHRIVASTAVA M N and SESHU D V 1983 Combining ability for yield and associatedcharacters in rice. Crop Science 23:741-744.

SRIVASTAVA R B, SINGH H G and CHANDRA V S 1978 Genetic architecture of somequality traits in the F

2population of rice. Indian Journal of Agricultural Sciences 48 : 568-578.

SOOD B C, SIDDIQ E A and ZAMAN F U 1983. Genetic analysis of kernel elongation inrice. Indian Journal of Genetics 43: 40-43.

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Genetic Divergence Analysis in Grain Amaranth(Amaranthus hypochondriacusL.)*

H. V. KALPANDE 1, J. D. DESHMUKH2, I. A. MADRAP3and V. K.GITE4

Department of Agricultural Botany, Marathwada Agricultural University,

Parbhani 431402

ABSTRACT

On the basis of D2analysis, 61 genotypes of grain amaranth were grouped into ten clusters. Cluster

I accompanied highest number of genotypes (23) followed by cluster II with 17 genotypes, cluster III with

seven genotypes, cluster IV with six genotypes, cluster V and VI with two genotypes each whereas, clusters

VII, VIII, IX, and X were with solitary genotype. Inter cluster distance was maximum between clusters III and

X followed by clusters III and IV, Clusters II and VII. While, minimum inter cluster distance was observed

between clusters V and X.

Grain amaranth is a multipurpose crop with good potential for grain, vegetable and

fodder. The grains are rich in protein (15.6%) with high lysine and other essential amino

acids. Being an excellent source of iron and - carotene, it can help in removing iron and

vitamin A deficiency. Presence of high amount of folic acid helps in increasing the blood

haemoglobin level. Besides having high nutritional quality and high tolerance to arid conditions

and sub soils, there are also other attributes to be looked for its future cultivation prospects.

To breed adaptable cultivars for wide agro climatic zones, selection of suitable parents isimportant. The concept of D2statistic developed by Mahalanobis (1936) is useful in quantifying

the degree of divergence between the biological populations at genotypic level and to assess

the relative contribution of different components to the total divergence at both intra and inter

cluster levels. Such studies are very meagre in grain amaranth. Hence, the present study

was initiated to ascertain the magnitude of the genetic divergence using Mahalanobis

generalized divergence (D2) in grain amaranth (Amaranthus hypochondriacus L.).


The present investigation comprised 61 genotypes of grain amaranth (Amaranthus

hypochondriacus L.). The experiment was conducted at Department of Agricultural Botany,

Marathwada Agricultural University, Parbhani during kharif-2004 in randomized block designwith two replications. The spacing of 45 cm between rows and 15 cm within the plants was

* Part of M.Sc. (Ag.) Thesis submitted by the first author to Marathwada Agricultural University, Parbhani.

1. Assistant Professor

3. Professor

2 & 4. M.Sc. (Ag.) Students

J.Res. ANGRAU 35(3) 21 - 26 , 2007


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maintained. Observations were recorded on five randomly selected plants in each treatment

in each replication for the characters days to 50 percent flowering, days to maturity, plant

height (cm), number of spikelets / inflorescence, inflorescence length (cm), inflorescence

girth (cm), stem girth (cm), leaf area / plant (cm2), 50 ml volume seed weight (g), harvest

index (%) and grain yield/plant (g). The genetic diversity existed between genotypes with

respect to a set of eleven characters and was estimated using Mahalanobis D---2 Statistics

(Mahalanobis,1936). Treating D2as a generalized statistical distance, the criteria used by

Tocher (Rao,1952) was applied for determining the group constellation. After establishing

the clusters, intra and inter cluster distances were worked out.


The analysis of variance indicated significant variation among the 61 genotypes for

all the characters studied, suggesting adequate variability among them. The analysis of

dispersion for the mean values based on Wilks criterion revealed the existence of significant

differences among the genotypes for pooled effect of eleven characters studied (660 df, 2=

3783.05). The sixty one genotypes could be grouped in ten clusters depending upon the

genetic constitution (Table 1). Similary Kamble (2000) grouped 50 genotypes of grain amaranth

into 11 clusters, Shukla and Singh (2002) grouped 66 genotypes into 9 clusters and

Suryawanshi (2003) grouped 54 genotypes into 8 clusters. Cluster I was accommodated

with maximum number of 23 genotypes followed by cluster II with 17 genotypes, cluster III

with seven genotypes, cluster IV constituted six genotypes, cluster V and VI had two

genotypes each. However, clusters VII, VIII, IX and X were quite unique having

monogenotypic nature indicating their distinctness from other genotypes for most of the

characters. The genotypes selected showed greater diversity, due to factors like selection

under different environments, heterogeneity, genetic drift and history of selection, (Murthy

and Arunachalam, 1966). Hence, for hybridization, the selection of parents should be based

on genetic diversity besides per seperformance and geographical origin.

The intra cluster values varied from 0.00 to 115.19. The maximum intracluster

distance of 115.19 was noticed in cluster III. It was 80.20 in cluster I, 73.11 in cluster II and

50.28 in cluster IV. The genotypes belonging to these clusters can be considered as parents

for hybridization programme since genotypes within these clusters with a high degree ofdivergence would produce more desirable breeding material for achieving maximum genetic

advance with regard to per se. The maximum intracluster value exhibited by cluster V and VI

indicated that limited genetic diversity existed among the constituent genotypes. The rest of

the clusters had zero intracluster distance as they had only one genotype each. Similarly

Kamble (2000) and Suryawanshi (2003) reported intracluster D2 values ranging from 0.00 to

15.39 and 0.00 to 34.43 respectively.

