Loading...
Kerala Agricultural University, Thrissur
The history of agricultural education in Kerala can be traced back to the year 1896 when a scheme was evolved in the erstwhile Travancore State to train a few young men in scientific agriculture at the Demonstration Farm, Karamana, Thiruvananthapuram, presently, the Cropping Systems Research Centre under Kerala Agricultural University. Agriculture was introduced as an optional subject in the middle school classes in the State in 1922 when an Agricultural Middle School was started at Aluva, Ernakulam District. The popularity and usefulness of this school led to the starting of similar institutions at Kottarakkara and Konni in 1928 and 1931 respectively.
Agriculture was later introduced as an optional subject for Intermediate Course in 1953. In 1955, the erstwhile Government of Travancore-Cochin started the Agricultural College and Research Institute at Vellayani, Thiruvananthapuram and the College of Veterinary and Animal Sciences at Mannuthy, Thrissur for imparting higher education in agricultural and veterinary sciences, respectively. These institutions were brought under the direct administrative control of the Department of Agriculture and the Department of Animal Husbandry, respectively. With the formation of Kerala State in 1956, these two colleges were affiliated to the University of Kerala. The post-graduate programmes leading to M.Sc. (Ag), M.V.Sc. and Ph.D. degrees were started in 1961, 1962 and 1965 respectively.
On the recommendation of the Second National Education Commission (1964-66) headed by Dr. D.S. Kothari, the then Chairman of the University Grants Commission, one Agricultural University in each State was established. The State Agricultural Universities (SAUs) were established in India as an integral part of the National Agricultural Research System to give the much needed impetus to Agriculture Education and Research in the Country. As a result the Kerala Agricultural University (KAU) was established on 24th February 1971 by virtue of the Act 33 of 1971 and started functioning on 1st February 1972. The Kerala Agricultural University is the 15th in the series of the SAUs.
In accordance with the provisions of KAU Act of 1971, the Agricultural College and Research Institute at Vellayani, and the College of Veterinary and Animal Sciences, Mannuthy, were brought under the Kerala Agricultural University. In addition, twenty one agricultural and animal husbandry research stations were also transferred to the KAU for taking up research and extension programmes on various crops, animals, birds, etc.
During 2011, Kerala Agricultural University was trifurcated into Kerala Veterinary and Animal Sciences University (KVASU), Kerala University of Fisheries and Ocean Studies (KUFOS) and Kerala Agricultural University (KAU).
Now the University has seven colleges (four Agriculture, one Agricultural Engineering, one Forestry, one Co-operation Banking & Management), six RARSs, seven KVKs, 15 Research Stations and 16 Research and Extension Units under the faculties of Agriculture, Agricultural Engineering and Forestry. In addition, one Academy on Climate Change Adaptation and one Institute of Agricultural Technology offering M.Sc. (Integrated) Climate Change Adaptation and Diploma in Agricultural Sciences respectively are also functioning in Kerala Agricultural University.
Browse
9 results
Search Results
ThesisItem Open Access Economic analysis of production and marketing of tea in Wayanad district(Economic analysis of production and marketing of tea in Wayanad district, Vellayani, 2020) Marupilla, Supriya; KAU; Paul Lazarus, TThe present study entitled “An economic analysis of production and marketing of tea in Wayanad district” was conducted during 2019-20. The specific objectives of the study was to know the input use pattern, analyze the costs and returns from tea cultivation, to examine resource use efficiency, to study marketing aspects and constraints in the production and marketing of tea. The study was based on both primary and secondary data. The study was conducted in Muppainad village from Kalpetta block and Ambalavayal village from Sulthan Bathery block in Wayanad district. Primary data was collected from the farmers through formal interviews. The farmers in the study area were categorized into two groups on the basis of size of land holding small farmers (≤ 2 ha land) and large farmers (>2 ha of land). From each of the selected village panchayats, 12 farmers each of small and large size will be selected. The total sample size of study was thus 48. Secondary data pertaining to tea production and marketing and data regarding socio- economic status physiographic and demographic factors were collected from the official websites and government annual reports. On average, the total amount of human labour utilized was 404.80, 324.64 and 382.50 mandays per hectare on large, small and pooled farms respectively, and thus indicated a direct relationship between human labour and the size of the farm. The major labour needed operations were harvesting (87.60%) followed by application of fertilizers and manures (3.97%), plant protection chemicals (3.52%), pruning (3.03%) and weeding (1.88%) on pooled farms. Among the owned and hired labour, owned labour occupied 7.83 per cent and hired labour occupied 92.16 per cent on pooled farms. The annual maintenance Cost of cultivation of tea was carried out using cost concepts. The total cost of cultivation (cost C) of tea incurred by the small and large farmers was found to be ` 1,86,438.82 ha-1 and ` 2,45,143.60 ha-1 respectively. It was found that cost of cultivation was more for large farmers than small farmers. For both small and large farmers, per cent share of hired labour in cost A1 was the highest followed by manures and fertilizers. The net return at cost C for small and large farmers was ` 85,943.18 ha-1 and 1,54,156.40 ha-1 respectively. It was found that profitability was more for large farmers with a B:C ratio of 1.46 while small farmers had a comparatively smaller B:C ratio of 1.62. Resource use efficiency in tea cultivation was estimated using Cobb-Douglas production function and it was fitted separately for small and large farmers. The results showed that R2 value for small and large farms in tea cultivation was 0.71 and 0.90 respectively and it indicated good fit of both the regression models. Marginal productivity analysis showed that, all the independent variables were having a K value more than one, which indicated the suboptimal or underutilization of resources by both small and large farmers. Allocative efficiency of these inputs can be improved only by the enhanced utilization. The study done on the respondent