1. KAUTIR (Kerala Agricultural University Theses Information and Retrieval)
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Item Effectiveness of certificate course on integrated nutrient management for fertilizer dealers(Department of Agricultural extension, College of Agriculture, Vellanikkara, 2025-01-21) Sathiswaran, R.; Helen, SThe fertilizer dealers are the prime source of agricultural information and suppliers of quality inputs to the farming community. However, majority of the fertilizer dealers do not have a formal degree or adequate knowledge on scientific practices in agriculture. Realizing the importance of equipping fertilizer dealers and enhancing their professional competency of fertilizer dealers, the Ministry of Agriculture and Farmers’ Welfare issued an amendment called Fertilizer Control Order in 1985. It is mandatory for all the fertilizer dealers to undergo a 15-day certificate course to obtain and renew their license for fertilizer dealership. Kerala Agricultural University (KAU) introduced online certificate course on Integrated Nutrient Management (INM) in 2020 for fifteen batches and thereafter conducted nine offline batches till 2023. In this background, a study on “Effectiveness of certificate course on integrated nutrient management for fertilizer dealers” was carried out to assess the effectiveness of online and offline certificate course on Integrated Nutrient Management (INM) as perceived by fertilizer dealers, relationship of profile characteristics of fertilizer dealers with their perceived effectiveness towards online and offline certificate course on INM, identify constraints faced by fertilizer dealers in participating online and offline certificate course and formulate strategies to improve the certificate course for empowering fertilizer dealers. The seven districts of Kerala, viz. Kannur, Kozhikode, Malappuram, Thrissur, Palakkad, Alappuzha and Kollam were selected purposively for the study by considering the maximum number of fertilizer dealers participated in the certificate course. A representative sample of 150 respondents each from online and offline certificate courses was selected by adopting proportionate random sampling technique, thus making the total sample size of 300 respondents. The profile of online and offline trained fertilizer dealers revealed that, 46.00 per cent of online trained dealers were in the middle age group, while 36.00 per cent of offline trained dealers were in the young age group. It was found that for both categories of dealers, the majority were males, educated up to the graduation level, and had good computer proficiency. Most of the dealers were retailers, and more than half had business experience of less than five years. It was revealed that 35.33 per cent of online trained dealers had an annual income between Rs.50,001 and Rs.1,00,000, whereas 28.66 per cent offline trained dealers earned above Rs.2,00,000 annually. Among online trained dealers, 30.00 per cent dealt with any two types of inputs, while more than one-fifth of offline trained dealers (27.33%) dealt with any two and three types of inputs each. The data also showed that the government agencies were the major source of motivation for more than half of both the categories of dealers. It was revealed that the majority of both categories of dealers had a medium level of extension contact, mass media participation and information-seeking behaviour. Both categories of online as well as offline trained fertilizer dealers exhibited a medium level of management orientation, decision-making ability, economic motivation, risk-taking ability and level of aspiration. The perceived effectiveness of the certificate course using the Kirkpatrick's four-level hierarchical model revealed that, the ‘reaction’ level of the evaluation of the certificate course composed of the components viz; quality, course content, teaching methods, duration and time of training. It showed that the mean score of 4.36 secured by offline trained fertilizer dealers was higher compared to the mean score 3.78 gained by online trained fertilizer dealers towards the reaction level under the evaluation of the certificate course on INM. At the ‘learning’ level evaluation of the certificate course constituted the components viz; utility, coverage, knowledge gained and skill development. It clearly showed that the mean score secured under learning level of the offline trained fertilizer dealers 4.24 was higher in comparison to online trained fertilizer dealers with mean score of 3.83. The ‘behaviour’ level of the evaluation of the certificate course comprised the change in job performance, confidence level and management skills among the fertilizer dealers after completing the certificate course. It showed that the mean score 4.21 obtained by offline trained fertilizer dealers was higher compared to the mean score 3.76 secured by online trained fertilizer dealers. Finally, the ‘result’ level of the evaluation consisted of role of certificate course in moulding the respondents viz; professional competency, management of fertilizer dealership, transfer of technology and overall satisfaction. It showed that the mean score 4.25 obtained by offline trained fertilizer dealers was higher compared to the mean score 3.86 received by online trained fertilizer dealers related to the ‘results level of them after attending the certificate course. The Spearman’s rank correlation coefficient (rsp) analysis revealed that the variables viz; age, educational status, business experience, mass media participation, types of input marketed, computer proficiency, management orientation, information seeking behaviour, economic motivation, risk taking ability and level of aspiration were found to be positively correlated with perception