基于手机数据的植物色素无损检测

IF 0.6 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS
M. Vasilev, V. Stoykova, P. Veleva, Z. Zlatev
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引用次数: 0

摘要

本文提出了使用手机视频传感器的数据确定植物色素的方法和工具。该领域已知研究的一个缺点是,它们主要旨在测定叶绿素含量。很少有研究涉及类胡萝卜素、类黄酮和β赖氨酸等色素的测定,这些色素在测定植物培养条件方面也很重要。之所以选择黄瓜,是因为保加利亚长期干旱,导致这些植物的种植损失。使用包含颜色和光谱指数的矢量。这些特征是通过手机上的视频传感器获得的。主成分的核方法变体减少了它们。使用因子分析、对应分析和相关方法来选择特征向量。已经开发了预测模型来确定植物色素。色素叶黄素和叶绿素A的预测精度高(90%以上)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Non-Destructive Determination of Plant Pigments Based on Mobile Phone Data
This paper proposes methods and tools for determining plant pigments using data from a mobile phone video sensor. A disadvantage of the known studies in this field is that they are mainly aimed at determining the chlorophyll content. There are few studies related to the determination of pigments such as carotenoids, flavonoids, and betalains, which are also important in terms of determining the condition of plants in their cultivation. Cucumbers were chosen because the long periods of drought in Bulgaria, lead to losses in cultivating these plants. Vectors containing colour and spectral indices were used. These features are obtained through a video sensor on a mobile phone. The kernel method variant of principal components reduces them. Feature vectors are selected using factor analysis, correspondence analysis, and the correlation method. Predictive models have been developed to determine plant pigments. With high accuracy (over 90%), the pigments xanthophyll and chlorophyll A can be predicted.
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来源期刊
TEM Journal-Technology Education Management Informatics
TEM Journal-Technology Education Management Informatics COMPUTER SCIENCE, INFORMATION SYSTEMS-
CiteScore
2.20
自引率
14.30%
发文量
176
审稿时长
8 weeks
期刊介绍: TEM JOURNAL - Technology, Education, Management, Informatics Is a an Open Access, Double-blind peer reviewed journal that publishes articles of interdisciplinary sciences: • Technology, • Computer and informatics sciences, • Education, • Management
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