farmers revealed that there existed two marketing channels of tea: Marketing channel- I Producer Commission agent Processing unit Wholesaler Retailer Consumer Marketing channel-II Producer Processing unit Wholesaler Retailer Consumer In channel-1 The total marketing cost incurred was Rs 9.22/- and the total cost incurred in channel-II was Rs 8.12/- per one kg of green tea leaf, which shows that total marketing cost in channel-I is more as compared to channel-II, respectively. The total margin observed in channel-I was Rs 89.78/-, which was slightly higher than Rs 89.28/- per one kg of green tea leaf as obtained in channel-II, respectively. It can be concluded that channel-I is less efficient than channel-II. This shows that as intermediaries increases between producer and consumer, marketing efficiency decreases. In channel-I, producer‟s share in consumer price was Rs 10.00/-, which is less than Rs 11.81/- per kg of green tea leaf as obtained in channel-II, respectively. Detailed assessment and interpretation of the constraints faced by tea farmers were required to improve the net return, socio-economic status and also to find policy implications. Garrett‟s ranking method was used for the constraint analysis. The major constraints faced by small and large were same, the ranking procedure was performed separately for both production and marketing. High labour cost was considered as the major production constraint faced by tea growers and high price fluctuation of green tea leaves was considered as the most important marketing constraint faced by the tea growers in Wayanad district. Major portion of the cost of cultivation of tea was occupied by labour cost. So, farmers should get remunerative prices for their produce to compensate the labour cost. In the study area, usage of all of the inputs were under suboptimal levels, this should be further improved by educating or training the farmers with respect to the allocative efficiency of inputs. The role of commission agent can be minimized if direct purchasing by factories is practiced. Marketing of tea leaves and produce should be sold directly to processing units so that the farmers will get remunerative prices for tea leaves. To control high price fluctuation of green tea leaves, the fixation of suitable prices based on quality of green tea leaves will help the farmers. Thus the study can be a guide for planners and policy makers and reference for further studies.ThesisItem Open Access Value chain analysis of pineapple in Ernakulam district(Department of Agricultural Economics, College of Horticulture, Vellanikkara, 2020) Apeksha K, Rai; KAU; Chitra, ParayilPineapple (Ananus comosus) is a fruit with excellent juiciness, exciting tropical flavour and enormous health benefits. It is a rich source of Vitamin A, B and C and also contains a large number of vital nutrients for human health with less fat and cholesterol. It can be used to produce a large number of value-added products like jam, jelly, squash, pickle, candy, etc., which not only provides remunerative prices for the farming community in a sustainable manner but also creates employment opportunities for the unemployed rural community. The research work entitled “Value chain analysis of Pineapple in Ernakulam district” was undertaken to prepare the value chain map of Pineapple in Ernakulam district, to assess the value chain production system; evaluate their technical efficiency; to identify the institutional and infrastructural issues that affect the competitiveness of the selected value chain and to propose interventions for upgrading the Pineapple value chain. The study area was confined to Ernakulam district of Kerala state, since it accounted for 60 per cent of the Pineapple production in the state. The sample respondents were selected from Avoli and Manjaloor Panchayats of Muvattupuzha block and Koothattukulam and Ramamangalm Panchayats of Pampakkuda block. Twenty Pineapple farmers were selected from each Panchayat at random. In addition, data was collected from ten processors, five traders, five transporters and twenty consumers using separate sets of pretested interview schedules by personal interview method. The total sample size was 120. The data analysis was done by value chain mapping (Commodity Chain Analysis), descriptive statistics, growth analysis, cost concepts, Production function analysis, Data Envelopment Analysis(DEA), marketing concepts (market cost, market margin, price spread, market efficiency), rank method and Garrett ranking technique. The results of value chain mapping revealed that the major core processes included in the Pineapple value chain were input supply, production, collection, wholesaling, processing, retailing and consumption. The main actors who actively participated in the value chain were input suppliers, pineapple farmers, traders, exporters, wholesalers, processors, retailers and consumers. The facilitators involved in the value chain were sucker dealers, Krishibhavans, transporters, Pineapple Research Station (PRS), Pineapple Farmers’ Association (PFA), Pineapple Merchants’ Association, Kerala Pineapple Mission and financial institutions. Cost of cultivation for Mauritius variety was estimated for three years. The input cost estimated for first, second and third year was ₹ 500575, ₹ 277742 and ₹ 248188 ha-1 respectively. During the first year major share of the Cost A1 was contributed by planting material. During second and third year lease amount contributed more towards Cost A1. Net returns at Cost A1 for first, second and third year were found to be ₹ 476105 ha-1, ₹ 512729 ha-1 and ₹ 289576 ha-1 respectively. Second year reported higher net returns since variable cost like machine, planting material and manure cost were not considered as ratoon cropping system was followed. B:C ratio for Cost A1, Cost A2, Cost B and Cost C for three years were computed and it was found that Pineapple farming was profitable business in the study area and more profit can be earned by cultivating Pineapple in owned land than in leased land. From Production function analysis, it was found that plant density significantly contributed towards the yield and increasing returns to scale (1.56) was observed for Pineapple farming in the district. Data envelopment analysis showed the efficiency of Pineapple farm with a mean technical efficiency of 0.73 in Ernakulam. Mean scale efficiency and allocative efficiency value of 0.83 and 0.91 was obtained respectively. The marketing cost and marketing margin in fresh fruit and processed product channels were observed and found that traders and wholesalers incur maximum marketing cost in fresh Pineapple and processors in case of processed