towards the effectiveness of certificate course either 1% or 5% level of significance. The major constraints faced by online trained fertilizer dealers were: receipt of study materials after completion of online sessions, some lectures were too fast, internet connectivity issues and lack of communication and low interaction with other participants. Whereas, the major constraints faced by offline trained fertilizer dealers were: classroom session was too long to concentrate, no adequate follow-up and difficult to maintain work life balance during the course period. The specific strategies were developed to improve the effectiveness of the certificate course on Integrated Nutrient Management (INM). Based on the Kirkpatrick's level of evaluation model, strategies were framed viz. Reaction level: group discussion, method demonstration and group presentation may be organized. Learning level: enhancement of knowledge, upgradation of skills and favourable attitude towards the job. Behaviour level: Understanding market dynamics, disseminating technology and staying updated with latest technologies. Results level: sessions on conducting market research, encouraging to share knowledge with colleagues and farmers, networking with suppliers and manufacturers, evaluating new technologies and follow up may be adoptedItem Impact of online education during covid-19 in Kerala agricultural university:students' and teachers' perspectives(Department of Agricultural Extension, College of Agriculture,Vellayani, 0023) Ashitha, A R.; Bindu PodikunjuAgricultural extension , Impact of online education during covid-19 The present study entitled “Impact of online learning during COVID-19 in Kerala Agricultural University: Students’ and teachers’ perspectives” was conducted in the four colleges of Kerala Agricultural University viz, College of Agriculture (CoA), Vellayani; CoA, Vellanikkara; CoA, Padannakkad and CoA, Ambalavayal. The objective was to study the perception of students and teachers about effectiveness of online education, delineation of factors affecting its effectiveness and identification of constraints therein. The sample consisted of 150 students and 40 teachers from the four colleges under KAU. Based on the judges rating and literature review, ten and eight independent variables were selected for the students and teachers, respectively. Perception of students and teachers about effectiveness of online education were selected as the dependent variable for the study. The variables were measured and analyzed with the help of various statistical tools like frequency, percentage analysis, mean, standard deviation, quartiles, chi square test, correlation and t test. The detailed investigation on the profile characteristics of students pointed out that, majority of the students (80%) were females, more than half of them (60%) belonged to rural family background and majority of them (55.8%) had medium annual income. Majority of the students (58.67%) were quite ready for the online classes during COVID-19 and most of them (86%) had self-owned devices for attending online classes. Seventy-one percentage of students had medium exposure to technology and seventy three per cent of the students used digital technology at a medium level. Majority of the students (68%) had medium adaptability with digital platforms and learning management system and nearly half of the them (46%) had fair quality of internet connection for attending online classes during COVID-19. The proportion of students who intend to continue their education online (50.67%) is marginally higher than the reverse (49.33%). Analysis of the profile characteristics of teachers revealed that majority of the teachers (65%) were female and half of them (50%) were middle aged. Majority of the teachers (65%) had less teaching experience. More than half of the teachers had prior 140 online experience before COVID-19 (60%) and had received training for taking online classes (65%). Sixty three percent of teachers belonged to the category of medium use of digital technology and majority of them (60%) had good quality internet connection for conducting online classes during COVID-19. More than half of the teachers (52.5%) had positive continuance intention for online education. The results of the study revealed that majority of the students (64%) and teachers (60%) had positive perception about effectiveness of online education. There was no significant difference observed between the perception of students and teachers about online education during COVID-19. Based on the result of chi square test, profile characteristics of students such as place of residence, annual income, continuance intention, e-readiness, exposure to technology and internet accessibility were found to have significant association with the perception of students about online education. In case of teachers, profile characteristics such as gender, age, prior online experience, training received and continuance intention had significant association with perception about online education. Among the five factors affecting effectiveness of online education viz., selfefficacy, subjective norm, attitude, digital competence and technostress, subjective norm had the highest score for students as well as teachers. Self-efficacy and attitude had positive significant correlation whereas subjective norm and technostress had negative significant correlation with the perception of students about online education. For teachers, self-efficacy and attitude had positive significant correlation whereas technostress had negative significant correlation with the perception about online education. In case of constraints in online education during COVID-19, technological and health constraints were ranked as the important constraints faced