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乌物种认证:通过近红外光谱学推进标签控制,作为快速,环保和强大的方法

Sarah Currò¹, Stefania Balzan¹, Enrico Novelli¹

¹Department of Comparative Biomedicine and Food Science, University of Padova, Agripolis, Viale dell'Università 16, 35020 Legnaro, Italy.

Foods (Basel, Switzerland)

|August 12, 2023

概括

近红外光谱学 (NIRS) 可以准确地识别渔业中的鱼物种. 这种快速,环保的方法确保了食品安全,并防止了海鲜认证的经济损失.

科学领域:

渔业科学渔业科学
分析化学分析化学
食品科学食品科学食品科学

背景情况:

准确的物种识别在渔业部门对于食品安全,消费者保护和防止经济损失至关重要.
像形态检查这样的传统方法可能耗时且需要专业知识.
开发快速可靠的认证技术对于海鲜行业至关重要.

研究的目的:

评估近红外光谱学 (NIRS) 的有效性,以准确识别鱼的物种.
为了将NIRS性能与传统的形态识别方法进行比较.
评估NIRS作为一种在加工后阶段验证渔产品真实性的工具.

主要方法:

从四个物种 (S. officinalis,S. bertheloti,S. aculeata,Sepiella inermis) 收集了93个冷解的鱼样本.
使用形态特征和近红外光谱学 (NIRS) 用便携式光谱仪 (900-1680 nm) 进行了物种识别.
分析了NIRS数据,使用主要组件分析 (PCA) 和支持矢量机 (SVM) 来进行分类.

主要成果:

近红外光谱学 (NIRS) 在识别乌鱼物种方面取得了93%的高整体准确性.
尼尔斯在物种识别方面表现出强度和有效性,即使在复杂的环境中也是如此.
光谱分析被证明是一种可靠的方法,用于区分四种研究的鱼物种.

结论:

近红外光谱 (NIRS) 是一种非常有效和准确的工具,用于鱼物种的识别.
NIRS提供了一种快速,环保和强大的方法来验证渔业产品的真实性.
这种光谱分析方法具有显著的潜力,可以改善该行业的海鲜安全和质量控制.

关键词:

化学测量方法化学测量方法食品检查食品检查食品检查食品检查海鲜海鲜海鲜海鲜支持矢量机器的支持矢量机器不定位的方法不定位的方法

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