IRTA, Food Quality and Technology Program, Finca Camps i Armet, s/n, 17121 Monells, Girona, Spain.
IRTA, Food Quality and Technology Program, Finca Camps i Armet, s/n, 17121 Monells, Girona, Spain.
Spectrochim Acta A Mol Biomol Spectrosc. 2023 Dec 15;303:123217. doi: 10.1016/j.saa.2023.123217. Epub 2023 Jul 28.
Non-invasive technologies could help to guarantee quality standards of canned tuna fish. The aim of this study was to investigate the ability of bench-top (FT-NIR) and low-cost (LC-NIR) near infrared spectrometers to determine salt content and texture in canned tuna. Salt content distribution was also investigated using hyperspectral imaging (HSI) and computed tomography. Spectra were acquired on canned tuna and reference analysis performed. Partial least squares regression and discriminant analysis were used to develop salt content predictive and texture classification models. Salt content predictive errors were 0.10%, 0.22% and 0.22% for FT-NIR, LC-NIR and HSI, respectively. Salt content was not always homogeneously distributed in the can which was attributed to the salt content differences between internal and external parts of the tuna fish. Low-cost sensors could be a suitable solution to standardise the production and enable precise nutritional labelling, but more sophisticated algorithms are needed to identify textural defects.
非侵入性技术可有助于保障金枪鱼罐头的质量标准。本研究旨在探究台式（FT-NIR）和低成本（LC-NIR）近红外光谱仪在测定金枪鱼罐头盐含量和质地方面的能力。还使用高光谱成像（HSI）和计算机断层扫描来研究盐含量分布。对金枪鱼罐头进行光谱采集并进行参考分析。采用偏最小二乘回归和判别分析建立盐含量预测和质地分类模型。FT-NIR、LC-NIR 和 HSI 的盐含量预测误差分别为 0.10%、0.22%和 0.22%。罐内盐含量并非始终均匀分布，这归因于金枪鱼内外部分之间的盐含量差异。低成本传感器可能是标准化生产和实现精确营养标签的合适解决方案，但需要更复杂的算法来识别质地缺陷。
