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Proceedings Paper

Disease stress detection on citrus using a leaf optical model and field spectroscopy
Author(s): Mrunalini R. Badnakhe; Surya Durbha; J. Adinarayana
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Paper Abstract

As citrus is progressively contributing to horticultural production, wealth and economy of a country, it is necessary to understand the factors impacting citrus production. Gummosis is one of the most serious diseases causing considerable loss of overall citrus production and yield quality. A qualitative and quantitative analysis of citrus leaf biochemical properties are necessary to monitor the crop health, disease /pest stress and production. Total leaf chlorophyll content (Cab) represents one of the key biochemical factors which contributes in water, carbon, and energy exchange processes. Photosynthesis process in citrus will be disturbed as gummosis disease life cycle progresses. It is important to study Cab to evaluate the photosynthesis rate and disease stress. In this study the potential of Radiative Transfer (RT) PROSPECT model to retrieve Cab in citrus orchards was undertaken at different sites. The main goal is to evaluate the relationship between Cab and gummosis disease stress for citrus at various phenological stages. Inversion of PROSPECT model on measured hyperspectral data is carried out to extract the leaf level parameters influencing the disease. This model was inverted with the ground truth hyperspectral reading. The testing was separately initiated for healthy and infected plant leaves. This can lead to understand the disease stress on citrus leaves. For accuracy, raw spectra are filtered and processed which is an input parameter for Inversion PROSPECT model. Here, retrieved Cab content was correlated with gummosis disease stress in terms of oozing with R2 = 0.6021 and RMSE= 0.481272.

Paper Details

Date Published: 14 October 2015
PDF: 6 pages
Proc. SPIE 9637, Remote Sensing for Agriculture, Ecosystems, and Hydrology XVII, 963709 (14 October 2015); doi: 10.1117/12.2194486
Show Author Affiliations
Mrunalini R. Badnakhe, Indian Institute of Technology Bombay (India)
Surya Durbha, Indian Institute of Technology Bombay (India)
J. Adinarayana, Indian Institute of Technology Bombay (India)


Published in SPIE Proceedings Vol. 9637:
Remote Sensing for Agriculture, Ecosystems, and Hydrology XVII
Christopher M. U. Neale; Antonino Maltese, Editor(s)

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