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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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2020 - 20213
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Subject: Irrigation and Drainage Engineering × Start date: 2020 × Thesis Type: M.Tech. ×
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    ThesisItemOpen Access
    GIS integrated site-specific fertigation recommendations for Instructional farm, KCAET, Tavanur
    (Department of Irrigation and Drainage Engineering, KCAET, Tavanur, 2021) Subhasree, N; Sajeena, S
    Excessive application of fertilizers can cause wastage of fertilizer which increases input cost and environmental pollution. Implementation of Precision Agriculture through site specific nutrient management is the best suitable solution to increase nutrient application efficiency and thereby increase crop productivity. Site Specific Nutrient Management (SSNM) is the real time feeding of crops with nutrients while recognizing the spatial variability within the fields. In this context a study on “GIS Integrated Site-Specific Fertigation Recommendations for Instructional Farm, KCAET, Tavanur” was conducted. Delineation of the study area was done with the help of cadastral map of KCAET campus and coordinates of the corner of the study which were found using hand held GPS during the study. Sampling points were located by using gridding tool. The soil samples were collected at the 40 sampling points and analysed for the soil chemical properties such as pH, Electric Conductivity, Available Nitrogen, Available Phosphorous, Available Potassium, Boron and Sulphur by using standard methods. Spatial variability maps of soil chemical properties were prepared by using Inverse Distance Weighing method of interpolation tool in spatial analyst tool of Arc tool box in ArcGIS. Based on soil analytical values, site specific nutrient recommendations were calculated to each grid for Coconut, Banana and different vegetables by Site Specific Soil Nutrient Calculator (SSSNC). It is a winForm Windows application created with the help of Objective-C using Visual studio 2019. Based on nutrient index rating given by Meena et al., (2006), potassium and phosphorous were found in the range of ‘medium fertility’ (1.67-2.33), nitrogen and sulphur were under ‘low fertility’ (<1.67) and boron was found to be under high fertility range (>2.33) in the study area. According to the criteria given by Wilding et al., (1985), pH was found to be least variable whereas nitrogen and boron were moderately variable and the remaining parameters such as organic carbon, phosphorous, potassium and sulphur were found to be most variable parameters in the study area. The maps and the Site-Specific Soil Nutrient (SSSN) App which were developed during the study will help farmers to make better site-specific nutrient recommendations. From this study, it can be concluded that implementation of site-specific fertigation recommendations can eliminate the excessive application of fertilizers and a significant amount of fertilizer can be saved when compared to Package of Practice/ adhoc recommendation.
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    ThesisItemOpen Access
    Water conservation measures and cropping pattern for a watershed using geospatial techniques and swat modelling
    (Department of Irrigation and Drainage Engineering, Kelappaji College of Agricultural Engineering and Technology, Tavanur, 2020) Panchamy Balan; KAU; Asha, Joseph
    The Manali watershed located in Thrissur district of Kerala with a drainage area of 140.94 km2 receives an average annual rainfall of 2501.08 mm. But the watershed experiences increased water level rise during monsoon and scarcity of water during non-monsoon season. In order to address the problem of water scarcity in the watershed, an attempt was made to plan conservation measures and cropping pattern using geospatial techniques and SWAT modelling. SWAT model was used effectively for the hydrologic water balance assessment and water availability in the watershed. Water demand was estimated as the sum of agricultural and non-agricultural water demand. Agricultural water demand was estimated using CROPWAT 8 model. An analysis of monthly water availability and water demand was carried out to know the status of water in the watershed. Site suitability modelling was done using GIS to locate water conservation measures and IMSD guidelines were applied to select the type of water conservation measures. Cropping pattern was proposed based on existing crops, soil type, physiography and aridity index. The model was calibrated and validated satisfactorily for the watershed with NSE values 0.71 and 0.61 and R2 values 0.81 and 0.61 during calibration and validation respectively. The highest water availability (71.57 Mm³) was found in the month of June and lowest (1.28 Mm³) in the month of January. Water demand was highest in the month of January (8.91 Mm³) and lowest in the month of June (1.23 Mm³). Water surplus was observed in almost all the months of the year except January, February, March and December. The annual total water surplus in the watershed was obtained as 227.43 Mm3. Hence conservation measures were proposed for the watershed. Thus 32 farm ponds, 7 percolation ponds and 4 check dams were suggested to construct in the watershed area. Farm ponds were found to be the most suitable conservation measure in the area. Suitable cropping pattern like sequential cropping and intercropping were also suggested to improve the productivity and economic status of the watershed.
