Detection and Dynamic Variation Characteristics of Rice Nitrogen Status after Anthesis Based on the RGB Color Index

Abstract

We aimed to elucidate the color changes of rice leaves after anthesis and create an algorithm for monitoring the nitrogen contents of rice leaves and of the whole plant. Hence, we aimed to provide a theoretical basis for the precise management of rice nitrogen fertilizer and the research and development of digital image nutrition monitoring equipment and reference. We selected the leaf colors of the main stems of four major rice varieties promoted in production, including Huaidao 5 (late-maturing medium japonica rice), Yangjing 4227 (early maturing late japonica rice), Changyou 5 (late japonica hybrid rice), and Yongyou 8 (late japonica hybrid rice). Under different nitrogen levels, the leaf R, G, and B values of the four rice varieties at different stages after anthesis, the dynamic changes in RGB normalized values, the correlations between RGB normalized values and leaf SPAD values, the leaf nitrogen content and whole plant nitrogen content, and the nitrogen prediction model were studied. The research results demonstrate the following: (1) regardless of nitrogen levels, the leaf of R, G, B, NRI, NGI and NBI of different rice varieties after anthesis followed the order, G > R > B. R, G, NRI, NGI, and days after heading could be fitted according to a logarithmic equation, y = aebx (0.726 ≤ R2 ≤ 0.992); B, NBI, and days after heading could be fitted using a linear equation, y = a + bx (0.863 ≤ R2 ≤ 0.992). Both fitting effects were significant (except NGI). (2) A quadratic function (Y = −1296.192x2 + 539.419x − 10.914; Y = −1173.104x2 + 527.073x − 12.993) was adopted to construct a monitoring model for the NBI and SPAD values of japonica rice and hybrid japonica rice leaves after anthesis and the R2 values were 0.902 and 0.838, respectively. Exponential functions (Y = 5.698e7.261x; Y = 3.371e9.326x) were employed to construct monitoring models of leaf nitrogen content, and the R2 values were 0.833 and 0.706, respectively. Exponential functions (Y = 5.145e4.9143x; Y = 3.966e5.364x) were also used to construct a monitoring model for the nitrogen content of the whole plant, and the R2 values were 0.737 and 0.511, respectively. The results obtained from prediction tests by using Determination Coefficient (R2), Relative Percent Deviation (RPD), and Root Mean Square Error (RMSE) showed that it was feasible, accurate, and efficient to use a scanner for measuring the nitrogen content of rice.