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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.
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ThesisItem Open Access Export performance and value chain analysis of chilli in India(Department of Agricultural Economics, College of Agriculture, Vellanikkara, 2021) Akhil Reddy, M; KAU; Anil, KuruvilaChilli and chilli products are the most important spices exported from India. The country is world's leading producer of chilli as well as exporter, accounting for almost half of the global export volume of chilli. The present study entitled “Export performance and value chain analysis of chilli in India," analysed the performance of chilli exports from India; assessed the export competitiveness measures and factors affecting chilli exports from India and undertook the value chain analysis of chilli in Telangana and Andhra Pradesh. The export performance of Indian chilli was examined for the period from 1960 to 2019. The rate of growth in chilli exports from India has increased in the post-2001 period as compared to the pre-2001 period, while the instability of chilli exports has decreased in the post-2001 period. Among all the decomposed components of the changes in the average export value, the contribution of the changes in the mean export unit value of chilli was found to be highest. The commodity concentration of chilli exports from India was high in pre-2001 period and the exports became more diversified in the post-2001 period. The average value of the commodity concentration index for chilli was 76.46 for the overall period from 1986-87 to 2019-20. The exports of chilli from India became increasingly diversified to different countries and hence the Gini concentration indices have decreased over the years. Before 2001, the geographic concentration estimated using the Hirshman index was above 40 per cent, denoting the higher level of concentration and uneven distribution of export markets. The Markov chain analysis showed that in the post-WTO period, a greater number of stable markets for chilli exports from India were identified. China, Thailand, Malaysia, Vietnam, Pakistan, Brazil and Indonesia became major markets for Indian chilli exports in the post-WTO period. China was an unstable export market for Indian chilli in the pre-WTO period, but it became a stable market in the post-WTO period due to high demand for chilli in China. The increasing trend in the trade complementarity indices of India with partner countries in the trade of chilli after 2001 confirmed that India and its partner countries are becoming more complementary, which implied that India’s export pattern was matching with the import requirements of those countries. The estimated elasticity coefficients of the log-log model for finding out the determinants of Indian chilli exports showed that the production in India and the international price were statistically significant and having positive effects on export supply of Indian chilli, while an increase in the domestic prices and real exchange rate were found to result in a II decrease in the export of chilli from India. The Revealed Comparative Advantage (RCA) analysis showed that India and China were having high comparative advantage in the production and export of chilli. The estimated Nominal Protection Coefficient (NPC), Effective Protection Coefficient (EPC), and Domestic Resource Cost Ratio (DRCR) values were found to be less than one. The Policy analysis Matrix (PAM) analysis under exportable hypotheses suggested that Indian chilli was a moderately competitive crop as an export commodity. The findings revealed that chilli was an efficient exportable item, demonstrating Indian chilli's international competitiveness. The analysis of demand for chilli in the value chain showed that the countries with greatest potential for export of chilli from India are China, United states of America, Thailand and Sri Lanka. The markets with greatest untapped potential for India’s chilli exports are USA, China and Spain. The highest number of NTMs on chilli exported from India were imposed by China, USA, Sri Lanka and Vietnam. The analysis of institutional set-up of chilli value chain has shown that the major institutions providing technical, extension and administrative supports in the chilli value chain are Spices Board, Directorate of Marketing and Inspection (DMI), National Horticulture Board (NHB), Agricultural and Processed Food Products Export Development Authority (APEDA), State Agricultural Marketing Board (SAMBs), Department of Agriculture, Agricultural Produce Market Committees (APMC), Regional Agricultural