The objective of this study was to validate and parameterize an Agricultural Production Systems Simulator model for explaining genotypic and environmental variations in the growth and yield of rain-fed wheat by integrating data on crops, soils and climate. Climate forecasts are being increasingly used to support decision making in agriculture based on risk management under variable climate. Improved skills in seasonal forecasting benefited agricultural management and production. To significantly improve financial profitability, economic efficiency and resource risk management of wheat based cropping systems in rain-fed areas of the Pakistan well targeted studies need to be done by applying seasonal climate forecasts and quantifying climate variability. The present study has been conducted to improve and enhance the utilization of seasonal climate forecast and crop simulation modeling in the agronomic studies to better understand wheat productivity in Pothwar Plateau in the province of Punjab. The present study was conducted from 2008 to 2010 wheat season in collaboration with the National Agricultural Research Centre (NARC), Islamabad, the Barani Agriculture Research Institute Chakwal (BARI) and at farmer field Talagang. Experiments using Randomized Block Design were conducted using three wheat genotypes, five planting times (started from mid of October and extended until the beginning of December). The study emphasized on understanding the physiological and ecological aspects of wheat yield over diverse planting dates using crop simulation modeling technique as a bioinformatics tool. The aim was to better understand the wheat performance in relation to variant climate and also to use this tool for strategic management decisions. The results showed that changing sowing dates affected the adaptability patterns of wheat crop at three locations in the study area because of changes in air temperature and precipitation over the phenological stages of wheat. The planting window as a management instrument influenced biomass production and grain yield of wheat genotypes. Early sowing of wheat in Islamabad (location 1) accelerated expansion of leaf area, especially prior to stem elongation, enhanced tiller growth and resulted in good yield i.e. 4605 kilogram per hectare (kg ha-1). A similar trend was observed in planting window two with the yield potential of 4500 kg ha-1. Negative trend were observed for later planting dates. In Chakwal (location 2) highest yield was obtained in planting window one (PW1) because of availability of conserved moisture in field and due to good crop stand but trend was not negative with late sowing. Talgang being the low precipitation and high temperature area of Pothwar has shown the lowest yield. The highest was recorded in PW2 i.e. 2770 kg ha-1. The whole-process model simultaneously explained the observed genotypic and environmental variation in the dynamics of above-ground biomass growth (coefficient of determination (R2) = 0.95), LAI development (R2 = 0.82) and spikelet number per unit area (R2 = 0.83) and grain yield (R2 = 0.87).
|Keywords:||SOI, APSIM, Pothwar/Pakistan, Phenology, Crop Yield, Agriculture, Climate Variability|
Lecturer, Department of Agronomy, Faculty of Crop and Food Sciences, Arid Agriculture University Rawalpindi, Rawlpindi, Pakistan
Professor, Department of Agronomy, Faculty of Crop and Food sciences, Arid Agriculture University Rawalpindi, Rawlpindi, Pakistan
Commisioner, Minor Crops, MINFA, Islamabad, Islamabad, Pakistan
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