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Using satellite remote sensing to understand maize yield gaps in the North China Plain
Journal Article

Substantial gaps have been reported between the average farmer’s maize yield and yield potential in China, especially the North China Plain (NCP). This maize yield gap as identified by previous studies indicates large opportunities for raising yield by improving agronomy. Agronomic factors are either transient or persistent. Transient factors, which explain yield differences depending on unpredictable weather conditions, can have significantly different optimums from one year to another. While those transient factors are difficult to improve without reliable forecasts, persistent factors influence yield more consistently and therefore represent the best near-term targets for shrinking yield gaps. In this study, multi-year satellite images are used to quantify field-scale maize yield variation in Quzhou County of NCP, and this variation is then analyzed to determine the role of soil type and persistent management factors in explaining yield gaps. Results indicate that (i) remote sensing can provide reasonably reliable estimates of maize yields in this region; (ii) soil type has a clear effect on maize yields, and one that interacts strongly with growing season rainfall amounts; and (iii) on average roughly 20% of yield differences that appear within any one year are related to factors that persist in other years. Overall, the study presents a generalizable methodology of assessing yield gap as well as the proportion arising from persistent factors using satellite data. Our results suggest that the majority of yield gap is dominated by transient factors, and shrinking this gap may require high quality forecasts to make informed optimal management decisions.

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