Using hyperspectral signatures for predicting foliar nitrogen and calcium content of tissue cultured little-leaf mockorange (Philadelphus microphyllus A. Gray) shoots

IF 2.3 3区 生物学 Q3 BIOTECHNOLOGY & APPLIED MICROBIOLOGY
Razieh Khajehyar, Milad Vahidi, Robert Tripepi
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引用次数: 0

Abstract

Determining foliar mineral status of tissue cultured shoots can be costly and time consuming, yet hyperspectral signatures might be useful for determining mineral contents of these shoots. In this study, hyperspectral signatures were acquired from tissue cultured little-leaf mockorange (Philadelphus microphillus) shoots to determine the feasibility of using this technology to predict foliar nitrogen and calcium contents. After using a spectroradiometer to take hyperspectral images for determining foliar N and Ca contents, the correlation between the hyperspectral bands, vegetation indices, and hyperspectral features were calculated from the spectra. Features with high correlations were selected to develop the models via different regression methods including linear, random forest (RF), and support vector machines. The results showed that non-linear regression models developed through machine learning techniques, including RF methods and support vector machines provided satisfactory prediction models with high R2 values (%N by RF with R2 = 0.72, and %Ca by RF with R2 = 0.99), that can estimate nitrogen and calcium content of little-leaf mockorange shoots grown in vitro. Overall, the RF regression method provided the most accurate and satisfactory models for both foliar N and Ca estimation of little-leaf mockorange shoots grown in tissue culture.

Abstract Image

利用高光谱特征预测组织培养的小叶橘(Philadelphus microphyllus A. Gray)嫩枝的叶面氮和钙含量
确定组织培养嫩枝的叶片矿物质状况既费钱又费时,但高光谱特征可能有助于确定这些嫩枝的矿物质含量。本研究从组织培养的小叶橘(Philadelphus microphillus)嫩枝中获取了高光谱特征,以确定使用该技术预测叶片氮和钙含量的可行性。使用光谱辐射计拍摄高光谱图像以确定叶片氮和钙含量后,根据光谱计算高光谱波段、植被指数和高光谱特征之间的相关性。通过线性、随机森林(RF)和支持向量机等不同的回归方法,选择相关性高的特征来建立模型。结果表明,通过机器学习技术(包括射频方法和支持向量机)建立的非线性回归模型提供了令人满意的预测模型,具有较高的 R2 值(射频方法的氮含量百分比为 R2 = 0.72,射频方法的钙含量百分比为 R2 = 0.99),可以估算离体生长的小叶橘芽的氮和钙含量。总体而言,射频回归法为组织培养的小叶橘嫩枝叶面氮和钙的估算提供了最准确和最令人满意的模型。
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来源期刊
Plant Cell, Tissue and Organ Culture
Plant Cell, Tissue and Organ Culture 生物-生物工程与应用微生物
CiteScore
5.40
自引率
13.30%
发文量
203
审稿时长
3.3 months
期刊介绍: This journal highlights the myriad breakthrough technologies and discoveries in plant biology and biotechnology. Plant Cell, Tissue and Organ Culture (PCTOC: Journal of Plant Biotechnology) details high-throughput analysis of gene function and expression, gene silencing and overexpression analyses, RNAi, siRNA, and miRNA studies, and much more. It examines the transcriptional and/or translational events involved in gene regulation as well as those molecular controls involved in morphogenesis of plant cells and tissues. The journal also covers practical and applied plant biotechnology, including regeneration, organogenesis and somatic embryogenesis, gene transfer, gene flow, secondary metabolites, metabolic engineering, and impact of transgene(s) dissemination into managed and unmanaged plant systems.
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