干旱区生态环境知识资源中心(Arid): Sustainability insights: Enhancing rainfed wheat and barley yield prediction in arid regions

Arid

DOI	10.1016/j.agwat.2024.108857
	Sustainability insights: Enhancing rainfed wheat and barley yield prediction in arid regions
	Sharafi, Saeed; Nahvinia, Mohammad Javad
通讯作者	Sharafi, S
来源期刊	AGRICULTURAL WATER MANAGEMENT
ISSN	0378-3774
EISSN	1873-2283
出版年	2024
卷号	299
英文摘要	Climate variability plays a pivotal role in rainfed agriculture, especially within arid regions. Analyzing these fluctuations across diverse climatic conditions establishes a foundation for subsequent investigations. In Iran, the FAO 56 aridity index categorizes the nation into very dry, dry, semidry, and humid climate classifications. This study aimed to explore equations derived from multiple linear regression (MLR) and the disparities between predicted and observed yields of rainfed wheat and barley across Iran 's varying climates. Meteorological data, encompassing rainfall (R), mean temperature (T mean ), solar radiation (S), and wind speed (U 2 ), were compiled from 44 synoptic stations spanning 1981 -2020. These data constituted inputs for the MLR models employed to simulate rainfed wheat and barley yields. The Global Performance Indicator (GPI), a 5 -point statistical criteria index, was utilized to assess MLR model performance. The findings unveiled superior MLR model performance in dry climates (R 2 =0.84 for wheat and R 2 =0.9 for barley) compared to humid climates (R 2 =0.69 for wheat and R 2 =0.66 for barley), evidenced by lower statistical error criteria values. Moreover, across all climates, the MLR models exhibited more accurate predictions for rainfed wheat yield (GPI =1559.3) in contrast to rainfed barley (GPI =1536). In conclusion, this study sheds light on the notable role of climate in rainfed agriculture, showcasing the efficacy of MLR models in predicting yields across varying climatic contexts.
英文关键词	Agriculture Climate changes Correlation Rainfed farming Yield gap
类型	Article
语种	英语
开放获取类型	hybrid
收录类别	SCI-E
WOS记录号	WOS:001252956200001
WOS关键词	SOLAR-RADIATION MODELS ; CLIMATE-CHANGE IMPACTS ; VARIABILITY ; PERFORMANCE ; VALIDATION ; RESISTANCE ; REGRESSION ; PROVINCE ; SYSTEMS ; DEMAND
WOS类目	Agronomy ; Water Resources
WOS研究方向	Agriculture ; Water Resources
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/402674
推荐引用方式 GB/T 7714	Sharafi, Saeed,Nahvinia, Mohammad Javad. Sustainability insights: Enhancing rainfed wheat and barley yield prediction in arid regions[J],2024,299.
APA	Sharafi, Saeed,&Nahvinia, Mohammad Javad.(2024).Sustainability insights: Enhancing rainfed wheat and barley yield prediction in arid regions.AGRICULTURAL WATER MANAGEMENT,299.
MLA	Sharafi, Saeed,et al."Sustainability insights: Enhancing rainfed wheat and barley yield prediction in arid regions".AGRICULTURAL WATER MANAGEMENT 299(2024).