Classification of “Ricotta” whey cheese from different milk and Designation of Origin-protected samples through infrared spectroscopy and chemometric analysis

IF 4 2区 农林科学 Q2 CHEMISTRY, APPLIED
Martina Foschi, Alessandra Biancolillo, Samantha Reale, Francesco Poles, Angelo Antonio D’Archivio
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Abstract

Whey cheeses are produced in various parts of the world, such as Portugal, Spain, and Turkey. In Italy, whey cheese goes under the name “ricotta”. This study investigates the classification of ricotta whey cheese derived from various milk sources (either protected designation of origin (PDO) or not) using an Attenuated Total Reflectance Fourier-transform infrared (ATR-FTIR) spectroscopy combined with chemometric analysis. Employing the SPORT-LDA method, which can incorporate Variable Importance in Projection (VIP) analysis, 287 samples of ricotta cheese produced using milk from four different animals (sheep, cow, goat, and water buffalo) were classified according to the animal origin. This led to the correct classification of 97 % of the test samples (3 misclassified samples over 97). VIP analysis revealed that the spectral ranges of 3300–3100 cm⁻¹, 2900–2800 cm⁻¹, and 1700–1300 cm⁻¹ are consistently relevant across all milk sources, thanks to the key molecular vibrations associated with protein structures, lipid content, and water. Eventually, the analysis was circumscribed to sheep ricotta cheeses, because some of these present the PDO quality mark. SIMCA was used to classify PDO samples with respect to the Non-PDO sheep ricotta individuals. The application of SIMCA to model class PDO led to 82.1 % of sensitivity and 82.7 % of specificity (in external validation). The findings underscore the robustness of ATR-FTIR spectroscopy and chemometrics in maintaining the integrity of PDO products and ensuring quality control.
通过红外光谱和化学计量分析对来自不同牛奶和原产地名称保护样品的 "Ricotta "乳清干酪进行分类
世界各地都生产乳清奶酪,如葡萄牙、西班牙和土耳其。在意大利,乳清奶酪的名称是 "ricotta"。本研究使用衰减全反射傅立叶变换红外光谱(ATR-FTIR)结合化学计量分析法,对来自不同奶源(原产地名称受保护(PDO)或非原产地名称受保护)的乳清干酪进行分类。采用 SPORT-LDA 方法(该方法可结合投影中的变量重要性(VIP)分析),根据动物来源对使用四种不同动物(绵羊、奶牛、山羊和水牛)的牛奶生产的 287 个乳清干酪样品进行了分类。结果是 97% 的测试样品分类正确(97 个样品中有 3 个分类错误)。VIP 分析表明,3300-3100 cm-¹、2900-2800 cm-¹ 和 1700-1300 cm-¹ 光谱范围与所有牛奶来源一致相关,这要归功于与蛋白质结构、脂质含量和水分相关的关键分子振动。最终,分析局限于绵羊乳清干酪,因为其中一些干酪具有 PDO 质量标志。SIMCA 用于将 PDO 样品与非 PDO 羊乳干酪个体进行分类。应用 SIMCA 建立 PDO 类别模型的灵敏度为 82.1%,特异度为 82.7%(外部验证)。研究结果表明,ATR-傅立叶变换红外光谱和化学计量学在维护 PDO 产品的完整性和确保质量控制方面具有强大的功能。
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来源期刊
Journal of Food Composition and Analysis
Journal of Food Composition and Analysis 工程技术-食品科技
CiteScore
6.20
自引率
11.60%
发文量
601
审稿时长
53 days
期刊介绍: The Journal of Food Composition and Analysis publishes manuscripts on scientific aspects of data on the chemical composition of human foods, with particular emphasis on actual data on composition of foods; analytical methods; studies on the manipulation, storage, distribution and use of food composition data; and studies on the statistics, use and distribution of such data and data systems. The Journal''s basis is nutrient composition, with increasing emphasis on bioactive non-nutrient and anti-nutrient components. Papers must provide sufficient description of the food samples, analytical methods, quality control procedures and statistical treatments of the data to permit the end users of the food composition data to evaluate the appropriateness of such data in their projects. The Journal does not publish papers on: microbiological compounds; sensory quality; aromatics/volatiles in food and wine; essential oils; organoleptic characteristics of food; physical properties; or clinical papers and pharmacology-related papers.
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