by students whereas insufficient/ unstable internet connectivity followed by the technical problems were the important constraints faced by the teachers. To conclude, students and teachers had shown interest in the use of online education in their academic activities and its use was no doubt intensified by the sudden outbreak of the COVID-19 pandemic. Even though online education had worked as an 141 aid during COVID-19, shifting completely to online mode may not be possible in agricultural education system where many courses are practical oriented. Hence, there is a need of designing a hybrid mode of education which will be beneficial for both teachers and learners during any future crisis-like situations.Item Risk assessment of agricultural supply chain: case of coconut enterprises in Kerala(Department of Agricultural Extension Education, College of Agriculture, Vellanikkara, 2023-03-18) Reshma, R.; Binoo, P BonnyIn the agrarian economy of Kerala, coconut plays a significant role. The supply chain of an agricultural commodity consisted of the processes from its raw material procurement to its distribution as a final product. It is a network that encompasses the actors and activities where individuals, organizations, resources, credit, and information flow are present. The presence of this multitude of actors and activities make the supply chain vulnerable to risks. Risk can be defined as the possibility of the occurrence of any loss or harm. In order to manage the supply chain risks, effective supply chain risk management has become imperative. The study was undertaken with this rationale to map the major coconut supply chains, assessment and ranking of the major supply chain risks in terms of perceived probability and severity of occurrence. Also, assessment of the risk management behaviour of major actors along the supply chain was undertaken. A sustainable framework for effective risk management in the coconut supply chain was also attempted. The study followed ex-post facto research design. Through criteria-based random selection, the three districts of Kerala viz. Malappuram, Kozhikode, and Kannur were selected for the study. The criteria for selection was their lead role in the area and production of coconut and also the inclusion of coconut products as the highest ranked district product under the One District One Product (ODOP) under Pradhan Mantri Formalisation of Micro food processing Enterprises (PMFME) scheme of the Ministry of Food Processing Industry (MoFPI) implemented in Kerala. The details of the micro and small enterprises of the respective districts were collected from the District Industries Centres (DICs), State Department of Agriculture, Coconut Development Board (CDB), and Krishi Vigyan Kendra’s (KVKs). From the list collected, a proportionate sample of 50 enterprises were selected from each district to form a total sample size of 150. The study could map and delineate the coconut supply chain by using social network analysis (SNA) by fixing each district as the boundary of the network. From the upstream level of supply chain (SC), procurement supply chain network (SCN) has been delineated. The financial assistance and training and capacity-building SCN had been mapped to represent the midstream level of SC. The downstream level mainly consisted of activities related to the distribution of final product and thus marketing SCN was mapped at this level. By calculating the centrality measures, the out-degree centrality was found to be higher for coconut farmers within the district in case of procurement SCN in all three districts. In the case of financial assistance and training and capacity-building SCN the District Industries Centre (DIC) of the respective districts played the key role and for marketing the final local consumers secured the highest degree centrality. Thus, entrepreneurs with direct contact with these actors could attain more advantages in the supply chain through the reduction of intermediaries. For the procurement and marketing SCN, the significant presence of informal actors with more than 90 percent of the total actors were reported in the study. This implied the need for formal registered vendors as well as formal marketing support functionaries at the local level. The supply chain risks were assessed by through the estimation of risk perception. Risk perception was operationalized as the product of the likelihood and severity of the occurrence of risks. The obtained scores were then used to classify the risks into different categories following the risk matrix. The production and marketing risks scored the highest risk perception score and were grouped as the high-risk category. The medium risks were the environmental risks and the organisational risk while the supply risk was classified under the low-risk category. Ranking of the identified supply chain risks were done by following the analytic hierarchy process (AHP). The major risk dimensions selected were environmental risk, supply risk, organisational risk, production/manufacturing risk, and market risk. The triggering factors for each dimension were defined as sub-criteria. Pair-wise comparison between criteria’s and sub-criteria’s within each criteria were done and the ranks were obtained. The market risk ranked top among the major risks and the environmental risk, production/manufacturing risk, and organisational risk followed it. The supply risk was the least ranked risk in the supply chain of coconut. The results could obtain a consistency ratio of less than 0.1 which implied the stability of the results. The risk management behaviour of the entrepreneurs were found as the behavioural outcome of risk attitude towards the risk management strategies. The majority of the population derived were of risk-neutral