Abstract

Modern rice production systems need a reliable, easy-to-use, efficient, and environmentally-friendly method to determine plant nitrogen (N) status , predict grain yield, and optimize N management. We conducted field experiments to determine the influence of different N rates on Soil Plant Analysis Development (SPAD) readings of rice leaves. We also performed field validations to evaluate the grain yield and N use efficiency under recommended N rates. Our results showed that leaf SPAD readings increased as N rates increased. We applied the recommended N based on the relationships between the N rates and leaf SPAD readings at the tillering and booting stages. The recommended N decreased N rates and improved N use efficiency without sacrificing grain yield. When compared to farmer practices (FP), the recommended N rates of optimization (OPT) decreased by 5.8% and 10.0%, respectively. In comparison with FP, the N agronomic efficiency of OPT increased by 5.8 and 10.0% while the partial factor productivity of N increased by 6.0 and 14.2%, respectively. The SPAD meter may be a reliable tool to analyze the N in rice, estimate real-time N fertilization, and improve N use efficiency.

Highlights

  • Rice (Oryza sativa L.) is one of the most important cereal crops and food sources in the world

  • The N0 treatment resulted in the lowest leaf Soil Plant Analysis Development (SPAD) readings, while N270 showed the highest leaf SPAD readings in both years

  • In 2008, N270 leaf SPAD readings increased by 31.5–42.8% in experiment 1 and by 27.2–56.2% in experiment 2 when compared with N0

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Summary

Introduction

Rice (Oryza sativa L.) is one of the most important cereal crops and food sources in the world. N is arguably the most important limiting factor, aside from water, for rice production. Most farmers apply N in excess relative to the actual crop’s needs to harvest more grain. This practice leads to low N use efficiency due to high N losses through runoff, denitrification, leaching, volatilization, and a high risk of environmental contamination (Zeng et al, 2012; Liu et al, 2013; Bodirsky et al, 2014; Xiong et al, 2015). The average N use in China’s rice production has been reported to be

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