Suppr超能文献

利用近红外漫反射光谱法从磨碎奶酪光谱中鉴别帕尔马干酪和格拉纳·帕达诺法定产区奶酪及其成熟时间。

Use of NDSS to discriminate between Parmigiano Reggiano and Grana Padano PDO and their ripening times from grated cheese spectra.

作者信息

Stocco Giorgia, Molle A, Biffani Stefano, Pizzamiglio Valentina, Cruz Jordi, Ferragina Alessandro, Cipolat-Gotet Claudio

机构信息

Department of Veterinary Science, University of Parma, Strada del Taglio 10, Parma 43126, Italy.

Department of Veterinary Science, University of Parma, Strada del Taglio 10, Parma 43126, Italy; Institute of Agricultural Biology and Biotechnology, National Research Council, Via Alfonso Corti 12, Milano 20133, Italy.

出版信息

Spectrochim Acta A Mol Biomol Spectrosc. 2025 Sep 5;337:126087. doi: 10.1016/j.saa.2025.126087. Epub 2025 Mar 20.

Abstract

This study focuses on using spectral data recorded with two different Near-Infrared (NIR) instruments (a benchtop and a portable device) to differentiate between Parmigiano Reggiano (PR) and Grana Padano (GP) Protected Designation of Origin (PDO) cheeses and their ripening times. Key findings showed that NIR spectroscopy effectively discriminated between PR and GP, with spectral range differences linked to their chemical composition, including fat, protein, and carbohydrate content. Specifically, certain wavelength ranges (1375-1400 nm, 1205-1250 nm, and 1410-1440 nm) were identified as significant in distinguishing PDO labels, highlighting the roles of fat and protein content in the cheese classification. Spectral features are also distinguished between ripening times, with specific wavelength bands tied to biochemical modifications during maturation, such as changes in moisture, protein, and fat content. In terms of instrument performance, the benchtop device achieved high accuracy in PDO classification (up to 0.97 F1 score), particularly when using a first derivative pre-treatment. The portable device performances showed higher variability but performed flawlessly for PDO classification. While both instruments effectively classified cheeses of distinct ripening ages, they were less successful at detecting samples containing mixtures of different aged cheeses. The portable instrument showed better results when combining the visible spectrum (350-950 nm) with the NIR spectrum (950-1650 nm), capturing surface color changes alongside internal structural transformations related to aging. Overall, the study validates the potential of NIR spectroscopy, especially when combined with established preprocessing techniques, as a powerful non-destructive tool to authenticate specific cheese PDO and assess ripening stages.

摘要

本研究聚焦于使用两种不同的近红外(NIR)仪器(一台台式仪器和一台便携式设备)记录的光谱数据,以区分帕尔马干酪(PR)和格拉纳·帕达诺干酪(GP)这两种受原产地保护(PDO)的奶酪及其成熟时间。主要研究结果表明,近红外光谱法能够有效区分PR和GP,光谱范围的差异与它们的化学成分有关,包括脂肪、蛋白质和碳水化合物含量。具体而言,某些波长范围(1375 - 1400纳米、1205 - 1250纳米和1410 - 1440纳米)被确定为区分PDO标签的重要范围,突出了脂肪和蛋白质含量在奶酪分类中的作用。光谱特征在成熟时间方面也有所不同,特定的波段与成熟过程中的生化变化相关,如水分、蛋白质和脂肪含量的变化。在仪器性能方面,台式设备在PDO分类中达到了较高的准确率(F1分数高达0.97),特别是在使用一阶导数预处理时。便携式设备的性能表现出较高的变异性,但在PDO分类方面表现完美。虽然这两种仪器都能有效地对不同成熟年龄的奶酪进行分类,但在检测含有不同年龄奶酪混合物的样品时不太成功。当将可见光谱(350 - 950纳米)与近红外光谱(950 - 1650纳米)结合时,便携式仪器显示出更好的结果,能够捕捉表面颜色变化以及与老化相关的内部结构转变。总体而言,该研究验证了近红外光谱法的潜力,特别是与既定的预处理技术相结合时,作为一种强大的无损工具来鉴定特定奶酪的PDO并评估成熟阶段。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验