KALPANDE et al.


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Table 1: Grouping of 61 genotypes of grain amaranthus into ten clusters

Cluster GenotypesNumber ofGenotypes

I 23 Mozri, IC-354545, IC-35410, Pedgaon local-6, MP-commercial-9, TN-55, IC-35391, IC-35419, LohgaonParbhani-, Khanapur-4, SKNA-7, SKNA-2, Pedgaonlocal-7, IC-41998, IC-35404, MGA-2, IC-35402, IC-35440, IC-35405, IC-35773, Jawala local-1, IC-35687,Pedgoan local-3.

II 17 Jawala local-6, IC-35446, IC-35414, IC-35501, Sawna-4, Khanapur-6, MP commercial-3, IC-35498, IC-32195,RMA-4, IC-35494, Pedgoan local-13, IC-35439, BGA-3, IC-35433, MP commercial-8, IC-35490.

III 7 Jawala local-2, Sindkhed raja, Jawala local-8, Suvarna,GA-1, IC-120588, RMA-2

IV 6 RGAS-92-10-1, IC-35377, IC-35428, Pedgaon local-1, MGA-1, IC-35449.

V 2 RMA-3, IC-35490

VI 2 IC-32696, IC-35713

VII 1 IC-95366

VIII 1 IC-35436

IX 1 IC-35450

X 1 Pedgaon local-6

The maximum inter cluster distance was observed between clusters III and X (432.37)

followed by clusters III and IV (382.28), clusters II and VII (380.95), clusters III and VII

(368.17), clusters III and VIII (338.87), clusters IV and V (335.70), clusters II and IX (329.08)

clusters I and III (306.13) indicating greater diversity among the genotypes included in those

clusters. Hence, the genotypes from these clusters could be selected for hybridizationprogramme as they are expected to produce highly heterotic crosses. Similarly, Kamble

(2000) reported maximum inter cluster distance between cluster VI and IX (121.48) followed

by cluster II and IX (107.53) and cluster V and VI (97.70). Suryawanshi also reported

maximum inter cluster distance between cluster III and VI (129.70) followed by IV and VI

(105.29), VI and VIII (102.28), II and III (93.21), VI and VIII (87.48).

GENETIC DIVERGENCE ANALYSIS


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GENTIC DIVERGENCE ANALYSIS


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The cluster means for the characters are presented in Table 3. The perusal of data

suggests that considerable differences existed for all the characters studied between the

clusters. Among the clusters, cluster V recorded the highest means for most of the characters

viz., plant height (166.50 cm), number of spikelets / inflorescence (59.00), inflorescence

length (55.17 cm) and stem girth (5.63 cm). The cluster III showed maximum values for

inflorescence girth (15.54 cm), 50 ml volume, seed weight (43.88 g) and grain yield / plant

(23.85 g). Cluster IX had highest mean for leaf area/ plant (1419.30 cm2). Further, it was

earliest in days to 50 percent flowering whereas, cluster VI was earliest in days to maturity

(93.00).

It can be concluded that all the characters studied contributed to the maximum

divergence indicating the utility of multivariate analysis in identifying useful parents with high

yield and other desirable characters.

References

KAMBLE A K 2000 Genetic divergence and path analysis in grain Amaranthus. M. Sc. (Ag.)Thesis submitted to Mahatma Phule Krishi Vidyapeeth, Rahuri.

MAHALANOBIS P C 1936 On the generalized distance in statistics. Proceeding in nationalacademy of sciences 12 : 49-55.

MURTHY B R and ARUNACHALAM V 1966 The nature of divergence in relation to breeding

systems in some crop plants. Indian Journal of Genetics. 26: 188-198.RAO C R 1952 Advanced Statistical Method in Biometrical Research John Wiley and sons,Inc., New York.

SHUKLA S and S P SINGH 2002 Genetic divergence in amaranth. Indian Journal of Genetics62: 336 337.

SURYAWANSHI N V 2003 Path analysis and genetic diversity in grain Amaranthus.M. Sc.(Ag.) Thesis submitted to Mahatma Phule Krishi Vidyapeeth, Rahuri.

KALPANDE et al.


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Heterosis for Grain Yield and its Components in Maize (Zea maysL.)*

C. APPUNU and E. SATYANARAYANA 2

Department of Genetics and Plant Breeding, College of Agriculture,Rajendranagar, Hyderabad

ABSTRACT

The ten parents of maize inbred were crossed in 10 10 diallel fashion (without reciprocals) and

raised in randomized block design to assess the extent of heterosis in 45 F-1- hybrids. The ten parents and

their 45 crosses were used to estimate the heterosis for 12 traits including grain yield. Based on heterosis and

per seperformance, the superior crosses were identified for each trait. Heterosis for yield was generallyaccompanied by heterosis for component traits. The cross P

1 P

3, which showed superior performance in

yield and yield components namely days to 50 per cent silking and total biomass emerged out as the best

combination among the 45 crosses evaluated.

Maize is mainly utilized for direct human consumption in developing countries and

for livestock feed in developed countries. However, in recent years its utilization for diversified

value-added product has made it an important crop. Increased production of maize will not

only contribute greatly towards increasing food production in the country but also provide raw

material for various maize based industries. Hence, there is a continuous need to evolve

new hybrids which should be superior to the existing hybrids. The magnitude of heterosis

provides information on the extent of genetic diversity of parents involved in a cross and

helps to choose the parents in developing superior F1s, so as to exploit hybrid vigour. The

present investigation was carried out to know the direction and magnitude of heterosis for

components of grain yield in maize.


