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浙江大学学报(理学版)  2022, Vol. 49 Issue (6): 715-725    DOI: 10.3785/j.issn.1008-9497.2022.06.010
化学     
基于元素及稳定同位素分析的大黄鱼产地区分技术
梅光明1,2(),杨盈悦1,3,张玉汝4,赵月涵1,3,张小军1,2(),黄丽英1,2,郑斌3
1.浙江省海洋水产研究所,浙江 舟山 316021
2.浙江省海水增养殖重点实验室,浙江 舟山 316021
3.浙江海洋大学 食品与医药学院,浙江 舟山 316022
4.浙江舟山环境工程设计有限公司,浙江 舟山 316000
Geographical identification of Larimichthys crocea based on analysis of elements and stable isotope ratios
Guangming MEI1,2(),Yingyue YANG1,3,Yuru ZHANG4,Yuehan ZHAO1,3,Xiaojun ZHANG1,2(),Liying HUANG1,2,Bin ZHENG3
1.Zhejiang Marine Fisheries Research Institute,Zhoushan 316021,Zhejiang Province,China
2.Key Laboratory of Mariculture and Enhancement of Zhejiang Province,Zhoushan 316021,Zhejiang Province,China
3.College of Food Science and Pharmacy,Zhejiang Ocean University,Zhoushan 316022,Zhejiang Province,China
4.Zhouhuan Environmental Engineering Design Co. ,LTD,Zhoushan 316000,Zhejiang Province,China
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摘要:

为实现对4种大黄鱼(Larimichthys crocea)产地(分别来自福建宁德养殖、浙江温州养殖、浙江舟山养殖和舟山渔场自然海域捕捞)的区分,应用电感耦合等离子体质谱仪(inductively coupled plasma mass spectrometry,ICP-MS)及元素分析-同位素质谱仪对大黄鱼肌肉中19种矿物元素及δ13C、δ15N和C、N元素的质量分数进行了测定,基于质量分数差异并结合主成分分析(principal component analysis,PCA)、聚类分析(cluster analysis,CA)和Fisher判别分析对4种不同产地大黄鱼进行区分。单因素方差分析(ANOVA)及事后多重比较(LSD和Tamhane T2检验)结果表明,12种元素(C、N、Mg、Al、K、Ti、Cr、Cu、Zn、Se、Sn、Ba)及δ13C、δ15N在不同产地大黄鱼中具有较明显的地域特征差异。PCA结果表明,前2个主成分(累计方差贡献率为64.1%)的得分散点图分成了4个相对集中的区域,4种不同产地大黄鱼彼此无重叠,能被有效区分。CA结果表明,4种不同产地大黄鱼中除温州养殖大黄鱼样本被分为两类,其他3种大黄鱼样本均各自聚为一类。Fisher判别分析结果显示,原始分类结果的判别准确率为100%,“留一法”交叉验证分类结果显示,有85.7%的舟山养殖大黄鱼样本被正确分类,14.3%的被误判为温州养殖大黄鱼,其余3种大黄鱼样本分类准确率均为100%。研究结果表明,利用元素及稳定同位素比值差异结合化学计量学分析手段,可有效实现大黄鱼的产地区分,为大黄鱼产地鉴别提供参考。

关键词: 大黄鱼产地区分元素稳定同位素化学计量学    
Abstract:

In order to distinguish the geographic origins of four Larimichthys crocea (L. crocea,three species rearing in Ningde, Wenzhou, and Zhoushan, and one farming in sea area of Zhoushan), the contents of 19 mineral elements, carbon stable isotope ratio (δ13C), nitrogen stable isotope ratio (δ15N), carbon (C) and nitrogen (N) in the muscle tissues were determined by inductively coupled plasma mass spectrometry (ICP-MS) and elemental analysis-isotope mass spectrometry. Based on the difference on contents of such elements, and combined with principal component analysis (PCA), cluster analysis (CA) and Fisher discriminant analysis, the four producing areas of L. crocea were distinguished. Single factor ANOVA test and multiple comparisons (LSD and Tamhane T2 test) showed the contents of C, N, Magnesium (Mg), Aluminium (Al), Kalium (K), Titanium (Ti), Chromium (Cr), Cuprum (Cu), Zinc (Zn), Selenium (Se), Stannum (Sn), Barium (Ba), δ13C and δ15N had obvious regional differences. PCA analysis showed that the score scatter plot of the first two principal components (with the cumulative variance contribution rate of 64.1%) was divided into four relatively concentrated and independent regions without overlapping. CA analysis showed that samples of L. crocea rearing in Wenzhou were divided into two groups and samples of the other three species each were clustered into one group respectively. Fisher discriminant analysis showed that the accuracy of the original classification results was 100%, while the 'leave-one-out' cross-validation classification showed that 85.7% samples of L. crocea rearing in Zhoushan were correctly classified (the other 14.3% were misclassified as rearing in Wenzhou), and the samples of other three species of L. crocea were 100% correctly identified. The results show that the application of analysis on elements and stable isotope ratios, combined with chemometric analysis can effectively distinguish the geographical origin of L. crocea, provide reference for origin authenticity identification.