Pineapple. Traders and retailers earn more profit in fresh Pineapple whereas, processors in case of processed Pineapple channel. Producer share and marketing efficiency were found to be high for fresh Pineapple than the processed Pineapple. High cost of planting material and scarcity of hired labour were the major constraints in Pineapple production. Price fluctuation and decreasing demand were the major constraints in Pineapple marketing. The interventions drawn to upgrade Pineapple value chain include: 1) Supply of subsidized inputs at the farm level 2) Good agricultural practices should be followed to produce cost effective and export quality Pineapple 3) Advanced and affordable technology should be made available to farmers for value addition activities 4) Market yards, storage facilities and processing plants should be established and 5) Commercialization of new and improved Pineapple products. To conclude, the Pineapple value chain is lacking in horizontal and vertical integration among chain actors. The small producer-farmers are not able to reach the final market directly as they are dominated by the extended value chain actors and this situation made their position weak and helpless in the market with less bargaining power.ThesisItem Open Access Effect of salinity on paddy production in Alappuzha district of Kerala an economic analysis(Department of Agricultural Economics, College of Agriculture, Vellayani, 2020) Nithin Raj, K; KAU; Paul Lazarus, TThe present study entitled “Effect of salinity on paddy production in Alappuzha district of Kerala- An economic analysis” was conducted during 2019-20, with specific objectives of examining the resource use efficiency in paddy production, to analyse the impact of salinity on crop production and farm income and to study the major constraints faced by paddy farmers. The current study was focused on both primary as well as secondary data. The study was conducted in the salt water affected and unaffected paddy fields of Alappuzha district. Primary data was collected from the farmers through formal interviews. Farmers in the study area were grouped in to salt water affected and unaffected farmers based on the extent of salinity levels in the area. From each of the two groups, 25 salt water affected and 25 unaffected farmers were selected. Thus the total sample size was 50. Secondary data pertaining to water salinity, socio economic status and physiographic factors were collected from various sources. Average annual cost of cultivation of paddy by the salt water unaffected farmers was almost similar to that of salt water affected farmers and was found to be ₹ 1,03,322.85 and ₹ 1,04,145.13 per hectare respectively. In both the case of the unaffected and affected farmers, per cent share of hired labour in the total cost A1 was highest followed by machine labour. The average cost of production of paddy by the salt water unaffected and the affected farmers were ₹ 17,200 and ₹ 27,398 per tonne respectively. Cobb-Douglas production function was fitted separately for rice production among salt water affected and unaffected farmers to examine the resource use efficiency. The results showed that R2 value for salt water unaffected and affected paddy cultivation was 0.90 and 0.89 respectively and it indicated good fit of both the regression models. Marginal productivity analysis for examining the allocative efficiency showed that, all the variables except manures and fertilizers were having a K value of more than unity, indicated the suboptimal utilization of the resources. The average rice yield obtained from paddy cultivation in the salt water unaffected and affected area was 6.01 and 3.80 tonnes per hectare respectively. Chow test was used to analyse the effect of salinity on rice production. The test revealed significant differences in regression coefficients and hence concluded that the two groups differ significantly. Farmers in salt water unaffected areas obtained a gross income of ₹ 1,61,883.36 per hectare while farmers in salt water affected area obtained ₹ 1,02,443.05 per hectare. Farming in salt water unaffected areas were highly profitable at cost C with a B-C ratio of 1.57, but it was not much profitable for the unaffected farmers (0.98). Weed problems and scarcity of hired labour was the severe constraint faced by most of the farmers from salt water unaffected areas. But the major constraint for paddy production in the salt water affected area was salt water intrusion. According to the farmers, main reason behind the salt water intrusion in to their paddy fields was the improper construction and maintenance of bunds. Majority of the farmers perceived that, there was an increase in cost of cultivation, usage of machines, market price of paddy, availability of seeds, labour wages, emergence of new weeds and use of adaptation or mitigation strategies for preventing salt water intrusion in Haripad over the past ten years. In order to avoid the problem of quality deterioration of paddy in the salt water affected areas, more researches may be directed towards the development of location specific high yielding salinity tolerant rice varieties in the years envisaged. Usage of majority of the inputs were under suboptimal levels, this component needed to be further improved by educating or training the farmers with respect to the economic efficiency of inputs. It was found from study that there was overutilization of fertilizer in the study area. Hence, soil test based fertilizer recommendation could be suggested for farmers in Haripad. The conflicting needs by paddy farmers and fish farmers in the case of salt water intrusion need to be addressed properly. Institutional measures may be made more effective, which is the most important factor to address the issue of salt water intrusion.ThesisItem Open Access Economic impact of an extreme weather event on the production of cardamom in Idukki district of Kerala(Department of Agricultural Economics, College of Horticulture, Vellanikkara, 2020) Elizabeth, Benny.; KAU; Paul Lazarus, TThe study entitled ‘the economic impact of an extreme weather event on the production of cardamom in Idukki district of Kerala’ was carried out with objective to assess the loss in production of cardamom due to extreme weather event of 2018, to analyse its effect on farm income, and to examine the adaptation strategies to mitigate the loss. Primary data were collected from Santhanpara and Senapathy gramapanchyats of Idukki district with a pre-tested well-structured survey schedule. From each gramapanchayat twenty five cardamom farmers were selected and the total sample size was fifty. The relevant secondary data regarding climatic variables, area, production and