PhD Thesis
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Item Identification of superior genotypes for yield and quality in red gram[Cajanas cajan (L.)Millsp.] suitable for Kerala(Department of Genetics and Plant Breeding, College of Agriculture, Vellayani, 2026-01-05) Shirsat Mahesh Santosh; Beena ThomasRed gram [Cajanus cajan (L.) Millsp.], commonly known as pigeonpea, is an important tropical and subtropical legume valued for its edible seeds. It serves as both a green vegetable and a split pulse (‘dhal’), being a rich source of protein, carbohydrates, vitamins, minerals, and essential amino acids such as lysine, methionine, and tryptophan. In combination with cereals, pigeonpea provides a nutritionally balanced diet and contributes to food security and sustainable smallholder farming systems. India is the largest producer of pigeonpea. It ranks second among pulses after chickpea, with major cultivation in Maharashtra, Karnataka, Madhya Pradesh, Uttar Pradesh, and Gujarat. In Kerala, however, despite being an integral part of the diet, commercial cultivation of pigeonpea is meagre. Therefore, the present research entitled “Identification of superior genotypes for yield and quality in red gram [Cajanus cajan (L.) Millsp.] suitable for Kerala” was undertaken in the Department of Genetics and Plant Breeding, College of Agriculture, Vellayani, during 2021-2025. In the first experiment, thirty genotypes originating from ICRISAT (Hyderabad), TNAU (Coimbatore), and IARI (New Delhi) were collected and evaluated in the field to study variability parameters and genetic divergence (D2). Analysis of variance revealed highly significant differences among genotypes for all 16 traits studied, indicating substantial genetic variability. The genotypic and phenotypic coefficients of variation (GCV and PCV) exhibited high values for traits such as the number of primary branches per plant, number of pods per plant, seed yield per plant, biological yield, and the content of total phenol, tannin, and methionine, indicating a strong potential for improvement through selection. High heritability coupled with high genetic advance as a percentage of the mean was observed for most traits, indicating the predominance of additive gene action, making direct selection effective. Correlation analysis revealed that seed yield per plant was positively and significantly associated with number of pods per plant, biological yield, harvest index, primary branches, and seeds per pod, while phenol content showed a significant negative correlation. Path analysis indicated that biological yield, flowering traits, and harvest index exerted strong positive direct effects on seed yield, whereas days to bud initiation and plant height contributed negatively. All thirty genotypes were assembled into six clusters using D² analysis. Cluster III had the highest number of genotypes (9), followed by cluster IV (5 genotypes), and clusters I, II, V, and VI each had one genotype. The highest intra-cluster distance was recorded in cluster IV and the lowest in cluster II, whereas the highest inter-cluster distance was observed between clusters I and VI, followed by clusters IV and V. Molecular diversity analysis among the 30 genotypes was conducted using 30 Simple Sequence Repeat (SSR) markers. Of these, 14 were polymorphic, 9 were monomorphic, and 7 markers failed to amplify. The Polymorphic Information Content (PIC) values of polymorphic SSR markers ranged from 0.12 (ASSR 363) to 0.50 (ASSR 281). The lowest Jaccard’s similarity coefficient was observed between genotypes ICPL 300 and ICPL 22081 (0.167). UPGMA cluster analysis grouped all 30 pigeonpea genotypes into six clusters, with Cluster I being the largest (12 genotypes), followed by Cluster III (11 genotypes), Cluster V (3 genotypes), Cluster IV (2 genotypes), and Clusters II and VI with one genotype each. Principal Coordinate Analysis (PCoA) confirmed the presence of considerable genetic diversity among the 30 red gram genotypes. Ten superior genotypes, viz., ICPL 11259, ICPL 11300, ICPL 11318, ICPL 11326, ICPL 20327, ICPL 22045, ICPL 22084, ICPL 22081, APK 1, and Pusa Arhar 16, were selected based on seed quality attributes and seed yield per plant. Phenological evaluation of these genotypes was conducted in the field for three seasons (Rabi, Summer, and Kharif). Seasonal evaluation revealed that seed yield per plant was highest during Kharif, though with high variability, whereas Rabi showed relatively stable but lower yields, and Summer provided balanced performance with moderate yield consistency. Among the ten genotypes, APK 1 and Pusa Arhar 16 consistently recorded high seed yield across all three seasons along with good quality traits and are suitable for cultivation in Kerala. Genotypes grouped in different clusters with maximum inter-cluster distances indicate high genetic diversity, which can be exploited in future breeding programmes to manifest heterosis and develop superior hybrids. Genotypes with high molecular diversity can serve as parental lines for making crosses with a broad genetic base, thereby enhancing the scope of genetic improvement.Item Structural and functional dynamics of NICRA villages in Kerala and Karnataka:stakeholder analysis(Department of Agricultural Extension,College of Agriculture,Vellayani, 