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° 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.

中文翻译：

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使用高光谱成像系统绘制甘蔗茎中白利糖度和水分含量的空间图

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。在这项研究中，开发了一个高光谱成像系统来评估和可视化甘蔗茎中的白利糖度值和水分含量，用作育种计划的工具。通过 ENVI 编码提取光谱数据后，使用 450-950 nm 波长范围内的数据通过偏最小二乘回归生成白利糖度和水分含量的预测模型。发现白利糖度和水分含量预测模型的确定系数分别为 0.70 和 0.68。交叉验证的均方根误差对于白利糖度为 1.28°，对于水分含量为 1.49%，性能与偏差比分别为 1.71 和 1.61。将模型应用于超立方体数据的每个像素，以确定甘蔗茎中白利糖度和水分含量的分布。两种分布图都表明，节间区域的白利糖度和水分含量水平较低。结果证明了使用高光谱成像来可视化甘蔗茎中的白利糖度和水分含量的可行性。开发的方法在农业管理和育种计划中具有潜在的应用。结果证明了使用高光谱成像来可视化甘蔗茎中的白利糖度和水分含量的可行性。开发的方法在农业管理和育种计划中具有潜在的应用。结果证明了使用高光谱成像来可视化甘蔗茎中的白利糖度和水分含量的可行性。开发的方法在农业管理和育种计划中具有潜在的应用。