productivity of cardamom in Idukki district were collected from the concerned institutions. The study followed damage and loss assessment methodology given by FAO to assess the major objective. It also followed ABC cost concepts, percentage analysis, Garrett’s ranking technique to find meaningful results. The annual maintenance cost of cardamom for the pre disaster year 2017-18 was calculated using ABC cost concept. The total cost (Cost C) of cultivation incurred by farmers was ₹6,83,366.06 ha-1. B:C ratio at Cost C was calculated as 1.29 which indicated that the cardamom cultivation is profitable. The heavy rainfall during 2018 had resulted in severe landslides and erosion causing the death of several people and considerable damage to dwellings and the crops cultivated. There was a huge loss of 404.25 kg per ha of cardamom in Santhanpara gramapanchayat and 349.61 kg per ha in Senapathy gramapanchayat to an expected yield of 901.21 kg per ha and 889.57 kg per ha cardamom respectively. It was revealed that due to extreme weather event 42.09 per cent of expected yield was lost to farmers and only 518.49 kg per ha of cardamom was the harvested yield. The total area covered by respondents were 57.41 ha. The value of total loss that occurred among the respondents were ₹ 2.50 crores. Out of which 84.67 per cent was due to the yield loss. Short run expenses and replacement costs were 10.26 per cent and 5.06 per cent respectively. The loss incurred per hectare in cardamom was ₹ 4.37 lakhs and loss accounted per farmer was ₹ 5.02 lakhs. The disaster loss per hectare was extrapolated to the total area of cardamom in Idukki district, it was a whooping sum of around ₹1362 crores. Cardamom contributed more than 90 per cent of farm income during year 2017-18. The income from cardamom of respondents in Santhanpara gramapanchayat and Senapathy gr mapanchayat in 2017-18 were ₹ 2.4 crores and ₹ 2.5 crores respectively which formed a total of ₹ 5.04 crores. After the incidence of extreme weather event farmers faced about 42.08 per cent of shortage in farm income from cardamom. The total farm income from cardamom during disaster year was reduced to ₹ 2.92 crores. Most of the farmers regularly follows weather updates. However, none of the farmers insured their crops against natural calamities. Through crop insurance scheme, natural calamity affected cardamom plantations get an assistance of ₹ 60000 per hectare. Natural calamity assistance was given by government of Kerala through Krishi bhavans and farmers who suffered crop loss were got a compensation of ₹ 25000 per hectare. Adaptation strategies were followed by farmers in order to reduce the vulnerability to extreme weather events. Most of the farmers practiced prophylactic spraying of fungicides as an adaptation strategy. Around 22 per cent of farmers were not following any adaptation strategies. The other adaptation strategies such as mulching, cultivation of different varieties and construction of shallow ditches to facilitate water flow were followed. Most of them followed crop diversification, livestock rearing, aquaculture to avert risk. The study examined the problems faced by farmers of cardamom cultivation in the post disaster scenario. Constraints for production of cardamom faced by farmers were high cost plant protection chemicals and high incidence of pest and diseases. Fluctuation in market price and delay in payment of sale proceeds were identified as the major marketing constraints. The major barriers to adaptation were lack of knowledge about adaptation practices, lack of disease resistant varieties and high cost of adaptation. Marginal farmers were not eligible to receive crop insurance there exists a ceiling of one hectare productive cardamom land to receive the indemnity amount. Hence as a policy matter the government may consider reducing the existing ceiling of one hectare productive cardamom land. The farmers can reduce the risk through diversification of crops and mixed farming. It reduces the extent of loss at times of disaster. Better maintenance of farm with proper phyto sanitary measures will help the farmers in reducing the incidence of pests and disease and therefore the cost on plant protection chemicals can be reduced. Delayed payment for the produce and high volatility in prices is a matter of concern which point outs the need for urgent institutional interventions in cardamom marketing. Farmers need more varieties of cardamom resistant to pest and diseases without compromising on high yield. Future researches can be directed towards this goal. Thus, the study can be a reference for planners and policy makers.ThesisItem Open Access Economic analysis of production and marketing of tea in Wayanad district(Department of Agricultural Economics, College of Agriculture, Vellayani, 2020) Marupilla, Supriya; KAU; Paul Lazarus, TThe present study entitled “An economic analysis of production and marketing of tea in Wayanad district” was conducted during 2019-20. The specific objectives of the study was to know the input use pattern, analyze the costs and returns from tea cultivation, to examine resource use efficiency, to study marketing aspects and constraints in the production and marketing of tea. The study was based on both primary and secondary data. The study was conducted in Muppainad village from Kalpetta block and Ambalavayal village from Sulthan Bathery block in Wayanad district. Primary data was collected from the farmers through formal interviews. The farmers in the study area were categorized into two groups on the basis of size of land holding small farmers (≤ 2 ha land) and large farmers (>2 ha of land). From each of the selected village panchayats, 12 farmers each of small and large size will be selected. The total sample size of study was thus 48. Secondary data pertaining to tea production and marketing and data regarding socio- economic status physiographic and demographic factors were collected from the official websites and government annual reports. On average, the total amount of human labour utilized was 404.80, 324.64 and 382.50 mandays per hectare on large, small and pooled farms respectively, and thus indicated a direct relationship between human labour and the size of the farm. The major labour needed operations were harvesting (87.60%) followed by application of fertilizers and manures (3.97%), plant protection chemicals (3.52%), pruning (3.03%) and weeding (1.88%) on pooled farms. Among the owned and hired labour, owned labour occupied 7.83 per cent and hired labour occupied 92.16 per cent on pooled farms. The annual maintenance Cost of cultivation of tea was carried out using cost concepts. The total cost of cultivation (cost C) of tea