2025-07-16) Manju Prem,S; Jayalekshmi,GThe present research, titled "Structural and Functional Dynamics of NICRA Villages in Kerala and Karnataka: Stakeholder Analysis," explores how socio economic characteristics, agro-ecological conditions, and stakeholder roles contribute to climate resilience in agriculture. The study was conducted across four NICRA villages, representing distinct climatic challenges: two drought-affected villages in Karnataka (Hanumaigarahalli in Chikkaballapur and Durgadanagenahalli in Tumkur), one drought-affected village (Pattithara in Palakkad), and one flood-affected village (Edathua in Alappuzha) in Kerala. A total of 300 respondents participated, including 160 farmers, 40 KVK (Krishi Vigyan Kendra) officials, and 100 other stakeholders, including researchers, line department officials, local government representatives, and NGOs. The study employed a mixed-method approach, combining quantitative and qualitative tools to collect and analyse data on stakeholders' perceptions of climate change, vulnerability, capacity needs, and training preferences. The dependent variable of the study is the perception of capacity needs under NICRA. Perception scales were developed and validated for both farmers and KVK officials to assess their capacity needs under the NICRA program. Thirteen independent variables for farmers and six for KVK officials were selected. Statistical tools used included frequency and percentage analysis, mean, standard deviation, Z-test, one way ANOVA, correlation analysis and multiple regression analysis. The majority of farmers (45%) perceived their capacity needs as upper medium, followed by 23.75 per cent perceiving them as lower medium, and 16.25 per cent as low. KVK officials, on the other hand, predominantly perceived their capacity needs as lower medium (57.5%), with only a small proportion perceiving them as high (12.5%). These scales were correlated with objective measures such as operational landholding and service experience, further validating the perception results. Key findings revealed that farmers, especially smallholders, were identified as the most important stakeholders in the NICRA project, followed by women farmers and KVK officials. Local self-government bodies, such as Panchayats and Gram Sabhas, also played a critical role, while NGOs and community-based organizations (CBOs) were found to be less influential in project execution. This shows there is a need to prioritize engagement with the most important stakeholders for effective implementation of climate resilience initiatives. The study also examined the socio-economic characteristics of the farmer respondents. The majority (81.25%) of respondents were male, with education levels ranging from illiterate to high school, and most managed marginal to small landholdings. The majority of respondents were relatively inexperienced in farming, with a significant portion of farmers falling into the novice or advanced beginner categories. Income levels were predominantly low to middle, indicating significant economic challenges. The frequency of contact with extension agencies, especially KVK, was found to be high, and participation in capacity-building activities varied, with crop management and integrated farming systems being the most popular topics. Farmers' preferences and adoption of climate-resilient practices were also examined. High Yielding Varieties, Soil Conservation, and Custom Hiring Centres were the most preferred practices, with High Yielding Varieties ranking highest in adoption. Farmers reported significant benefits from these practices, including increased income, reduced climate risks, and enhanced crop production. However, farmers emphasized the need for continued government support, lower initial investment costs, and sustained assistance from the NICRA project to enhance the uptake of these practices. The study found that farmers in both Kerala and Karnataka perceived significant climate changes, particularly rising temperatures. In Kerala, 93.75 per cent of farmers and in Karnataka, 90 per cent of farmers noted an increase in temperature. Precipitation patterns also varied significantly between the two states, with 45 per cent of farmers in Kerala observing a decrease in rainfall and 93.75 per cent of farmers in Karnataka reporting reduced rainfall, indicating more severe drought conditions in the latter state. Both states reported concerns about delayed monsoon onset, with 98.75 per cent of Karnataka farmers and 56.25 per cent of Kerala farmers noting this shift, which disrupts planting schedules. Also, a significant reduction in the frequency and intensity of rainfall was reported across both regions, emphasizing the growing climate challenges farmers are facing. The study also examined the farming practices most vulnerable to climate stresses. In Kerala, crop production was found to be the most vulnerable due to dependence on monsoon rains, followed by pisciculture and horticulture, which are affected by water scarcity and temperature fluctuations. In Karnataka, horticulture was identified as the most vulnerable practice, followed by pisciculture and crop production. Poultry and livestock farming showed moderate vulnerability, while floriculture and beekeeping were less impacted by climate