Research Stations (RARS), and Krishi Vigyan Kendras (KVK). The major input suppliers for chilli are fertilizer and pesticide shops owned by input dealers and majority of the farmers were growing the chilli variety “Teja”. The Supply Utilization Account (SUA) published by the Food and Agriculture Organisation (FAO) was used to analyse the quantity flows of chilli along the value chain in India. In 2018-19, the production of chilli in India was 18,08,011 tonnes, out of which, 12,52,823 tonnes were used for consumption. The opening stock was 8,87,466 tonnes and the import and export quantities were 1,361 tonnes and 3,86,276 tonnes respectively. The closing stock in the country was 10,13,683 tonnes. The estimated weighted average of cost A incurred for chilli cultivation in the sample districts was computed as ₹3,33,459 per ha. The weighted average value of cost B and C for chilli cultivation in these districts were ₹3,98,014 per ha and ₹4,67,610 per ha respectively. The highest values for all the three costs were found in Guntur, whereas it was the least for Mahabubabad district. The major share of input-wise cost incurred for cultivation of chilli in all the districts under study was accounted by hired human labour and was followed byfamily labour. The weighted average of net returns estimated at cost A, B and C were ₹4,69,312 per III ha, ₹4,13,339 per ha and ₹3,44,097 per ha respectively. The B-C ratio for chilli cultivation at cost A varied between the highest value of 2.66 for Guntur and the lowest value of 2.09 for Mahabubabad. The B-C ratio for chilli cultivation at cost B was found to be highest (2.2) in Guntur, while it was lowest (1.83) in Mahabubabad. Similarly, B-C ratio at cost C varied between 1.90 in Guntur and 1.48 in Mahabubabad. The price spread in marketing of chilli was found to be highest in channel IV for dry chilli, while in the case of chilli powder, channel III had the highest price spread. The producer’s share in consumer’s rupee was highest (80.89 per cent) and the price spread was found to be the least (₹27.29/kg) in channel II for dry chilli, while for chilli powder the producer’s share in consumer’s rupee was highest (60.89 per cent) and the price spread was found to be the least (₹89.45/kg) in channel V. The marketing efficiency for dry chilli was found to be highest in channel I due to low marketing cost, and it was highest for chilli powder in channel V as the price paid by the consumer in this channel was the highest. The scarcity of labour was identified as the most important constraint in the production and marketing of chilli and high labour charges as well as price volatility were identified as the other important constraints. Lack of infrastructural facilities like storage and processing were identified as the most significant constraint faced by the intermediaries. The major constraint faced by chilli exporters was highly volatile international price, and in the case of processors, the lack of infrastructure was identified as the major constraint. As SPS measures were the major NTMs in International trade, the quality of Indian chilli should be ensured by encouraging the farmers to adopt Good Agricultural Practices (GAP), while the processors should be motivated to implement Good Manufacturing Practices (GMP). Development of proper warehousing facilities is essential for scientific storage of chilli as absence of proper storage facilities was reported as a major constraint. The chilli prices were highly volatile and hence the recommendation of Minimum Support Price (MSP) or possibility for making a price deficiency payment to the farmers based on a realistically estimated base price need to be explored. The dissemination of timely marketing intelligence is necessary to help the farmers to decide on the time of harvest, period of storage and place of sales. Indian chilli exports were found to be concentrated on few products and the country needs to explore the possibilities for value addition and product diversification which will help the farmers to move up in the value chain. India needs to develop trade policies to sustain as well as increase the share in stable export markets of chilli and must make efforts to enter non-traditional markets.ThesisItem Open Access Economic analysis of rice based integrated farming system models in Kuttanad(Department of Agricultural Economics, College of Agriculture, Vellanikkara, 2021) Nanda, Baiju; KAU; Prema, AIn any developing economy, in order to attain pro-poor growth and economic development, it is necessary that the agriculture sector flourishes, along with improvement in farmers’ income. According to Agricultural