• Spectroscopy and Spectral Analysis
  • Vol. 39, Issue 9, 2829 (2019)
ZHANG Yin-jie*, WANG Lei, BAI You-lu, YANG Li-ping, LU Yan-li, ZHANG Jing-jing, and LI Ge
Author Affiliations
  • [in Chinese]
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    DOI: 10.3964/j.issn.1000-0593(2019)09-2829-07 Cite this Article
    ZHANG Yin-jie, WANG Lei, BAI You-lu, YANG Li-ping, LU Yan-li, ZHANG Jing-jing, LI Ge. Nitrogen Nutrition Diagnostic Based on Hyperspectral Analysis about Different Layers Leaves in Maize[J]. Spectroscopy and Spectral Analysis, 2019, 39(9): 2829 Copy Citation Text show less

    Abstract

    In order to clarify the location of nitrogen nutrient diagnosis of maize leaves at different growth stages, and to establish an accurate and robust model to diagnose maize’s nitrogen nutrition, which aims to guide rational fertilization and improve recovery rate, in this experiment, a single factor pot experiment was designed, and maize (Zhengdan 958) was used as the research object to study the distribution and variation of nitrogen content in different layers of leaf under different nitrogen nutrition levels. The distribution and variation of N content and the spectral response characteristics of maize leaves were analyzed. And the correlation relationship between nitrogen content and spectral reflectance of different layers leaves at different growth stages was investigated. Moreover, the regression relationship between the leaf nitrogen content and the ratio spectral index (RSI) which was composed of any two bands between 400~2 000 nm was explored. According to these analyses, leaf layer, optimal RSI and estimation models were initially determined at different stages for nitrogen nutrition diagnosis by spectral technique. The main results are as follows: The results indicate that the maize’s nitrogen content in different layers is as follows: the upper layer>the middle layer>the lower layer; and that as the stages of growth forward, leaves’ nitrogen content in upper layer, under the condition of low-nitrogen, appears to first decrease and then increase (after manuring) and decrease again while keeping the tendency of decrease under the condition of high-nitrogen, with the leaves’ nitrogen content in the levels of middle and low appearing to decrease. At the Six-leaf stage, the lower layer of leaves has a larger sensitivity range and a stronger correlation coefficient. At Nine-leaf and Filling stage, spectral reflectance of the upper layer maize leaves was more sensitive and correlated. At the flowering and silking stage, spectral reflectance of the middle layer leaves was more sensitive and relevant. SO the lower leaves were selected as the diagnosis target at the Six-leaf stage, and the optimal ratio spectral index RSI (1 811, 1 842) was selected to establish the linear estimation model. The upper leaves were selected as the diagnostic target at the Nine-leaf stage and the Filling stage, and the optimal ratio spectral indices were RSI (720, 557), RSI (600, 511) to establish the linear estimation model, respectively. The middle leaves were selected as the diagnostic target during the anthesis-silking stage, and the RSI (688, 644) spectral index was selected to establish the estimation model. The research results could provide a theoretical basis for rapid and accurate nitrogen nutrition spectrum diagnosis method in maize or other crop.
    ZHANG Yin-jie, WANG Lei, BAI You-lu, YANG Li-ping, LU Yan-li, ZHANG Jing-jing, LI Ge. Nitrogen Nutrition Diagnostic Based on Hyperspectral Analysis about Different Layers Leaves in Maize[J]. Spectroscopy and Spectral Analysis, 2019, 39(9): 2829
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