Ph.D

The study titled "Impact of KVKs on dissemination of improved practices and technologies through OFTs: A multidimensional analysis" was conducted from 2021 to 2024. The research aimed to investigate the spatial and temporal dynamics of improved practices and technologies disseminated through On-Farm Trials (OFTs) by KrishiVigyanKendras (KVKs), and to delineate the technological, socio-psychological, and economic factors influencing the adoption of these practices, with a focus on assessing their sustainability. Additionally, the study sought to evaluate the feasibility of adopting these technologies across different Agro-Ecological Units (AEUs), and to identify the constraints in OFT implementation as perceived by farmers, extension agents, and scientists. The study focused on AEUs that had conducted OFTs during the 2019-20 to 2021-22 period, excluding AEU 5 (Pokkali lands), AEU 8 (southern laterites), AEU 16 (Kumily hills), and AEU 17 (Marayoor hills). A total of 235 beneficiary farmers of OFTs from 19 AEUs were surveyed, alongside 45 scientists from the participating KVKs and 115 extension personnel. A desk review of OFTs conducted by 13 KVKs (excluding the KVK in Ernakulam district) was also undertaken. The analysis of the spatial dynamics of OFTs revealed that cereals and millets (36.84 ha) accounted for the largest area coverage, followed by human-animal conflict trials (16.80 ha). Vegetables emerged as the dominant crop for both the number of OFTs (61) and the number of technologies disseminated (200), followed by spices (23 OFTs and 82 technologies). Vegetables also had the highest farmer participation, with 314 farmers, followed by livestock (129 farmers). KVK in Kollam district stood out in all aspects of OFT implementation, including the total number OFTs (26), farmer participation (191 farmers), and introduced technologies (91). In terms of area covered under OFTs, KVK in Palakkad district is the fore fronter with 21.18 hectares. The study revealed a high level of farmer-to-farmer communication regarding the adoption of technologies disseminated through OFTs, with 77.02 per cent of farmers sharing OFT technologies with others. A total of 2,594 non-OFT farmers adopted these technologies, with AEU 10 leading in adoption, involving 459 farmers and the highest mean adoption rates observed in AEU 7 (25.85) and AEU 10 (22.95). The majority ofcultural Extension Education | KVKs on dissemination | OFTsfarmers (60.85%) perceived the spread of technologies/practices through OFTs as limited, with all farmers in AEU 18 and AEU 19 perceiving the extent of dissemination as low. Temporal dynamics of OFT technologies were assessed through a desk study of trials conducted in 2019-20, 2020-21, and 2021-22. The results indicated that only KVKs in Kottayam, Malappuram, and Alappuzha districts conducted OFTs on cereals annually during the study period. For vegetables, Thiruvananthapuram, Kollam, Kottayam, Thrissur, Palakkad, Malappuram, Kozhikode, and Wayanad conducted annual OFTs, with Thiruvananthapuram leading with 10 OFTs and Kollam dominating with 33 technologies. OFTs on pulses and oilseeds were absent in 2019-20, while Kollam conducted OFTs on pulses in 2020-21 and 2021-22, with 2 trials and 8 technologies. OFTs on coconut were conducted only in 2019-20, with Kasaragod district leading with 2 trials and 9 technologies. Idukki was the only district to conduct annual OFTs on fruit crops, while Thiruvananthapuram and Idukki conducted annual OFTs on tuber crops. Kannur and Pathanamthitta were the primary districts for spices and condiments, with Kannur leading in both the number of OFTs (4) and technologies (18). Wayanad, Malappuram, and Kollam conducted OFTs on other crops, except in 2020-21. The target achievement analysis of OFTs by KVKs in Kerala revealed that Kannur, Thrissur, Kollam, Wayanad, Idukki, and Alappuzha districts consistently achieved 100 per cent of their targets for OFTs and farmer participation from 2019-20 to 2021-22. The impact of KVKs on the dissemination of improved practices and technologies through OFTs was assessed using frequency, percentage, and cluster analysis. The results indicated that the majority of farmers reported medium to high production (41.28%), economic (33.62%), social (37.02%), psychological (40.43%), and environmental (39.15%) impacts. Among these, social impact (38.51) had the highest mean, followed by environmental impact (37.14), production impact (33.00), economic impact (24.29), and psychological impact (21.23). Cluster analysis of the impact of OFT technologies identified 4 clusters of production impact, 5 clusters of economic impact, 6 clusters of social impact, 8 clusters of psychological impact, and 6 clusters of environmental impact among farmers. Correlation analysis revealed that tenindependent variables—such as area under cultivation, KVK experience, farm income, total income, extension orientation, training received, linkages with local institutions, innovation proneness, economic motivation, and scientific orientation—had a positive and significant correlation with the impact of OFTs at 1 per cent level of significance. The analysis of the types of technologies and practices disseminated through OFTs revealed that 78.3 per cent of respondents were exposed to only one type of technology or practice, with farmers in AEU 3, AEU 4, AEU 18, AEU 19, and AEU 22 receiving only a single technology or practice. In terms of crop-wise OFTs, vegetables dominated with 101 trials, followed by rice with 52 trials. Varietal evaluation