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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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Author: KAU × End date: 2021 × Start date: 2020 × Rating Count: 5 ×
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    ThesisItemOpen Access
    Modelling climate change impact on surface runoff and sediment yield in a watershed of Shivalik region
    (Academy of Climate Change Education and Research, Vellanikkara, 2020) Anu Raj, D; KAU; Mary Regina, F
    The climate change refers to the seasonal changes over a long duration in relation to the increasing amount of greenhouse gasses in the atmosphere. Global warming leads to a more vigorous hydrological cycle, including higher amount rainfall and more frequent high-intensity rainfall events. The Himalayan region is suffering from a serious problem of soil erosion and rivers flowing through this region transport a massive load of sediment. Climate change has a significant contribution to soil erosion. It leads to loss of nutrient-rich top soil which in turn can affect the nation’s food security. The present study depicts modelling climate change impact on surface runoff and sediment yield in a watershed of Shivalik region of Himachal Pradesh using a process-based Agricultural Policy/ Environmental eXtender(APEX) model. Terrain characteristics were analysed with the aid of Cartosat DEM. Land use/land cover characteristics were extracted from Resourcesat-2 LISS-IV and ground observations. Soil samples were collected from the field were analysed to identify soil physical and chemical properties. Surface runoff and sediment yield data required for model calibration and validation were collected from the gauging station constructed in the field. The future climate scenarios (temperature and rainfall) namely A2 and B2 of the study area were downscaled using statistical downscaling model (SDSM). APEX model parameterization was done as per local conditions. The APEX model was calibrated on a daily basis for 2017 and 2018. For calibration and validation of the model used low to medium rainfall days. The model calibrated quite well for surface runoff (r2 - 0.92) and sediment yield (r2 - 0.88) with RMSE of 4.98 mm and 0.20 t/ ha for surface runoff and sediment yield, respectively. The model was validated well for surface runoff (r2 - 0.81) and sediment yield (r2 - 0.81) with RMSE of 2.6 mm and 0.11 t/ha for surface runoff and sediment yield respectively. The model performance was identified based on Nash- Sutcliffe efficiency (NSE). The model performed quite well for surface runoff and sediment 224 yield of NSE 0.71 and 0.70 respectively. The change in soil loss under A2 and B2 scenarios with respect to baseline period were predicted for the study area to recognize the effect of climate change on soil loss. The general trend in future climate shows there is an increase in rainfall under both A2 and B2 scenario. Under the A2 scenario, rainfall increases marginally higher than B2 scenario. A total of 41.35 per cent increase in rainfall during 2080, 20.14 per cent during 2050, and 27.27 per cent during 2020 were observed. But in B2 scenario due to lower emission, change in rainfall is relatively lower than A2 scenario. It was observed that 24.71 per cent, 29.13 per cent and 35.16 per cent increase during 2020, 2050 and 2080 respectively. Maximum temperature increases 3.7 oC during 2080 under A2, while under B2 scenario the increase is 2.6 oC. Similarly, minimum temperature also rising at 3.6 oC during 2080 under A2 scenario and 2.7 oC under B2 scenario. The increase in temperature under both scenarios is almost similar and a marginal difference was observed. Highest soil loss was estimated from scrub land (38.42 t/ha/yr) followed by agriculture (26.97 t/ha/yr) then open forest (21.69 t/ha/yr) and lowest in the dense forest cover (14.70 t/ha/yr) under baseline period. The average annual soil loss from the watershed is 25.45 t/ha/yr. It was observed that 64.61 per cent of the study area was under moderate (10-20 t/ha/yr) erosion risk class. 24.15 per cent area with severe (20-40 ton ha-1 yr-1) erosion and 11.23 per cent area contribute very severe (>40 ton ha-1 yr-1) erosion. Under A2 scenario the average soil loss during 2020s, 2050s and 2080s may increase 27.71, 21.84 and 46.94 per cent respectively. Similarly under B2 scenario average soil loss may increase 23.24, 30.71 and 38.80 per cent, respectively. The climate change impact on soil erosion under both scenarios suggests that there is an increasing soil erosion due to the increase in rainfall in Shivalik region of Himachal Pradesh. Due to the high intensity of rainfall and steep slopes of the study area the mechanical conservation measures are preferred. The agronomic, mechanical and biological measures can be also used to conserve the soil and water.
