PhD

The study on “Risk behaviour of vegetable farmers in Special Agricultural
Zones in Kerala: An empirical analysis” was conducted during 2018 to 2021 with
the objectives to identify the crop dominance in vegetables, analyse the perception
on different risk sources, develop a risk attitude scale and risk propensity index of
the vegetable farmers. The study also delineated the factors influencing the
farmer’s attitude towards the risks in vegetable farming and profiled farmer’s
strategies at combating the risks associated with vegetable farming.
Blocks of Devikulam in Idukki district, Kanjikuzhy in Alappuzha district,
Pazhayannur in Thrissur district and Chittoor- Kollengode in Palakkad district,
identified as SAZ for vegetables were selected as the location for study. A total of
270 vegetable farmers selected randomly from six panchayats representing
different AEUs in the blocks were the respondents of the study. Thirty extension
personnel from the SAZs were also included in the study.
The numerical, economic and total mean dominance of crops were worked
out for each SAZs. The results revealed that cowpea was found to be the most
dominant crops in the SAZ Kollengode with a total mean value of 3.20 and in
Pazhayannur (2.97). The most dominant crop in SAZ Chitoor was found to be
tomato (3.40). Bhindi (4.49) and beans (4.12) were found to be the most dominant
vegetable crops in SAZ Kanjikuzhy and Devikulam respectively.
Vegetable crop biodiversity profile of SAZs was calculated using ShannonWeiner diversity index and the highest total mean diversity index for vegetables
was found in Kollengode panchayat (1.118) followed by Kanjikuzhy (1.108).
Least diversity for vegetables was found in Chelakkara panchayat of SAZ
Pazhayannur (0.740). Analysis of Variance (ANOVA) followed by LSD test was
performed to identify the variations in diversity between panchayats and it was
found that the diversity of vegetables grown in Kollengode, Kanjikuzhy,
Devikulam and Vattavada panchayats were high and on par compared to the

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vegetable diversity in Vadakarapathy and Chelakkara panchayats that were low
and on par.
Risk perceptions play a key role in the production and investment
behaviour of farmers. Mean scores and ranks based on farmer’s perception on
each source of risk under each risk category was found out. Results revealed that
risk due to pest and diseases had emerged as major production risk in Kollengode
(4.87), Vadakarapathy (4.64) and Kanjikuzhy (4.18) panchayats. Whereas,
climatic variations (4.33) and fragmented land holding (4.49) emerged as major
production risk in Vattavada and in Devikulam panchayats. In case of market
risks, high cost of production was perceived as major market risks in Kollengode
(4.04) and surplus production in Chelakkara (4.64) and Devikulam (4.31)
panchayats. With respect to financial risks, complicated banking procedures
emerged as major risk in five panchayats except in Vattavada panchayat where
high demand of collaterals by banks (3.82) was the highest ranked risk. Import of
produce from other states was perceived as the major institutional risk in
Kollengode (4.47), Chelakkara (4.64) and Kanjikuzhy (4.62) panchayats whereas
lack of government support (4.58) and lack of vegetable-oriented schemes (4.80)
had emerged as highest ranked institutional risk sources in Devikulam and
Vattavada panchayat. Labour shortage and migration was the highest ranked
human risk source in Kollengode (4.33) Chelakkara (4.40), Vadakarapathy (3.76),
Kanjikuzhy (4.07) panchayats whereas in Vattavada (3.58) and Devikulam (3.07)
panchayats, farm accidents were perceived as major human risks. Paired wise
comparison of risk sources revealed that in Kollengode, Chelakkara and
Devikulam panchayats, production risks ranked first among all major categories
of risks. In Vadakarapathy, Kanjikuzhy and Vattavada panchayats, price or market
risk was the top ranked risk.
An exploration into the severity of all the risk sources as perceived by
farmers was done using the Pareto analysis. The results revealed that eighty per
cent of the risk in vegetable farming was accounted by risk sources viz. crop
damage by wild animals, surplus production of same crop, complicated banking

