Yield gap and resource utilization efficiency of three major food crops in the world – A review

Yield gap analysis could provide management suggestions to increase crop yields, while the understandings of resource utilization efficiency could help judge the rationality of the management. Based on more than 110 published papers and data from Food and Agriculture Organization (FAO, www.fao.org/f...

Full description

Bibliographic Details
Main Authors: Liang-bing RONG, Kai-yuan GONG, Feng-ying DUAN, Shao-kun LI, Ming ZHAO, Jianqiang HE, Wen-bin ZHOU, Qiang YU
Format: Article
Language:English
Published: Elsevier 2021-02-01
Series:Journal of Integrative Agriculture
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2095311920635559
Description
Summary:Yield gap analysis could provide management suggestions to increase crop yields, while the understandings of resource utilization efficiency could help judge the rationality of the management. Based on more than 110 published papers and data from Food and Agriculture Organization (FAO, www.fao.org/faostat) and the Global Yield Gap and Water Productivity Atlas (www.yieldgap.org), this study summarized the concept, quantitative method of yield gap, yield-limiting factors, and resource utilization efficiency of the three major food crops (wheat, maize and rice). Currently, global potential yields of wheat, maize and rice were 7.7, 10.4 and 8.5 t ha–1, respectively. However, actual yields of wheat, maize and rice were just 4.1, 5.5 and 4.0 t ha–1, respectively. Climate, nutrients, moisture, crop varieties, planting dates, and socioeconomic conditions are the most mentioned yield-limiting factors. In terms of resource utilization, nitrogen utilization, water utilization, and radiation utilization efficiencies are still not optimal, and this review has summarized the main improvement measures. The current research focuses on quantitative potential yield and yield gap, with a rough explanation of yield-limiting factors. Subsequent research should use remote sensing data to improve the accuracy of the regional scale and use machine learning to quantify the role of yield-limiting factors in yield gaps and the impact of change crop management on resource utilization efficiency, so as to propose reasonable and effective measures to close yield gaps.
ISSN:2095-3119