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结合热成像和可见光成像来估算冠层温度并识别植物胁迫。

Combining thermal and visible imagery for estimating canopy temperature and identifying plant stress.

作者信息

Leinonen Ilkka, Jones Hamlyn G

机构信息

University of Dundee at SCRI, Plant Science Research Group, Invergowrie, Dundee DD2 5DA, Scotland, UK.

出版信息

J Exp Bot. 2004 Jun;55(401):1423-31. doi: 10.1093/jxb/erh146. Epub 2004 May 7.

Abstract

Thermal imaging is a potential tool for estimating plant temperature, which can be used as an indicator of stomatal closure and water deficit stress. In this study, a new method for processing and analysing thermal images was developed. By using remote sensing software, the information from thermal and visible images was combined, the images were classified to identify leaf area and sunlit and shaded parts of the canopy, and the temperature statistics for specific canopy components were calculated. The method was applied to data from a greenhouse water-stress experiment of Vicia faba L. and to field data for Vitis vinifera L. Vaseline-covered and water-sprayed plants were used as dry and wet references, respectively, and two thermal indices, based on temperature differences between the canopy and reference surfaces, were calculated for single Vicia faba plants. The thermal indices were compared with measured stomatal conductance. The temperature distributions of sunlit and shaded leaf area of Vitis vinifera canopies from natural rainfall and irrigation treatments were compared. The present method provides two major improvements compared with earlier methods for calculating thermal indices. First, it allows more accurate estimation of the indices, which are consequently more closely related to stomatal conductance. Second, it gives more accurate estimates of the temperature distribution of the shaded and sunlit parts of canopy, and, unlike the earlier methods, makes it possible to quantify the relationship between temperature variation and stomatal conductance.

摘要

热成像技术是一种用于估算植物温度的潜在工具,植物温度可用作气孔关闭和水分亏缺胁迫的指标。在本研究中,开发了一种处理和分析热图像的新方法。通过使用遥感软件,将热图像和可见光图像的信息相结合,对图像进行分类以识别叶面积以及冠层的受光和遮荫部分,并计算特定冠层组件的温度统计数据。该方法应用于蚕豆温室水分胁迫实验的数据以及葡萄的田间数据。分别将涂抹凡士林的植物和喷水的植物用作干旱和湿润对照,针对单株蚕豆计算了基于冠层与对照表面之间温度差异的两个热指标。将这些热指标与实测气孔导度进行了比较。比较了自然降雨和灌溉处理下葡萄冠层受光和遮荫叶面积的温度分布。与早期计算热指标的方法相比,本方法有两大改进。首先,它能更准确地估算指标,因此这些指标与气孔导度的相关性更强。其次,它能更准确地估算冠层遮荫和受光部分的温度分布,并且与早期方法不同的是,它能够量化温度变化与气孔导度之间的关系。

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