stress. These findings highlight the need for targeted interventions in these sectors to reduce vulnerability. Farmers' preferences regarding NICRA training were also analysed. The most preferred training agency was KVK, followed by universities and private seed/fertilizer companies. Demonstration was the preferred training method, emphasizing the importance of practical, hands-on learning. Farmers preferred training durations of 3-6 days, ideally conducted before the cropping season to ensure preparedness. Monthly training was also favoured, with pest and disease management being the top priority for both knowledge and skill development. The study also highlighted the strengths and gaps in the capacity development of farmers. Teamwork, norms, and network building were identified as strong social capacities, while gaps were observed in group process skills, shared vision, and strategic planning. Among individual capacities, leadership and entrepreneurship showed promise, but weaknesses were evident in technology adoption and financial literacy. Targeted training in these areas is needed to equip farmers to navigate challenges and adopt climate-resilient agricultural practices effectively. Key constraints faced by farmers in relation to NICRA training were also identified. The most significant constraint was the inadequate assessment of training needs, which led to a mismatch between training content and farmers' practical requirements. Other constraints included lack of storage facilities for perishable produce, absence of follow-up actions for clarification, and lack of participatory planning. Addressing these gaps in training delivery and logistical support could significantly enhance the effectiveness of the NICRA program. The study further examined the profiles of KVK officials, revealing diverse characteristics in terms of age, education, and service experience. Most officials had postgraduate or PhD qualifications, with a mix of experienced and novice respondents. NICRA-specific experience was limited, with most officials being novices or moderately experienced in the program. Training participation was varied, with some officials having attended advanced or intensive training. These findings emphasize the need for further capacity-building efforts to strengthen the expertise of officials, especially in NICRA-specific activities. The study's relational analysis revealed that service experience and NICRA-specific experience significantly influenced officials' perceptions of the program. Age, education, and training participation showed weaker correlations. These findings underlines the importance of experience in shaping officials' perceptions and highlight the potential for targeted training to improve the implementation of the NICRA program. A framework named “NICRA Capacity Development and Implementation Framework” (NCDIF) was developed for the study, designed to enhance climate resilience among stakeholders. Phase 1 involves needs assessment, stakeholder analysis, baseline data collection, and resource mapping. Phase 2 focuses on capacity building through customized training programs, workshops on financial literacy, and access to resilient crop varieties. Phase 3 emphasizes implementation, improving resource accessibility, networking, and forming farmer cooperatives. Phase 4 includes monitoring, evaluation, and feedback to assess success and adjust strategies. The framework covers short-term (0-6 months), medium-term (6-12 months), and long-term (18-36 months) goals. To address constraints in the NICRA program, strategies for farmers include participatory training needs assessments, cold storage units, structured follow-ups, participatory planning, crop insurance awareness, pre-training surveys, monitoring frameworks, vocational training, improved credit access, and gender-sensitive programs for women. For officials, strategies focus on mechanization subsidies, participatory planning, enhanced communication skills, transparent trainee selection, timely input availability, and hands-on training. Also, real-time service monitoring and performance-based incentives for extension staff are recommended. These strategies aim to enhance farmer engagement, training relevance, and program delivery. This research emphasizes the vital role of stakeholders in boosting climate resilience in agriculture. The findings stress the importance of a targeted, inclusive approach to engaging farmers, KVK officials, and other stakeholders in capacity building initiatives. Addressing constraints, refining training assessments, and enhancing both individual and social capacities are essential for the success of climate resilient agricultural practices within the NICRA program. By focusing on these areas, stakeholders can collaborate to mitigate climate change impacts and strengthen the resilience of farming communities in Kerala and Karnataka.Item Bioecology of major coccinellid predators of Kerala(Department of agricultural entomology, college of agriculture , Vellayani, 2023-07-07) Anusree, S S; Anitha, NAn investigation on “Bioecology of major coccinellid predators of Kerala” was carried out at Department of Entomology, College of Agriculture, Vellayani during 2017-2022 with the objective to identify major coccinellid predators of pests infesting agricultural crops from agro ecological zones of Kerala and to study biology and predatory potential of select coccinellids. In the present investigation, 40 species of predatory coccinellids belonging to 23 genera under 6 tribes in the Subfamily Coccinellinae were illustrated. Taxonomic study on tribes Aspidimerini and Chilocorini resulted in the identification of three species in each tribe. Examination on specimens of tribe Coccidulini resulted in identifying 16 species within five genera. 