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Aerial images and machine learning methods to emulate the late blight severity in potato crops

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Title Aerial images and machine learning methods to emulate the late blight severity in potato crops
 
Creator Loayza, H.
Palacios, S.
Silva, L.
Gastelo, M.
Aponte, M.
Ramírez, D.
 
Subject potatoes
phytophthora infestans
 
Description Assessment of Phytophthora infestans’ incidence and severity are frequently performed
based on visual crop inspection, which is a labor-intensive task prone to errors associated with
its subjectivity. Therefore, alternative methods to relate disease incidence and severity with
changes in crop traits are of great interest. Optical imagery in the visible and near-infrared (VisNIR) can detect changes in crop traits caused by pathogen development. In addition, Unmanned
Aerial Vehicles (UAV) with cameras on board have flexible data collection capabilities allowing
adjustments considering the trade-off between data throughput and its resolution.
This work presents a quantitative prediction of the severity of the disease caused by
Phytophthora infestans in potato crops using image processing and machine learning (ML)
algorithms such as Random Forests (RF) and Extreme Gradient Boost (XGBoost). The ML
algorithms were trained using datasets from multispectral data captured at the canopy level
with a UAV carrying a multispectral camera. The results indicate that RF and XGBoost using 11
classes with 18 bands, including vegetation indexes and band features, can predict late blight
severity on potato crops with an acceptable accuracy of 81.02% for RF and 74.19% for RF
XGBoost.
 
Date 2022-12
2023-02-07T19:59:41Z
2023-02-07T19:59:41Z
 
Type Report
 
Identifier Loayza, H.; Palacios, S.; Silva, L.; Gastelo, M.; Aponte, M.; Ramirez, D. 2022. Aerial images and machine learning methods to emulate the late blight severity in potato crops. International Potato Center. 34 p.
https://hdl.handle.net/10568/128499
 
Language en
 
Rights Copyrighted; all rights reserved
Limited Access
 
Format 34 p.
application/pdf
 
Publisher International Potato Center