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Application of the Non-Destructive NIR Technique for the Evaluation of Strawberry Fruits Quality Parameters

机译:无损近红外技术在草莓果实品质参数评价中的应用

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摘要

The determination of strawberry fruit quality through the traditional destructive lab techniques has some limitations related to the amplitude of the samples, the timing and the applicability along all phases of the supply chain. The aim of this study was to determine the main qualitative characteristics through traditional lab destructive techniques and Near Infrared Spectroscopy (NIR) in fruits of five strawberry genotypes. Principal Component Analysis (PCA) was applied to search for spectral differences among all the collected samples. A Partial Least Squares regression (PLS) technique was computed in order to predict the quality parameters of interest. The PLS model for the soluble solids content prediction was the best performing—in fact, it is a robust and reliable model and the validation values suggested possibilities for its use in quality applications. A suitable PLS model is also obtained for the firmness prediction—the validation values tend to worsen slightly but can still be accepted in screening applications. NIR spectroscopy represents an important alternative to destructive techniques, using the infrared region of the electromagnetic spectrum to investigate in a non-destructive way the chemical–physical properties of the samples, finding remarkable applications in the agro-food market.
机译:通过传统的破坏性实验室技术确定草莓果实质量存在一些局限性,这些局限性涉及样品的幅度,时间安排以及供应链各个阶段的适用性。这项研究的目的是通过传统的实验室破坏性技术和近红外光谱法(NIR)确定5种草莓基因型水果的主要定性特征。应用主成分分析(PCA)来搜索所有采集样品之间的光谱差异。计算偏最小二乘回归(PLS)技术以预测感兴趣的质量参数。用于可溶性固形物含量预测的PLS模型是性能最好的-实际上,它是一个可靠可靠的模型,验证值表明了其在高质量应用中的可能性。还获得了用于预测硬度的合适的PLS模型-验证值趋于稍微变差,但仍可以在筛选应用中接受。近红外光谱法是破坏性技术的重要替代方法,它使用电磁波谱的红外区域以非破坏性方式研究样品的化学-物理性质,从而在农产品市场上找到了非凡的应用。

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