Integrating Remote Sensing and Weather Variables for Mango Yield Prediction Using a Machine Learning Approach

Integrating Remote Sensing and Weather Variables for Mango Yield Prediction Using a Machine Learning Approach

Accurate pre-harvest yield forecasting of mango is essential to the industry as it supports better decision making around harvesting logistics and forward selling, thus optimizing productivity and reducing food waste. Current methods for yield forecasting such as manually counting 2–3% of the orchar...

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Bibliographic Details
Main Authors: Benjamin Adjah Torgbor, Muhammad Moshiur Rahman, James Brinkhoff, Priyakant Sinha, Andrew Robson
Format: Article
Language:English
Published: MDPI AG 2023-06-01
Series:Remote Sensing
Subjects:
pre-harvest yield prediction
mango (<i>Mangifera indica</i>)
remote sensing
Landsat
XGBOOST
random forest (RF)
Online Access:https://www.mdpi.com/2072-4292/15/12/3075

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https://www.mdpi.com/2072-4292/15/12/3075

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