type (60%). They are indifferent to the risks. They won’t averse or seek the risks. This population must be more focussed on the entrepreneurial ecosystem through capacity-building programs. The remaining 23.33 percent were of risk-averse nature and were highly calculated towards the risk. The risk seekers (16.67%) had the highest risk tolerating capacity and they will take risks in order to regain from the loss already happen. The profile attributes of the enterprises and entrepreneurs were also delineated. Based on the results the study formulated a framework for the effective management of the supply chain by incorporating the four delineated components. The components used were risk identification, risk analysis, risk evaluation, and risk treatment. In risk identification, the actors and activities involved in the coconut supply chain were identified. The risks identification was based on the supply chain analysis done at the respective levels. The risk score for risks at each level was analysed and classified as high, medium, and low according to their likelihood and severity of occurrence. The major risks were ranked based on evaluation along the supply chain. Mitigation practices were suggested for the upstream, midstream, and downstream level of supply chain risk management (SCRM). The results of the study could contribute to the sectoral policy and regulatory reform processes by apprehending the major risks and evolving the management strategies.Item Sustainability assessment of banana value chains of Palakkad district, Kerala(Department of Agricultural Extension Education, College of Agriculture, Vellayani, 2023-05-08) Nikhil, K S; Aparna RadhakrishnanThe study entitled Sustainability assessment of banana value chains of Palakkad district, Kerala was undertaken during 2021-2022. The study was based on the objectives viz, mapping of banana value chains depicting the value chain actors, functions, and dimensions; sustainability assessment and identification of constraints in banana value chain and formulation of sustainable framework for the banana value chain. The study was conducted in Agali, Kumaramputhur, and Karimpuzha panchayaths of Palakkad district, with a sample size of 170 value chain actors. The sample comprised of 19 input dealers, 105 banana farmers, 19 commission agents, 19 wholesalers, 17 value addition dealers, 19 retailers and 105 consumers. The major role of the above mentioned actors observed were supply of inputs, internal handling and management of resources, physical handling of the product and arranging for its sale, providing system for procurement, storage and distribution to the retailers and export agency, minimizing perishability risk and enhancing shelf life, grading, sorting, packaging of banana and its value added product for export purpose, acting as basic unit of demand of the commodity. More than ten value chains were identified during the study, and seven major value chains out of ten were selected for mapping viz, raw and ripe banana value chain, auction system value chain, chips export value chain, chips bakery value chain, banana product mix value chain, banana export value chain and banana powder value chain. It was realized that the chains were widely disbursed over the state and country and some ends abroad. During the investigation information flow, money flow, and product flow were observed and analysed. The former was depicted by social network analysis, and the latter is by causal circular loop method. The major information shared between actors observed were on marketing, consumer demand, risk, and opportunities existing in the chain, and it has resulted in the formation of virtual clusters within the chains. The transfer of money and products from actor to actor was depicted in money flow and product flow respectively. The of Palakkad district, Kerala sustainability was measured under four factors: economic, social,environmental, and technical. The weighted index method used for calculating sustainability and weightage of indicators was collected from the major actors by key informant interview and focus group discussion. On analysis, it was found that auction system value chain showed higher sustainability, raw and ripe banana value chain exhibited low sustainability and other chains depicted medium sustainability. In auction system value chain, actors were highly equipped with economic factors, socially forward, environmentally aware and technically well advanced. The major actors were from tribal community of Agali region, were less oriented towards marketing aspects, socially backward, poor in handling and use of plant protection chemicals and technologically less adapted, the raw and ripe banana value chain showed less sustainability among the others. The result of Karl Pearson correlation analysis revealed that independent variables namely profitability, credit availability, government support, labour availability, perception on soil health, waste management, environmental awareness, use of micronutrients and botanicals, integrated pest management, propping method and pre cooling and processing of banana showed highly significant correlation with the sustainability of the chains. The constraints on sustainability of banana value chain were grouped into four categories: economic, social, environmental and technical. Analytical hierarchy process was used to rank the constraints and the results exposed that economic category ranked highest, followed by technical, social and environmental categories. Invasion of cheapest banana from neighboring states, inadequate value addition centres, exploitation of producers by middlemen in rural areas, and product loss due to wild animal attack were the highest ranked constraints in the above-mentioned categories. Based