11 species belonging to nine genera were illustrated under tribe Coccinellini. A single species was illustrated and studied under tribe Hyperaspidini. The specimens studied under tribe Sticholotidini belonged to six species within four genera. Among the 40 illustrated species, 28 species were identified, while identity of 12 species are to be confirmed, of which three are putative new species. Phrynocaria perfida Poorani collected and illustrated during this investigation were confirmed and described as a new species (Poorani et al., 2021). Chilocorus sp.1 and Scymnus (Pullus) sp.4 are the other two putative new species. Phrynocaria perrotetti (Mulsant), Cryptogonus orbiculus (Gyllenhal) and Sticholotis ferruginea (Gorham) are new records from Kerala.Item Performance effectiveness of biodiversity management at gramapanchayats in Kerala(Department of Agricultural Extension Education, College of Agriculture , Vellayani, 2024-03-11) Rehma, A Victor.; 1. Anil Kumar, AThe study entitled ‘Performance effectiveness of biodiversity management at Grama Panchayats in Kerala’ was conducted from 2019 to 2023. The primary objectives were to study the performance effectiveness of Biodiversity Management Committee (BMC) at Grama Panchayat level in Kerala, Socio- political dynamics in biodiversity management and perception of BMC members and other stakeholders on depletion of natural resources. Constraints experienced by the BMCs in implementing biodiversity conservation were also studied. Historical documentation of environmental movements for biodiversity conservation in Kerala was also undertaken. Based on the biodiversity richness and ecological sensitivity four blocks each were selected purposively from low lands of Kannur and Alappuzha districts, mid lands of Kollam and Malappuram districts and high ranges of Wayanad and Idukki districts of Kerala. Thus, a total number of 12 blocks were identified for the study. From each block 5 Panchayats were selected randomly. Therefore, a total number of 60 Panchayats were selected for the study. BMC members and other stakeholders comprised the respondent categories. From each Panchayat selected, 3 BMC members each were identified randomly. Hence, 15 BMC members were selected from each block. Thus 60 BMC members each were selected from low lands, mid lands and high ranges. Therefore, a total of 180 BMC members were selected from the 6 districts for the study purpose. In the other stakeholder respondent category, a minimum of 5 each were ensured from the traders, social activists, general public, farmers and officials of departments concerned with biodiversity. Twenty-five other stakeholders from the above categories were selected from each block. Thus 100 stakeholders each were selected from low lands, mid lands and high ranges. Therefore, a total of 300 other stakeholders were selected from the 6 districts for the study purpose. Thus, a total of 480 respondents comprising of BMC members and other stakeholders were selected for the study. The relationship between twelve independent variables with performance effectiveness of BMC Members was worked out and it was found that ten out of twelve independent variables were positively and significantly correlated. The variables that had positive and significant correlation were gender (0.312), education (0.278), environmental concern (0.388), self-confidence (0.343), leadership (0.210), perception of workload (0.225), decision making ability (0.351), political orientation (0.236), participation efficiency (0.518) and environmental awareness (0.271) at 1 per cent level of significance. Education (0.312), environmental concern (0.369), self-confidence (0.196), leadership (0.296), decision making ability (0.327), political orientation (0.200), participation efficiency (0.263) and environmental awareness (0.231) of BMC members had positive and significant correlation (1%) with their perception of depletion of natural resources. The major constraints experienced by the BMCs in implementing biodiversity conservation were lack of interest of members in BMC activities, PBR preparation was considered as one time task by many BMCs who do not take efforts to update the information, public are not aware of activities of BMC, PBR preparation its timely updation and development of an electronic database of PBR is an enormous task, BMC members them self were not aware of the activities to be carried out by BMC, training programmes was not properly designed for elected representatives and officials of local governments. The environmental movements for biodiversity conservation in Kerala were Silent Valley movement (1973), Save Chaliyar Movement (1974), Mullaperiyar Dam Movement (1979), Kallen Pokkudan Movement (1989), Movement against Endosulfan (2000), Plachimada Coca-Cola Movement (2000), Muthanga Adivasi Movement to Recover Land (2003), Thottapally anti-mining movement (2003), Panamaram Airport Movement (2013), Aranmula Greenfield Airport Movement (2014), Ayiravallipara environmental movement (2022) Suggestions that can be put forward for improving the performance effectiveness of BMCs includes, provide regular trainings and handholding support to BMC members, conduct awareness programs and campaigns to educate the community about the importance of biodiversity conservation and existence of an institutional mechanism for implementing the same, timely and systematic updation of PBR should be done. All the BMCs should take effort to complete e-PBR, undertake comprehensive biodiversity surveys and assessments to understand the local flora and fauna, develop a database to document the biodiversity in the area, including threatened and endangered species, regular evaluation of BMC performance and seeking feedback from community members, provision of incentives or recognition to individuals or groups that contribute significantly to biodiversity conservation efforts, ensuring that BMC activities are sustainable and continue beyond the tenure of individual committee members. BMC activities should be made mandatory and strictly followed up by Kerala State Biodiversity Board, BMC meetings should be conducted regularly and registers has to be maintained systematically and constitution of BMC should be strictly based on as per Kerala Biological Diversity Rules 2008, Section 22 Sub Section (4) and should not be based on any kind of nepotism, staff strength of KSBB at the district co-ordination level has to be increase for strictly monitoring the activities of BMCs at the district level.Item Leadership dynamics of farmer in lead farmer centered extension advisory and delivery services (leads) in Kerala : critical analysis(Department of Agricultural Extension Education, College of Agriculture, Vellayani, 2024-06-03) Sreekanth, M S.; Bindu PodikunjuThe study entitled ‘Leadership dynamics of farmers in Lead Farmer Centered Extension Advisory and Delivery Services (LEADS) in Kerala: A critical analysis” was conducted with the primary objectives of developing a Leadership Competency Index (LCILEADS) for measuring the leadership competency of lead farmers and analyzing the contributing indicators of LCILEADS. Leadership competency development package was also developed for improving their leadership competencies. Eliciting and evaluating role expectation and role performance of lead farmers and satellite farmers was done. Constraint analysis on role performance was done and guidelines for effective leadership performance were also developed. Study also envisaged to find out the effectiveness of LEADS in Kerala for which a multi-dimensional scale was developed. The study was conducted in Kollam, Kannur, Palakkad and Wayanad districts. From each district, 30 lead farmers,30 satellite farmers and 30 practicing farmers were selected for the study, thereby constituting 90 farmers per district. Thus, a total of 360 respondents were selected for the study. To summarise, Kollam had the highest leadership competency index (6.60) and the least was found in Wayanad district (0.624). Psychological dimension was found to have the highest index value (0.705) and least index value was found in political dimension (0.550). The PCA results indicated that group cohesion, assertiveness, adoption of organic measures in farming and membership in organisations were the major contributing indicators of the LCILEADS. Effectiveness of LEADS programme was found to be high in Palakkad in all the respondent categories of lead, satellite and practicing farmers and lowest effectiveness was found in Wayanad in all respective categories. Among the dimensions’ technical efficiency was found to be the most significant. In case of perception, there was a no significant difference in perception of satellite farmers regarding the role expectation of lead farmers, but there was significant difference in perception of practicing farmers regarding the role expectation of satellite farmers. The LCDPLEADS developed as part of the study was found to effective in imparting knowledge and skill in all aspects, especially in case of good agricultural practices and soil sampling. The major constraints experienced in leads programme were technology repetition over the years and inadequate technology innovation fund. In conclusion, leadership competency stands as a linchpin for the sustainable advancement of agriculture. In a sector grappling with technological evolution, environmental challenges, and global market dynamics, effective leadership is imperative. Competent leaders drive innovation, foster collaboration, and navigate complexities inherent in modern agriculture.Item Risk behaviour of vegetable farmers in special agricultural zones in Kerala: an empirical analysis(Department of Agricultural Extension, College of Agriculture, Vellayani, 2022-11-04) Navitha Raj; Allan ThomasThe 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 239 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 240 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 241 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). 242 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.