Abstract

The present study was initiated in the Kolar and Chikkaballapur districts of Karnataka with the overall objective of assessing the growth in production and allocation of the area under vegetables in situations. The study was based on time series data collected from the Directorate of Economics and Statistics, Bangalore. Compound Annual Growth Rate and Triennium averages were worked out to examine the trend in area, production and productivity of major vegetable crops. Markov chain analysis was used to examine the dynamic shift in the area, production, and productivity of major vegetable crops for a decade from 2007-08 to 2017-18. The triennium end average of area major vegetable crops in Kolar district for the period TE 2010-11 was 2480.20 ha reduced to 1424.00 ha in TE 2017-18. The productivity of major vegetable crops is increasing to 15134.30 kg/ha from 8830.10 kg/ha (TE 2000-01). The triennium end average of area major vegetable crops in Chikkaballapur district for the period TE 2010-11 was 1085.20 ha increased to 1311.00 ha in TE 2017-18. The productivity of major vegetable crops is increasing to 14422.30 kg/ha from 12166.40 kg/ha (TE 2000-01). The overall growth in the area and productivity of vegetables in Kolar was -7.37 and 8.14 per cent, respectively whereas the overall growth in the area and productivity of vegetables in Chikkaballapur was 4.80 and 1.98 per cent, respectively. Implies growth in the area, production, and productivity showing a decline turn to negative. Whereas, the triennium end average of area for major vegetable crops for the period TE 2017-18 was 124765.7 ha growth of 3.1 per cent and a productivity average of 2165.7 kg/ha with a growth of -0.3 per cent. The tomato and cabbage were the highest retention capacity of 69 per cent equally in both districts. Beans, Brinjal, and Dry chilli have zero retention capacity in the Chikkaballapur district whereas onion, brinjal, and cabbage have zero retention capacity in the Kolar district. i.e these crops lost their 100 per cent area to the other crops. This will be projected by using Markov chain analysis.

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