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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Bibliografiske detaljer

Principais autores:	Benjamin Adjah Torgbor, Muhammad Moshiur Rahman, James Brinkhoff, Priyakant Sinha, Andrew Robson
Format:	Artigo
Sprog:	Inglês
Udgivet:	MDPI AG 2023-06-01
Serier:	Remote Sensing
Fag:	pre-harvest yield prediction mango (<i>Mangifera indica</i>) remote sensing Landsat XGBOOST random forest (RF)
Online adgang:	https://www.mdpi.com/2072-4292/15/12/3075
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