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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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1984 - 19877
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Subject: Statistics × Author: KAU × End date: 1987 × Start date: 1983 × Type: Thesis × Thesis Type: M.Sc ×
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Now showing 1 - 7 of 7
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    ThesisItemOpen Access
    Forecasting models for crop yield in cashew (anacahdium occident ale l.)
    (Department of Statistics, College of Veterinary and Animal Sciences, Mannuthy, 1987) Usha, Menon R; KAU; George, K C
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    ThesisItemOpen Access
    Milk marketing in the organised sector- a programming approach to optimisation of collection and distribution
    (Department of Statistics, College of Veterinary and Animal Sciences, Mannuthy, 1987) Asokan, M V; KAU; Ravindranathan, N
    Two milk collection and one distribution route were taken for suggesting a suitable transportation model for optimizing the cost of collection and distribution of milk in dairy plants. Three Vehicle Scheduling Models, viz. saving model (model 1) suggested by Clarke and Wright (1964) λ model (model II) and ∏ model (model III) suggested by Gaskel (1967) were used in this study. Since there was high variation in supply of milk by each society to chilling plant, median and third quartile values of daily supply of milk of two selected months for each season was taken as expected availability of milk. Maximum distance that can be travelled by a truck in a route was calculated by considering the time. Morning and evening routes were formed with median and third quartile values as expected availability of milk in each season. Routes obtained in all cases indicated that routes formed by model 1 were the best. In the case of distribution of milk routes obtained by the model I was found to be the best. Using traveling salesman problem technique, an attempt was made to check the optimality of the routes obtained by each model and found that the routes were not optimum in most of the cases. Refinement method suggested by Holmes and Parker (1976) was tried out for knowing whether any further improvement is possible in model I. In certain cases better routes could be achieved. From this study, it is suggested that for the route formation in dairy plants for collection and distribution of milk, three techniques, viz. Clarke and Wright method (model I). Refinement method and traveling Slaesman problem technique should be used in the order stated. Forty four dairy co-operative societies were considered in the analysis of performance rating and grading of societies. Seven parameters were taken and subjective weights were given to each of them. Total score for each society was calculated and based on it the societies were graded as A, B, C and D.
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    ThesisItemOpen Access
    Comparative study of lactation curves in cattle
    (Department of Statistics, College of Veterinary & Animal Sciences, Mannuthy, 1985) Mathew Sebastian; KAU; George, K C
    An investigation, based on 174 normal lactation records of 93 Jersey crossbred cows and 90 normal Isolation records of 55 Brown Swiss crossbred cows belonged to the University Livestock Farm, Mannuthy, was undertaken : (1) to compare the relative efficiency of various isolation curve models and to select the best one (ii) to compare the two genetic groups based on order of Isolation and season of calving and (iii) to develop equations for predicting total milk yield from part yields. Records upto the 4th Isolation were included in the study. The observations spread over a period of six years from 1978 to 1983. The year was delinested into dry, rainy and moderate seasons.
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    ThesisItemOpen Access
    Assessment of genetic divergence by factor analysis in groundnut (Arachis hypogaea L.)
    (Department of Statistics, College of Veterinary & Animal Sciences, Mannuthy, 1986) Muralidharan, K; KAU; Saraswathi, P
    Factor analysis, Principal component analysis, discriminent analysis, and cluster analysis were carried out with a multivariate data on 30 characters of 62 bunch type groundnut varieties grown in upland during khariff 1982 and rice fallows during summer 1982. Vegetative, reproductive and growth factors were identified as the causative factors of genetic divergence in both the environments. A height factor was also found to work with rice fallows. The characters which were most amenable to change due to selection in these factors were identified. They were not found to agree with the results obtained from discriminant analysis. When factor loadings were estimated from principal components, clustering of characters were found identical to those obtained from factor analysis.
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    ThesisItemOpen Access
    Comparison of different techniques for the estimation of genotype-environment interaction
    (Department of Statistics, College of Veterinary & Animal Sciences, Mannuthy, 1984) Laly John, C; KAU; Gopinathan Unnithan, V K
    The genotypic stability analyses of Eberhart and Russell (1966), Perkins and Jinks (1968), Freeman and Perkins (1971), Wricke (1966) and Shukla (1972) were studied in detail. The mistakes in the analysis of variance of Perkins and Jinks (1968) were corrected. The first three analyses which used the theory of regression explains a large part of the genotypic environment interaction. On the otherhand, when the regression cannot explain a large part of the genotype - environment interaction, Wrioke's ecovalence ratio and Shukla's stability variance could satisfactorily be used.
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    ThesisItemOpen Access
    Optimum plot size for field experiments on turmeric (Curcuma longa L)
    (Department of Statistics, College of Veterinary & Animal Sciences, Mannuthy, 1984) Gopakumaran Nair, B; KAU; Prabhakaran, P V
    A uniformity trial on turmeric (Curcuma Longa. L.) was conducted at the experimental field of College of Horticulture, Vellanikkara, during the period from June 1983 to January 1984 to assess the nature and magnitude of soil heterogeneity of the experimental field, and to determine the optimum size and shape of experimental plots and blocks in conducting field trials on turmeric by different methods. At the time of harvest, the yield data from 864 plots each of size 0.6m x 0.75m were recorded separately, discarding the external border row.
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    ThesisItemOpen Access
    Pre-harvest forecasting of sugarcane yield
    (Department of Statistics, College of Veterinary and Animal Sciences, Mannuthy, 1984) Alphi Korath; KAU; Prabhakaran, P V
    Several yield prediction models were tried to examine their suitability for the pre-harvest prediction of yield of two varieties of sugarcane namely CO-997 and CO-62175 in different months of plant growth using biometric characters based on the data collected from the Sugarcane Research Station, Thiruvalla. The methods of multiple regression analysis, path coefficient analysis and principal component analysis were used for the above purpose. Multiple regression analysis using plant biometric characters revealed that cane yield could be predicted on the basis of observations on height of the cane, girth of the cane find estimated total leaf area per cane or area of third leaf from the seventh month after planting onwards with an accuracy in the range of 59*5 to 81.9 per cent. The estimated cane yield when multiplied by the number of canes in the plot will give an advance estimate of the plot yield Linear models with five biometric characters viz., height of the cane, girth of the cane, width of the third leaf determined from the selected plants of each plot and number of canes/tillers and number of leaves determined on a whole plot basis were sufficient to predict the plot yield of the crop as early as in the fifth month of plant growth with an accuracy in the range 68 to 90 per cent. Path analysis revealed that height of the cane and girth of the cane were the t wo important characters contributing towards cane yield in all stages of plant growth. Using the forecasting models fitted with principal components as explanatory variables, yield could effectively be predicted with 81.4. per cent accuracy for variety CO-997 and with 76 per cent accuracy for variety 00-62175 in the Sixth month of plant growth.