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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 Economic assessment of the use of microbial inoculants in black pepper (Piper nigrum L.) in Idukki district(Department of Agricultural Economics, Vellayani, 2017) Salma Muslim; KAU; Santha, A MThe research entitled ‘Economic assessment of the use of microbial inoculants in black pepper (Piper nigrum L.) in Idukki district. The objectives of the study were to quantify the extent of use of microbial inoculants (MI) used in black pepper, assess the economics of microbial inoculants (MI) application and identify the constraints of microbial inoculants adoption in pepper cultivation. At the first stage two blocks namely Kattappana and Nedumkandam were selected purposively and Irattayar and Nedumkandam panchayat were selected respectively from the 2 development blocks. The required information was collected from 30 MI using farmers and 30 non-MI farmers of black pepper by simple random sampling from the two panchayats. Thus the total sample size was 60. Percentage analysis was done to analyze socio economic variables and extent of adoption of MI. Cost ABC concept was used to calculate the cost of cultivation of MI using farmers and non-MI farmers separately. Resource use efficiency was calculated using Cobb Douglas production function and constraints were ranked by Garret’s ranking technique. Black pepper occupied about 45 per cent of cropped area and 30 per cent area occupied by cardamom. Plantation crops like cocoa, coffee, spices like nutmeg clove, vanilla and annuals like banana and vegetables were also cultivated in this area. Major varieties of black pepper cultivated were Panniyur I, Panniyur 4, local varieties like Karimunda, Neelamundi, Vellamundi, Kottanadan, Kuthiravaly, Kalluvallyand major standards for trailing pepper were Murukku, Silver Oak and Kilinjil. Average size of land holding was 1.85 ha for MI using farmers and 2.10 ha for non-MI farmers. Seventy three per cent of MI using farmers and 56 per cent of non-MI farmers had holdings ranging from 0.4-1.2 ha under pepper. Forty percent of high income farmers were following non-MI pepper farming. Analysis of extent of use of microbial inoculants revealed that only 33 per cent were following the recommended rate of MI whereas 46.6 per cent of farmers used in excess.Total cost of cultivation of black pepper per hectare was more for non-MI farmers when compared to MI using farmers. Cost A1 of MI adopted farmers was Rs. 133797.24 ha-1 and that for non-MI was Rs. 155720.64 ha-1. Cost C was calculated as Rs. 295050.13 ha-1 and Rs. 439399.87 ha-1 for MI using famers and non-MI respectively. Major share of cost A1 was contributed by cost of hired labourfor both categories followed by cost of manures, fertilizers and soil ameliorants. Yield of black pepper did not show much difference, but the farmers using MI were mostly following organic farming, fetches a higher price of Rs.700 per kg against the price ofRs.680 per kg for the non-MI famers. Net returns at cost C for MI using farmers was Rs. 135749.75 which was higher than that of non-MI farmers. BC ratios were 1.8 and 1.23 for MI adopters and non-MI farmers respectively at cost C. The Cobb Douglas production function analysis showed that number of bearing pepper vines had a positive and significant impact on yield in both the cases. In case of MI using farmers along with number of bearing vines, quantity of manures had positive and significant impact on yield. Quantity of MI showed positive coefficient but was non-significant. For the non-MI pepper farmers, number of hired labour and quantity of manures showed positive and significant impact in addition to number of bearing pepper vines. Difficulty in proper identification of pests and diseases in the study area, less availability of microbial inoculants other than Pseudomonas and Trichoderma, Lack of knowledge about recommended method, dose and time of application of MI and climate change were the major constraints observed. Present research revealed that by using MI, farmers could reduce the use of chemical fertilisers and pesticides; thereby they could reduce the cost of cultivation and increase profitability. Excess adoption of MI was prominent among the users and proper guidance is required to the farmers on the application of recommended dose of microbial inoculants along with adequate availability of all microbial inoculants.ThesisItem Open Access Market access to quality paddy seed in Kerala(Department of Agricultural Economics, College of Horticulture, Vellanikkara, 2017) Fathimath Nufaisa, P; KAU; Prema, ASeed is the basic and critical input in agricultural production. It helps to enhance production without adding much to the extent of land under cultivation. Area under rice in Kerala fell from 2.34 Lakh hectares in 2009-10 to 1.99 lakh hectares in 2015-16, the production corresponding to the above period registered a reduction of only 0.49 Lakh tones. Availability and access to quality seeds is one of the important aspect in maintaining at least the current level of production of rice in the state. Hence the present study was carried out to document the major rice seed supply chains in Kerala and to assess their economic performance, to elucidate the demand - supply gap in rice seed production and to conduct a SWOC analysis of the rice seed market in the state. The study was conducted in three major rice growing districts in Kerala viz., Palakkad, Alappuzha and Thrissur. From each district one block having maximum area under rice cultivation was