Sensitive Spectral and Temporal-Spatial Characteristic Analysis of Leaf SPAD in Maize Under Variety and Nitrogen Coupling Effects.

Abstract

Accurate estimation of leaf SPAD is crucial for maize growth and yield formation. Many methods for monitoring SPAD currently lack the analysis of sensitive leaf position in different stages of maize. In this paper, the spectra and temporal-spatial characteristics of maize leaf SPAD were analyzed to describe the sensitive stage and leaf position. After exploring the dynamic growth effects of SPAD in maize leaves, the sensitive stage of SPAD was determine. Several preprocessing methods and spectral vegetation indices were used to analyze the spectral reflectance of typical leaf positions in sensitive stages. The function regression methods based on single vegetation index and the random forest regression (RFR) based on multi-vegetation indices were employed. The results showed that the twelve-leaf (V12) and the silking (R1) were the sensitive stages. The strongest RVI at the V12 stage and NDRE for the ear leaves at the R1 stage were observed under SG-SNV method. The best prediction data ( R 2 = 0.7) was showed at the V12 stage under MSC-RF. The prediction effect of the ear leaves after MSC pretreatment was slightly better ( R 2 = 0.69). In addition, SPAD value can indirectly reflect the chlorophyll content, nitrogen content and yield status of maize leaves, and its accurate monitoring provides effective guidance for maize leaf nutrition information and yield prediction.

Plant phenotyping relevance

トウモロコシ葉のSPADをスペクトル情報と回帰モデルで推定する方法を中心に、感受性時期・葉位や予測性能を分析しており、植物表現型取得手法が主要な内容である。

Code and data availability

The supplied article blocks describe a maize leaf SPAD/hyperspectral phenotyping study (field experiment, spectral preprocessing, vegetation indices, RFR modeling) but contain no public dataset deposit, no author analysis code or model availability statement, and no public URLs other than the CC-BY license notice. The

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