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High-Resolution and Non-destructive Evaluation of the Spatial Distribution of Nitrate and Its Dynamics in Spinach (Spinacia oleracea L.) Leaves by Near-Infrared Hyperspectral Imaging

机译:近红外高光谱成像技术对菠菜(Spinacia oleracea L.)叶片中硝酸盐的空间分布及其动力学的高分辨率和无损评价

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摘要

Nitrate is an important component of the nitrogen cycle and is therefore present in all plants. However, excessive nitrogen fertilization results in a high nitrate content in vegetables, which is unhealthy for humans. Understanding the spatial distribution of nitrate in leaves is beneficial for improving nitrogen assimilation efficiency and reducing its content in vegetables. In this study, near-infrared (NIR) hyperspectral imaging was used for the non-destructive and effective evaluation of nitrate content in spinach (Spinacia oleracea L.) leaves. Leaf samples with different nitrate contents were collected under various fertilization conditions, and reference data were obtained using reflectometer apparatus RQflex 10. Partial least squares regression analysis revealed that there was a high correlation between the reference data and NIR spectra (r2 = 0.74, root mean squared error of cross-validation = 710.16 mg/kg). Furthermore, the nitrate content in spinach leaves was successfully mapped at a high spatial resolution, clearly displaying its distribution in the petiole, vein, and blade. Finally, the mapping results demonstrated dynamic changes in the nitrate content in intact leaf samples under different storage conditions, showing the value of this non-destructive tool for future analyses of the nitrate content in vegetables.
机译:硝酸盐是氮循环的重要组成部分,因此存在于所有植物中。但是,过量施氮会导致蔬菜中硝酸盐含量高,这对人类来说是不健康的。了解叶子中硝酸盐的空间分布有助于提高氮的吸收效率并减少蔬菜中氮的含量。在这项研究中,近红外(NIR)高光谱成像用于菠菜(Spinacia oleracea L.)叶片中硝酸盐含量的无损和有效评估。在不同的施肥条件下收集硝酸盐含量不同的叶片样品,并使用反射计设备RQflex 10获得参考数据。偏最小二乘回归分析表明,参考数据与NIR光谱之间具有高度相关性(r 2 < / sup> = 0.74,交叉验证的均方根误差= 710.16 mg / kg)。此外,菠菜叶中的硝酸盐含量已成功地以高空间分辨率绘制了图,清楚地显示了其在叶柄,叶脉和叶片中的分布。最后,绘图结果显示了在不同储存条件下完整叶片样品中硝酸盐含量的动态变化,显示了这种无损检测工具对蔬菜中硝酸盐含量未来分析的价值。

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