Mancini Manuela, Mazzoni Luca, Gagliardi Francesco, Balducci Francesca, Duca Daniele, Toscano Giuseppe, Mezzetti Bruno, Capocasa Franco
Agricultural, Food and Environmental Sciences, Università Politecnica delle Marche, via Brecce Bianche 10, 60131 Ancona, Italy.
Foods. 2020 Apr 6;9(4):441. doi: 10.3390/foods9040441.
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.
通过传统的破坏性实验室技术来测定草莓果实品质存在一些局限性，这些局限性与样本数量、时间以及在供应链各阶段的适用性有关。本研究的目的是通过传统实验室破坏性技术和近红外光谱（NIR）来测定五种草莓基因型果实的主要品质特征。应用主成分分析（PCA）来寻找所有采集样本之间的光谱差异。计算偏最小二乘回归（PLS）技术以预测感兴趣的品质参数。用于预测可溶性固形物含量的PLS模型表现最佳——实际上，它是一个稳健且可靠的模型，验证值表明了其在品质应用中的使用可能性。还获得了一个适用于预测硬度的PLS模型——验证值略有变差，但在筛选应用中仍可接受。近红外光谱是破坏性技术的重要替代方法，它利用电磁光谱的红外区域以非破坏性方式研究样本的化学物理性质，在农业食品市场中有显著应用。
