TY - JOUR
T1 - Impact of Climate Warming on Cotton Growth and Yields in China and Pakistan: A Regional Perspective
AU - Arshad, Adnan
AU - Raza, Muhammad Ali
AU - Zhang, Yue
AU - Zhang, Lizhen
AU - Wang, Xuejiao
AU - Ahmed, Mukhtar
AU - Habib-ur-Rehman, Muhammad
PY - 2021
Y1 - 2021
N2 - 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.
AB - 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.
KW - agrometeorology
KW - temperature increase
KW - cotton phenology
KW - climate-smart management
KW - APSIM-cotton crop modelling
KW - agrometeorology
KW - temperature increase
KW - cotton phenology
KW - climate-smart management
KW - APSIM-cotton crop modelling
UR - https://res.slu.se/id/publ/111125
U2 - 10.3390/agriculture11020097
DO - 10.3390/agriculture11020097
M3 - Journal article
SN - 2077-0472
VL - 11
JO - Agriculture
JF - Agriculture
IS - 2
M1 - 97
ER -