Ten maize inbreds viz., P1, P

2, P

3, P

4, P

5, P

6, P

7, P

8, P

9and P

10were crossed in a

diallel fashion excluding reciprocals at Agricultural Research Station, Amberpet, Hyderbad

during kharif, 2001 and the resultant 45 hybrids along with the parents and checks were

raised in a randomized block design in three replications at College Farm, College of Agriculture,

Rajendranagar, Hyderabad during rabi, 2001-2002. Data were recorded on ten randomly

selected plants as explained previously (Appunu et al., 2006) and averages were used forstatistical analysis.Estimates of heterosis of F

1s over mid parent and better parent were

calculated by the methods of Turner (1953) and Liang et al.(1972).

J.Res. ANGRAU 35(3) 27-30 , 2007

*. Part of M.Sc. Thesis by the former author to Acharya N.G. Ranga Agricultural University, Rajendranagar,Hyderabad.

2. Professor, Agricultural research station (Maize), Amberpet, Hyderabad (A.P), India.


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The data on range of heterosis, number of superior crosses and their per se

performance are presented in Table 1. In the present study for grain yield per plot, heterosis

was significant in 23 and 14 crosses over mid parent and better parent, respectively. Cross

P1P

3exhibited highest magnitude of heterobeltiosis. For leaf area index and anthesis-

silking interval, the range of heterosis varied from 23.00 to 33.33 per cent and -66.00 to

133.3 per cent over mid parent and -38.39 to 28.47 per cent and -78.35 to 123.10 per cent

over better parent, respectively. The range of heterosis for plant height and ear height characters

varied from -22.25 to 14.47 per cent and -11.47 to 66.48 per cent over mid parent and -30.41

to 12.76 per cent and -20.40 to 55.57 per cent over better parent, respectively. Similar

results for grain yield, leaf area index, anthesis-silking interval, plant height and ear height

were also reported by Beck and Vasal (1990). These hybrids are worthy to follow up as they

are likely to yield desirable segregants in subsequent generations.

Significant negative heterosis for days to 50 per cent tasselling, days to 50 per cent

silking, days to 50 per cent maturity and effective kernel filling period characters ranged from

-13.05 to 14.98 per cent, - 4.42 to 19.00 per cent, -6.42 to 4.10 per cent and -18.52 to 11.29

per cent over mid parent and -17.91 to 10.18 per cent, -9.38 to 8.23 per cent, -10.63 to 1.23

per cent and -30.89 to 9.73 per cent over better parent, respectively. This indicates an added

advantage of developing early maturing maize with physiological efficiency. Out of 45 crosses,

17 and 36 crosses showed significant positive heterosis and heterobeltiosis for the character

tassel length, in which heterosis ranged from -11.16 to 16.75 per cent and -22.56 to 15.98 per

cent, respectively. For chlorophyll content significant positive heterosis and heterobeltiosis

were observed in 20 and 41 crosses respectively. The heterosis magnitude range varied

from -17.84 to 17.43 per cent over mid parent and -25.79 to 18.45 per cent over better parent,

which was in concurrence with the findings of Fleming and Palmer (1975) and Krebs et al.

(1996). The range of heterosis for total biomass character varied from -16.61 to 32.20 per

cent over mid parent and -21.15 to 31.72 per cent over better parent. A desirable degree of

vegetative growth is essential for realising high yield as total biomass production is one of

the components for deciding high grain yield in many crops. Similar results of heterosis for

total biomass were also reported earlier by Djisbar and Gardner (1989).From the foregoing discussion, it is suggested that yield is an important quantitative

trait and so there is no separate gene system for yield per seand the yield is an end product

of the multiplicative interactions between various yield components (Grafius, 1959). The

results of present investigation also revealed that the hybrid P1P

3which recorded high

heterosis for yield also expressed high heterosis for yield components viz., days to 50 per

APPUNU and NARAYANA


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HETEROSIS FOR GRAIN YIELD


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cent silking and total biomass indicating the additive or synergistic effect of the component

characters on seed yield. This can be considered to be the best cross combination among

the 45 crosses evaluated in the study and can be used for the development of hybrid maize

in future crop improvement programmes.

References

APPUNU C, SATYANARAYANA E and NAGESHWAR RAO T 2006 Genetic architecture ofgrain yield and physiological characters in maize (Zea mays L.). Research on crops7: 181-186.

BECK D and VASAL L 1990 Heterosis and combining ability of CIMMYTS tropical early andintermediate maize germplasm. Maydica 35: 279-285.

DJISBAR A and GARDNER F P 1989 Heterosis for embryo size and source and sinkcomponents of maize. Crop Science 29: 985-992.

FLEMING A A and PALMER J H 1975 Variation in chlorophyll content of maize lines andhybrids. Crop Science 15: 617-620.

GRAFIUS J E 1959 Heterosis in barley. Agronomy Journal 51: 551-554.

KREBS D, SYNKOVA H, AVRATOUSCUKOVA N, KOCOVA M and SESTEK Z 1996Chlorophyll fluorescence measurements for genetic analysis of maize cultivars.Photosynthetica32:595-606.

LIANG C H, REDDY C R and DAYTON A D 1972 Heterosis, inbreeding depression andheritability in a systematic series of grain sorghum genotypes. Crop Science 12:409-411.

TURNER J H 1953 A study of heterosis in upland cotton. Agronomy Journal 45:485-490.