emerged as the leading thrust area, accounting for 134 trials, followed by Integrated Disease Management (IDM) with 45 trials. The demonstrated technologies and practices were found to be highly acceptable to 42.13 per cent of farmers and acceptable to 40.43 per cent of farmers. The technological contributions of KVKs were assessed in terms of varietal replacement, adoption, and yield improvement. A total of 113 varietal replacements were made through varietal trials, with AEU 7 leading in varietal replacement (11 varieties), followed by AEU 1 (10 varieties). A majority of farmers (63.83%) experienced yield increases through the adoption of OFT technologies, and farmers in AEU 3 and AEU 22 had significant yield improvements. Additionally, 58.3 per cent of farmers fully adopted the OFT technologies and practices, with all farmers in AEU 19 and AEU 22 fully adopting them. In contrast, 77.78 per cent of farmers in AEU 14 did not adopt the OFT technologies and practices. The correlates of adoption of sustainable recommendation domains in OFT interventions were identified using a scale developed through Likert’s Summated Rating method. The results indicated that most respondents had medium levels of economic, social, psychological, technological, physical, human resource, and institutional correlates of adoption. Specifically, 32.77 per cent of respondents had low to medium economic correlates, 31.91 per cent had medium to high social correlates, 35.32 per cent exhibited medium to high psychological correlates, 48.09 per cent had medium to high technological correlates, 38.72 per cent had medium to high physical correlates, 36.17 per cent had medium to high human resource correlates, and 44.68 percent had medium to high institutional correlates of adoption. A one-way ANOVA revealed significant differences in the means of all correlates of adoption across AEUs (p < 0.05). Correlation analysis showed that all correlates of adoption were positively and significantly correlated with the adoption of OFT technologies and practices at the 1 per cent level of significance. Farmers' perceptions of the effectiveness of KVKs were measured using a Likert scale. The results showed that 38.72 per cent of farmers had medium to high perceptions of KVK effectiveness, while 26.81 per cent had low to medium perceptions. The Kruskal-Wallis test indicated a significant difference in farmers’ perceptions across AEUs (p = 0.017). Correlation analysis of farmers' perceptions with independent variables revealed that seven variables—such as area under cultivation, KVK experience, extension orientation, linkages with local institutions, innovation proneness, economic motivation, and scientific orientation—had positive and significant correlation with farmers’ perceptions at the 1per cent level of significance. Additionally, four variables—area under OFT, farm income, total income, and training received—had positive and significant correlations with farmers’ perceptions at the 5 per cent level of significance. The Client Satisfaction Index (CSI) revealed that 37.87 per cent of farmers had medium to high motivation and 45.53 per cent had medium to high satisfaction with the OFT technologies. A significant difference in CSI across AEUs was identified using the Kruskal-Wallis test and correlation analysis of CSI with various socio-economic variables including area under cultivation, experience with KVK, farm income, total income, extension orientation, training received, linkages with local institutions, innovation proneness, economic motivation and scientific orientation had positive and significant correlation with CSI at 1 percent level of significance and area under OFT had positive and significant correlation with CSI at 5 percent level of significance. Technology gap analysis highlighted the adaptation phase as having the highest gap, followed by integration and testing phases. Knowledge gaps were found to be moderate, with the highest gap in AEU 20. The study analyzed the socio-demographic characteristics of farmers, revealing that most respondents were male (71.06%), with secondary education (37.45%),farming as their primary income source (57.87%), and small-scale farming practices. Over half of the farmers (53.19%) had below-average farming experience and training exposure (55.32%), with many having limited contact with local extension services and institutions. The study further assessed the effectiveness of the OFT system by examining the five phases where conducting and assessment phases were deemed the most critical for technology adoption, with significant differences across the phases identified through ANOVA analysis Constraints faced by farmers and scientists were also assessed, with climatic uncertainty and planting material scarcity being major concerns for farmers, while scientists pointed to workload and difficulties in technology dissemination. Suggestions for improving OFT implementation included strengthening extension services, developing user-friendly platforms for information dissemination, and fostering partnerships with local governments. In conclusion, this study emphasized the importance of assessing the impact of KVKs on technology adoption through OFTs and suggests that more targeted interventions across AEUs are necessary to enhance the adoption of sustainable agricultural technologies. The study provides valuable insights into the current status of technology adoption and outlines strategies to overcome barriers, ultimately aiming to promote sustainable agricultural development.