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Research new methods to obtain plant growth information in facility agriculture by near infrared spectrum analysis

机译:通过近红外光谱分析研究了在设施农业中获取植物增长信息的新方法

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In this study, using the pepper leaves in facility agriculture as the experimental materials, research the application of near infrared spectrum analysis technique to obtain plant growth information. Chlorophyll content of plant leaves is useful information in describing and interpreting the performance of whole-plant systems grows under various conditions, and Near-infrared spectroscopy is a non-destructive analytical technique, which is widely used in farm production. In order to establish a model to predist the relationship between near infrared spectrum and leaf chlorophyll content, a chlorophyll meter and a near infrared spectrometer were used to get chlorophyll content and spectrum of pepper leaf respectively, after that, we use OMINIC and TQ software to acquire and process spectrums of leaves, and use partial least squares (PLS) technique to analyze the data we get by normal experimentation and near infrared spectrometer, set up a calibration model to predict the leaf chlorophyll content based on the characteristics of diffuse reflectance spectrums of pepper leaves. Result showed that NIR technique could acquire chlorophyll content in plant leaves conveniently and quickly. The best model of chlorophyll content has a root mean square error of prediction (RMSEP) of 2.44 and a calibration correlation coefficient (R2) value of 0.969.
机译:在这项研究中,在设施农业中使用辣椒叶作为实验材料,研究近红外光谱分析技术的应用,获得植物生长信息。植物叶片的叶绿素含量是在描述和解释各种条件下的全植物系统的性能的有用信息,近红外光谱是一种非破坏性分析技术,广泛用于农业生产。为了建立一种模型来预测近红外光谱和叶片叶绿素含量之间的关系,使用叶绿素表和近红外光谱仪来分别获得叶绿素含量和辣椒叶谱,之后,我们使用Ominic和TQ软件获取和处理叶片的频谱,并使用部分最小二乘(PLS)技术来分析我们通过正常实验和近红外光谱仪进行的数据,建立校准模型以预测基于漫反射谱的特性的叶叶绿素含量胡椒叶。结果表明,NIR技术可以方便且快速地在植物叶中获得叶绿素含量。叶绿素含量的最佳模型具有2.44的预测(RMSEP)的根均方误差,校准相关系数(R2)值为0.969。

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