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Assessing Interactions between Nitrogen Supply and Leaf Blast in Rice by Hyperspectral Imaging

Remote Sensing · 7 Mar 2024 · 10.3390/rs16060939

Abstract

Mineral nitrogen (N) supply reportedly increases rice susceptibility to the fungal pathogen Magnaporthe oryzae causing blast disease. These biotic and abiotic factors cause changes in spectral reflectance of leaves; however, the effects of N × pathogen interactions on spectral characteristics of rice have not been studied. In this study, hyperspectral imaging was used to assess the effect of N supply on symptoms of rice leaf blast under greenhouse conditions. Three rice genotypes differing in blast susceptibility grown at low, medium, and high N supply were inoculated at the four-leaf stage with three M. oryzae isolates differing in virulence. The reflectance spectra (400 to 1000 nm) of healthy and symptomatic leaves were analyzed using the spectral angle mapper algorithm for supervised classification. Mineral N supply increased the contents of chlorophyll and total N. The number and area of lesions and total blast severity varied depending on rice genotype—M. oryzae isolate interactions and the amount of mineral N applied. The reflectance spectra of healthy tissue and of blast symptom subareas differed with N supply; rice genotypes differed in the response to N supply. Infected plants at high mineral N supply could be distinguished from those at low N supply due to higher differences in the spectra of symptom subareas. Results reveal the potential (and limitations) of hyperspectral imaging for quantifying N effects on rice leaves, disease severity, and symptom expression. The impact of these findings on plant phenotyping and remote sensing under field conditions is discussed.

Plant phenotyping relevance

イネ葉の病害症状・病害重症度・窒素影響をハイパースペクトル画像で分類・定量する方法を中心に評価しており、植物フェノタイピングへの応用可能性と限界も検討しているため。

abstracthyperspectral imaging was used to assess the effect of N supply on symptoms of rice leaf blast under greenhouse conditions.
abstractResults reveal the potential (and limitations) of hyperspectral imaging for quantifying N effects on rice leaves, disease severity, and symptom expression.

Code and data availability

The paper describes hyperspectral imaging of rice leaves under varying nitrogen supply and blast infection, but no public phenotype dataset, image collection, analysis code, or trained model is deposited. The Data Availability Statement only offers to direct inquiries to the first author, and the supplementary material

No evidence-backed public reproduction asset is currently recorded.

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