incurred by the small and large farmers was found to be ` 1,86,438.82 ha-1 and ` 2,45,143.60 ha-1 respectively. It was found that cost of cultivation was more for large farmers than small farmers. For both small and large farmers, per cent share of hired labour in cost A1 was the highest followed by manures and fertilizers. The net return at cost C for small and large farmers was ` 85,943.18 ha-1 and 1,54,156.40 ha-1 respectively. It was found that profitability was more for large farmers with a B:C ratio of 1.46 while small farmers had a comparatively smaller B:C ratio of 1.62. Resource use efficiency in tea cultivation was estimated using Cobb-Douglas production function and it was fitted separately for small and large farmers. The results showed that R2 value for small and large farms in tea cultivation was 0.71 and 0.90 respectively and it indicated good fit of both the regression models. Marginal productivity analysis showed that, all the independent variables were having a K value more than one, which indicated the suboptimal or underutilization of resources by both small and large farmers. Allocative efficiency of these inputs can be improved only by the enhanced utilization. The study done on the respondent farmers revealed that there existed two marketing channels of tea: Marketing channel- I Producer Commission agent Processing unit Wholesaler Retailer Consumer Marketing channel-II Producer Processing unit Wholesaler Retailer Consumer In channel-1 The total marketing cost incurred was Rs 9.22/- and the total cost incurred in channel-II was Rs 8.12/- per one kg of green tea leaf, which shows that total marketing cost in channel-I is more as compared to channel-II, respectively. The total margin observed in channel-I was Rs 89.78/-, which was slightly higher than Rs 89.28/- per one kg of green tea leaf as obtained in channel-II, respectively. It can be concluded that channel-I is less efficient than channel-II. This shows that as intermediaries increases between producer and consumer, marketing efficiency decreases. In channel-I, producer‟s share in consumer price was Rs 10.00/-, which is less than Rs 11.81/- per kg of green tea leaf as obtained in channel-II, respectively. Detailed assessment and interpretation of the constraints faced by tea farmers were required to improve the net return, socio-economic status and also to find policy implications. Garrett‟s ranking method was used for the constraint analysis. The major constraints faced by small and large were same, the ranking procedure was performed separately for both production and marketing. High labour cost was considered as the major production constraint faced by tea growers and high price fluctuation of green tea leaves was considered as the most important marketing constraint faced by the tea growers in Wayanad district. Major portion of the cost of cultivation of tea was occupied by labour cost. So, farmers should get remunerative prices for their produce to compensate the labour cost. In the study area, usage of all of the inputs were under suboptimal levels, this should be further improved by educating or training the farmers with respect to the allocative efficiency of inputs. The role of commission agent can be minimized if direct purchasing by factories is practiced. Marketing of tea leaves and produce should be sold directly to processing units so that the farmers will get remunerative prices for tea leaves. To control high price fluctuation of green tea leaves, the fixation of suitable prices based on quality of green tea leaves will help the farmers. Thus the study can be a guide for planners and policy makers and reference for further studies.ThesisItem Open Access Economic analysis of cowpea seed production in Palakkad district(Department of Agricultural Economics, College of Horticulture, Vellanikkara, 2020) Vechalapu Lakshmi, Sindhuja; KAU; Chitra ParayilCowpea [Vigna unguiculata (L.) Walp.] is one of the most essential food which is extensively adapted, stress tolerant grain legume, vegetable, and fodder crop. Kerala is striving to move towards self-sufficiency in vegetables and in this context, the timely availability of quality seed is gaining importance. Plant types are often categorized as trailing and semi trailing varieties. The varieties selected for the study were Vellayani Jyothika which is of trailing type, Anaswara, which is a semi-trailing variety (both for seed purpose) and Arka Mangala which is of trailing type was selected for comparison between seed and vegetable production. The two blocks selected for the study were Nenmara and Chittur because these blocks had maximum number of registered farmers. The registered farmers under VFPCK’s seed production of cowpea were selected for the study. From the list of registered farmers, farmers growing both vegetable and seed cowpea with at least 50 cents area were selected at random. Twenty farmers were selected from Nenmara block and 60 farmers were selected from Chittur block in proportion to the area of seed production undertaken by VFPCK in the respective blocks. The results of the study are as follows. The distribution of respondents based on age showed that majority of cowpea seed farmers fall under 50-60 years age group. It was observed that the farmers who had secondary school education fell in this category. Majority of the respondents were in the medium-sized family category (4-6 members). The findings support the fact that joint families are on a decline. It was observed that respondents had about 25-30 years’ experience in seed production of cowpea. The results showed that they were mostly small holding farmers (1-2 ha) who are involved in cow pea seed production. The growth rate of area and production for vegetables in Kerala were negative -0.26 per cent and -0.14 per cent respectively, while the growth rate for productivity was positive (0.85%) and was found to be significant. This indicates that there has been a significant increase in the productivity of vegetables in Kerala due to the introduction of HYVs during this period (1991-2018). It was found that the cost of cultivation for Anaswara (Rs.148386.8 ha -1 ), Vellayani Jyothika (Rs. 164065.4 ha -1 ) were high in Chittur and for Arka Mangala varieties (Rs.119991 ha -1 ) was high in Nenmara. The reason was a marginal increase in the wage rate in Chittur compared to Nenmara. Anaswara (Rs. 235015 ha-1) and Vellayani Jyothika (Rs. 383925 ha-1) yielded higher in Chittur compared to Nenmara. The B:C ratio for the varieties were Vellayani Jyothika (2.36) which is high in Chittur, followed by Anaswara (1.58), it was high in Nenmara and for Arka Mangala it was 1.60, which were same in both the blocks. The findings indicate