Census of 2015-16, the average operational land holding in Kerala was found to be 0.18 ha. Hence, the scope of horizontal expansion is limited and the only possible alternative is vertical expansion. Integrated Farming System (IFS) is a resource management strategy that ensures year round income to the farm families with the integration of appropriate subsidiary enterprises. It helps in meeting the diverse requirements of the farm household, ensures employment generation and sustainable livelihood of small and marginal farmers along with minimizing the risk associated with monocropping. Rice farmers in Kuttanad have taken up subsidiary enterprises like duckery, fish, dairy and poultry to ensure additional returns. The different IFS models identified among the 100 sample farmers from the study area were Rice+ Duckery, Rice+ Fish, Rice+ Dairy, Rice- Fish sequential farming, Rice+ Fish+ Poultry, Rice+ Fish+ Duckery, Rice+ Fish+ Dairy, Rice+ Fish+ Poultry+ Duckery, Rice+ Dairy+ Poultry, Rice+ Dairy+ Fodder and Rice+ Banana+ Dairy+ Duckery. The predominant models in the study area were Rice+ Duckery which was followed by Rice+ Fish and Rice+ Fish+ Poultry+ Duckery. The economic analysis of the rice based IFS models were carried out to identify the most profitable models. It was observed that fish and duckery enterprises were profitably integrated with rice among the farmers in Kuttanad. The model Rice+ Fish and Rice+ Fish+ Duckery showed a high B-C ratio of 2.52 at Cost A1. Rice+ Duckery was the next most profitable model at a B-C ratio of 2.42. At Cost C, Rice+ Fish showed the highest B-C ratio of 1.45 followed by Rice+ Duckery and Rice+ Fish+ Duckery at B-C ratios 1.32 and 1.26 respectively. The models involving dairy showed significantly lower B-C ratios attributing to the labour intensive nature of the enterprise and high cost of dairy concentrates. Rice–Fish sequential farming showed highest employment generation of 348 Person Days/yr. Economic sustainability of the IFS models were analysed using Sustainable Value Index (SVI) and System Economic Efficiency (SEE). The highest economic sustainability was obtained for the model i Rice+ Banana+ Dairy+ Duckery at an SVI of 0.73 and SEE of ₹1133/day and the lowest was observed for the model Rice+ Dairy+ Poultry at SVI and SEE of -0.14 and ₹147/day respectively. Analysing the resource use efficiency of rice under IFS in Kuttanad revealed that the wetland area was underutilized, and hired human labour was over utilized. The rice based IFS model developed by The Integrated Farming System Research Station, Karamana was analysed for its profitability. The model included dairy, duckery, fish, vegetable cultivation on the dykes and allied activities like vermicomposting. The model was found to be profitable at a discounted B-C ratio of 1.03, NPW of ₹47,617 and IRR of 20 percent. Components of the model like cultivation of vegetables on dykes and construction of duck shelter over the fish pond could be well adopted by farmers in Kuttanad. Constraints in adoption of the IFS models by the farmers were studied using the Garrett ranking technique and the agreement between the respondents in ranking the constraints was studied using Kendall’s coefficient of concordance. The most important constraint that prevents farmers from adoption of the IFS models was unfavourable weather conditions. This corresponded to the fact that the farmers in Kuttanad face severe hardships as the area gets flooded during the monsoon making it difficult for them to raise cattle, poultry and duckery. Although farmers have come up with coping strategies like constructing cattle shed on raised platforms, these have not received widespread acceptance. The other important constraints were labour scarcity, avian diseases, soil acidity and salinity, high input cost, crop pests and diseases, lack of technical knowledge, lack of proper extension support, lack of improved variety/breeds and poor storage facilities. The Kendall’s W statistic of 0.63 indicated that there was general agreement between the farmers in ranking the constraints. Increasing the awareness of the farmers regarding the benefits of IFS through trainings, capacity building programmes for a more skilled labour force, localised weather forecasting and warning systems, strengthening of risk minimising strategies like insuring the crops and livestock and support for taking up allied activities like mushroom cultivation have been suggested.ThesisItem Open Access Dynamics of fertilizer consumption and its marketing: a comparative study in two states of south India(Department of Agricultural Economics, College of Agriculture, Vellanikkara, 