on the sustainable food value chain framework developed by Food and Agriculture Organization (FAO), the study proposed a conceptualised sustainable framework on the core value chains of study area which relates to the actors, their core functions, sustainability dimensions and the enabling environment. The value chain study can be adopted to the other major crops in Kerala to analyse the sustainability and the framework can be adopted for policy making.Item Lease land farming for sustainable livelihood by women collectives in Thrissur district(Department of Agricultural Extension Education, College of Agriculture ,Vellanikkara, 2023-03-16) Swapna , Thomas; Mercykutty , M JItem Farmer innovations in the field of agricultural machinery: a multi-dimensional analysis(Department of Agricultural Extension Education, College of Agriculture,Vellanikkara, 2023-04-20) Jaizen, Kuriakose.; Sunil, V GItem Risk assessment of agricultural supply chain: case of coconut enterprises in Kerala(Department of Agricultural Extension Education, College of Agriculture,Vellanikkara, 2023-03-18) Reshma, R; Binoo P, BonnyIn the agrarian economy of Kerala, coconut plays a significant role. The supply chain of an agricultural commodity consisted of the processes from its raw material procurement to its distribution as a final product. It is a network that encompasses the actors and activities where individuals, organizations, resources, credit, and information flow are present. The presence of this multitude of actors and activities make the supply chain vulnerable to risks. Risk can be defined as the possibility of the occurrence of any loss or harm. In order to manage the supply chain risks, effective supply chain risk management has become imperative. The study was undertaken with this rationale to map the major coconut supply chains, assessment and ranking of the major supply chain risks in terms of perceived probability and severity of occurrence. Also, assessment of the risk management behaviour of major actors along the supply chain was undertaken. A sustainable framework for effective risk management in the coconut supply chain was also attempted. The study followed ex-post facto research design. Through criteria-based random selection, the three districts of Kerala viz. Malappuram, Kozhikode, and Kannur were selected for the study. The criteria for selection was their lead role in the area and production of coconut and also the inclusion of coconut products as the highest ranked district product under the One District One Product (ODOP) under Pradhan Mantri Formalisation of Micro food processing Enterprises (PMFME) scheme of the Ministry of Food Processing Industry (MoFPI) implemented in Kerala. The details of the micro and small enterprises of the respective districts were collected from the District Industries Centres (DICs), State Department of Agriculture, Coconut Development Board (CDB), and Krishi Vigyan Kendra’s (KVKs). From the list collected, a proportionate sample of 50 enterprises were selected from each district to form a total sample size of 150. The study could map and delineate the coconut supply chain by using social network analysis (SNA) by fixing each district as the boundary of the network. From the upstream level of supply chain (SC), procurement supply chain network (SCN) has been delineated. The financial assistance and training and capacity-building SCN had been mapped to represent the midstream level of SC. The downstream level mainly consisted of activities related to the distribution of final product and thus marketing SCN was mapped at this level. By calculating the centrality measures, the out-degree centrality was found to be higher for coconut farmers within the district in case of procurement SCN in all three districts. In the case of financial assistance and training and capacity-building SCN the District Industries Centre (DIC) of the respective districts played the key role and for marketing the final local consumers secured the highest degree centrality. Thus, entrepreneurs with direct contact with these actors could attain more advantages in the supply chain through the reduction of intermediaries. For the procurement and marketing SCN, the significant presence of informal actors with more than 90 percent of the total actors were reported in the study. This implied the need for formal registered vendors as well as formal marketing support functionaries at the local level. The supply chain risks were assessed by through the estimation of risk perception. Risk perception was operationalized as the product of the likelihood and severity of the occurrence of risks. The obtained scores were then used to classify the risks into different categories following the risk matrix. The production and marketing risks scored the highest risk perception score and were grouped as the high-risk category. The medium risks were the environmental risks and the organisational risk while the supply risk was classified under the low-risk category. Ranking of the identified supply chain risks were done by following the analytic hierarchy process (AHP). The major risk dimensions selected were environmental risk, supply risk, organisational risk, production/manufacturing risk, and market risk. The triggering factors for each dimension were defined as sub-criteria. Pair-wise comparison between criteria’s and sub-criteria’s within each criteria were done and the ranks were obtained. The market risk ranked top among the major risks and the environmental risk, production/manufacturing risk, and organisational risk followed it. The supply risk was the least ranked risk in the supply chain of coconut. The results could obtain a consistency ratio of less than 0.1 which implied the stability of the results. The risk management