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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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1986 - 1989111990 - 20001
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Subject: Statistics × Author: KAU × Start date: 1986 × Type: Thesis ×
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Now showing 1 - 9 of 12
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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
    Comparative study of genotype environment interactions in sesame
    (Department of Statistics, College of Veterinary and Animal Sciences, Mannuthy, 1989) Mini, C J; KAU; George, K C
    The present study has been conducted to choose a consistent variety for all the regions and all seasons in the light of genotype-environment interaction with the following objectives. (i) to evaluate the existing techniques available for studying GE interaction in sesame (ii) to develop new concepts and methods to solve some problems peculiar to crop sesame like non-linearity of interactions, non-orthogonality of data and different patterns of genotype-environment (GE) interactions that are encountered while studying the stability of varieties simultaneously for several traits.
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    ThesisItemOpen Access
    Statistical approach on the pattern of development of shank length in ducks
    (Department of Statistics, College of Veterinary and Animal Sciences, Mannuthy, 1989) Sunanda, C; KAU; George, K C
    The present investigation entitled ‘‘statistical approach on the pattern of development of shank length in Ducks’’ has been undertaken to study the following objectives. 1. To examine the pattern of development of shank length in two breeds of ducks in University Duck Farm, Mannuthy. 2. To compare them (a) between genetic group (b) between males and females within each genetic groups (c) between males of genetic group (d) between females of genetic group and 3. To fit appropriate growth curves for prediction of body weight through shank length at different stages of growth. For this purpose shank length and body weights on 14 males and 25 females of Desi ducklings and 26 males and 26 females of White Pekin (WP) ducklings were utilized. The ducklings were reared for twelve weeks in Kerala Agricultural University Duck Farm, Mannuthy under uniform feed formula and identical management practices. In the day old and the twelfth week of age uniformity could be seen in the mean shank length of the four groups. But at the fourth and eighth week of age, mean shank length of the four groups was not uniform. Upto ninth week of age, Desi females had higher shank length than the other three groups except at the fifth week. But during the fifth, tenth, eleventh and twelfth week of age Desi males had the highest shank length. The least shank length was always observed for WP males. During the entire period, Desi ducklings had higher shank length than WP duckling. The growth pattern of body weight was not uniform in the four groups except the initial body weight. High correlation was found between the body weight and shank length. It revealed that shank length can be made a criterion for selection for higher body weight. The method of comparison of growth rates recommended by Rao (1958) was found unsuitable for the present study. Among the functional relationships worked out linear, exponential and second degree equations were found to be unsuitable for fitting shank length as a function of age. Modified exponential, logistic, Gompertz and Von-Bertalanffy equations were found to be suitable for fitting shank length over a period of time. Among these four, Gompertz was found to be the best fit. The second best fitted equation was logistic. Graphs of the best fitted equations ie. Gompertz and logistic were drawn for all the six group along with the observed values. This also confirms above result. Among the two functional relations ie. linear and exponential used for predicting body weight from shank length, exponential was found to be most suitable.
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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
    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
    Factor analysis of genetic divergence in sesame
    (Department of Statistics, College of Veterinary & Animal Sciences, Mannuthy, 1988) Tes, P Mathew; KAU; Saraswathi, P
    Sesame is an important annual oil seed crop grown in India. It is grown in a very limited area of 1453 hecters in Kerala. The lack of high yielding varieties suitable to the seasons in different regions was the main factor limiting the productivity of sesame in our State. The genetically divergent parents will produce better segregants in the hybridisation programme. The present study was undertaken to delineate the underlying causes of divergence in the sesame plants using the factor analytic methods.
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    ThesisItemOpen Access
    Forecasting of rice yield using climatological variables
    (Department of Statistics, College of Veterinary and Animal Sciences, Mannuthy, 1986) Ajitha, T K; KAU; Prabhakaran, P V
    Systematic crop and weather observations on autumn and winter paddy at Pattambi Rice Research Station, during 1949-50 to 1973-74 have been analysed in order to evaluate the effect of different climatic factors on rice yield and to develop suitable prediction models for the preharvest forecasting of rice yield with sufficient degree of precision. The varieties under observation were PTB 1 and PTB 5 in the autumn season and PTB 12 and PTB 20 in the winter season. The crop was raised as rainfed through out the entire period of investigation. The moteorological variables included in the study were total rainfall (mm), number of rainy days, maximum temperature (°C), minimum temperature (°C), maximum humidity (%), minimum humidity (%), total hours of sunshine and wind velocity (km/h).
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    ThesisItemOpen Access
    Comparative study of genotype environment interactions in Sesame
    (Department of Statistics, College of Veterinary and Animal Sciences, Mannuthy, 1989) Mini, C J; KAU; George, K C
    The present study has been conducted to choose a consistent variety for all the regions and all seasons in the light of genotype-environment interaction with the following objectives. (i) to evaluate the existing techniques available for studying GE interaction in sesame (ii) to develop new concepts and methods to solve some problems peculiar to crop sesame like non-linearity of interactions, non-orthogonality of data and different patterns of genotype-environment (GE) interactions that are encountered while studying the stability of varieties simultaneously for several traits.
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    ThesisItemOpen Access
    Divergence analysis of morphological and quality traits in sugarcane
    (Department of Statistics, College of Veterinary and Animal Sciences, Mannuthy, 1989) Santhi, T E; KAU; Saraswathy, P
    Multivariate analytical techniques are found to be very useful in plant breeding research to explain the influence of various factors on the phenomenon under study. Factor analysis is found to be an appropriate tool to identify the factors of genetic divergence. D2 – analysis is helpful to group the divergent genotypes into various clusters when measurements on a number of related characters are available on a large number of genotypes such that the genotypes within a cluster are homogeneous with respect to these characters and heterogeneous between the clusters. The present study is aimed at identifying the factors of divergence in relation to morphological and quality traits in forty eight clones of sugarcane. The fifteen clones T.67172, Co.7717, Co.419, Coc.779, Co.7219, Coc.777, Ic.225, Co.6304, S - 99, Coc.773, Coc.772, Co.62198, Co.62101, Coc.778 and S – 77 are able to group into one cluster. Four more clusters are able to form respectively with five varieties (Co.658, Co.62175, S – 105, Co.6907, Co.995) in the second cluster, nine (F.1 – 2, Co.62174, S – 87, KHS 3296, Coc. 671, Co.7704, Co.785, CoM.7114, CoM.7125) in the third, seven (Co.6807, Co.1340, Co.527, S – 33, Co.6806, B. 37172, Co. 527 – M – 10) in the fourth and four varieties (Co.1307, CoA.7602, Coc.705, Co.453) in the fifth cluster. The remaining clones are not able to group. Among these clusters are utilized for factor analysis. A factor related to quality is extracted as the first factor in all the three clusters. The characters pol at 12th month, C.C.S. percentage, brix at 12th month, purity percentage and sugar yield per plot dominated this factor. Among these characters pol at 12th month, C.C.S. percentage and brix at 12th month are found to be more amenable to changes due to selection. The second factor is identified by the characters cane yield per plot, shoot count germination count and number of millable canes. Apart from these characters weight of cane is also included in this factor in cluster 1. The characters which are more amenable to change due to selection are cane yield per plot and shoot count. The characters are not common in the remaining four factors. These six factors are able to explain 66.84 percent, 79.44 percent and 87.41 percent of variation respectively in the first, third and fourth cluster.