APPUNU and NARAYANA


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J.Res. ANGRAU 35(3) 31-40 , 2007

Effect of Fly Ash and Farm Yard Manure on Soil Enzymatic Activities

in a Saturated Inceptisol under Incubated Conditions*

T. PRABHAKAR REDDY1, M.UMADEVI2, P. CHANDRASEKHAR RAO3 and

V.B. BHANUMURTHY4

Department of Soil Science and Agricultural Chemistry, College of Agriculture,

Rajendranagar, Hyderabad - 500 030

ABSTRACT

An incubation experiment was conducted for 60 days with one kg soil (fine loamy, mixed hyperthermicTypic Haplustept) at saturated moisture conditions. It was treated with 0, 5, 10 and 15 t fly ash ha -1soil with and

without FYM. Compared to the initial soil status all the enzyme activities viz., urease, dehydrogenase, acid and

alkaline phosphatase and cellulase increased by 7 DAI, which in general showed a decline thereafter. The

enzyme urease, dehydrogenase and cellulase were significantly influenced by fly ash, FYM and their interactions

at all the time intervals. The addition of fly ash @ 10 or 15 t ha -1along with FYM @ 10 t ha-1has recorded the

highest contents of urease (3.66, 2.80, 2.74 and 2.81 g NH4+released g-1soil d-1), dehydrogenase (5.66, 4.36,

3.73 and 3.41 mg of TPF produced g -1soil d-1) and cellulase (4.00, 2.70, 2.54 and 2.16 mg of glucose released

g-1 soil d-1) at 7, 15, 30 and 60 days after incubation, respectively. Acid and alkaline phosphate activities

decreased significantly with increase in levels of fly ash application. However, addition of FYM and their

interaction showed significant response on its activities.

Fly ash is a by-product of thermal power stations where electricity is produced by

firing finely powdered coal. In India, 12.21 million tons of fly ash is produced per year and for

storing 1 t fly ash 0.35 m2area is required. This huge quantity of fly ash produced is dumped

in ash disposal areas, which pose great threat to the environment. In an attempt to effectively

solve the disposal problem of this enormous solid industrial waste, some efforts have been

made to utilize it as an amendment to improve soil fertility and crop production.

The enzyme urease involves in the reactions related to breakdown of urea to CO2,

water and NH4

+. The enzyme dehydrogenase transfers electrons from one substance to

another and is involved in degradation of carbohydrates, liquids, etc. By involving water, the

enzyme phosphatase breaks humus-O-P-OH, bond to produce humus-OH and H3PO

4, which

helps to decompose humus, making P available to plants. The enzyme cellulase breaks

celluloses, which are long chain of sugar units. It is important in organic matter decay.* Part of M.Sc.(Ag.) Thesis submitted by the first author to Acharya N. G. Ranga Agricultural University,

Rajendranagar, Hyderabad.

1. Ph.D. Scholar

2. Associate Professor

3. Professor

4. Associate Director of Research, Regional Agricultural Research Station, Jagtial, Karimnagar District,Andhra Pradesh.


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The enzyme urease, phosphatase and cellulase are the extra cellular enzymes secreted by

soil microorganisms, whereas dehydrogenase enzyme is exposed in intact cell. Thus, the

amount and activities of these enzymes indicate essentially the biological activity of the

soil. Hence, an experiment was conducted to study the effect of integrated use of fly ash

and FYM on soil enzymatic activities (urease, dehydrogenase, acid and alkaline phosphotase

and cellulase) of an inceptisol under incubated conditions.


An incubation experiment was conducted with one kg soil at saturated moisture

conditions. It was treated with 0, 5, 10 and 15 t fly ash ha-1soil with and without FYM for 60

days. The fly ash was collected from National Thermal Power Corporation (NTPC),

Ramagundam, Andhra Pradesh. It contained the nutrients like N (27.5 mg/kg), P2O

5(29.6

mg/kg), K2O (110.5 mg/kg), S (25.4 mg/kg), Ca (7.25 mg/kg), Mg (2.20 mg/kg), Fe (17.50

mg/kg), Mn (3.34 mg/kg), Cu (0.98 mg/kg) and Zn (1.83 mg/kg). The texture of fly ash was

silty loam with pH 8.1 and EC 0.37 dS m -1. The experimental soil was sandy clay loam in

texture, slightly alkaline in reaction (pH 7.9), non-saline (EC 0.29 dS m -1), low available N

(210 kg/ha), available phosphorus (8.7 kg P2O

5/ha), medium in available potassium (180 kg

K2O/ha), low in available sulphur (8.3 mg/kg) and sufficient in micronutrient status (Fe 8.62

mg/kg, Mn 5.56 mg/kg, Cu 1.09 mg/kg and Zn 1.05 mg/kg). The samples were drawn

periodically on the 7th, 15th, 30thand expressed as 60thday after incubation (DAI) and were

analyzed for activities of enzymes urease, dehydrogenase, acid and alkaline phosphataseand cellulase. Statistical analysis of data was worked out by applying the technique of

analysis of variance for factorial technique in randomized block design.

Urease activity was assayed by quantifying the rate of release of NH4+from the

hydrolysis of urea as described by Tabatabai and Bremner (1972) with some modifications

as suggested by Sankara Rao (1989). Dehydrogenase activity was assayed by quantifying

the mg of TPF (2, 3, 5-triphenyl formazon) produced and expressed as g-1soil d-1as described

by Casida et al.(1964). The acid and alkaline phosphatase activity was assayed by quantifying

the amount of P-nitrophenol released and g of soil h -1as described by Tabatabai and Bremner

(1969). Cellulase activity as measured by monitoring the release of reducing sugar using

carboxymethyl cellulose as substrate following the procedure outlined by Poncholy and

Rice Elory (1973).

