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首页> 外文期刊>Progress in Artificial Intelligence >A Leaf Selfie: Using a Smartphone to Quantify Leaf Vulnerability to Hydraulic Dysfunction
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A Leaf Selfie: Using a Smartphone to Quantify Leaf Vulnerability to Hydraulic Dysfunction

机译:叶子自拍照:使用智能手机量化液压功能障碍的叶片脆弱性

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摘要

Accurate predictions of species distribution under current and future climate conditions require modeling efforts based on clear mechanistic relationships between climate variables and plant physiological functions. Vulnerability of leaves to xylem embolism is a key mechanistic trait that might be included in these modeling efforts. Here, we propose a simple set-up to measure leaf vulnerability to embolism on the basis of the optical method using a smartphone, a light source, and a notebook. Our data show that this proposed set-up can adequately quantify the vulnerability to xylem embolism of leaf major veins in Populus nigra and Ostrya carpinifolia, producing values consistent with those obtained in temperate tree species with other methods, allowing virtually any laboratory to quantify species-specific drought tolerance on the basis of a sound mechanistic trait.
机译:在当前和未来的气候条件下,对物种分布的准确预测需要基于气候变量与植物生理功能之间的明确机制关系来建模努力。 叶片的脆弱性栓塞栓塞是一种关键机制特征,可能包括在这些建模努力中。 在这里,我们提出了一种简单的设置,以根据使用智能手机,光源和笔记本电脑的光学方法来测量栓塞的叶片脆弱性。 我们的数据表明,这一提议的设置可以充分量化杨树和鸵鸟菌的叶片主要静脉的脆弱性易受血栓性的脆弱性,并产生与温带树木种类中获得的值与其他方法一致的值,几乎可以达到任何实验室量化物种 - 基于音质机械特性的具体干旱耐受性。

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