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Journal of Pharmacognosy and Phytochemistry

Journal of Pharmacognosy and Phytochemistry

Vol. 11, Issue 4 (2022)

Hyperspectral remote sensing for discrimination for plant disease forecasting: Review

Author(s):

P Avinash, A Ramathilaga and P Valarmathi

Abstract:

Forecasting plant disease is the process of predicting the severity of diseases affected by plants. Based on the environmental conditions, seasonal changes in nature, and weather conditions, the pathogen spread varies in plant diseases. Early forecasting gives farmers sufficient time to rearrange their crop schedules and protect the susceptible crop from severe infection by the pathogen. To prepare a forecasting system detailed observations over several years based on weather conditions may be necessary. Typically, pathogens tend to result in either loss of leaves or shoot area or changes in a leaf colour due to a reduction in photosynthetic activity. Remote sensing (RS) technologies provide a diagnostic tool that can serve as an early warning system, allowing the agricultural community to intervene early on to counter potential problems before they spread widely and negatively impact crop productivity. With the recent advancements in sensor technologies, data management and data analytics currently, several RS options are available to the agricultural community. By using RS data, the agricultural community can identify and quantify the health of agricultural systems, helping them to make management decisions that can increase farm profits while lowering agriculture-driven environmental problems.

Pages: 208-215  |  603 Views  306 Downloads


Journal of Pharmacognosy and Phytochemistry Journal of Pharmacognosy and Phytochemistry
How to cite this article:
P Avinash, A Ramathilaga and P Valarmathi. Hyperspectral remote sensing for discrimination for plant disease forecasting: Review. J Pharmacogn Phytochem 2022;11(4):208-215.

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