that Vellayani Jyothika variety had high procurement price of seed, high returns and higher B:C ratio. The returns to scale was also greater than one i.e. 1.29, indicating increasing returns to scale in cowpea. Cobb-Douglas production function was fitted to estimate the resource use efficiency in Cowpea and it was found that quantity of labour contributed significantly towards the increase in the yield. Marginal productivity analysis was carried out and it was found that the k ratio (MVP/MFC) for the resources, quantity of labour and quantity of manures and fertilizers were found to be greater than one. This indicated sub-optimal utilization of these resources. The k-value for rouging (man days/ha) and quantity of plant protection chemicals were found to be less than one, which indicates excess utilization of the above resources. The results of linear regression to understand the factors affecting availability of seed to vegetable farmers in general are pests and diseases attack and costs of production of different cowpea varieties. High cost of input seed and limited returns from vegetable cowpea are the major constraints faced by the cowpea farmers. Since the procurement prices of seeds have been recently revised, it can be concluded that seed production in cowpea is highly remunerative, given the increasing demand for quality seeds in vegetables. Thus cowpea seed production can be seen as a profitable venture in order to proceed towards the path to self-sufficiency in vegetables in our state.ThesisItem Open Access Assessment of agricultural loss due to 2018 flood to farm households in the flood pains of Chalakudy river(Department of Agricultural Economics, College of Horticulture, Vellanikkara, 2020) Femi Elizabeth, George; KAU; Prema, ADisaster-induced economic damage has been increasing in the past few decades and is likely to continue growing because of urban development, population growth and ecosystem alteration. The state Kerala, with its location along the sea coast with a steep gradient along the slopes of the Western Ghats is highly vulnerable to natural disasters. Floods are the most common natural hazard in the State. Kerala encountered the most exceedingly awful floods in its history since 1924, between June 1st and August 19th of 2018. The state‟s economy and a large number of agriculture dependent rural households, most of which are involved in subsistence agriculture, are found to have borne the brunt of the unprecedented deluge and its aftermath. It is in this context that the present study entitled „Assessment of agricultural loss due to 2018 Flood to farm households in the flood plains of Chalakudy river‟ was undertaken. Damage and Loss Assessment (DaLA) methodology given by the Food and Agriculture Organization (FAO) in 2012 was used for the damage and loss assessment with appropriate modifications. The term damage in the study means destruction (total or partial) of physical assets, while the term loss indicates the change in economic flows arising from the disaster. The study was conducted selecting 10 panchayats across three blocks, viz. Chalakudy and Mala blocks in Thrissur district and Parakkadavu block in Ernakulam district. Both primary as well as the secondary data were used for the study, however, the study was based mostly on primary data. The assessment of disaster effects on the farm households along the flood plains of the river with respect to damage and loss suffered to crops, assets and livestock showed that on an average a farm household in the flood plain has suffered a damage of ₹12,837 to agricultural assets, while the damage suffered was ₹75,538 for seasonal crops and ₹9,391 for perennial crops. With respect to livestock and poultry, on an average a farm household has suffered a damage of ₹12,216. Crop loss to the individual farm households as the crops were either damaged/lost or the production declined was also estimated. The results revealed that on an average a farm household xxx in the flood plain has suffered a loss of ₹1,59,469 from seasonal crops and ₹1,52,358 from totally destroyed perennial crops and ₹32,854 from partially destroyed perennial crops. The result suggested that it is the loss from seasonal crops which was accounted as investment loss contributed the most to the total loss suffered by a farm household. The assessment of disaster effects in the flood plains of the river with respect to damage and loss suffered to crops, assets and livestock showed that the flood plain has suffered a damage of ₹7.32 crores to agricultural assets, while the damage suffered was ₹43.10 crores for seasonal crops and ₹5.36 crores for perennial crops. The flood plain has lost about ₹6.97 crores due to the death of livestock and poultry. An estimation of the agricultural loss was also carried out in the flood plains as almost all the households reported losses from seasonal crops and perennial crops. The study showed that the flood plain has suffered a loss of ₹90.85 crores from seasonal crops and ₹86.72 crores from totally destroyed perennial crops and ₹18.55 crores from partially destroyed perennial crops. The study concluded that the flood plain has lost about ₹258.87 crores to the 2018 Kerala floods. An attempt was made to analyse the resilience level of the affected farmers. In the study wherein resilience was taken as the ability of the farmer to continue next season cropping, it was found that the sample respondents on an average showed a resilience of 0.48 in a scale of zero to one. Risk orientation, level of indebtedness, insurance, relief fund, savings, other losses and damage level were found to be the important perceived factors that help in building resilience with importance of these factors in the order mentioned above. The results of logistic regression to understand the influence of socio-economic variables on resilience suggested that while education and subsidiary occupation positively influenced the resilience, family size and crop diversification index was found to have a negative influence. Major hardships faced by the respondents were identified as flooded house, crop loss, disruption in power supply, inadequate transportation facilities, field inundation, disrupted communication services, loss of labour days and non-availability of drinking water. Keeping in view the inconsistencies with regard to the xxxi xxxi estimated flood impact to agriculture and the corresponding reported values by the Government offices, adopting standardized methodological approach based on internationally approved frame work for assessing the impact of disasters on agriculture was suggested as the major policy intervention. Understanding the importance of having a subsidiary