Calibration and Validation of Infocrop Simulation Model for Bt Cotton Hybrids
Loading...
Files
Date
2017-08
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
University of Agricultural Science, Dharwad
Abstract
Crop simulation models are used as tool for agricultural risk analysis and allow researchers to explore potential cropping location and appropriate farm management strategies. These models, when properly calibrated and validated against experimental data have the potential for tactical and strategic decision making in agriculture.
In the present investigation, INFOCROP v2, a generic model that integrates genotype, soil, environmental and management practices was used to simulate the phenology, growth and yield of Bt cotton crop sown on different dates. The genetic coefficients were generated for three popular Bt cotton hybrids viz., ATM, Chiranjeevi and Firstclass. By conducting a field experiment during kharif season of 2016 at Main Agricultural Research station, UAS, Dharwad, Karnataka. Three dates of sowing were assigned as main plot treatments viz., 25th June, 10th July and 25th July with three Bt hybrids as sub plot treatments. The results of simulation studies in respect of the effect of different dates of sowing on phenology, crop growth parameters and seed cotton yield were compared with the observed values from the field experiment.
Performance of INFOCROP v2 was evaluated in terms of per cent deviation from the observed. Under normal date of sowing (First and second) it was over estimated the yield by 18.3 per cent. This over estimation further increased at third date of sowing. Over estimation for the growth parameters were 5.3 per cent for days to anthesis, 2.2 per cent for days to maturity, 28.2 per cent for leaf area index, 15.5 per cent for boll number, 7.3 per cent for boll weight, 15.6 per cent for total dry matter and 23.2 per cent for seed cotton yield. Thus it was observed that INFOCROP v2 estimated about 87 per cent accuracy across the different dates of sowing and genotypes by considering all the parameters under study.