2021) Ankitha Thakur; KAU; Prema, AMore than half of India's population relies on agriculture for survival. According to the Economic Survey 2020-21, agriculture and related industries contributed 17.8 per cent of the country's Gross Value Added (GVA) at current prices in 2019-20, The country's most challenging problem currently is maintaining a balance between population boom and agricultural production. The fertilizer industry in India has been under strict governmental control for most of the period since independence. The Government of India declared fertilizer as an essential commodity and notified the Fertilizer Control Order (FCO) in 1957. Major controls on prices and distribution of fertilizers were introduced in 1973 under the Fertilizer Movement Control Order. The Retention Price cum Subsidy Scheme (RPS) was introduced in 1977 for encouraging investment in the fertilizer sector. The economic reforms of 1991 paved way for many policy changes and it also resulted in the formation of several committees. Price of fertilizers were deregulated and new schemes like New Pricing Scheme (NPS) and Direct Benefit Transfer (DBT) were introduced. The growth trend in the chemical fertilizer production and consumption was studied. The results showed that in the year 1950-51, the all-India consumption of N, P2O5, K2O fertilizers was 55.0, 8.8 and 6.0 (‘000 tonnes) respectively. In the 1990s, the total fertilizer consumption varied between 12.15 and 16.8 million tonnes. In 2007-08, the total consumption outreach was 22.5 million tonnes. The total estimated nutrient consumption for 2019-20 (N+P2O5+K2O) was 29.04 million metric tonnes. Fertilizer production in India has increased at a rapid rate i.e., 38.7 thousand tonnes in 1951-52 to about 17.9 million tonnes in 2015-16. Fertilizer production increased modestly by 3.3 per cent to 18.5 million tonnes (N+P2O5) in 2019-20. The production of fertilizers accompanied by the imports in the country have resulted in high fertilizer use by the farmers. The gap between the domestic consumption and production was also studied and the results indicated a deficit (1.31) in the total production and consumption. Forecasting for the next 6 years from 2020-21 to 2025- 26 was also carried out and it showed an increasing trend in both consumption and production for all the major chemical fertilizers. A comparative analysis of fertilizers usage and its marketing in Kerala and Telangana was also studied. Two districts with the highest area under paddy was purposively selected. Two panchayats from each block were randomly selected. The sample included 120 farmers and 20 traders. Second order polynomial regression was carried out to analyse the effect of consumption of N, P and K on the yield. Fisher’s t test was also performed to know whether there is any significant difference between the consumption of N, P, K and yield in the two study areas. It was found that consumption of N and P fertilizers were different in the two states. Yield was found to be higher in Telangana. The consumption of K fertilizers was more or less equal. A significant value of Kendall’s coefficient of concordance showed that there existed strong agreement among the respondents to rank the various brands of fertilizers. It was found that IFFCO fertilizers was preferred in Telangana and in Kerala it was FACT. The marketing system of fertilizers in India is based on the Direct Benefit Transfer system. All subsidised fertilizers are sold to farmers/buyers through Point of Sale (PoS) devices installed in each retailer shop. Dealers must sell fertilizers through PoS devices under the Aadhaar enabled Fertilizers Distribution System (AeFDS). The web-based Integrated Fertilizer Management System keeps track of fertilizer sales (iFMS). The marketing channels in the two states were studied and it revealed that fertilizers in Kerala are mostly distributed to the farmers via the co-operative banks (PACS) to Padashekara samithis. The farmers in Telangana mostly purchased fertilizers from retail shops. There also exists another channel wherein the TS MARKFED supplies fertilizers to various institutes through which farmers avail fertilizers. The fertilizer industry in India is dominated by the co-operative and private companies. IFFCO is one of the largest fertilizer co-operatives as well as producers of fertilizers in India. SWOC analysis of IFFCO showed that the cooperative nature and new venture and businesses of IFFCO are few of its major strengths. Rigid organizational sector and slow feedback are some of its weaknesses. Opportunities include increasing the installation capacity and energy efficient