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Spatial mapping of Brix and moisture content using hyperspectral imaging system in sugarcane stalk

机译:使用高光谱成像系统在甘蔗秸秆中使用高光谱成像系统的空间映射

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摘要

Hyperspectral imaging is a powerful technique that can rapidly, accurately, and non-destructively determine the quality of agricultural products. In this study, a hyperspectral imaging system has been developed to evaluate and visualize the Brix values and moisture contents in sugarcane stalks to be used as a tool for breeding programmes. After extracting the spectral data via ENVI coding, data in the wavelength range of 450-950 nm were used to generate prediction models for Brix and moisture content via partial least squares regression. The coefficients of determination of the predictive models for Brix and moisture content were found to be 0.70 and 0.68, respectively. The root mean square errors of cross-validation were 1.28 degrees for Brix and 1.49% for moisture content, and the performance to deviation ratios were 1.71 and 1.61, respectively. The models were applied to each pixel of the hypercube data in order to determine the distributions of Brix and moisture content within the sugarcane stalks. Both distribution mappings indicated that the Brix and the moisture content level were lower in the internode regions. The results demonstrated the feasibility of using hyperspectral imaging to visualize Brix and moisture content in sugarcane stalks. The developed method has potential applications in farming management and also in breeding programs.
机译:高光谱成像是一种强大的技术,可以快速,准确,无损地确定农产品的质量。在该研究中,已经开发了一种高光谱成像系统以评估和可视化甘蔗秸秆中的Brix值和水分含量,以用作繁殖程序的工具。在通过ENVI编码中提取光谱数据之后,使用450-950nm的波长范围内的数据来通过部分最小二乘回归产生BRIX和湿度含量的预测模型。发现Brix和水分含量的预测模型的测定系数分别为0.70和0.68。交叉验证的根均方误差为Brix为1.28度,水分含量为1.49%,分别对偏差比率的性能分别为1.71和1.61。将模型应用于HyperCube数据的每个像素,以确定甘蔗秸秆内的Brix和水分含量的分布。两者分布映射都表明,在节间区域中,Brix和水分含量水平较低。结果表明,使用高光谱成像以在甘蔗秸秆中可视化Brix和水分含量的可行性。开发方法具有潜在的农业管理应用以及繁殖计划。

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