behaviour of the entrepreneurs were found as the behavioural outcome of risk attitude towards the risk management strategies. The majority of the population derived were of risk-neutral type (60%). They are indifferent to the risks. They won’t averse or seek the risks. This population must be more focussed on the entrepreneurial ecosystem through capacity-building programs. The remaining 23.33 percent were of risk-averse nature and were highly calculated towards the risk. The risk seekers (16.67%) had the highest risk tolerating capacity and they will take risks in order to regain from the loss already happen. The profile attributes of the enterprises and entrepreneurs were also delineated. Based on the results the study formulated a framework for the effective management of the supply chain by incorporating the four delineated components. The components used were risk identification, risk analysis, risk evaluation, and risk treatment. In risk identification, the actors and activities involved in the coconut supply chain were identified. The risks identification was based on the supply chain analysis done at the respective levels. The risk score for risks at each level was analysed and classified as high, medium, and low according to their likelihood and severity of occurrence. The major risks were ranked based on evaluation along the supply chain. Mitigation practices were suggested for the upstream, midstream, and downstream level of supply chain risk management (SCRM). The results of the study could contribute to the sectoral policy and regulatory reform processes by apprehending the major risks and evolving the management strategies.Item Impact of online education during covid-19 in Kerala agricultural university:students' and teachers' perspectives(Department of Agricultural Extension, College of Agriculture,Vellayani, 2023) Ashitha, A R; Bindu , PodikunjuThe present study entitled “Impact of online learning during COVID-19 in Kerala Agricultural University: Students’ and teachers’ perspectives” was conducted in the four colleges of Kerala Agricultural University viz, College of Agriculture (CoA), Vellayani; CoA, Vellanikkara; CoA, Padannakkad and CoA, Ambalavayal. The objective was to study the perception of students and teachers about effectiveness of online education, delineation of factors affecting its effectiveness and identification of constraints therein. The sample consisted of 150 students and 40 teachers from the four colleges under KAU. Based on the judges rating and literature review, ten and eight independent variables were selected for the students and teachers, respectively. Perception of students and teachers about effectiveness of online education were selected as the dependent variable for the study. The variables were measured and analyzed with the help of various statistical tools like frequency, percentage analysis, mean, standard deviation, quartiles, chi square test, correlation and t test. The detailed investigation on the profile characteristics of students pointed out that, majority of the students (80%) were females, more than half of them (60%) belonged to rural family background and majority of them (55.8%) had medium annual income. Majority of the students (58.67%) were quite ready for the online classes during COVID-19 and most of them (86%) had self-owned devices for attending online classes. Seventy-one percentage of students had medium exposure to technology and seventy three per cent of the students used digital technology at a medium level. Majority of the students (68%) had medium adaptability with digital platforms and learning management system and nearly half of the them (46%) had fair quality of internet connection for attending online classes during COVID-19. The proportion of students who intend to continue their education online (50.67%) is marginally higher than the reverse (49.33%). Analysis of the profile characteristics of teachers revealed that majority of the teachers (65%) were female and half of them (50%) were middle aged. Majority of the teachers (65%) had less teaching experience. More than half of the teachers had prior 140 online experience before COVID-19 (60%) and had received training for taking online classes (65%). Sixty three percent of teachers belonged to the category of medium use of digital technology and majority of them (60%) had good quality internet connection for conducting online classes during COVID-19. More than half of the teachers (52.5%) had positive continuance intention for online education. The results of the study revealed that majority of the students (64%) and teachers (60%) had positive perception about effectiveness of online education. There was no significant difference observed between the perception of students and teachers about online education during COVID-19. Based on the result of chi square test, profile characteristics of students such as place of residence, annual income, continuance intention, e-readiness, exposure to technology and internet accessibility were found to have significant association with the perception of students about online education. In case of teachers, profile characteristics such as gender, age, prior online experience, training received and continuance intention had significant association with perception about online education. Among the five factors affecting effectiveness of online education viz., selfefficacy, subjective norm, attitude, digital competence and technostress, subjective norm had the highest score for students as well as teachers. Self-efficacy and attitude had positive significant correlation whereas subjective norm and technostress had negative significant correlation with the perception of students about online education. For teachers, self-efficacy and attitude