Anil, KuruvilaOtieno Felix, OwinoKAU2020-12-182020-12-182020174910https://krishikosh.egranth.ac.in/handle/1/5810156945MScKerala 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.EnglishStructural transformation and spatio temporal variations of agriculture in KeralaThesis