ORCID Profile
0000-0002-9249-185X
Current Organisation
University of Agriculture Faisalabad
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Publisher: SAGE Publications
Date: 18-08-2016
Abstract: Maize is one of the main cereal crops in Pakistan with sensitivity to drought at various developmental stages known to influence the yield. The impact of variable weather conditions on maize yield can be analyzed with crop simulation models. The CSM-CERES-Maize model has been widely used to assess irrigation strategies for maize. This research was conducted to test the CSM-CERES-Maize model for its ability to accurately predict maize biomass and grain yield under water limiting and non-limiting conditions in semiarid conditions. Four growth stage-based irrigation treatments and two potential soil moisture deficit-based treatments were defined. During model calibration, the simulated maximum leaf area index (LAI), total dry matter (TDM), and grain yield were all within 10% of observed values. During model evaluation, there was generally satisfactory agreement between observed and simulated values for two hybrids (Monsanto-919 and Pioneer-30Y87) with the model showing variability of −17.9–20.0%, −9.2–14.3%, and −19.6–19.9% for maximum LAI, TDM, and grain yield, respectively, for the two hybrids among various treatments. The CERES-Maize model was useful in providing information to decision-making regarding erse irrigation regimes at the farm level in a semiarid environment.
Publisher: Springer Science and Business Media LLC
Date: 04-11-2018
DOI: 10.1007/S11356-017-0592-Z
Abstract: Sunflower (Helianthus annuus L.) is the leading non-conventional oilseed crop in Pakistan. Nitrogen fertilizer can affect plant growth and productivity by changing canopy size which has an effect on the radiation use efficiency (RUE) of the crop. The response of sunflower hybrids in terms of phenology, fraction of intercepted radiation (F
Publisher: Elsevier BV
Date: 12-2017
Publisher: Springer Science and Business Media LLC
Date: 05-03-2018
DOI: 10.1007/S11356-018-1587-0
Abstract: Growth, development, and economic yield of agricultural crops rely on moisture, temperature, light, and carbon dioxide concentration. However, the amount of these parameters is varying with time due to climate change. Climate change is factual and ongoing so, first principle of agronomy should be to identify climate change potential impacts and adaptation measures to manage the susceptibilities of agricultural sector. Crop models have ability to predict the crop's yield under changing climatic conditions. We used OILCROP-SUN model to simulate the influence of elevated temperature and CO
Publisher: Springer Science and Business Media LLC
Date: 08-06-2017
DOI: 10.1007/S11356-017-9308-7
Abstract: The combination of nitrogen and plant population expresses the spatial distribution of crop plants. The spatial distribution influences canopy structure and development, radiation capture, accumulated intercepted radiation (Sa), radiation use efficiency (RUE), and subsequently dry matter production. We hypothesized that the sunflower crop at higher plant populations and nitrogen (N) rates would achieve early canopy cover, capture more radiant energy, utilize radiation energy more efficiently, and ultimately increase economic yield. To investigate the above hypothesis, we examined the influences of leaf area index (LAI) at different plant populations (83,333, 66,666, and 55,555 plants ha
Publisher: Informa UK Limited
Date: 02-08-2017
Publisher: SAGE Publications
Date: 03-2016
DOI: 10.5367/OA.2015.0226
Abstract: Climate change, food security, water scarcity and environmental sustainability have all become major global challenges. As a consequence, improving resource use efficiency is an important aspect of increasing crop productivity. Crop models are increasingly being used as tools for supporting strategic and tactical decision making under varying agro-climatic and socioeconomic conditions. These tools can also support climate change assessment and the evaluation of adaptation strategies to limit the adverse impacts of climate change. In this paper, the authors report on a case study conducted to assess the potential impact of climate change on grain yield in sunflower under arid, semi-arid and subhumid conditions in the Punjab region of Pakistan. Experimental data obtained between 2008 and 2009 were used for model evaluation. The study focused on the impacts of incremental temperature change on sunflower production. The modelling suggests that grain yield could reduce by up to 15% by the 2020s with an average increase in temperature of +1°C, and by up to 25% if temperatures increased by up to 2°C for the 2050s. Adaptation strategies showed that, if the crop were sown between 14 days (for 2020) and 21 days (for 2050) earlier than the current date (last week in February), yield losses could potentially be reduced.
Publisher: Elsevier BV
Date: 04-2017
Publisher: Elsevier BV
Date: 11-2018
Publisher: Elsevier BV
Date: 03-2016
Publisher: Elsevier BV
Date: 05-2019
Publisher: Elsevier BV
Date: 05-2018
Publisher: MDPI AG
Date: 10-02-2017
Abstract: Understanding the impact of the warming trend on phenological stages and phases of cotton (Gossypium hirsutum L.) in central and lower Punjab, Pakistan, may assist in optimizing crop management practices to enhance production. This study determined the influence of the thermal trend on cotton phenology from 1980–2015 in 15 selected locations. The results demonstrated that observed phenological stages including sowing (S), emergence (E), anthesis (A) and physiological maturity (M) occurred earlier by, on average, 5.35, 5.08, 2.87 and 1.12 days decade−1, respectively. Phenological phases, sowing anthesis (S-A), anthesis to maturity (A-M) and sowing to maturity (S-M) were reduced by, on average, 2.45, 1.76 and 4.23 days decade−1, respectively. Observed sowing, emergence, anthesis and maturity were negatively correlated with air temperature by, on average, −2.03, −1.93, −1.09 and −0.42 days °C−1, respectively. Observed sowing-anthesis, anthesis to maturity and sowing-maturity were also negatively correlated with temperature by, on average, −0.94, −0.67 and −1.61 days °C−1, respectively. Applying the cropping system model CSM-CROPGRO-Cotton model using a standard variety in all locations indicated that the model-predicted phenology accelerated more due to warming trends than field-observed phenology. However, 30.21% of the harmful influence of the thermal trend was compensated as a result of introducing new cotton cultivars with higher growing degree day (thermal time) requirements. Therefore, new cotton cultivars which have higher thermal times and are high temperature tolerant should be evolved.
Publisher: Springer Science and Business Media LLC
Date: 17-10-2016
No related grants have been discovered for Ashfaq Ahmad.