Results and discussion

Compared to the initial status (1.24 g of NH4+released/g soil/h) urease activity

increased by seven days after incubation which in general declined thereafter (Table 1). At

all the time intervals, either fly Ash @ 10 or 15 t ha-1 recorded higher activity which was on

REDDY et al.


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EFFECT OF FLY ASH


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EFFECT OF FLY ASH


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EFFECT OF FLY ASH


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REDDY et al.


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par to each other and was about 2 to 3 times higher when compared to the control. Among

the interactions, the highest activity was recorded in FA10

FYM10

(7 DAI) and FA15

FYM10

(15,

30 and 60 DAI) which was on par with each other. The treatments FA10

FYM0and FA

15FYM

0

were on par with each other and lowest was recorded by FA0FYM

0. At 60 DAI, the treatments

FA10

FYM0and FA

5FYM

0were on par with each other. Increase in urease activity due to

application of fly ash either in the presence or absence of FYM under incubation conditions

was reported by Lal et al. (1996a).

Compared to the initial status (2.98 mg of TPF produced/g soil/d) the dehydrogenase

activity increased by 7 DAI which in general showed decline thereafter. Similar to urease

activity, application of fly ash @ 10 or 15 t ha -1 recorded higher dehydrogenase enzyme

activities which were on par to each other. Among the interactions, the highest was recorded

in FA15

FYM10

which was on par with FA10

FYM10

. At all the time intervals, the treatments

FA10

FYM0and FA

15FYM

0were on par with each other and lowest activity was recorded by

FA0FYM

0(Table 2).

Fly ash levels did not significantly influence the acid and alkaline phosphatase activity.

However, FYM application and its interaction with fly ash (Tables 3 and 4) significantly

influenced it. Compared to the initial status acid and alkaline phosphatase activity was

highest at 7 DAI, which later declined. Application of FYM @ 10 t ha-1 recorded 69.7, 46.5,

64.3 and 91.4 percent increase in acid phosphatase activity compared to FYM application at

7, 15, 30 and 60 DAI, respectively. Similarly, the alkaline phosphatase activity was increased

nearly two times due to FYM application at all the time intervals. A reduced acid phosphatase

activity was observed due to application of fly ash as reported by Lal et al.(1996a).

The cellulase activity was significantly influenced by fly ash levels FYM and their

interactions. Compared to the initial status (1.02 mg of glucose released g -1soil d-1), the

cellulase activity increased by 7 DAI which in general showed a decline thereafter. Application

of fly ash @ 10 or 15 t ha-1along with FYM recorded higher cellulase activity at all the time

intervals which were on par with each other. Among the interactions, the highest activity was

recorded in FA10

FYM10

(7 DAI) and FA15

FYM10

(15, 30 and 60 DAI) which were on par with

each other. At all the time intervals, the treatments FA10

FYM0and FA

15FYM

0were on par

with each other and the lowest was recorded by FA 0 FYM0(Table 5).

The urease enzyme activity was found to be significantly and positively correlated

(0.94) with available N status. The dehydrogenase and cellulase activities were found to be

highly significant and positively correlated with all the treatments under study (N, P, K, S,

Fe, Mn and Zn) except Cu. The activity of acid and alkaline phosphatase were found to be

not significantly and positively correlated with phosphorus in soil (Table 6).

EFFECT OF FLY ASH


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References

CASIDA L E, KLEIN D A and SANTARO J 1964 Soil dehydrogenase activity. Soil Science98:371-376.

LAL J K, MISHRA B, SARKAR A K and LAL S 1996a Effect of fly ash on soil microbial andenzymatic activity. Journal of Indian Society of Soil Science 44:77-80.

PONCHOLY K and RICE L-ELORY 1973 Soil enzymes in relation to old field succession:Amylase, cellulase, invertase, dehydrogenase and urease. Soil Science Society of AmericanProceedings 37:47-49.

SANKARA RAO V 1989 Distribution of kinetics and some interactions of urease andphosphomonoesterase in soils. Ph. D. Thesis submitted to Andhra Pradesh AgriculturalUniversity, Hyderabad.

TABATABAI M A and BREMNER J M 1969 use of p-nitrophenyl phosphate for assay of soilphosphatase activity. Soil Biology and Biochemistry 1: 301-307.

TABATABAI MA and BREMNER J M 1972 Assay of urease activity in soils. Soil Biologyand Biochemistry 4: 479-489.

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Growth Estimation of Sunflower using Spline Regression Function

K.ALIVELU1, B.S .KULKARNI2and G.RAMAKRISHNA RAO3

Department of Statistics and Mathematics, College of Agriculture, RajendranagarHyderabad -500 030.

ABSTRACT

Log linear and linear trend models are frequently used for estimating the relative or absolute changes

in the dependent variable, over time. Measuring the decadal growth is a well known concept in agriculture for

studying the trend of the data. It assumes uniform growth rate in the respective decades. In the context of

agricultural data , this assumption may not be always valid. It may also lead to the estimates , which are

misleading. To overcome this situation , the applicability of piecewise regression approach is explored in the

context of measuring growth rate of sunflower yield. The approach involves identification of the points of

discontinuity, which leads to formation of sub periods of data. The time series data of 32 years from 1970-

71 to 2001-02 was divided into two optimum sub periods by applying the criteria of residual sum of squares and

R2by varying the k values, which represent the transitional period (year). The sunflower productivity exhibited

decreasing trend with annual growth of 4 per cent in the first period and 1 per cent in the second period. The

piecewise regression approach thus measured the growth in two different periods that represents the periods

of discontinuous growth, which is not possible in the conventional approach.

