Monitoring Hybrid Rice Phenology at Initial Heading Stage Based on Low-Altitude Remote Sensing Data

Yi Ma,Xianting Wu,Yi Peng,Yan Gong,Bo Duan,Qi Jiang,Shenghui Fang,Renshan Zhu

doi:10.3390/rs13010086

Abstract

Accurate monitoring of hybrid rice phenology (RP) is crucial for breeding rice cultivars and controlling fertilizing amount. The aim of this study is to monitor the exact date of hybrid rice initial heading stage (IHSDAS) based on low-altitude remote sensing data and analyze the influence factors of RP. In this study, six field experiments were conducted in Ezhou city and Lingshui city from 2016 to 2019, which involved different rice cultivars and nitrogen rates. Three low-altitude remote sensing platforms were used to collect rice canopy reflectance. Firstly, we compared the performance of normalized difference vegetation index (NDVI) and red edge chlorophyll index (CIred edge) for monitoring RP. Secondly, double logistic function (DLF), asymmetric gauss function (AGF), and symmetric gauss function (SGF) were used to fit time-series CIred edge for acquiring phenological curves (PC), the feature: maximum curvature (MC) of PC was extracted to monitor IHSDAS. Finally, we analyzed the influence of rice cultivars, N rates, and air temperature on RP. The results indicated that CIred edge was more appropriate than NDVI for monitoring RP without saturation problem. Compared with DLF and AGF, SGF could fit CIred edge without over fitting problem. MC of SGF_CIred edge from all three platforms showed good performance in monitoring IHSDAS with good robustness, R2 varied between 0.82 and 0.95, RMSE ranged from 2.31 to 3.81. In addition, the results demonstrated that high air temperature might cause a decrease of IHSDAS, and the growth process of rice was delayed when more nitrogen fertilizer was applied before IHSDAS. This study illustrated that low-altitude remote sensing technology could be used for monitoring field-scale hybrid rice IHSDAS accurately.

Highlights

Introduction nal affiliationsWith the rapid growth of the world population, food security has become an urgent issue, attracting worldwide attention
The results indicated that double logistic function (DLF) and asymmetric gauss function (AGF) proved to have good performance in fitting CIred edge of SKYE and MCA with higher R2 and lower root mean square errors (RMSE)
We presented the processing steps for monitoring hybrid rice IHSDAS

Summary

Introduction

With the rapid growth of the world population, food security has become an urgent issue, attracting worldwide attention. Rice is a very important crop that provides staple food for almost 50% of the world’s population [1]. Hybrid vigor (heterosis) is a universal phenomenon in crops, and the yield of hybrid rice is usually higher than that of conventional rice [2,3]. Hybrid rice makes a great contribution to the world’s food security, with more than half the growth of rice yield [4,5,6]. Hybrid rice is widely planted in large areas of. Asian region, including China, Japan, and Southeast Asian countries. Breeding hybrid rice cultivars with high yield and good quality has been an important part of these countries’

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Conclusion