selected and from each block two panchayaths were randomly selected. Primary data collection was done from 60 rice farmers and 60 rice seed growers in the selected panchayaths. Relevant data were also collected from Kerala State Seed Development Authority (KSSDA), Kerala Agricultural University (KAU) research stations and National Seeds Corporation (NSC). Rice seed supply chains in Kerala could be broadly classified into formal and informal system. The informal system constitutes farm saved seed and seed exchange among farmers, friends and relatives. The formal rice seed supply system constitutes institutionalized rice seed supply mechanisms. Major formal rice seed supply chains identified were KSSDA rice seed supply chain, KAU rice seed supply chain and NSC rice seed supply chain. Economic performance of rice seed production under the identified supply chains was analyzed using Commission on Agricultural Costs and Prices (CACP) cost concepts and Benefit Cost Ratio (BCR). BCR of rice seed production in KAU research farm was 0.76 followed by 0.89 for KSSDA and 1.04 for participatory rice seed production in KAU. Seed production systems in KAU research farms and KSSDA was found to be economically inefficient as indicated by the BCR values. Demand- supply gap in rice seed production was worked out as the difference between the quantity of high yielding variety seed required for the area reported and the quantity of seeds distributed through the formal supply chains. The demand supply gap over the years (2012 to 2016) ranged from 30 per cent to 50 per cent of the total demand indicating that 50-70 per cent of total rice seed demand was met through formal rice seed supply system. KSSDA was found to be the major source of rice seed supply (88.97 per cent) followed by NSC ( 8.57per cent) and KAU (2.46 per cent). Constraints faced by rice farmers in access to quality rice seed was analyzed using Garrett ranking technique. Timely availability of rice seed was the major constraint followed by poor rice seed quality. Analysis of constraints faced by seed growers have shown that lack of timely procurement and payment was the major constraint. Strengthening of seed production system with establishment of separate seed certification agency and sufficient seed storage and processing facilities at seed growers’ level was suggested.ThesisItem Open Access Economic analysis of production, marketing and price behavior of coconut(Department of Agricultural Economics, College of Horticulture, Vellanikkara, 2017) Preethi, V P; KAU; Jesy Thomas, KCoconut (Cocos nucifera L.) is an important crop cultivated in Kerala which covers 39 per cent of net area sown in the state and contributes 15 per cent to the state agricultural GDP. Even though the state has the largest area under coconut cultivation, per palm productivity is very low at 42 nuts per tree. Now the state is losing its share to other competitive states like Tamil Nadu which ranks first in production. Hence the present study was carried out to analyse the trend in area, production and productivity and price behaviour of coconut in Kerala along with an understanding of production and marketing structure. Kozhikode district was selected as the study area which has the largest area under coconut cultivation in Kerala. Based on the list of farmers collected from Krishibhavans, 40 farmers were randomly selected from the two selected blocks making a total sample size of 80. The information was also collected from 25 market intermediaries including wholesalers, retailers and millers. Trend analysis was done to understand the growth pattern of coconut in terms of area, production and productivity both at national and state level from 1980-01 to 2015-16. In India, area, production and productivity of coconut showed an increasing trend. The analysis on the growth performance of coconut in India revealed that area, production and productivity of coconut had shown an increasing trend, with the exception of growth in area and production during Period I. During Period II, in spite of a higher growth in productivity, the growth rate was lower for production due to stagnant growth in area. However, the growth in area, production and productivity during the overall period under study was significant and positive. In case of Kerala, productivity-based growth of output was observed which means that the growth in production of coconut was mainly by the contribution of growth in productivity rather than in area. The price behavior of coconut and copra in major markets of Kerala viz., Alappuzha and Kozhikode were analyzed by decomposing the monthly price data into four components viz., secular trend, seasonal variation, cyclical variation and irregular variation assuming a multiplicative model of time series. The price of coconut and copra in these markets showed an increasing trend in the long run. While analysing the seasonal variation it was noticed that during the Period I (1980-01 to 1995-96), price of coconut showed wide fluctuations in both the markets but it was considerably low in Period II (1995-96 to 2015-16) whereas, the seasonal variation of copra price in both the markets showed a similar pattern. Three to four cycles were seen in both the market prices but the length of cycles was observed to be varying. Co-integration analysis of coconut prices in the above two markets were carried out and it was revealed that both the markets were integrated. In order to provide additional evidence as to whether and in which direction, price transmission was occurred Granger causality test was carried