近红外光谱结合多元分析研究新西兰啤酒花产地溯源

IF 5.3 2区 农林科学 Q1 FOOD SCIENCE & TECHNOLOGY
Emily Fanning, Graham T. Eyres, Russell Frew, Biniam Kebede
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引用次数: 0

摘要

精酿行业对具有独特香味的啤酒花的需求不断增加,这增加了与啤酒花来源有关的欺诈活动的风险。鉴于食品欺诈的显著增加和消费者对原产地透明度的日益关注,需要快速认证方法来核实原产地。本研究采用近红外(NIR)光谱结合多元数据分析,对新西兰啤酒花在区域和农场层面的地理来源可追溯性进行了研究。从新西兰塔斯曼地区的八个农场收集了三个啤酒花品种。此外,还比较了塔斯曼和中奥塔哥地区的6个品种对。对原始近红外光谱进行预处理,采用偏最小二乘判别分析(PLS-DA)进行分类。Suderdelic™品种在农场之间显示出最高的分离,每个样本形成不同的组,没有任何重叠。Nectaron®品种显示了三个主要集群,而Nelson Sauvin™品种显示了农场起源之间的最小差异。区域样品PLS-DA分类模型显示遗传是主要因素,同一品种的样品位置靠得比较近。有趣的是,在PLS-DA模型的第三维度上出现了明显的位置效应。本研究展示了近红外光谱结合多元数据分析的潜力,可以根据不同规模(农场和地区)的地理来源对啤酒花样品进行快速分类,从而有助于预防和检测与来源相关的食品欺诈。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Near-Infrared Spectroscopy Combined with Multivariate Analysis for the Geographical Origin Traceability of New Zealand Hops

The increased demand for hops with distinctive aromas by the craft brewing industry has elevated the risk of fraudulent activities linked to their origin. Given the significant rise in food fraud and consumers’ growing attention to origin transparency, there is a need for rapid authentication methods to verify origin. This study employed near-infrared (NIR) spectroscopy combined with multivariate data analysis for the geographical origin traceability of New Zealand hops at the regional and farm levels. Three hop cultivars were collected from eight farms in the Tasman region of New Zealand. Additionally, six cultivar pairs were compared between the Tasman and Central Otago regions. The raw NIR spectra were preprocessed, and partial least squares discriminant analysis (PLS-DA) was employed for classification. The Suderdelic™ cultivar displayed the highest separation between the farms, with each sample forming distinct groups without any overlap. The Nectaron® cultivar displayed three primary clusters, while the Nelson Sauvin™ cultivar illustrated the least variation between farm origins. The regional samples PLS-DA classification model revealed genetics as the dominant factor, where the samples from the same cultivar were positioned close to each other. Interestingly, an apparent location effect emerged in the third dimension of the PLS-DA model. This study demonstrated the potential of NIR spectroscopy combined with multivariate data analysis to rapidly classify hop samples by their geographical origin at different scales (farms and regions), thereby aiding in the prevention and detection of food fraud related to origin.

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来源期刊
Food and Bioprocess Technology
Food and Bioprocess Technology 农林科学-食品科技
CiteScore
9.50
自引率
19.60%
发文量
200
审稿时长
2.8 months
期刊介绍: Food and Bioprocess Technology provides an effective and timely platform for cutting-edge high quality original papers in the engineering and science of all types of food processing technologies, from the original food supply source to the consumer’s dinner table. It aims to be a leading international journal for the multidisciplinary agri-food research community. The journal focuses especially on experimental or theoretical research findings that have the potential for helping the agri-food industry to improve process efficiency, enhance product quality and, extend shelf-life of fresh and processed agri-food products. The editors present critical reviews on new perspectives to established processes, innovative and emerging technologies, and trends and future research in food and bioproducts processing. The journal also publishes short communications for rapidly disseminating preliminary results, letters to the Editor on recent developments and controversy, and book reviews.
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