had positive significant correlation whereas technostress had negative significant correlation with the perception about online education. In case of constraints in online education during COVID-19, technological and health constraints were ranked as the important constraints faced by students whereas insufficient/ unstable internet connectivity followed by the technical problems were the important constraints faced by the teachers. To conclude, students and teachers had shown interest in the use of online education in their academic activities and its use was no doubt intensified by the sudden outbreak of the COVID-19 pandemic. Even though online education had worked as an 141 aid during COVID-19, shifting completely to online mode may not be possible in agricultural education system where many courses are practical oriented. Hence, there is a need of designing a hybrid mode of education which will be beneficial for both teachers and learners during any future crisis-like situations.Item Social dynamics of urban agriculture (UA): a critical analysis(Department of Agricultural Extension, College of Agriculture,Vellayani, 2023-05-08) Archana T , Shaji; Sreedaya, G SThe study entitled “Social Dynamics of urban agriculture (UA): A critical analysis’’ was conducted during the year 2021-2022. The main objective of the study was to find the subjective well-being (SWB) formed among urban farmers, the motivational patterns of people involved in UA, nature and spatial typology of UA, delineating existing models of marketing and urban farmers perception regarding the marketing models. The research design used for the study was ex post facto design. Locale of study was Thiruvanthapuram, Kollam and Kochi Corporation, most urbanized areas in southern Kerala. Thirty farmers who were actively involved in urban agriculture practices were purposively selected from each corporation constituting a sample of ninety farmers. Ten officials were also purposively selected from three districts for data collection, thus comprising a total sample size of 120. SWB of urban farmers was the dependent variable of the study and was measured by developing Subjective well-being index using life satisfaction, positive affect and negative affect. Motivational patterns were measured using methodology followed by Othman et al.(2019). Twelve independent variables also studied. The statistical tools used for the study includes frequency, standard deviation, percentage analysis, correlation, chi-square analysis, Kruskal-wallis test, Principal component analysis, anova and t-Test. Regarding nature and spatial typology the main type of urban agriculture practice was rooftops farming in grow bags and container (43.33 %). The main combination of crops cultivated was of solanaceous, legume, crucifers and leafy vegetables combination was cultivated by 20 per cent of farmers. The result indicated that majority of the urban farmers (46.67 %) have medium level of subjective well-being and 27.78 per cent of respondents have high level of SWB, only 25.56 per cent farmers belonged to low SWB category. Kruskal-wallis test was used to compare the difference among subjective well-being formed among different corporations and farmers practicing different typologies of UA. The result revealed that there was not much significance difference between SWB formed among urban farmers of different categories. Urban farming experience, annual income, health consciousness, scientific orientation, environmental orientation, innovativeness and social capital had significantly positive relation with subjective well-being. PCA results indicated that main motivational factor influencing farmers for practicing urban agriculture was physical and health factor. Age of urban farmers had a significant relationship with social factor, health and environmental factors of motivational pattern. Income of urban farmers didn’t have any significant relationship with their motivational patterns.The gender of the farmers had significant relationship with environmental and economic factors. The most common model of marketing among urban farmers was combination of direct and indirect marketing (42.25 %) followed by direct (39.44 %). Regarding the farmers perception about marketing models, 94.45 per cent urban farmers were aware about marketing models while only 61.11 per cent urban farmers were willing to sell their extra produce through the channels. Most of the farmers (54.44 %) didn’t face any difficulty in selling their produce and only 47.78 per cent urban farmers were aware of strategies for marketing produce. The main constraint in selling produce by farmers were, the quantity of produced were less to make it marketable, the high level of competition from other conventional farmers and not getting remunerative prices for their produce. To conclude majority of urban farmers had medium level of subjective wellbeing (46.67 %). The main motivating factors encouraging urban people to practice the UA were health, environmental and social factor. Most of the farmers are engaged in UA for producing vegetables and fruits for their own consumption, only the extra produce are marketed. The market access is not a problem for the respondents. The issue of low supply of produce can be solved through group farming and marketing and fair price can be ensured by selling commodities through direct marketing. The main problem in enhancing food production through UA is the limited land availability. Therefore, it is recommended that through the use of new technologies and conversion of fallow land to cultivable land UA can be scaled up.Item Technology adoption behaviour cassava growers in Kollam district(Department of Agricultural Extension, College of Agriculture, Vellayani, 2020) Kavya, V S; Bindu, Podikunju