out and the results proved the existence of unidirectional causality between Kozhikode and Alappuzha market prices in the long run. Since coconut is a perennial crop, its yielding phase was assumed to be 50 years, with a non-bearing phase of 7 years. The cost and returns were estimated taking into account the establishment cost and the maintenance cost. The cost of cultivation per hectare was Rs.1,01,989 with a net return of Rs.24,011. It was noted that human labour accounted for 50 per cent of the total cost. To evaluate resource use efficiency in coconut cultivation, Cobb-Douglas production function was fitted. Manures, fertilizers and plant protection chemicals were found to be significantly contributing towards the yield. Moreover, an increasing returns to scale in coconut production was observed in the study area which implies that there is ample scope to increase the profit of farmers by proper adoption of technology and by optimal allocation of resources. Marketing plays a predominant role in agricultural development and is as important as production to any producer. Thus, an efficient marketing system can increase the level of income of producers and raise the satisfaction of consumers. Marketing of coconut needs further attention in Kerala, the land of coconut as it serves the lives for more than 80 per cent of the people in the state. The most common marketing channel identified in the study area was channel I (Producer- village trader- wholesaler- retailor- consumers). It was found that lack of storage facilities and fluctuating prices drive the producers to sell raw nuts immediately after harvesting instead of waiting for a higher price for their produce. Major constraints identified in the study area were wide fluctuations in coconut prices, high labour cost, pests and diseases attack and inadequate procurement scheme. In order to tackle these problems, it is necessary to encourage coconut farmers to replant old and senile trees by providing subsidy and ensure high production by strengthening the existing procurement scheme. Strategies emphasizing implementation of comprehensive coconut rejuvenation programmes, enhancing productivity through better technology integration and value addition through product diversification to ensure better price for farmers are suggested.ThesisItem Open Access Economic impact of climate change and adaptation strategies in black pepper (Piper nigrum L.) cultivation in Kerala(Department of Agricultural Economics, Vellayani, 2017) Amogh, P Kumar; KAU; Paul Lazarus, TThe research entitled “Economic impact of climate change and adaptation strategies in black pepper (Piper nigrum L.) cultivation in Kerala” was conducted in Wayanad and Idukki districts. The objective of the study was to quantify the impact of climate change on black pepper, to understand the adaptation practices followed by farmers to overcome climate change and to study the extent of governments’ compensation to farmers due to weather extremes. Secondary data regarding area production, productivity and climatic variables were collected for Idukki and Wayanad districts for the period 1987-2016. Secondary data on compensation provided by government due to weather extremes were collected only for Wayanad district for the period 2005-2016 and primary data were confined to Wayanad district for the agricultural year 2015-2016. Panel data analysis was done to identify the climatic variables that are influencing the production, binary logit regression was fitted to understand the socioeconomic variables influencing adoption of adaptation practices, ABC cost concepts were used to calculate the annual maintenance cost of pepper farmers, Cobb Douglas production function was fitted to calculate the allocative efficiency of the resources, Garrett ranking technique to determine the constraints faced by pepper farmers and compound annual growth rate was calculated for the compensation given by the government during weather extremes to know the growth trend. From the panel data analysis, it was found that average temperature during Q3 (July – September) and Q4 (October – December) had a negative and significant impact on the production of pepper. A one percent increase in the average temperature during Q3 will decrease the production by 3.41 per cent and a one percent increase in the temperature during Q4 will decrease the production by 2.69 per cent. Rainfall during Q2 (April – June), which coincides with flowering of pepper, was found to have positive effect on production but was statistically insignificant. Binary logit regression analysis was done to identify the socioeconomic variables influencing adaptation practices followed by adopters. Number of year of experience in pepper farming was found to be statistically significant which had positive influence. From, the estimated partial elasticity, 1 per cent increase in year of farming experience in pepper will increase the probability of adopting adaptation practices by 0.99 per cent. Odds ratio obtained was 5.68 for year of experience in pepper farming. It indicated that farmers with more number of years of experience are likely to adopt adaptation practices five times higher than the farmers who have less experience. Cost A1 for the adopter farmers was `1,68,959.65 ha-1. Out of this, hired labour accounted for 39.30 per cent, followed by manures, fertilizers and soil ameliorants which was 21.13 per cent. Cost A2, Cost B and Cost C were `2,04,584.65 ha-1, `2,51,241.35 ha-1, and `2,79,533.43 ha-1respectively. In non adopter farmers Cost A1 was `1,56,149.14 ha-1. Out