Suitability of cotton cultivation in shrink–swell soils in central India |
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| Institution: | 1. School of Earth and Environmental Sciences, University of Adelaide, South Australia 5005, Australia;2. School of Agriculture, Food and Wine, University of Adelaide, South Australia 5005, Australia;3. School of Physical Sciences, University of Adelaide, South Australia 5005, Australia;1. INRA, UR1321 ASTRO Agrosystèmes tropicaux, F-97170 Petit-Bourg, Guadeloupe, France;2. AgroParisTech, UMR 211 Agronomie, F-78850 Thiverval-Grignon, France;3. INRA, UMR 211 Agronomie, F-78850 Thiverval-Grignon, France;1. Università degli Studi di Milano, DEMM, Cassandra Lab, via Celoria 2, 20133 Milano, Italy;2. Università degli Studi di Milano, DiSAA, Cassandra Lab, via Celoria 2, 20133 Milan, Italy;3. Leibniz Centre for Agricultural Landscape Research (ZALF) e.V., Institute for Landscape System Analysis, Eberswalder Str. 84, 15374 Müncheberg, Germany;4. European Commission, Joint Research Centre, Institute for Environment and Sustainability, Monitoring Agricultural Resources Unit—H04, Via Fermi 2749, TP 263, I-21027 Ispra, VA, Italy;5. Luiz de Queiroz College of Agriculture (ESALQ), University of São Paulo, Brazil |
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| Abstract: | Rainfed cotton farming is a risky enterprise. It has always been a challenge to sustain cotton productivity under rainfed conditions not only in India but also in similar agro-environments elsewhere. The present study is an attempt to find out the most sustainable soil under varying rainfall through crop yield correlation with agro-environment factors, like soil physiographic conditions, growing period rainfall, crop ET and phasic rainfall, by conducting (farmers’) field experiment in a representative catena with four different soil types in central India. Cotton (hybrid-H4) was grown for 5 years; 3 years under normal rainfall, 1 year under excessive rainfall and 1 year under drought conditions. The investigation revealed that in the excess rainfall to drought years, yield fluctuation varied from 2% to 38% over the normal year in shallow soils occurring on a pediment plain to the very deep soils in a valley plain. However, the yield fluctuation in deep Vertisols occurring on lower Piedmont and narrow valley, representing Vertic Haplustepts (P3) and Typic Haplusterts (P4), was 25–38% and 6–25%, respectively. The low yield fluctuation and high yield correlation with agro-environmental factors, observed for P3 soils, suggests the suitability of Vertic Haplustepts (P3) for cotton production under varying rainfall conditions. Cultivating P3 soils for cotton could stabilize the income of cotton farmers and research relating to cotton genotype improvement under rainfed conditions should be carried out to minimize soil effects. The international land evaluation criteria suggested by FAO show that Vertisols (P3 and P4) qualify as a suitable category for cotton production under rainfed conditions. However, the present study indicates that this categorization may need revision in view of the adverse climatic conditions of central India. In order to improve the effectiveness of the FAO’s land evaluation criteria for sub-tropical Vertisols, the study suggests that more emphasis be given to rainfall in the critical growth phases related to crop yield and to soil hydraulic conductivity related to the Ca2+/Mg2+ ratio in computing land indices, rather than total quantum rainfall during the growing period. Also, too many soil properties are presently considered in the FAO method. A quantum of 250–325 mm rainfall at the square initiation to peak flowering stages was found to influence yield. Under climatic aberration, the high fluctuation of cotton productivity in deep Vertisol (P4) may be minimized by adoption of any soil management technology (e.g. ridges or broad-bed furrow system) that helps in improving internal drainage. It is, therefore, urgent that the Indian Government should enact special legislation or introduce incentives for the Vertisol farmers who mostly use old cultivation practices to adopt such technology on a large scale. A quadratic regression model developed in this study to compute the yield under varying rainfall may help in estimating the economic losses to the farmers and quantifying crop insurance compensation. |
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