Evaluating the Risk of Cassava Mosaic Disease Using Imagery from Unmanned Aerial Vehicles and Synthetic Vegetation Indices.
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Abstract
Cassava mosaic disease (CMD) is a viral disease that causes significant damage to cassava crops. Nakhon Ratchasima province in Thailand has experienced the highest prevalence of Cassava mosaic virus (CMV) outbreaks in the country, resulting in losses amounting to 1,605 million baht. The objectives of the study were 1) to analyze the synthetic vegetation indices (VI) of CMD occurrence locations, 2) to develop a risk map for CMD outbreaks, and 3) to analyze the relationship between vegetation indices and disease risk levels. Data on disease occurrence locations were collected, and aerial images were captured using an unmanned aerial vehicle (UAV) to analyze the vegetation indices. Seven indices were included: GRDI, VDVI, ExG, GCC, VARI, TGI, and GLI, to determine the index values at CMD occurrence locations. The data were then analyzed to assess disease risk levels, and vegetation index data were correlated with these risk levels using spatial statistics. The results revealed that 353 cassava plants were infected with CMD. The average values for the GRDI, VDVI, ExG, GCC, VARI, TGI, and GLI indices were 0.0359, 0.0417, 0.0674, 0.0352, 0.0636, 0.0296, and 0.0575, respectively. The highest moderate risk level was identified in 3,056 pixels. The Moran's I spatial autocorrelation coefficient for the vegetation index was 0.207, with a Z-score of 25.099. Most image pixels exhibited a high-high spatial clustering pattern, with high-risk points (Z-scores greater than 1.96 at a 99% confidence level) totaling 1,583 image points. This study contributes to improving the efficiency of monitoring and tracking CMD outbreaks in cassava crops, offering a valuable tool for disease management and prevention.
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References
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