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    ThesisItemOpen Access
    Structural transformation and spatio temporal variations of agriculture in Kerala
    (Department of Agricultural Economics, College of Horticulture, Vellanikkara, 2020) Otieno Felix, Owino; KAU; Anil, Kuruvila
    Kerala had been undergoing several transformations in its agricultural sector. This was caused by the shift of resources like labourers from the agricultural sector to the secondary and tertiary sector. The transformation could also be seen where ever the rising agricultural wages affected the profitability of major crops due to the increase in the cost of production. The shortage of farm labourers coupled with other factors like uneconomic size of land holdings, sustained conversion of agricultural lands to non-agricultural uses and low profitability in agriculture had hampered the growth in the sector. The structural adjustments could also be observed in the state income in which there was an increase in share of income from the tertiary sector and decline in share from the primary sector. The decline in the share of agriculture in the state income was due to an aggregation of factors. Thus, the present study sought to find out the reasons leading to the transformations in Kerala agriculture by analysing the growth of agriculture and assessing the disparities among the districts in agricultural development in Kerala, examining the dynamics in land use and cropping patterns, studying the dynamics in economics, efficiency and profitability of cultivation of major crops and estimating the total factor productivity and its determinants for major crops in Kerala. The time series data for the period from 1970-71 to 2018-19 was used to understand the objectives of this study. The entire series was subjected to (Bai and Perron, 1998) methodology and six phases of growth were obtained, on which the entire study was based. These periods were Period I (1970-71 to 1980-81), Period II (1981-82 to 1987-88), Period III (1988-89 to 1994-95), Period IV (1995-96 to 2003-04), Period V (2004-05 to 2010-11) and Period VI (2011-12 to 2018-19). The Compound annual growth rates and Cuddy-Della Instability Indices were used to understand the growth performance of the crops. The results of the analyses of growth in crops revealed that food grains, tapioca, ginger and cashew had the largest loss in area throughout the period under study. Pulses, paddy, tapioca, cashew and ginger exhibited annual declines of -6.58 per cent, -3.89 per cent, -3.71 per cent, -2.44 per cent and -2.12 per cent in their area. These crops also had the lowest growth in productivities which affected the production. This was found to be due to fall in the prices of these crops, rising cost of inputs and rising prices of other crops. Rubber had the largest annual rise in area of 2.56 per cent in the entire period of the study. Other crops that were found to have performed well were coconut and banana and other plantains. The trend break analysis was also used to study the growth performance of crops in Kerala. It was established that the main reason for breaks in areas under most crops was related to profitability. It was noted that with increases in prices, especially for plantation crops, the areas under the crops also increased. Several crops had breaks in their areas exactly at the time when rubber was recording its best prices in 1995 and from 2007-08 to 2009-10. Due to the sustained rise in prices of rubber, crops like paddy were much affected, since it is a labour-intensive crop and an increase in the wages of field labour impacted it negatively. Plantation crops on the other hand were less labour intensive and the increases in prices were an incentive for the farmers to expand the area under the cultivation of those crops. In turn, the area under rubber and coconut increased tremendously especially from late 1980s. Thus, changes in prices was a major cause for most breaks in most of the crops. The government policies and interventions in the agricultural sector were found to be the major contributor to the trend breaks. The introduction of policies that promoted the cultivation of crops such as paddy led to increase in their areas and these led to the breaks. These include the group farming scheme implemented in 1988-89, promotion of paddy cultivation in the fallow lands of 2004-05 and the enactment of the conservation of paddy land and wetland act of 2008. Seemingly Unrelated Regression (SUR) model was used to understand the determinants of the growth in the GSDP from agriculture. The model revealed that the largest contributor to per capita agricultural GSVA was gross cropped area irrigated. This meant that for every additional hectare of land brought to irrigation every year, it added 75.3 per cent of the value of the output per hectare from the crop to the per capita income from agriculture. The area under high value crops was also found to be significant and positively influencing per capita GSVA from agriculture and this was a confirmation that increased cultivation of high value crops was key to growth in earnings from agriculture in Kerala State. The fertiliser consumption was also found to be important in improving the earnings realised from agriculture. The use of fertilisers improved the contribution from crops to the agriculture per capita income by 24 per cent, while rainfall improved the earnings by 10.5 per cent. The study on the land use and cropping pattern changes revealed through transition probability matrices obtained from Markov chain analyses showed that various land use classes apart from forest were not stable throughout, but had seasons of loss and gain to and from other different land use classes, which was also the same case for crops. For instance, area put to non-agricultural uses and, permanent pastures and grazing lands were the most stable land use classes in the first phase of the study (1970-71 to 1980-81). This phase was the beginning of shift from various crops to plantation crops and large tracts of lands in which other crops were grown were converted to the cultivation of plantation crops like rubber due to increasing prices and profitability. This shift in land use helped to increase the net sown area. The net sown area also had 4.4 per cent probability of receiving land from permanent pastures and grazing lands, and a probability of 21.4 per cent from area under miscellaneous tree crops. However, in contrast to the first phase, in the last and sixth phase from 2011-12 to 2018-19, the area under non-agricultural uses which got a stimulus in the fifth phase, showed a 100 per cent probability of holding to its share in the sixth phase. The cultivable waste drew gains from net sown area. The area under pastures showed a 93.2 per cent of probability of transition to net sown area, an indication that the area under permanent pastures and grazing lands was getting cleared and converted to farm lands. The study on economics, efficiency and profitability of crops revealed that the profitability of tapioca, coconut and black pepper were highest in the large and medium holdings. Ginger presented an inverse of the trend shown in many crops in which small holdings were the least profitable. This was attributed to complexities in managing large ginger farms which were prone to diseases. Overall, the profitability improved over the period under study for all the crops other than ginger, which could be attributed to increased use of high yielding varieties and efficient fertilisers that improved the productivity. Banana and other plantains, autumn paddy and coconut had the largest TFP. The TFP growth in these crops were majorly driven by increases in their technological components. Winter paddy and summer paddy also had a slight increment in their TFP mainly driven by growth in their technological changes and hindered by decline in their technical efficiencies. Tapioca, black pepper and ginger recorded negative changes in their TFPs. The decline in TFP of these crops was majorly due to the decline in the technological changes in these crops. Therefore, there is need for increased public investment in the agricultural sector. The increased public investment will in turn promote private investment in potential areas of the state, which will sequentially help to provide incentives and favourable environment for agricultural development.