Simulation, validation and application of CERES-Maize model for yield maximization of maize in North Western Himalayas

Abstract

Maize (Zea mays L.) is one of the most important cereal crops of the world. Investigations were carried out for determination of genotypic coefficients of important varieties of maize by using CERES-Maize model in the Decision Support System for Agrotechnology Transfer (DSSAT v 3.5). The CERES-Maize model was evaluated with experimental data collected during two field experiments conducted in Palampur, India. Field experiments comprising of four dates of sowing (June 1, June 10, June 20 and June 30) and four varieties (KH 9451, KH 5991, early composite and local) of maize were conducted during Summer 2003 and 2004 in split plot design. Observations on development stages, dry matter accumulation at 15 days interval, yield attributes, yield (grains, stover and biological), nitrogen content and uptake were recorded. Genotypic coefficients of important varieties of maize were worked out. CERES-Maize model successfully simulated phenological stages, yield attributes (except single grain weight), yield and also N uptake with coefficient of variation (CV) nearly equal to 10%. CERES-Maize model was validated with fair degree of accuracy. Simulation guided management practices were worked out under potential production and resource limiting situations. Best time of sowing of both hybrids (KH 9451, KH 5991) was worked out to be last week of April. While for early composite (EC), first week of May proved advantageous and for local variety second fortnight of April was the best time of sowing. The best schedule of N application was 60 kg ha-1 at sowing time and 30 kg ha-1 at knee high stage for all varieties except for local where it was 60 kg ha-1 at sowing and 30 kg ha-1 each at knee high and silking stages. © 2012, ALÖKI Kft., Budapest, Hungary.