Abstract A comprehensive study of the feasibility of hyperspectral imaging in visible (400–1000 nm) and near infrared (900–1700 nm) regions was investigated for prediction and concentration mapping of Vitamin C, ascorbic acid (AA), dehydroascorbic acid (DHAA) and phenols in wild rocket (Diplotaxis tenuifolia) over a storage span of 12 days at 5 °C. Partial least squares regression (PLSR) with different data pretreatments and wavelength selection resulted in satisfactory predictions for all parameters in the NIR range except DHAA. Prediction models were used for concentration mapping to follow changes over time. The prediction maps will be comprehensively study to assess the pixel to pixel variation within the rocket leaves. The PLSR models for Vitamin C, AA and phenols yielded an R2 of 0.76, 0.73 and 0.78, respectively in external prediction with root mean square errors approximately equivalent to those of reference analysis. Conclusively, hyperspectral imaging, with the correct mapping approach, can be a useful tool for the prediction and mapping of phytonutrients in wild rocket (Diplotaxis tenuifolia) over time.

中文翻译：

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通过高光谱成像对储存过程中最低限度加工的火箭叶 (Diplotaxis tenuifolia) 中的植物营养素进行表面预测和绘图的可行性研究

摘要 对可见光 (400–1000 nm) 和近红外 (900–1700 nm) 区域高光谱成像的可行性进行了综合研究，以预测和浓度映射维生素 C、抗坏血酸 (AA)、脱氢抗坏血酸 (DHAA)和野生火箭（Diplotaxis tenuifolia）中的酚类物质，在 5°C 下储存 12 天。具有不同数据预处理和波长选择的偏最小二乘回归 (PLSR) 对 NIR 范围内除 DHAA 之外的所有参数产生了令人满意的预测。预测模型用于浓度映射以跟踪随时间的变化。将对预测图进行综合研究，以评估火箭叶片内像素到像素的变化。维生素 C、AA 和酚类的 PLSR 模型得出的 R2 为 0.76、0.73 和 0.78，分别在外部预测中均方根误差近似等于参考分析的误差。总之，高光谱成像采用正确的绘图方法，可以成为预测和绘制野生火箭 (Diplotaxis tenuifolia) 中植物营养素随时间变化的有用工具。