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    ThesisItemOpen Access
    Modelling the impact of land use land cover changes on the runoff processes of Chalakudy basin using HEC-HMS model
    (Department of Irrigation and Drainage Engineering, Kelappaji College of Agricultural Engineering and Technology, Tavanur, 2020) Nchumbeni M, Odyuo; KAU; Rema, K P
    Fast development of urbanization alongside other expanding anthropogenic factors have been distinguished as significant reasons for land use changes and land transformations. This eventually causes several devastations like floods, droughts, water contamination and soil debasement. There is a need for target evaluation and investigation on the land utilization patterns and the mode of operation of water conserving structures in order to take up any preventive and additional healing measures. The state of Kerala in particular is notable for significant level of development as far as socio–monetary components, education, human services and so forth are considered. The broad financial changes have prompted expanded pace of framework, building development and several land use changes in the most recent decade. Evaluating the spatial and temporal changes in land use and land cover (LULC) of a basin is one of the analytic strategies to comprehend the issues continuing in a basin and gives significant understanding of its effect on runoff processes. The Chalakudy river basin in Kerala was one of the worst affected basins during the floods of 2018 and has experienced unaccountable damages to human life, ranches, gardens, domesticated animals, buildings, roads etc. The present study compares the LULC changes over two different decades 1997- 2007 and 2007-2017 by analysing the LULC maps and the effect of these changes on the runoff processes in Chalakudy river basin. From the LULC maps, the area under each class, the percentage area coverage and decadal percentage change for each class were calculated. The Hydrologic Modelling System HEC-HMS, developed by the US Army Corps of Engineers Hydrologic Engineering Centre (HEC) was used to model the flood flows of the basin. Calibration and validation of the model was done by employing the SCS CN as the loss method. Calibration of the model was done for five years (2003- 2007) to discover the best parameters of HEC-HMS model while validation of the model was done for three years (2015- 2017). The final analysis of the model showed CN to be the most sensitive parameter for simulating the runoff in the basin. The Nash-Sutcliffe model efficiency (E) for the calibration period was found to increase from 0.726 to 0.766 and 0.816 for the validation period. The correlation coefficient (R2) value was observed to increase from 0.80 to 0.83 before and after the calibration and a value of 0.85 was obtained for the validation period respectively indicating good performance of the model. Simulation runs of the model were done separately for another three years i.e., 1997, 2007 and 2017 in order to analyze the changes in runoff with respect to land use changes. It was observed that the vegetation area decreased consequently from 886.21 km2 to 803.09 km2 while the urban area was found to increase from 31.74 km2 to 41.93 km2 (1997-2017). Aside from that the annual rate change for each class was calculated and results showed an increment in the class of paddy, palm, barren land and urban area while a decrease in annual rate change of vegetation class was also observed. LULC transition matrix was also prepared for 1997-2007 and 2007-2017. From the net loss and gain calculation it was observed that the highest loss from 1997-2007 was found to be for vegetation (-52.52 km2) and the highest gain was of Paddy (54.39 km2). In between 2007-2017 the highest loss was noticed to be for vegetation (-30.59 km2) while the highest gain was for barren land (54.39 km2). The study highlights a disturbing observation in the last two decades and how this change has prompted the occurrence of floods and runoff. After analyzing the decadal land use changes and the simulated runoff values, it was understood how, loss of vegetation cover and increase in urbanization being the most significant reasons for LULC changes have altered the overall basin ecology.