plants. High competition from other private and public companies and government regulations are the major challenges. Chemical fertilizers have made a substantial contribution to India's food grain self-sufficiency. Only by studying individual farm usage can a clearer picture of the country's fertilizer consumption pattern be identified. In order to increase agricultural growth and encourage balanced nutrient application, fertilizers must be made available to farmers at reasonable prices which in turn lead to enhancement of agricultural productivityThesisItem Open Access Estimation of post-harvest losses for vegetables in Palakkad district(Department of Agricultural Economics, College of Agriculture, Vellanikkara, 2021) Nithya Kalpana, E; KAU; Chitra, ParayilOver the last two decades, India’s food system with population surge has been undergoing a transformation with increase in demand for high value fruits and vegetables. However, farmers are unable to receive higher benefits from these transitions which are due to poorly developed value chain systems in the various post-harvest management practices of perishable crops like vegetables. The study entitled “Estimation of post-harvest losses for vegetables in Palakkad district” was aimed to examine and estimate the nature and extent of post-harvest losses for vegetables. Using time series data on the area, production and productivity of vegetables in India and area under vegetable cultivation in Kerala and Palakkad district, compound annual growth rates were calculated. The major vegetables like bitter gourd, snake gourd and vegetable cowpea were selected for the study in proportion to their production to the total vegetables. The respondents were selected using multi-stage random sampling technique. Thus, a sample of 180 farmers (60 for each vegetable) and fifteen vegetable traders from two blocks i.e. Chittur and Nenmara were selected for the study. The cost of cultivation for the three vegetables were worked-out using ABC cost concepts, where in, human labour accounted for the highest percentage (29 percent each for bitter gourd and snake gourd and nearly 49 per cent for vegetable cowpea) to total cost, in all the selected vegetables. The total cost of cultivation (cost A1) was found to be the highest in bitter gourd with ₹1,57,723 ha-1 , followed by snake gourd (₹1,35,805 ha-1 ) and vegetable cowpea (₹1,04,916 ha-1 ). The benefit-cost ratios at cost C were found to be stable with 2.78 for bitter gourd, 2.41 for snake gourd and 1.92 for vegetable cowpea. Also, the major marketing channels for vegetables in the study area were identified and majority of the farmers were found marketing their produce through VFPCK. The nature and extent of post-harvest losses in vegetables were determined by classifying them into three major categories viz. physical loss, physiological loss and loss due to biotic factors. In bitter gourd, the losses were found to be 3.68 (10.2 qtl/ha), 2.1 129 (5.82 qtl/ha) and 6.68 (18.51 qtl/ha) percent to the total production (per hectare) in terms of physical damages, physiological deterioration and loss due to biotic factors respectively at farm level. Thus, the total loss observed in bitter gourd at farm level was about 12.46 percent (34.53 qtl/ha). At trader level, the physiological loss contributed to almost 45 percent of the total losses. Hence, the total loss in bitter gourd was observed to be 21.88 per cent. Likewise in snake gourd, the extent of losses at farm level was found to be 9 percent (26.1 qtl/ha), where the highest losses (4.74 percent) were due to biotic factors like pests and diseases prevailing in the study area. Therefore, the total loss estimated in snake gourd was 13.89 percent which included 4.89 percent of loss at trader level. In vegetable cowpea, the total loss accounted for 20.2 percent to the total production per hectare i.e. 11.53 percent at farm level and 9.15 percent at trader level. Hence, based on the nature of produce the loss due to physical damage was highest in bitter gourd whereas the loss due to physiological factors was found highest in snake gourd and loss with respect to biotic factors was found to be maximum in vegetable cowpea. And, the post-harvest losses were observed as maximum in bitter gourd followed by vegetable cowpea and snake gourd. Economic loss is obtained by addition of post-harvest loss values and value of second grade produce. The monetary loss of vegetables at farm level were also estimated by taking into consideration the prevailing prices of ₹34 (bitter gourd), ₹23 (snake gourd) and ₹32 (vegetable cowpea) (per kg). The vegetables were graded by the shape