Special Thesis & Basic Research

Estimation of the Flag Leaf SPAD Value in Different Late Indica Rice Varieties Based on Hyperspectral Data

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  • 1Key Laboratory of Indica Rice Genetics and Breeding in the Middle and Lower Reaches of Yangtze River Valley, Ministry of Agriculture and Rural Affairs, Changsha 410125, China
    2College of Agronomy, Hunan Agricultural University, Changsha 410128, China
    3Hunan Rice Research Institute, Changsha 410125, China

1st author: 823945102@qq.com

*Corresponding author:zhzhkp@163.com

Received date: 2020-09-09

  Online published: 2021-01-20

Abstract

In this study, the SPAD values and reflectance spectra of flag leaves of different late indica rice varieties in the middle and lower reaches of the Yangtze river were measured. The estimation models of SPAD values of flag leaves in different late indica rice varieties was established by analyzing the correlation between the original spectral reflectance and its transformed data and SPAD values. And the average deviation rate was used to verify the model accuracy. The results showed that the sensitive band of SPAD value and the original spectral reflectance of rice leaves was between 710 nm and 720 nm, and the sensitive band of the first derivative spectrum was approximately 690 nm to 700 nm. Among all spectral parameters, the red edge value (Dr) had the best correlation, with the correlation coefficient of 0.6~0.8; the exponential model and quadratic curve model have better estimation effect in the selection of regression model; the index model y=85.512e-2.392x based on the original spectral reflectance at 715 nm had the best estimation effect, and the average deviation rate for inter-species verification was the lowest(5.01%). The results showed that the model established with the spectral parameters of the leaves of single late indica rice variety had certain applicability among different varieties.

Cite this article

Rongcai TIAN, Zhiqiang GAO, Kun ZHOU . Estimation of the Flag Leaf SPAD Value in Different Late Indica Rice Varieties Based on Hyperspectral Data[J]. China Rice, 2021 , 27(1) : 45 -50 . DOI: 10.3969/j.issn.1006-8082.2021.01.009

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