ORCID Profile
0000-0002-4616-8429
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: MDPI AG
Date: 17-08-2020
DOI: 10.3390/SU12166633
Abstract: Agricultural labor is largely informal, particularly for female agricultural labor in developing countries. Despite significant participation in the agricultural labor force in Pakistan, women’s contribution is not properly acknowledged and rewarded. The issue is further aggravated by the dearth of literature on gender–labor relations in cropping and livestock activities. Considering this gap in the literature, the current study was conducted with the specific objective of exploring the labor composition of different agricultural activities in different farm size categories in general and, particularly, female agricultural labor (family and hired labor) participation and its determinants in the rice–wheat cropping system of the Punjab province, Pakistan. The data were collected from 300 households across four districts of the province. Labor participation was calculated on an official farm size classification basis, i.e., small ( .5 acres), medium (12.6–25 acres) and large ( acres) farms. The findings show that female labor is predominantly demanded in the manual harvesting of wheat, rice nursery transplantation and harvesting, and the majority of the livestock-related activities. The regression model results showed that family female labor and hired female labor participation significantly depend on the landholding status of farmers, household size, family type and level of education. The interviews also illustrated that labor relations are rapidly changing—ongoing mechanization threatens conventional female labor activities due to the lack of machinery operation skills among females, caused by informal state policies and cultural barriers. The findings of the study have important policy implications for mainstreaming gender status in agricultural policy and rural development and contribute directly to the Sustainable Development Goals on Gender Equality (SDG#5) and Decent Work and Economic Growth (SDG#8), and indirectly to No Poverty (SDG#1), Zero Hunger (SDG#2), Responsible Consumption and Production (SDG#12) and Climate Action (SDG#13).
Publisher: Elsevier BV
Date: 2021
Publisher: Springer Singapore
Date: 2019
Publisher: Elsevier BV
Date: 02-2019
Publisher: MDPI AG
Date: 27-08-2020
DOI: 10.3390/RS12172782
Abstract: The frozen water reserves on the Earth are not only very dynamic in their nature, but also have significant effects on hydrological response of complex and dynamic river basins. The Indus basin is one of the most complex river basins in the world and receives most of its share from the Asian Water Tower (Himalayas). In such a huge river basin with high-altitude mountains, the regular quantification of snow cover is a great challenge to researchers for the management of downstream ecosystems. In this study, Moderate Resolution Imaging Spectroradiometer (MODIS) daily (MOD09GA) and 8-day (MOD09A1) products were used for the spatiotemporal quantification of snow cover over the Indus basin and the western rivers’ catchments from 2008 to 2018. The high-resolution Landsat Enhanced Thematic Mapper Plus (ETM+) was used as a standard product with a minimum Normalized Difference Snow Index (NDSI) threshold (0.4) to delineate the snow cover for 120 scenes over the Indus basin on different days. All types of errors of commission/omission were masked out using water, sand, cloud, and forest masks at different spatiotemporal resolutions. The snow cover comparison of MODIS products with Landsat ETM+, in situ snow data and Google Earth imagery indicated that the minimum NDSI threshold of 0.34 fits well compared to the globally accepted threshold of 0.4 due to the coarser resolution of MODIS products. The intercomparison of the time series snow cover area of MODIS products indicated R2 values of 0.96, 0.95, 0.97, 0.96 and 0.98, for the Chenab, Jhelum, Indus and eastern rivers’ catchments and Indus basin, respectively. A linear least squares regression analysis of the snow cover area of the Indus basin indicated a declining trend of about 3358 and 2459 km2 per year for MOD09A1 and MOD09GA products, respectively. The results also revealed a decrease in snow cover area over all the parts of the Indus basin and its sub-catchments. Our results suggest that MODIS time series NDSI analysis is a useful technique to estimate snow cover over the mountainous areas of complex river basins.
Publisher: Elsevier BV
Date: 2017
Publisher: Springer Science and Business Media LLC
Date: 17-10-2016
No related grants have been discovered for Tasneem Khaliq.