Estimating growth rate of time series data using linear or log linear equation is a

common practice. This assumes uniform growth rate throughout the period. In the context of

agricultural data such as area, production and productivity of crops recorded over the years,

this assumption is rarely satisfied. The agricultural data are frequently affected by changesover the years such as introduction of new varieties and its adoption by the farmers of the

region. These changes disturb the uniformity in the year-to-year variations of the data. The

temporal changes in growth behavior can be calculated using spline regression function.


Spline regression model is a piecewise regression model that accounts for the change in

trend resulting out of discontinuity in the year to year variations.

The model which accounts for straight lines with two different slopes after k thyear

and a jump from k to (k+1)th year can be described in semi log form as

Log Yt = a+1t1 +2(t-k-1)dt+3dtd

t=1 if t>k

=0 if t


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ALIVELU et al.

t1= t if tk

Where (1,

2) are respectively the slopes of first and second line. a is the intercept of the

first line and for the second line, it is : a+ 1k

+

1-

2k.

The optimum sub division of time period can be achieved by comparing RSS estimated by

changing the values of k. The one with smallest RSS is the optimum division of time period.

The growth rates during first and second time periods are

(dYt/dt)/Yt= 1 for t k+1

The compound growth rates are calculated by EXP(1)-1 and EXP(

2)-1 respectively

for first and second periods.

Fitting of spline regression models (piecewise regression models) is another

convenient approach for studying the temporal changes, which are not uniform. (Draper and

Smith,1988). (Draper and Smith (1988) explained the way of using piecewise regression

equation using dummy variables. Narayanareddy et al.(1998) compared different methods

for estimating agricultural growth.


The above model was applied to sunflower yield data of A.P over 32 years from

1970-71 to 2001-02, collected from oil seeds situation, A statistical compendium(Damodaram

T and Hegde D M, 2002) . The overall average yield was 547.45 kg/ha. The yields for the

years up to 1988-89 were mostly below this average and the yields for the following years

were all above average. The parameters of the model are estimated by ordinary least squares

method. The equation was fitted by changing k values around the transitional period and

residual sum of squares and R2values are given in Table 1. The optimum time period was

obtained based on RSS and R2values. The RSS is minimum when k=10.

The fitted model identified on the basis of piecewise regression equation is

Log Yt= 77.39 - 0.03594 t

1+ 0.01(t-k-1)d

t+ 0.1d

t

(153.6) (10.49) (3.81) (5.14)

R2A= 80.2%


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Table1: R2 and residual sum of Squares (RSS) values of fitted discontinuous piecewise

regression equation for sunflower time-series data on yield for different

transitional years (k).

K Actual transitional year RSS R2

10 1979-80 0.05849 0.802

11 1980-81 0.06532 0.769

12 1981-82 0.06609 0.754

13 1982-83 0.08074 0.722

14 1983-84 0.09286 0.679

15 1984-85 0.13043 0.649

16 1985-86 0.1320 0.662

17 1986-87 0.13569 0.629

18 1987-88 0.1563 0.525

19 1988-89 0.2642 0.504

20 1989-90 0.35841 0.499

21 1990-91 0.4656 0.481

22 1991-92 0.5533 0.387

23 1992-93 0.5788 0.360

24 1993-94 0.6842 0.259

25 1994-95 0.7534 0.194

26 1995-96 0.8527 0.120

27 1996-97 0.8688 0.104

28 1997-98 0.8726 0.101

29 1998-99 0.9133 0.071

30 1999-2000 0.9157 0.069

31 2000-01 0.9263 0.056

32 2001-02 0.9452 0.050

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The piecewise regression model clearly indicates that the growth of productivity

during the two periods was different. In the first period, it was a declining growth of 4 per

cent, while in the second period, the productivity increased annually with the rate of 1 per

cent.

It is evident from the above model that the conventional assumption of uniformity in

the year to year variations may not be always valid. The discontinuous growth can be

conveniently accounted in the Piece wise regression approach.

Piece wise regression helps in identifying the temporal changes in the growth

behavior. In formulating agricultural policies, growth rate is a close indicator.

References

DAMODARAM T and HEGDE D M 2002 Oil seeds situation: A Statistical Compendium.Directorate of oilseeds research, Hyderabad.

DRAPER N and SMITH H 1988 Applied Regression Analysis, Third edition , John Wiley andsons, New York.

JEROMI P D and RAMANADHAN 1993 World pepper market in India: An Analysis ofgrowth instability. Indian Journal of Agricultural Economics 48No.1. January - Marchpp. 88-97.

NARAYANA Reddy M, KATYAL J C, REDDY YV R and RAMANA RAO C A 1998 Estimating

agricultural growth A piecewise regression approach. Indian Journal of Agricultural economics53: 155-162.

ALIVELU et al.


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Enterpreneurial Behaviour of the Poultry Farmers

NARENDRA PAUL* and V.P.SHARMA**

Department of Extension Education,Rajasthan College of Agriculture, MPUAT, Udaipur - 313001 ( Rajasthan)

* Field Assistant, Division of Extension Education, Faculty of Agriculture, Shere-Kashmir University ofAgricultural Sciences and Technology of Jammu (SKUAST-J), Main campus, Jammu - 180009(J&K).

1. Professor and Head

Research NoteJ.Res. ANGRAU 35(3) 45 -51 , 2007

ABSTRACT

The values of entrepreneurial behavioral index for peripheral and distant poultry farmers were 45.20

and 41.96 respectively. The respondents had excellent degrees of regularity and dedication in their enterprises

followed by market orientations, technical background, time management and coordinating ability. Very lowlevels of goal setting ability, competitiveness, future orientation, challenge acceptance, tolerance to uncertainty/

failure and managerial ability was found among the respondents. It was observed that majority of the poultry

farmers had low level of entrepreneurial behaviour with respect to the major components studied.