of this, hired labour accounted for 41.87 per cent, followed by manures, fertilizer and soil ameliorants 22.14 per cent. Cost A2, Cost B and Cost C were `1,93,649.14 ha-1, `2,42,160.42 ha-1, and `2,65,117.63 ha- 1 respectively. At Cost C, adopter farmers had 5.43 per cent more cost of cultivation per hectare than non adopter farmers. Gross returns of adopters and non adopters was `4,50,363.87 ha-1 and `3,10,953.04 ha-1 respectively. B-C ratio at Cost C for adopters was 1.61 and for non adopters it was 1.17. The allocative efficiency, in adopter and non adopter farmers, family labour was used sub optimally. Plant protection chemicals were underutilized and manures and fertilizers were over utilized by adopters, whereas both plant protection chemicals and manures and fertilizers were over utilized by non adopters. Garrett ranking technique was used to rank the major constraints faced by the farmers. Increase in high incidence of pest and disease and high labour cost were the major production constraints faced by adopters and non adopters respectively. Fluctuation in market prices was the major marketing constraint for both categories of farmers. High cost of adaptation practices and lack of knowledge about adaptation practices were major constraints for adaptation faced by adopters and non adopters respectively. Compensation to pepper farmers in Wayanad from government during drought was an average `48,64,984 per annum and is growing at the rate of 1.04 per cent per annum. Compensation for flooding due to heavy rainfall & high speed wind was an average `1,32,81,192 per annum and is also growing at the rate of 1.04 per cent per annum. Q3 and Q4 temperature had negative impact on pepper production. Increase in number of years of experience in farming increases the probability of adopting adaptation practices. Net returns of adopters were more than that of non adopters. Increase in labour cost, fluctuation in market prices and high cost of adaptation practices were major constraints faced by both farmers. Compensation by government due to drought and heavy rainfall & high speed wind showed a positive growth trend. A negative trend of rainfall was observed for both the districts. Hence adaptation measures to conserve water such as rain water harvesting system, mulching, spraying 1 per cent lime solution, moisture conservation tillage and growing drought tolerant varieties (Paniyur-5, Paniyur-6 and Paniyur-7) helps to reduce the risk of drought.ThesisItem Open Access Value chain analysis (VCA) of coconut based food products(Department of Agricultural Economics, College of Horticulture, Vellanikkara, 2017) Ashly Mathews; KAU; Latha Bastine, CCoconut (Cocos nucifera) is one of the most useful tropical palms, almost all parts of which have various uses in both household and industrial sectors. In spite of the diverse value addition technologies developed by research institutions, the level of adoption was found to be low. A study entitled ‘Value Chain Analysis (VCA) of coconut based food products’ was taken up in order to identify the value chains, price spread, profitability and marketing efficiency of coconut based value added food products using the value chain analysis framework. The study also focused on the constraints faced by various chain players and measures for improving the performance of the chains. The study was conducted in Thrissur district of Kerala, and the four products selected for the study were coconut oil, Virgin Coconut Oil (VCO), desiccated coconut and coconut chips. Focus group discussions were held to identify the key chain players involved in the value chain. Survey method was used for the primary data collection. Expert opinions were also used for arriving at conclusions. The value chain map of each product was prepared including the product and byproduct flows. The main chain players involved were farmer/farmer cooperative, village traders, copra traders, processors, wholesalers, retailers, exporters and consumers. Coconut oil value chain involved almost all chain players. But for coconut chips large buyers like wholesalers were not present. The analysis of marketing cost showed that the costs involved were very less where the unnecessary middlemen were least involved or absent. Price spread analysis has shown that VCO has the lowest producer’s share in consumers’ rupee (24.04 per cent) whereas the producer’s share in consumer’s rupee was the highest in coconut oil (71.04 per cent). The index of Modified Marketing Efficiency (MME) was worked out which showed that coconut chips was the least efficiently marketed value added product (0.23). Low market price increased labour charges, increased cost of production and labour shortage were the major problems faced by the farming community. Product specific constraints faced by manufacturers were also studied. Unavailability of sufficient quality raw nut and copra was a major constraint faced by the manufacturers. Financial constraints, adulteration and price fluctuations were the major constraints faced by the wholesalers. High price of the product was the major constraint faced by the consumers of coconut products. Adulteration was also identified as a major constraint faced by the consumers of coconut oil. Ensuring continuous and large scale supply of raw nuts to the manufacturers is the primary need for the promotion of value addition in coconut. The manufacturers should adopt large scale of production with modern technology and the traders should ensure the quality standards of the products which would in turn enhance the marketing opportunities.