Key words: Larimichthys crocea    geographical identification    elements    stable isotope    chemometrics
收稿日期: 2022-07-27 出版日期: 2022-11-23
CLC:  O 657.63  
基金资助: 2021年浙江省科技厅科研院所扶持专项(33000091077504);国家重点研发计划项目(2020YFD0900900)
通讯作者: 张小军     E-mail: meigm123@163.com;xiaojun3627@163.com
作者简介: 梅光明(1984—),ORCID:https://orcid.org/0000-0002-9267-8112,男,硕士,高级工程师,主要从事水产品加工与质量安全研究,E-mail: meigm123@163.com.
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引用本文:

梅光明, 杨盈悦, 张玉汝, 赵月涵, 张小军, 黄丽英, 郑斌. 基于元素及稳定同位素分析的大黄鱼产地区分技术[J]. 浙江大学学报(理学版), 2022, 49(6): 715-725.

Guangming MEI, Yingyue YANG, Yuru ZHANG, Yuehan ZHAO, Xiaojun ZHANG, Liying HUANG, Bin ZHENG. Geographical identification of Larimichthys crocea based on analysis of elements and stable isotope ratios. Journal of Zhejiang University (Science Edition), 2022, 49(6): 715-725.

链接本文:

https://www.zjujournals.com/sci/CN/10.3785/j.issn.1008-9497.2022.06.010        https://www.zjujournals.com/sci/CN/Y2022/V49/I6/715

元素质量分数
福建宁德养殖浙江温州养殖浙江舟山养殖舟山渔场海域捕捞
Na*3512.52±1231.092897.81±771.532346.26±813.973763.95±938.77
Mg*1141.05±82.12b906.44±135c1157.73±68b1429.32±177.16a
Al*17.49±6.18a3.47±2.21c1.98±1.84c7.56±3.64b
K*12052.49±2576.39c13709.33±2195.89c16113.27±1073.7b19589.09±1122.68a
Ca*418.78±63.47457.53±155.23580.56±433.58419.63±80.92
Fe*15.29±7.4045.28±66.4216.73±6.6419.8±5.88
Ti747.82±281.83a231.73±70.71b292.35±59.27b628.09±104.07a
V13.01±2.9114.74±4.739.52±5.0413.79±3.92
Cr1144.91±444.51b2413.81±557.12a1642.96±1404.77ab1600.31±748.61ab
Mn480.45±177.47724.23±250.47908.4±499.78718.83±220.08
Co20.88±13.3737±8.7438.19±23.0628.24±9.4
Ni476.27±291.792681.44±3355.16757.62±510.36632.88±337.83
Cu705.95±199.72b5533.33±3243.93a1569.57±516.33a1322.62±633.21b
Zn13773.56±1223.57c15427.72±2101.17b16127.39±2254.35ab17433.37±1437.65a
Se944.23±116.32b980.27±212.15b927.48±213.92b1812.49±277.68a
Sr2425.39±380.192399.78±1074.952837.51±2420.822631.26±685.25
Mo16.56±8.2516.53±5.4910.98±8.5219.02±9.58
Sn49.76±22.33b289.81±89.56a107.22±88.99b94.97±45.76b
Ba132.68±44.88b80.55±20.41b144.55±77.25b259.72±126.54a
表1  不同产地大黄鱼肌肉中19种矿物元素的质量分数
大黄鱼来源稳定同位素比值碳、氮质量分数
δ13C/‰δ15N/‰C/%N/%
福建宁德养殖-20.64±1.71b10.98±2.20a53.45±2.89a10.37±0.55b
浙江温州养殖20.43±1.71b10.78±1.31a52.19±3.89a10.07±1.49b
浙江舟山养殖-21.34±1.08b8.83±0.89b50.96±1.97a11.03±0.61b
舟山渔场捕捞-17.62±0.85a11.79±0.93a47.69±2.02b12.57±1.17a
表2  不同产地大黄鱼肌肉中稳定同位素比值δ13C、δ15N和碳、氮质量分数
图1  不同产地大黄鱼PCA中PC1、PC2得分散点图
图2  元素在前2个主成分中的贡献
图3  主成分方差贡献率
图4  不同产地大黄鱼CA结果1-10 福建宁德养殖;11-20舟山渔场捕捞;21-30浙江温州养殖;31-39浙江舟山养殖。

大黄鱼

样品产地

产地预测集准确率/%
福建宁德养殖

舟山

渔场

捕捞

浙江温州养殖浙江舟山养殖
福建宁德养殖3000100
舟山渔场捕捞0300
浙江温州养殖0030
浙江舟山养殖0003
表3  不同产地大黄鱼测试集样本Fisher判别结果
验证方法产地预测组成员信息(占比/%)总计(占比%)
宁德养殖舟山渔场捕捞温州养殖舟山养殖
原始福建宁德养殖100000100
舟山渔场捕捞010000100
浙江温州养殖001000100
浙江舟山养殖000100100
交叉验证福建宁德养殖100000100
舟山渔场捕捞010000100
浙江温州养殖001000100
浙江舟山养殖0014.385.7100
表4  Fisher判别分析分类结果
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