A noninvasive, machine learning–based method for monitoring anthocyanin accumulation in plants using digital color imaging

Bryce C. Askey; Ru Dai; Won Suk Lee; Jeongim Kim

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A noninvasive, machine learning–based method for monitoring anthocyanin accumulation in plants using digital color imaging

机译：基于机器学习的基于机器学习方法，用于使用数字彩色成像监测植物中的花青素积累

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摘要

Premise When plants are exposed to stress conditions, irreversible damage can occur, negatively impacting yields. It is therefore important to detect stress symptoms in plants, such as the accumulation of anthocyanin, as early as possible.

机译：前提是当植物暴露于应力条件时，可能会发生不可逆的损伤，产生负面影响。因此，重要的是要检测植物中的应激症状，例如花青素的积累，尽早。

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《Applications in plant sciences.》 |2019年第11期|共8页
作者
Bryce C. Askey; Ru Dai; Won Suk Lee; Jeongim Kim;
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anthocyanindigital color imagingearly stress detectionmachine learning;

机译：花青素靛蓝颜色显像性压力检测冲突学习;

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6. A noninvasive machine learning–based method for monitoring anthocyanin accumulation in plants using digital color imaging [O] . Bryce C. Askey, Ru Dai, Won Suk Lee, 2019

机译：一种基于机器学习的无创方法使用数字彩色成像技术监测植物中的花色苷积累
7. A noninvasive, machine learning–based method for monitoring anthocyanin accumulation in plants using digital color imaging [O] . Bryce C. Askey, Ru Dai, Won Suk Lee, 2019

机译：基于机器学习的基于机器学习方法，用于使用数字彩色成像监测植物中的花青素积累

A noninvasive, machine learning–based method for monitoring anthocyanin accumulation in plants using digital color imaging

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