income in building the farmer resilience, encouraging farmers to take up different crop related and other enterprises was the other major policy intervention suggested.ThesisItem Open Access Structural transformation and spatio temporal variations of agriculture in Kerala(Department of Agricultural Economics, College of Horticulture, Vellanikkara, 2020) Otieno Felix, Owino; KAU; Anil, KuruvilaKerala had been undergoing several transformations in its agricultural sector. This was caused by the shift of resources like labourers from the agricultural sector to the secondary and tertiary sector. The transformation could also be seen where ever the rising agricultural wages affected the profitability of major crops due to the increase in the cost of production. The shortage of farm labourers coupled with other factors like uneconomic size of land holdings, sustained conversion of agricultural lands to non-agricultural uses and low profitability in agriculture had hampered the growth in the sector. The structural adjustments could also be observed in the state income in which there was an increase in share of income from the tertiary sector and decline in share from the primary sector. The decline in the share of agriculture in the state income was due to an aggregation of factors. Thus, the present study sought to find out the reasons leading to the transformations in Kerala agriculture by analysing the growth of agriculture and assessing the disparities among the districts in agricultural development in Kerala, examining the dynamics in land use and cropping patterns, studying the dynamics in economics, efficiency and profitability of cultivation of major crops and estimating the total factor productivity and its determinants for major crops in Kerala. The time series data for the period from 1970-71 to 2018-19 was used to understand the objectives of this study. The entire series was subjected to (Bai and Perron, 1998) methodology and six phases of growth were obtained, on which the entire study was based. These periods were Period I (1970-71 to 1980-81), Period II (1981-82 to 1987-88), Period III (1988-89 to 1994-95), Period IV (1995-96 to 2003-04), Period V (2004-05 to 2010-11) and Period VI (2011-12 to 2018-19). The Compound annual growth rates and Cuddy-Della Instability Indices were used to understand the growth performance of the crops. The results of the analyses of growth in crops revealed that food grains, tapioca, ginger and cashew had the largest loss in area throughout the period under study. Pulses, paddy, tapioca, cashew and ginger exhibited annual declines of -6.58 per cent, -3.89 per cent, -3.71 per cent, -2.44 per cent and -2.12 per cent in their area. These crops also had the lowest growth in productivities which affected the production. This was found to be due to fall in the prices of these crops, rising cost of inputs and rising prices of other crops. Rubber had the largest annual rise in area of 2.56 per cent in the entire period of the study. Other crops that were found to have performed well were coconut and banana and other plantains. The trend break analysis was also used to study the growth performance of crops in Kerala. It was established that the main reason for breaks in areas under most crops was related to profitability. It was noted that with increases in prices, especially for plantation crops, the areas under the crops also increased. Several crops had breaks in their areas exactly at the time when rubber was recording its best prices in 1995 and from 2007-08 to 2009-10. Due to the sustained rise in prices of rubber, crops like paddy were much affected, since it is a labour-intensive crop and an increase in the wages of field labour impacted it negatively. Plantation crops on the other hand were less labour intensive and the increases in prices were an incentive for the farmers to expand the area under the cultivation of those crops. In turn, the area under rubber and coconut increased tremendously especially from late 1980s. Thus, changes in prices was a major cause for most breaks in most of the crops. The government policies and interventions in the agricultural sector were found to be the major contributor to the trend breaks. The introduction of policies that promoted the cultivation of crops such as paddy led to increase in their areas and these led to the breaks. These include the group farming scheme implemented in 1988-89, promotion of paddy cultivation in the fallow lands of 2004-05 and the enactment of the conservation of paddy land and wetland act of 2008. Seemingly Unrelated Regression (SUR) model was used to understand the determinants of the growth in the GSDP from agriculture. The model revealed that the largest contributor to per capita agricultural GSVA was gross cropped area irrigated. This meant that for every additional hectare of land brought to irrigation every year, it added 75.3 per cent of the value of the output per hectare from the crop to the per capita income from agriculture. The area under high value crops was also found to be significant and positively influencing per capita GSVA from agriculture and this was a confirmation that increased cultivation of high value crops was key to growth in earnings from agriculture in Kerala State. The fertiliser consumption was also found to be important in improving the earnings realised from agriculture. The use of fertilisers improved the contribution from crops to the agriculture per capita income by 24 per cent, while rainfall improved the earnings by 10.5 per cent. The study on the land use and cropping pattern changes revealed through transition probability matrices obtained from Markov chain analyses showed that various land use classes apart from forest were not stable throughout, but had seasons of loss and gain to and from other different land use classes, which was also the same case for crops. For instance, area put to non-agricultural uses and, permanent pastures and grazing lands were the most stable land use classes in the first phase of the study (1970-71 to 1980-81). This phase was the beginning of shift from various crops to plantation crops and large tracts of lands in which other crops were grown were converted to the cultivation of plantation crops like rubber due to increasing prices and profitability. This shift in land use helped to increase the net sown area. The net sown area also had 4.4 per cent probability of receiving land from permanent pastures and grazing lands, and a probability of 21.4 per cent from area under miscellaneous tree crops. However, in contrast to the first phase, in the last and sixth phase from 2011-12 to 2018-19, the area under non-agricultural uses which got a stimulus