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procedures, climatic variations, lack of vegetable oriented schemes, price
fluctuation, high cost of production, lack of government support, import of
produce from other states, labour shortage, high interest rate, poor soil quality,
fragmented land holdings, water scarcity, poor extension to farmer linkage and
incidences of pest and diseases.
Distribution of respondents based on their risk propensity index values
was done using mean and standard deviation and it was found that majority
belonged to risk neutral category (69.63%) followed by risk takers category
(18.15%) and risk averse category (12.22%). In order to know the distribution of
respondents in each panchayat according to risk propensity, Skewness and
Kurtosis was estimated and it was found that Kollengode had more risk takers. To
understand the dispersion of risk neutral category, a scatter plot diagram was
generated and the results revealed that risk takers were more in Kollengode and
Kanjikuzhy whereas risk averse were more from Vadakarapathy, Chelakkara,
Vattavada and Devikulam panchayats.
Risk attitude scale was developed using the Likert’s Summated Rating
method wherein 28 statements were selected from 95 statements using item
discriminant analysis with ‘t’ value above 2.1 at 0.01 level of significance and
with a high reliability coefficient of 0.95. On administering the scale on 270
vegetable farmers revealed that majority of the vegetable farmers (74.07%)
belonged to moderately favourable category of risk attitude followed by farmers
in the favourable risk attitude category (16.67%). Whereas farmers in the
unfavourable category were 9.26 per cent. ‘P’ value was found to be less than
0.05 when administered with Kruskal–Wallis One Way Analysis of Variance
which signified that there was significant difference between risk attitudes of
farmers in more than one pair of panchayats.
Thirteen personal and social characteristics of farmers were selected as
independent variables of study. More than half (55.18%) of the farmers were
found in the age group of 35-55 years, 46.30 per cent had gone up to middle
school, 78.88 per cent of the farmers had an area up to 2.5acres, 37.03 per cent

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respondents were engaged in vegetable farming and allied works and 53.33 per
cent had economic water scarcity. With respect to all other variables, majority
farmers were found in the medium category of respective variables. Hence to find
the dispersion among respondents, mean value was used as the check value and it
was found that majority of the respondents were in the low category viz. below
mean in the case of vegetable farming experience (61.48%), annual income
(55.56%), innovation proneness (56.67%), economic motivation (56.3%),
extension participation (70%), social participation (94.44%), management
orientation (58.89%) and high category with regard to credit orientation (53.7%).
Result of correlation analysis between risk attitude and thirteen
independent variables revealed that seven of the variables viz., area under
vegetable cultivation, education, annual income, irrigation potential, extension
participation, innovative proneness, economic motivation had positive and
significant correlation with risk attitude of respondents at 1per cent level and
variables management orientation and social participation at 5 per cent level.
Stepwise multiple regression analysis was carried out to identify the most
important variables that affect the risk attitude of vegetable farmers and it was
found that four independent variables viz. innovation proneness, irrigation
potential, vocational diversification and area under vegetable cultivation
significantly predicted risk attitude (R2= 0.579) of vegetable farmers. Principal
Component Analysis was done to identify the commonalities among the factors
influencing the risk attitude and cluster them. Six principal components were
selected having eigen value greater than one. PC1 named as personal socioeconomic variable explained for 44.39 percentage of variance.
The risk management strategies adopted by vegetable farmers in the
decreasing order of importance were mixed farming (4.82), crop diversification
(4.03), investing in non-farm business (3.42), irrigation measures (3.40),
decreasing area under vegetable crops (3.28) and producing at lowest possible
cost (3.04).

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On doing the perceived social benefit cost analysis of dominant crops it
was found that beans (2.08) had the highest BC ratio followed by okra (1.79).
Perceived social benefits of vegetable farming was assessed using the PEST
(Political, Economic, Social and Technological) analysis tool and it was found
that farmers perceived economic benefits (16.54) above social benefits (14.95)
and technological benefits (13.61).
The top ranked constraints were inefficient pest and disease management
(57.4%), non-remunerative prices of produce (51.58%), poor marketing facilities
(50%), non-availability of labour during peak season and high wages (44.81%),
poor support from government agencies (43.7%).
Ensuring availability of vegetable subsidies (44.4%), timely availability
of inputs (37.78%), availability of quality planting materials (35.55%), timely
payment of money by government agencies such as Horticorp (35.18%), irrigation
facilities and creating awareness on improved irrigation methods for vegetable
cultivation (32.59%) were the major solutions as perceived by farmers for
remunerative and sustainable vegetable production.
To conclude, ascertaining the attitude of farmers towards risks is
important in understanding the risk behaviour of farmers. Therefore, in this
study, risk attitude scale was developed and administered to the vegetable farmers
which revealed that majority of the vegetable farmers belonged to moderately
favourable category of risk attitude. The perception of farmers on major risk
sources in vegetables and their propensity to take risk were identified which
revealed that majority of the farmers were found in risk neutral category.
Dominance-diversity profile of vegetable crops in SAZs was identified. Farmer’s
strategies to cope with risk and the constraints and solutions for remunerative and
sustainable vegetable production were delineated.