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Assessment of pesticide coating on cereal seeds by near infrared hyperspectral imaging

机译:近红外高光谱成像技术评估谷物种子上的农药涂层

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Author Summary: Classical chromatographic methods, such as ultra performance liquid chromatography (UPLC), are used as reference methods to assess seed quality and homogeneous pesticide coating of seeds. These methods have some important drawbacks since they are time consuming, expensive, destructive and require a substantial amount of solvent, among others. Near infrared (NIR) spectroscopy seems to be an interesting alternative technique for the determination of the quality of seed treatment and avoids most of these drawbacks. The objective of this study was to assess the quality of pesticide coating treatment by near infrared hyperspectral imaging (NIR-HSI) by analysing, on a seed-by-seed basis, several seeds simultaneously in comparison to NIR spectroscopy and UPLC as the reference method. To achieve this goal, discrimination—partial least squares discriminant analysis (PLS-DA)—models and regression—partial least squares (PLS)—models were developed. The results obtained by NIR-HSI are compared to the results obtained with NIR spectroscopy and UPLC instruments. This study has shown the potential of NIR hyperspectral imaging to assess the quality/homogeneity of the pesticide coating on seeds.
机译:作者摘要:经典色谱方法(例如超高效液相色谱法(UPLC))用作评估种子质量和种子均质农药涂层的参考方法。这些方法具有一些重要的缺点,因为它们耗时,昂贵,破坏性并且需要大量的溶剂。近红外(NIR)光谱似乎是确定种子处理质量的一种有趣的替代技术,它可以避免大多数这些缺点。这项研究的目的是通过逐个种子地分析近红外光谱法和以UPLC为参考方法的种子同时评估近红外高光谱成像(NIR-HSI)农药涂层处理的质量。为实现此目标,开发了偏最小二乘判别分析(PLS-DA)模型和回归偏最小二乘(PLS)模型。将NIR-HSI获得的结果与NIR光谱学和UPLC仪器获得的结果进行比较。这项研究表明,NIR高光谱成像技术可以评估种子上农药涂层的质量/均匀性。

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