in the fifth phase, showed a 100 per cent probability of holding to its share in the sixth phase. The cultivable waste drew gains from net sown area. The area under pastures showed a 93.2 per cent of probability of transition to net sown area, an indication that the area under permanent pastures and grazing lands was getting cleared and converted to farm lands. The study on economics, efficiency and profitability of crops revealed that the profitability of tapioca, coconut and black pepper were highest in the large and medium holdings. Ginger presented an inverse of the trend shown in many crops in which small holdings were the least profitable. This was attributed to complexities in managing large ginger farms which were prone to diseases. Overall, the profitability improved over the period under study for all the crops other than ginger, which could be attributed to increased use of high yielding varieties and efficient fertilisers that improved the productivity. Banana and other plantains, autumn paddy and coconut had the largest TFP. The TFP growth in these crops were majorly driven by increases in their technological components. Winter paddy and summer paddy also had a slight increment in their TFP mainly driven by growth in their technological changes and hindered by decline in their technical efficiencies. Tapioca, black pepper and ginger recorded negative changes in their TFPs. The decline in TFP of these crops was majorly due to the decline in the technological changes in these crops. Therefore, there is need for increased public investment in the agricultural sector. The increased public investment will in turn promote private investment in potential areas of the state, which will sequentially help to provide incentives and favourable environment for agricultural development.ThesisItem Open Access Risk analysis of agricultural economy of Wayanad(Department of Agricultural Economics, College of Horticulture, Vellanikkara, 2020) Thomas, K S; KAU; Anil, KuruvilaRisk is inevitable in agriculture as the farmers have very limited control over the production and marketing process. The uncertainties in weather, yield, prices, and government policies cause wide variations in farm income. Agrarian crises were prevalent in Wayanad district due to fall in prices of commodities, indebtedness, flood, drought, and instabilities in income. The present study estimated the agricultural risks in Wayanad district, identified the sources of risks and risk preferences of farmers, and assessed the types and determinants of coping mechanisms in the farm households of Wayanad. The study was based on both primary and secondary data. The primary data was collected from 100 respondents across four blocks in the district selected by the proportionate random sampling method, using a pretested interview schedule. There has been an increase in the Compound Annual Growth Rate (CAGR) of area and production of coffee, arecanut, rubber and coconut from 1981-82 to 2018-19. The decomposition analysis of production of crops showed positive effects of area in coffee, arecanut, coconut and black pepper. The productivity effect was found to be positive for coffee, rubber, coconut and paddy during the same period. Growth accounting analysis showed positive influence of prices on the growth in revenue from arecanut, rubber, coconut and black pepper. The analysis of trend breaks in area and production of crops carried out using Chow test showed significant trend break in area for coffee, arecanut, rubber, coconut, black pepper and paddy. Except for coconut and paddy, a significant trend break was also observed in the production of other crops. The estimation of climatic risks using Just and Pope production and risk functions showed that standard deviation in temperature and standard deviation in rainfall negatively influenced the production of coffee and black pepper respectively. The mean annual temperature was found to increase the production of coconut, while decrease the production of rubber. None of the climatic factors were found to influence significantly the variability in yield of any of the crops. The analysis of price instability using Cuddy-Della Valle index showed highest instability in prices for black pepper, followed by coconut, arecanut and rubber. The analysis of instability in income from the primary sector of Wayanad for the period from 1982-83 to 2018-19 using chain index and link relatives showed high income fluctuations. Compared to 1982-83, the income grew by 630 per cent in 2004- 05, which then decreased to 276 per cent in 2018-19. The district was found to have very high levels of crop diversification (Herfindahl index < 0.33) during all the years from 1981-82 to 2018-19. The production risks in Wayanad were identified using primary data by employing Just and Pope production and risk functions. Along with area, the other factors accounting for significant variability in production were identified as cost of human and machine labour for coffee, cost of machine labour and fertilizers for black pepper, and cost of human labour for coconut. Crop loss was found to be the highest in black pepper, both in terms of quantity (50 per cent) and number of respondents facing the loss (43 per cent). Using Garret ranking technique, low price and price fluctuation of products was identified as the major risk, followed by climate change and natural calamity, and shortage of labourers. The major risk coping strategies adopted by the respondents were identified as storage of produce, irrigation, employing family labour, and chemical control of pests and diseases. Other risk coping strategies were subscription of crop insurance, crop diversification (63 per cent respondents having Herfindahl index less than 0.5), income diversification, availing credit, and sale of assets. It was also found that 72 per cent of the respondents were beneficiaries of PMKISAN programme implemented by Government of India. The risk appetites of respondents were elicited using risk question and risk game. When majority of the respondents (52 per cent) assessed themselves to be moderately risk taking, risk game showed majority of them (35 per cent) to be extremely risk averse. The significant factors influencing the risk appetite of respondents were analysed using different regression models. Multiple regression showed factors like experience in farming, education, land holding size, and net revenue from agriculture to be significantly influencing the risk appetite. Logistic regression identified factors like land holding size, net revenue from agriculture, and non-farm income to be significantly influencing the classification of respondents as risk averse or risk takers.