and size of the produce into standard and second grades, and it was observed that the second grade fetched only half the price of the standard grade. The post-harvest monetary losses accounted for ₹1,17,402 ha-1 in bitter gourd. Farmers tend to lose the value of their produce for second grades. Thus, the economic losses were estimated at ₹3,05,439 ha-1 . Similarly, the monetary loss for snake gourd was computed as ₹60,040 ha-1 , whereas the economic loss valued at ₹94,316 ha-1 . In vegetable cowpea, the monetary losses and economic losses were estimated to be the same at ₹29,280 ha-1 , due to undesirable second 130 grade produce by the traders and consumers. Therefore, the monetary losses were observed to be highest in bitter gourd (32.41 percent to total value of production per hectare) followed by snake gourd and vegetable cowpea. Using the values of the farm level losses, the monetary losses were extrapolated to block and district levels. The estimated loss values for Chittur block were ₹10.82 lakh, ₹4.43 lakh and ₹58.56 lakh in bitter gourd, snake gourd and vegetable cowpea respectively, taking the production data into consideration. In Nenmara, the losses were estimated to ₹122.27 lakh for bitter gourd, ₹56.31 lakh for snake gourd and ₹58.47 lakh for vegetable cowpea. Similarly, for Palakkad district the estimated losses were ₹152.22 lakh, ₹59.49 lakh and ₹210.78 lakh respectively. Regression analyses were used to delineate the factors responsible for losses at farm level. In bitter gourd, area under cultivation, unfavourable weather conditions, pests and diseases and use of packing materials like jute sacks and wooden baskets were found as major determinants for losses. Area under cultivation, experience in farming and prevailing pests and diseases in snake gourd were found to affect the volume of postharvest losses at farm level. Besides these, the variable, timely labour availability was also found to contribute to the losses in vegetable cowpea. The socio-economic profile of the farmers was also analysed for the study. The knowledge, perception level and practices of the farmers regarding the losses were studied using the five-point Likert type scale and it was found that majority (76 percent) of the farmers were categorized under medium level of perception. Garrett ranking technique was used to find the major constraints faced by farmers in vegetable production and marketing. The unfavourable weather conditions, followed by high input cost and pest and disease incidence were found to be the major constraints in the study area. Thus, it can be concluded that with improvement in the awareness level among farmers regarding the post-harvest losses and by training them in the area of post-harvest operations and handling, we can reduce the losses occurring in the vegetables to a remarkable extent in the area studied.ThesisItem Open Access Economics of production and marketing of tuber crops in Palakkad district(Department of Agricultural Economics, College of Horticulture, Vellanikkara, 1997) Sheena, P A; KAU; Thomas, E KThe present investigation on the economics of production and marketing of tuber crops viz. coleus, sweet potato and tapioca in Palakkad district was undertaken during the year 1994-95. The study focussed on estimation of cost and returns and marketing system. Data for the study was generated through a sample survey of farmers, village traders, wholesalers and retailers. Two stage sampling technique was adopted for the study, with panchayats selected purposively and sample farmers by random sampling method. The sample size for each crop was 50 making a total of 150 sample respondents. The results of the cost structure analysis revealed that the largest single item of expense was rental value of own land for coleus and tapioca and for sweet potato chemical fertilizer had the highest expense. Among the explicit cost items male labour accounted the highest share in coleus while rental value of own land and farmyard manure were the most important item in sweet potato and tapioca respectively. Cost A1, Cost A2, Cost B1, Cost B2, Cost C1 and Cost C2 per hectare was Rs.10101.74, Rs.13016.86, Rs.10101.74, Rs.17593.80, Rs.10743.99 and Rs.18236.05 respectively for coleus and Rs.8124.94, Rs.8124.94, Rs.13304.05, Rs.8852.50 and Rs.14031.61 respectively for tapioca and Rs.6733.13, Rs.6733.13, Rs.6733.13 and Rs.9079.94, Rs.7311.04 and Rs.9654.84 respectively for sweet potato. The average per hectare yield of coleus, sweet potato and tapioca were 9154 kg, 8801 kilogram and 7398.73 kilogram respectively. Benefit-cost ratio for coleus was Rs.2.27, Rs.1.76, Rs.2.27, Rs.1.30, Rs.2.13 and