Ahmed, Mukhtar
- Department of Agricultural Research for Northern Sweden, Swedish University of Agricultural Sciences
- Pir Mehr Ali Shah Arid Agriculture University
Abstract
Year to year change in weather poses serious threats to agriculture globally, especially in developing countries. Global climate models simulate an increase in global temperature between 2.9 to 5.5 degrees C till 2060, and crop production is highly vulnerable to climate warming trends. Extreme temperature causes a significant reduction in crop yields by negatively regulating the crop phenology. Therefore, to evaluate warming impact on cotton (Gossypium hirsutum L.) production and management practices, we quantified agrometeorological data of 30 years by applying multiple crop modelling tools to compute the expected rise in temperature, impact of crop phenology, yield loss, provision of agrometeorology-services, agronomic technologies, and adaptation to climate-smart agriculture. Model projections of 15 agrometeorology stations showed that the growing duration of the sowing-boll opening and sowing-harvesting stages was reduced by 2.30 to 5.66 days decade(-1) and 4.23 days decade(-1), respectively, in Pakistan. Temperature rise in China also advanced the planting dates, sowing emergence, 3-5 leaves, budding anthesis, full-bloom, cleft-boll, boll-opening, and boll-opening filling by 24.4, 26.2, 24.8, 23.3, 22.6, 15.8, 14.6, 5.4, 2.9, and 8.0 days. Furthermore, present findings exhibited that the warming effect of sowing-harvest time was observed 2.16 days premature, and delayed for 8.2, 2.4, and 5.3 days in the 1970s, 1980s, and 1990s in China. APSIM-cotton quantification revealed that the sowing, emergence, flowering, and maturity stages were negatively correlated with temperature -2.03, -1.93, -1.09, and -0.42 days degrees C-1 on average, respectively. This study also provided insight into the adaptation of smart and better cotton by improving agrotechnological services.
Keywords
agrometeorology; temperature increase; cotton phenology; climate-smart management; APSIM-cotton crop modelling
Published in
Agriculture
2021, volume: 11, number: 2, article number: 97
Publisher: MDPI
SLU Authors
UKÄ Subject classification
Agricultural Science
Publication identifier
- DOI: https://doi.org/10.3390/agriculture11020097
Permanent link to this page (URI)
https://res.slu.se/id/publ/111125