液态乳及乳粉脂肪酸指纹工业特征分析
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(内蒙古农业大学食品科学与工程学院 呼和浩特 010018)

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贾佳(1996-),女,硕士生

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国家自然科学基金地区科学基金项目(31760489)


Analysis on Industry Property of Fatty Acids Fingerprint of Liquid Milk and Milk Powder
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(College of Food Science and Engineering, Inner Mongolia Agricultural University, Hohhot 010018)

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    摘要:

    乳及乳制品的脂肪酸(FAs)构成模式,即FAs指纹,不仅受物种来源、自然地理和气候环境决定或影响,还与家畜饲养方式、原乳质量、加工类型、加工标准和工艺参数等人为和工业因素有关。目前尚未提出乳制品"工业指纹"概念,也缺乏相应系统的研究。采集荷斯坦牛、牦牛和山羊原乳、超高温灭菌(UHT)乳和乳粉样品200份,采用气相色谱法测定FAs,按照① 加工类型;② UHT处理;③ 厂家/品牌;④ 液态乳品类(品系)和⑤ 饲养模式5类工业因素,对FA单指标和FAs多指标整体进行统计比较,通过主成分分析(PCA)观察样品的FAs指纹自然聚类情况。结果表明,多数FA在5类研究中都存在显著差异,而配伍方差和配对t检验FAs差异都不显著,说明传统统计不能区分FAs模式复杂的整体改变。PCA分析样品集的自然聚类与各加工处理、品牌品类及饲养模式一致,说明各工业因素对乳品FAs指纹都有特征性和模式化的影响。有望利用FAs指纹实现乳品生产加工方式、厂家品牌及品类等级等的区分,市售乳品完整性和真实性判别,奶畜科学饲养及功能性特色乳品研发效果多指标大数据的可视化评价。

    Abstract:

    Fatty acids (FAs) composition pattern, i.e. FAs fingerprints, of milk and dairy products is not only determined or affected by milk animal's species and breeds, natural geographical and climate environmental origin, also correlated to feeding pattern of milk animal, quality of raw milk, product type, product standard and processing parameters, etc., artificial and industrial factors. To date, the concept of "industrial fingerprint" of dairy products has not been proposed, and lacks systematic studies. A total of 200 Holstein cow (cow), Yak and Goat raw milk, Ultra high temperature (UHT) milk and milk powder samples were collected, and FAs were detected by gas chromatography method. According to the following five categories/aspects of industrial factors such as ①product type, ②UHT treatment, ③producer/brand, ④liquid milk series, and ⑤feeding pattern of cow, significant of differences of each single FA and overall differences of FAs data set were tested and compared, and principal component analysis(PCA) was conducted to observe the natural clustering of sample sets by their FAs fingerprints. As the results, most FA showed significant differences in each study aspects, but no significant differences were observed on general mean of overall FAs by block designed analysis on variance and paired t test, traditional statistics could not distinguish the complex overall changes of FAs pattern. PCA showed that the natural clustering of milk samples were consistent with processing methods, brands, series, and feeding patterns, proving that these various industrial factors could cause characteristic and patterned changes on FAs fingerprints of dairy products. Conversely, it is feasible and promising to establish FAs fingerprint model to distinguish the producing and processing methods, producer and brand of milk products, product series and so on, integrity and authenticity of market dairy foods, and also facilitate and visualize massive data/multivariate evaluation on effectiveness of scientific feeding on milk animals and functional and peculiar dairy product development.

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贾佳,郭军,李琪,郭珍琪.液态乳及乳粉脂肪酸指纹工业特征分析[J].中国食品学报,2022,22(9):226-238

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  • 收稿日期:2021-09-21
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  • 在线发布日期: 2022-10-26
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