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Climate trends and maize production nexus in Mississippi: empirical evidence from ARDL modelling

Climate change poses a significant threat to agriculture. However, climatic trends and their impact on Mississippi (MS) maize (Zea mays L.) are unknown. The objectives were to: (i) analyze trends in climatic variables (1970 to 2020) using Mann–Kendall and Sen slope method, (ii) quantify the impact o...

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Autores principales: Sharma, Ramandeep Kumar, Dhillon, Jagmandeep, Kumar, Pushp, Bheemanahalli, Raju, Li, Xiaofei, Cox, Michael S., Reddy, Krishna N.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10547789/
https://www.ncbi.nlm.nih.gov/pubmed/37789065
http://dx.doi.org/10.1038/s41598-023-43528-6
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author Sharma, Ramandeep Kumar
Dhillon, Jagmandeep
Kumar, Pushp
Bheemanahalli, Raju
Li, Xiaofei
Cox, Michael S.
Reddy, Krishna N.
author_facet Sharma, Ramandeep Kumar
Dhillon, Jagmandeep
Kumar, Pushp
Bheemanahalli, Raju
Li, Xiaofei
Cox, Michael S.
Reddy, Krishna N.
author_sort Sharma, Ramandeep Kumar
collection PubMed
description Climate change poses a significant threat to agriculture. However, climatic trends and their impact on Mississippi (MS) maize (Zea mays L.) are unknown. The objectives were to: (i) analyze trends in climatic variables (1970 to 2020) using Mann–Kendall and Sen slope method, (ii) quantify the impact of climate change on maize yield in short and long run using the auto-regressive distributive lag (ARDL) model, and (iii) categorize the critical months for maize-climate link using Pearson’s correlation matrix. The climatic variables considered were maximum temperature (Tmax), minimum temperature (Tmin), diurnal temperature range (DTR), precipitation (PT), relative humidity (RH), and carbon emissions (CO(2)). The pre-analysis, post-analysis, and model robustness statistical tests were verified, and all conditions were met. A significant upward trend in Tmax (0.13 °C/decade), Tmin (0.27 °C/decade), and CO(2) (5.1 units/decade), and a downward trend in DTR ( − 0.15 °C/decade) were noted. The PT and RH insignificantly increased by 4.32 mm and 0.11% per decade, respectively. The ARDL model explained 76.6% of the total variations in maize yield. Notably, the maize yield had a negative correlation with Tmax for June, and July, with PT in August, and with DTR for June, July, and August, whereas a positive correlation was noted with Tmin in June, July, and August. Overall, a unit change in Tmax reduced the maize yield by 7.39% and 26.33%, and a unit change in PT reduced it by 0.65% and 2.69% in the short and long run, respectively. However, a unit change in Tmin, and CO(2) emissions increased maize yield by 20.68% and 0.63% in the long run with no short run effect. Overall, it is imperative to reassess the agronomic management strategies, developing and testing cultivars adaptable to the revealed climatic trend, with ability to withstand severe weather conditions in ensuring sustainable maize production.
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spelling pubmed-105477892023-10-05 Climate trends and maize production nexus in Mississippi: empirical evidence from ARDL modelling Sharma, Ramandeep Kumar Dhillon, Jagmandeep Kumar, Pushp Bheemanahalli, Raju Li, Xiaofei Cox, Michael S. Reddy, Krishna N. Sci Rep Article Climate change poses a significant threat to agriculture. However, climatic trends and their impact on Mississippi (MS) maize (Zea mays L.) are unknown. The objectives were to: (i) analyze trends in climatic variables (1970 to 2020) using Mann–Kendall and Sen slope method, (ii) quantify the impact of climate change on maize yield in short and long run using the auto-regressive distributive lag (ARDL) model, and (iii) categorize the critical months for maize-climate link using Pearson’s correlation matrix. The climatic variables considered were maximum temperature (Tmax), minimum temperature (Tmin), diurnal temperature range (DTR), precipitation (PT), relative humidity (RH), and carbon emissions (CO(2)). The pre-analysis, post-analysis, and model robustness statistical tests were verified, and all conditions were met. A significant upward trend in Tmax (0.13 °C/decade), Tmin (0.27 °C/decade), and CO(2) (5.1 units/decade), and a downward trend in DTR ( − 0.15 °C/decade) were noted. The PT and RH insignificantly increased by 4.32 mm and 0.11% per decade, respectively. The ARDL model explained 76.6% of the total variations in maize yield. Notably, the maize yield had a negative correlation with Tmax for June, and July, with PT in August, and with DTR for June, July, and August, whereas a positive correlation was noted with Tmin in June, July, and August. Overall, a unit change in Tmax reduced the maize yield by 7.39% and 26.33%, and a unit change in PT reduced it by 0.65% and 2.69% in the short and long run, respectively. However, a unit change in Tmin, and CO(2) emissions increased maize yield by 20.68% and 0.63% in the long run with no short run effect. Overall, it is imperative to reassess the agronomic management strategies, developing and testing cultivars adaptable to the revealed climatic trend, with ability to withstand severe weather conditions in ensuring sustainable maize production. Nature Publishing Group UK 2023-10-03 /pmc/articles/PMC10547789/ /pubmed/37789065 http://dx.doi.org/10.1038/s41598-023-43528-6 Text en © This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Sharma, Ramandeep Kumar
Dhillon, Jagmandeep
Kumar, Pushp
Bheemanahalli, Raju
Li, Xiaofei
Cox, Michael S.
Reddy, Krishna N.
Climate trends and maize production nexus in Mississippi: empirical evidence from ARDL modelling
title Climate trends and maize production nexus in Mississippi: empirical evidence from ARDL modelling
title_full Climate trends and maize production nexus in Mississippi: empirical evidence from ARDL modelling
title_fullStr Climate trends and maize production nexus in Mississippi: empirical evidence from ARDL modelling
title_full_unstemmed Climate trends and maize production nexus in Mississippi: empirical evidence from ARDL modelling
title_short Climate trends and maize production nexus in Mississippi: empirical evidence from ARDL modelling
title_sort climate trends and maize production nexus in mississippi: empirical evidence from ardl modelling
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10547789/
https://www.ncbi.nlm.nih.gov/pubmed/37789065
http://dx.doi.org/10.1038/s41598-023-43528-6
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