Rs.1.25 based on costs A1, A2, B1, B2, C1 and C2 where as the corresponding figures for sweet potato were Rs.1.74, Rs.1.74, Rs.1.74, Rs.1.29, Rs.1.60 and Rs.1.21 respectively. In the case of tapioca Benefit cost ratio was Rs.3.19, Rs.3.19, Rs.3.19, Rs.1.95, Rs.2.93 and Rs.1.85. The income measures in relation to different cost concepts, in coleus cultivation such as gross income, farm business income, family labour income, net income and farm investment income were Rs.22884.72, Rs.12782.98, Rs.5290.92, Rs.4648.67 and Rs.12140.73 respectively and Rs.11734.04, Rs.5000.91, Rs.2654.10, Rs.2076.20 and Rs.4423.00 respectively for sweet potato and Rs.25895.56, Rs.17770.62, Rs.12591.51, Rs.11863.95 and Rs.17043.06 respectively for coleus. Functional analysis was carried out using Cobb-douglas production function and the results revealed that for coleus fertilizer was found to be negative and significant. The production elasticity of labour was negative and insignificant. Farmyard manure and planting material were found to be insignificant. With regard to sweet potato labour was found to be negative and significant and the production elasticity of fertilizer was found to be negative though insignificant. Farmyard manure and planting material was found to be significantly influencing production. Regarding tapioca the production elasticity of labour and farmyard manure was found to be negative though insignificant. The high value of production elasticity of area indicated the dominance of this particular factor. Marginal value product of farmyard manure and planting material for coleus and sweet potato were greater than their factor cost ratio and was negative for labour and fertilizer. In the case of marketing of coleus and sweet potato more than 95 per cent of the produce was sold to wholesalers through commission agents. The producer’s share was only 34.53 per cent and 31.76 per cent of the consumers’ rupee for coleus and sweet potato respectively. The index of marketing efficiency was 0.53 for coleus and 0.47 for sweet potato. Regarding tapioca the tubers who performed the role of commission agent and from them produce is taken by mill owners of Salem and Dindigul. Since there is a product diversification the marketing of tapioca tubers was studied only upto the intermediary level.ThesisItem Open Access Estimation of post-harvest losses for vegetables in Palakkad district(Department of Agricultural Economics, College of Agriculture, Vellanikkara, 2021) Nithya Kalpana, E; KAU; Chitra ParayilOver the last two decades, India’s food system with population surge has been undergoing a transformation with increase in demand for high value fruits and vegetables. However, farmers are unable to receive higher benefits from these transitions which are due to poorly developed value chain systems in the various post-harvest management practices of perishable crops like vegetables. The study entitled “Estimation of post-harvest losses for vegetables in Palakkad district” was aimed to examine and estimate the nature and extent of post-harvest losses for vegetables. Using time series data on the area, production and productivity of vegetables in India and area under vegetable cultivation in Kerala and Palakkad district, compound annual growth rates were calculated. The major vegetables like bitter gourd, snake gourd and vegetable cowpea were selected for the study in proportion to their production to the total vegetables. The respondents were selected using multi-stage random sampling technique. Thus, a sample of 180 farmers (60 for each vegetable) and fifteen vegetable traders from two blocks i.e. Chittur and Nenmara were selected for the study. The cost of cultivation for the three vegetables were worked-out using ABC cost concepts, where in, human labour accounted for the highest percentage (29 percent each for bitter gourd and snake gourd and nearly 49 per cent for vegetable cowpea) to total cost, in all the selected vegetables. The total cost of cultivation (cost A1) was found to be the highest in bitter gourd with ₹1,57,723 ha-1 , followed by snake gourd (₹1,35,805 ha-1 ) and vegetable cowpea (₹1,04,916 ha-1 ). The benefit-cost ratios at cost C were found to be stable with 2.78 for bitter gourd, 2.41 for snake gourd and 1.92 for vegetable cowpea. Also, the major marketing channels for vegetables in the study area were identified and majority of the farmers were found marketing their produce through VFPCK. The nature and extent of post-harvest losses in vegetables were determined by classifying them into three major categories viz. physical loss, physiological loss and loss due to biotic factors. In bitter