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Prediction of End-Of-Season Tuber Yield and Tuber Set in Potatoes Using In-Season UAV-Based Hyperspectral Imagery and Machine Learning
Potato is the largest non-cereal food crop in the world. Timely estimation of end-of-season tuber production using in-season information can inform sustainable agricultural management decisions that increase productivity while reducing impacts on the environment. Recently, unmanned aerial vehicles (...
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| Wydane w: | Sensors (Basel) |
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| Główni autorzy: | , , , , , , |
| Format: | Artigo |
| Język: | Inglês |
| Wydane: |
MDPI
2020
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| Hasła przedmiotowe: | |
| Dostęp online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7570686/ https://ncbi.nlm.nih.gov/pubmed/32947919 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3390/s20185293 |
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