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A new method for non-destructive measurement of biomass, growth rates, vertical biomass distribution and dry matter content based on digital image analysis

机译:基于数字图像分析的生物量,生长速度,垂直生物量分布和干物质含量的无损测量新方法

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Background and Aims Biomass is an important trait in functional ecology and growth analysis. The typical methods for measuring biomass are destructive. Thus, they do not allow the development of individual plants to be followed and they require many individuals to be cultivated for repeated measurements. Non-destructive methods do not have these limitations. Here, a non-destructive method based on digital image analysis is presented, addressing not only above-ground fresh biomass (FBM) and oven-dried biomass (DBM), but also vertical biomass distribution as well as dry matter content (DMC) and growth rates. Methods Scaled digital images of the plants silhouettes were taken for 582 individuals of 27 grass species (Poaceae). Above-ground biomass and DMC were measured using destructive methods. With image analysis software Zeiss KS 300, the projected area and the proportion of greenish pixels were calculated, and generalized linear models (GLMs) were developed with destructively measured parameters as dependent variables and parameters derived from image analysis as independent variables. A bootstrap analysis was performed to assess the number of individuals required for re-calibration of the models. Key Results The results of the developed models showed no systematic errors compared with traditionally measured values and explained most of their variance (R-2 >= 0.85 for all models). The presented models can be directly applied to herbaceous grasses without further calibration. Applying the models to other growth forms might require a re-calibration which can be based on only 10-20 individuals for FBM or DMC and on 40-50 individuals for DBM. Conclusions The methods presented are time and cost effective compared with traditional methods, especially if development or growth rates are to be measured repeatedly. Hence, they offer an alternative way of determining biomass, especially as they are non-destructive and address not only FBM and DBM, but also vertical biomass distribution and DMC.
机译:背景和目标生物质是功能生态学和生长分析的重要特征。测量生物量的典型方法具有破坏性。因此,它们不允许跟随个体植物的发育,并且它们需要培养许多个体以进行重复测量。非破坏性方法没有这些限制。在这里,提出了一种基于数字图像分析的非破坏性方法,不仅解决了地上新鲜生物量(FBM)和烤箱干燥生物量(DBM),而且还解决了垂直生物量分布以及干物质含量(DMC)和增长率。方法采集了27种草科(禾本科)的582个人的按比例绘制的植物轮廓的数字图像。使用破坏性方法测量了地上生物量和DMC。使用图像分析软件Zeiss KS 300,可以计算出投影面积和绿色像素的比例,并以具有破坏性的测量参数作为因变量,并从图像分析得出的参数作为自变量来开发广义线性模型(GLM)。进行了自举分析,以评估重新校准模型所需的个体数量。关键结果与传统的测量值相比,已开发模型的结果表明没有系统误差,并且解释了它们的大部分差异(所有模型的R-2> = 0.85)。提出的模型可以直接应用于草本植物,而无需进一步校准。将模型应用于其他增长形式可能需要重新校准,对于FBM或DMC,只能基于10-20个人,对于DBM,可以基于40-50个人。结论与传统方法相比,本文提出的方法在时间和成本上都具有成本效益,特别是在要重复测量发育或增长率的情况下。因此,它们提供了一种确定生物量的替代方法,特别是因为它们是非破坏性的,不仅解决了FBM和DBM,而且还解决了垂直生物量分布和DMC。

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