gourd, the losses were found to be 3.68 (10.2 qtl/ha), 2.1 129 (5.82 qtl/ha) and 6.68 (18.51 qtl/ha) percent to the total production (per hectare) in terms of physical damages, physiological deterioration and loss due to biotic factors respectively at farm level. Thus, the total loss observed in bitter gourd at farm level was about 12.46 percent (34.53 qtl/ha). At trader level, the physiological loss contributed to almost 45 percent of the total losses. Hence, the total loss in bitter gourd was observed to be 21.88 per cent. Likewise in snake gourd, the extent of losses at farm level was found to be 9 percent (26.1 qtl/ha), where the highest losses (4.74 percent) were due to biotic factors like pests and diseases prevailing in the study area. Therefore, the total loss estimated in snake gourd was 13.89 percent which included 4.89 percent of loss at trader level. In vegetable cowpea, the total loss accounted for 20.2 percent to the total production per hectare i.e. 11.53 percent at farm level and 9.15 percent at trader level. Hence, based on the nature of produce the loss due to physical damage was highest in bitter gourd whereas the loss due to physiological factors was found highest in snake gourd and loss with respect to biotic factors was found to be maximum in vegetable cowpea. And, the post-harvest losses were observed as maximum in bitter gourd followed by vegetable cowpea and snake gourd. Economic loss is obtained by addition of post-harvest loss values and value of second grade produce. The monetary loss of vegetables at farm level were also estimated by taking into consideration the prevailing prices of ₹34 (bitter gourd), ₹23 (snake gourd) and ₹32 (vegetable cowpea) (per kg). The vegetables were graded by the shape and size of the produce into standard and second grades, and it was observed that the second grade fetched only half the price of the standard grade. The post-harvest monetary losses accounted for ₹1,17,402 ha-1 in bitter gourd. Farmers tend to lose the value of their produce for second grades. Thus, the economic losses were estimated at ₹3,05,439 ha-1 . Similarly, the monetary loss for snake gourd was computed as ₹60,040 ha-1 , whereas the economic loss valued at ₹94,316 ha-1 . In vegetable cowpea, the monetary losses and economic losses were estimated to be the same at ₹29,280 ha-1 , due to undesirable second 130 grade produce by the traders and consumers. Therefore, the monetary losses were observed to be highest in bitter gourd (32.41 percent to total value of production per hectare) followed by snake gourd and vegetable cowpea. Using the values of the farm level losses, the monetary losses were extrapolated to block and district levels. The estimated loss values for Chittur block were ₹10.82 lakh, ₹4.43 lakh and ₹58.56 lakh in bitter gourd, snake gourd and vegetable cowpea respectively, taking the production data into consideration. In Nenmara, the losses were estimated to ₹122.27 lakh for bitter gourd, ₹56.31 lakh for snake gourd and ₹58.47 lakh for vegetable cowpea. Similarly, for Palakkad district the estimated losses were ₹152.22 lakh, ₹59.49 lakh and ₹210.78 lakh respectively. Regression analyses were used to delineate the factors responsible for losses at farm level. In bitter gourd, area under cultivation, unfavourable weather conditions, pests and diseases and use of packing materials like jute sacks and wooden baskets were found as major determinants for losses. Area under cultivation, experience in farming and prevailing pests and diseases in snake gourd were found to affect the volume of postharvest losses at farm level. Besides these, the variable, timely labour availability was also found to contribute to the losses in vegetable cowpea. The socio-economic profile of the farmers was also analysed for the study. The knowledge, perception level and practices of the farmers regarding the losses were studied using the five-point Likert type scale and it was found that majority (76 percent) of the farmers were categorized under medium level of perception. Garrett ranking technique was used to find the major constraints faced by farmers in vegetable production and marketing. The unfavourable weather conditions, followed by high input cost and pest and disease incidence were found to be the major constraints in the study area. Thus, it can be concluded that with improvement in the awareness level among farmers regarding the post-harvest losses and by training them in the area of post-harvest operations and handling, we can reduce the losses occurring in the vegetables to a remarkable extent in the area studied.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.