Much of the success in poultry farming depends on the efficiency of use of various

management skills considering the vocation as a viable enterprise. Actually, enterprise is

not a new word to the Indian economy. Entrepreneurship promises better employment to the

youth of the country who currently constitute the bulk of the unemployed figures. The problem

of unemployment cannot be resolved unless the youth are particularly educated and trained

and involved in employment oriented vocations.

Entrepreneurship is the degree to which an entrepreneur strives to maximize hisprofits by making a creative and innovative response to the environment through diversification

of the enterprise. This as a cosmopolite variable means that the person possessing

entrepreneurial behaviour has some specialized characteristics. Basically, an entrepreneur

is an innovator who introduces something new in the economy. He is the person who is

capable of taking investment decisions, calculated risks under conditions of uncertainty,

can plan and innovate, take prompt and wise decisions in selection of a product or product

mix, technology mix and marketing.

All round development of poultry industry is not possible without the effective utilization

of human and material resources. While rapid technological progress has made the production

process more knowledge or capital intensive, many of the potential poultry-preneurs are

showing their backs by closing the doors to this beneficial enterprise due to the lack of

professional know-how, skill and kind of orientation required to work in a competitive


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environment Therefore, development of entrepreneurial skill in addition to the spread of

professional education in a growing economy like India assumes immense importance for

the present as well as future growth of enterprises in general and poultry in particular.

To be a successful entrepreneur, a person has to acquire certain entrepreneurial

qualities to modify his behavior in this direction. This paper aims to study the extent to which

poultry farmers possess these qualities so as to develop suitable entrepreneurship training

modules for them.


The present study was conducted in purposively selected Kathua district of Jammuand Kashmir. Kathua district consists of eight blocks, of which four blocks viz; Kathua,

amoti, Hiranagar and Ghagwal were selected based on maximum number of poultry farms

functioning in these blocks. A comprehensive list of all the registered poultry farms in each

selected block of the proposed district was prepared with the help of poultry extension

officers of the concerned blocks. For recording un-registered poultry farmers, the feed supply

agents, chick supplying agents and middlemen involved in it were personally contacted and

a separate list of un-registered farms was prepared. To avoid duplication, both the lists were

merged as one. After preparations of the lists, the poultry farmers in each block were

categorized into two groups viz.; peripheral poultry farmers i.e. within the radius of 10 km

distance from the block poultry demonstration center of department of animal husbandry,

Jammu and Kashmir Government and distant poultry farmers i.e. those situated at the distanceof more than the radius of 10 km from the poultry demonstration center of the concerned

block. Further, from the separate lists so prepared, 30 poultry peripheral farmers and 30

distant poultry farmers from each of the selected blocks were randomly chosen. Thus, the

study sample consisted of 120 peripheral and 120 distant poultry keepers i.e. a total of 240

respondents.

The data were collected through standardized schedule and responses so obtained

were coded accordingly. In order to measure entrepreneurial behaviour of the poultry farmers,

a suitable scale was developed consisting of 18 components of entrepreneurship. The overall

scale was quantified for the responses always, sometimes and never by 2, 1 and 0 scores

respectively. Entrepreneurial behaviour index was calculated using the formula:Obtained score for dimension of entrepreneurship

Maximum obtainable score


The respondents, were classified into three categories i.e., high, medium and low

levels of entrepreneurship on the basis of calculated mean and standard deviation of the

Entrepreneurial behaiour = X100 index (EBI)

PAUL and SHARMA


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entrepreneurial behaviour scores obtained by the respondents.

The results showed that 54.58 per cent of the respondents possessed low -level of

entrepreneurship and 28.75 per cent respondents had medium level of entrepreneurship.

However, the respondents who fell in the category of high level of entrepreneurship were only

16.67 per cent. which is quite discouraging.

A further perusal of data revealed that 53.33 per cent of the peripheral and 55.83 per

cent ) distant poulty farmers had low level of entrepreneurship while, 28.34 per cent peripheral

and 29.17 per cent distant poultry farmers had medium level of entrepreneurship. However,

only 22 (18.33 per cent ) peripheral and 15.00 per cent distant poultry farmers had high levelof entrepreneurship.

These findings are in agreement with those of Mohammed and Storck (2001) and

Kumaret.al. (2003) who found that majority of the respondents had low level of entrepreneurial

behaviour.

The calculated entrepreneurial behavior index (EBI) for each component of

entrepreneurial behavior is presented in Table 2. It is clear that the overall entrepreneurial

behavior of the poultry farmers was 43.58. The values of EBI for peripheral and distant

poultry farmers were 45.20 and 41.96 respectively.

The respondents had excellent degrees of regularity and dedication (EBI 90.00) in

their enterprises followed by market orientation (EBI 81.88), technical background (EBI 77.72),

time management (EBI 76.88) and coordinating ability (EBI 73.34). Achievement motivation

with EBI 67.92 had been a fair component constituting the entrepreneurial behaviour of

poultry farmers with successor components as planning orientation (EBI 56.67) and risk

taking ability (EBI 55.84). Besides, the components with low EBI were cosmopoliteness

(EBI 35.63), initiative taking (EBI 26.25). However, the respondents had very low levels of

goal setting ability (EBI 17.92), competitiveness (EBI 16.25), future orientation (EBI 14.80),

challenge acceptance (EBI 12.50), tolerance to uncertainty/failure (EBI 0.42) and managerial

ability (EBI 9.17).

