Remote Sensing-Based Quantification of the Summer Maize Yield Gap Induced by Suboptimum Sowing Dates over North China Plain

Estimating yield potential (Yp) and quantifying the contribution of suboptimum field managements to gap (Yg) crops are important for improving crop effectively. However, achieving this goal on a regional scale remains difficult because challenges in collecting management information. In study, we retrieved information (i.e., emerging stage surrogate sowing date (SDT)) from remote sensing (RS) vegetation index time series. Then, developed new approach quantify maize Yp, total Yg, SDT-induced Yg (Yg0) using process-based RS-driven model (PRYM–Maize), which was our previous study. PRYM–Maize newly method were used over North China Plain (NCP) estimate Ya, Yg0 summer maize. Results showed that outputs reasonable estimates NCP, with correlations root mean standard deviation 0.49 ± 0.24 0.88 0.14 t hm−2, respectively, modeled annual yields versus reference value each year period 2010 2015 city level. Yp estimated can reasonably capture spatial variations site-level growth models literature. The 2010–2015 be 11.99 5.4 hm−2 found between Ya scale. An 29–42% (2010–2015) induced by SDT. also show not all persistent time. Future studies high spatial-resolution RS images disaggregate into non-persistent components small required increase NCP.