Study Findings on Machine Learning Reported by Researchers at　Anhui Agricultural University [Improving the prediction performance　of leaf wat er content by coupling multi-source data with machine　learning in rice (Oryza sa tiva L.)]

Robotics & Machine Learning Daily News2024，Issue(Apr.10) ：87-88.

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Study Findings on Machine Learning Reported by Researchers at　Anhui Agricultural University [Improving the prediction performance　of leaf wat er content by coupling multi-source data with machine　learning in rice (Oryza sa tiva L.)]

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Investigators publish new report on ar tificial intelligence. According to news reportingoriginating from Anhui Agricu ltural University by NewsRx correspondents, research stated, “Leaf watercontent (LWC) significantly affects rice growth and development. Real-time monitoring o f rice leaf waterstatus is essential to obtain high yield and water use efficie ncy of rice plants with precise irrigation regimesin rice fields.”

Key words

Anhui Agricultural University/Cyborgs/Emerging Technologies/Machine Learning/Technology

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出版年

2024

Robotics & Machine Learning Daily News

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Study Findings on Machine Learning Reported by Researchers at Anhui Agricultural University [Improving the prediction performance of leaf wat er content by coupling multi-source data with machine learning in rice (Oryza sa tiva L.)]

Study Findings on Machine Learning Reported by Researchers at Anhui Agricultural University [Improving the prediction performance of leaf wat er content by coupling multi-source data with machine learning in rice (Oryza sa tiva L.)]

Abstract

Key words

引用本文复制引用

出版年

Robotics & Machine Learning Daily News

Study Findings on Machine Learning Reported by Researchers at　Anhui Agricultural University [Improving the prediction performance　of leaf wat er content by coupling multi-source data with machine　learning in rice (Oryza sa tiva L.)]

Study Findings on Machine Learning Reported by Researchers at　Anhui Agricultural University [Improving the prediction performance　of leaf wat er content by coupling multi-source data with machine　learning in rice (Oryza sa tiva L.)]