The peripheral poultry farmers got second rank for market orientation (EBI 84.59).

Whereas, for the same component distant poultry farmers got third rank (EBI 79.17). Likewise,

technical background obtained third rank in case of peripheral (EBI 83.75) and fourth rank in

case of distant poultry farmers (EBI 71.67), coordinating ability got fourth rank for peripheral

(EBI 81.25) and sixth rank for distant (EBI 65.42) farmers. Time management secured fifth

position in case of peripheral (EBI 74.17) and second position in case of distant (EBI 79.59),

risk taking ability obtained sixth rank for peripheral (EBI 69.59) and eight rank for distant

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PAUL and SHARMA


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ENTREPRENERIAL BEHAVIOUR


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(EBI 42.08), achievement motivation got seventh rank for peripheral (MPS 65.42) and fifth

rank for distant (EBI 70.42), planning orientation obtained eighth rank for peripheral (EBI

53.75) and seventh rank for distant (EBI 59.59) farmers respectively. Cosmopoliteness was

assigned ninth rank by the peripheral distant (EBI45.83) and eleventh rank by the distant

(EBI 25.42), decision taking ability was assigned eleventh rank by the peripheral (EBI 29.58)

and twelth rank by distant (EBI 22.92), innovativeness got twelth rank in case of peripheral

(EBI 26.25) and ninth rank in case of distant (EBI 34.58) poultry farmers respectively. Similarly,

challenge acceptance obtained thirteenth position in case of peripheral (EBI 15.42) and

seventeenth position in case of distant (EBI 9.58), goal setting got fourteenth position for

peripheral (EBI 13.75) and thirteenth position for distant (EBI 22.08), cosmopolite got fifteenthrank for peripheral (EBI 12.08) and fourteenth rank for distant (EBI 20.41), future orientation

obtained sixteenth rank in peripheral (EBI 11.25) and fifteenth rank in distant (EBI 18.34),

management ability secured seventeenth position in case of peripheral (EBI 10.83) and

eighteenth position in case of distant (EBI 7.50) and tolerance to uncertainty / failure

obtained eighteenth rank for peripheral (EBI 8.75) and fifteenth rank for distant poultry farmers

(EBI 12.08). It can be observed that majority of the poultry farmers had low level of

entrepreneurial behaviour with respect to the major components deemed important.

These findings are in concordance with those of Prajapati and Patel (2000), Kumar

et al. (2003) and De (2003) who revealed that the respondents had fairly well to low levels of

entrepreneurial behaviour with regard to its various listed components. However, the findingsare in contrast to those of Patel and Patel (2000) who reported that majority of the respondents

possessed medium level of managerial ability.

References

KUMAR M, PATHAK C and SINGH A K 2003 Information sources of rural poor; A studyin U.S.Nagar district of Uttaranchal. IASSl Quarterly Journal XIX 3: 123-133.

MOHAMMED H and STORCK H 2001 Managerial behaviour of farmers as a factor influencingfarm performance in Ethiopia: The case of small holders in Eastern Hararghe. RajasthanJournal of Extension Education VIII & IX:1-9.

PRAJAPATI M R and PATEL R J 1999-2000. Entrepreneurial behaviour of potato growers.

Gujarat Journal of Extension Education Vol.X & XI :10-12.PATEL A A and PATEL R K 1999-2000. Growers managerial ability for plant protectionmeasures in chilli crop. Gujarat Journal of Extension. Education Vol. X&XI:1-4.

RAO M S and DE DEEPAK 2003 Entrepreneurial behaviour of vegetable growers. Journalof Research ANGRAU 31: 101-104.

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the four selected districts out of which only 150 respondents which form 69 per cent were

obtained.

Personal stressors were operationalised as those sources of stress that are related

to the ways in which the agricultural officers experience the world including their personality

structures, life experience, self concept, state of physical health and other issues that relate

to them.

Organizational stressors were operationalised as those sources of stress that relate

to the agricultural officers experiences in the world of work and career including his/her

feelings and experiences in job.

Job stressors were operationalised as the interaction of the agricultural officer with

job related factors which disrupt or enhance his or her psychological and physiological condition.

A number of stress items reflecting above said stressors were collected based on

the literature and discussion with experts and accordingly 72 items as personal stressors,

30 items as organizational stressors and 27 items as job stressors were identified. Quotients

were developed for the selected three stressors so as to estimate the stress of the

respondents. Then, the respondents were categorized into three groups namely low, moderate

and high based on mean and S.D. The data collected were subjected to statistical tests like

frequency, percentages, correlation and multiple linear regression and were used for analysis

and presentation of data.


The responses that were obtained were analysed for measuring the stress of

agricultural officers and shown in Table 1.

Table 1 : Distribution of agricultural officers according to their stressors

n= 150A) Personal stressors

S.No. Category Frequency Percentage

1. Low 24 16.00

2. Moderate 105 70.00

3. High 21 14.00

Total 150 100.00

Mean = 9.62 S.D. = 1.82

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It could be observed from Table 1 that about 70.00 per cent of the officers experienced

moderate level of personal stress. On the other hand, few officers (16.00%) had experienced

low level and only 14.00 per cent of the officers experienced high level of personal stress. It

could be inferred that a great majority of the agricultural officers had moderate to low level of

personal stress. The moderate level of personal stress indicates that in Indian context, the

average individual experiences an average of ten common stressful events in life time viz.,

family member unemployed, construction of house, death of close family member, financial

loss or problems, property damaged etc. The low level of personal stress might be due t

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