Researchers at University of Saskatchewan Target Machine Learning (Machine Learn ing Approach for Satellite-based Subfield Canola Yield Prediction Using Floral P henology Metrics and Soil Parameters)

Robotics & Machine Learning Daily News2024，Issue(Apr.24) ：37-38.

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Researchers at University of Saskatchewan Target Machine Learning (Machine Learn ing Approach for Satellite-based Subfield Canola Yield Prediction Using Floral P henology Metrics and Soil Parameters)

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Investigators publish new report on Ma chine Learning. According to news reporting outof Saskatoon, Canada, by NewsRx editors, research stated, “Early monitoring of within-field yield variabilityan d forecasting yield potential is critical for farmers and other key stakeholders such as policymakers.Remote sensing techniques are progressively being used in yield prediction studies due to easy access andaffordability.”

Key words

Saskatoon/Canada/North and Central Ame rica/Cyborgs/Emerging Technologies/Machine Learning/Remote Sensing/Universi ty of Saskatchewan

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出版年

2024

Robotics & Machine Learning Daily News

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