Department of Agricultural Sciences, University of Naples Federico II, via Università 100, 80055 Portici, NA, Italy.
Department of Agricultural Sciences, University of Naples Federico II, via Università 100, 80055 Portici, NA, Italy.
Food Chem. 2022 May 1;375:131822. doi: 10.1016/j.foodchem.2021.131822. Epub 2021 Dec 13.
The reflectance NIR spectroscopy and chemometric data treatment on mature intact lemons, Limone di Sorrento PGI (cv Ovale di Sorrento) and Limone Costa D'Amalfi PGI (cv Sfusato Amalfitano) from Campania region, collected in 2018 and 2019, were used to predict properties, and discriminate cultivar and geographical provenance. By PCA, lemon NIR spectra grouped for production years due to the year variation of lemon properties attributable to annual climatic differences, homogeneous in all sites. This agrees with lemon chemical and physical differences by production year. Consequently, the relationship of NIR spectra with lemon quality properties by MLR and the cultivar and provenances discrimination by LDA were affected by year climatic difference; therefore, better model reliability was for single production year. NIR detectability of lemon properties did not appear beyond lemon thick peels, therefore the measured properties of lemon juices could derive from measurable properties of peel correlating with pulp properties.
利用 2018 年和 2019 年采集的来自坎帕尼亚地区的成熟完整柠檬(PGI 品种 Sorrento 柠檬 Limone di Sorrento 和 PGI 品种 Amalfi 柠檬 Limone Costa D'Amalfi,cv Ovale di Sorrento 和 Sfusato Amalfitano)的近红外反射光谱和化学计量学数据处理,对其进行预测和区分品种和地理来源。通过 PCA,柠檬近红外光谱因柠檬属性的年度变化而按生产年份分组,这归因于年度气候差异,在所有地点都是均匀的。这与柠檬化学和物理性质因生产年份的差异一致。因此,MLR 中近红外光谱与柠檬品质属性的关系以及 LDA 中品种和产地的区分受到年度气候差异的影响;因此,单一生产年份的模型可靠性更好。NIR 对柠檬属性的检测似乎不能穿透柠檬厚厚的果皮,因此柠檬汁的测量属性可能来自于与果肉属性相关的果皮可测量属性。