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大黄鱼组织碳氮同位素分析:预处理方式的影响

齐林 黎莹 李子倩 郑炜坤 张润 周涛 郑敏芳 陈梦雅 陈敏

齐林,黎莹,李子倩,等. 大黄鱼组织碳氮同位素分析:预处理方式的影响[J]. 海洋学报,2025,47(x):1–12
引用本文: 齐林,黎莹,李子倩,等. 大黄鱼组织碳氮同位素分析:预处理方式的影响[J]. 海洋学报,2025,47(x):1–12
Qi Lin,Li Ying,Li Ziqian, et al. Carbon and nitrogen isotope analysis of large yellow croaker tissues: The impact of pretreatments[J]. Haiyang Xuebao,2025, 47(x):1–12
Citation: Qi Lin,Li Ying,Li Ziqian, et al. Carbon and nitrogen isotope analysis of large yellow croaker tissues: The impact of pretreatments[J]. Haiyang Xuebao,2025, 47(x):1–12

大黄鱼组织碳氮同位素分析:预处理方式的影响

基金项目: 福建省科技计划项目(2023Y0001);中央高校基本科研业务费专项(20720232022);厦门大学大学生创新训练计划项目(202310384090)。
详细信息
    作者简介:

    齐林( 2004 — ),男,浙江省泰顺县人,研究方向为同位素海洋化学。Email:22320212201366@stu.xmu.edu.cn

    通讯作者:

    张润( 1982 — ),男,博士,教授,博士生导师,研究方向为稳定同位素海洋生物地球化学。Email: zhangrun@xmu.edu.cn

Carbon and nitrogen isotope analysis of large yellow croaker tissues: The impact of pretreatments

  • 摘要: 碳氮稳定同位素组成(δ13C、δ15N)在揭示鱼类的生理动态、营养关系和产地溯源等方面具有独特的优势。样品的预处理方式可能在很大程度上影响鱼类组织同位素测定结果,但相关研究报道仍显不足,缺乏对于其内在机制的规律性认认识。本研究中,我们选取大黄鱼(Larimichthys crocea)—中国最重要的海洋养殖经济鱼类之一作为研究对象,评估了鱼体组织同位素分析前处理中两个关键步骤(肌肉去脂和鳞片酸浸)对大黄鱼组织碳氮稳定同位素组成的影响。结果表明,肌肉去脂操作总体上导致大黄鱼δ13C测值显著升高,而对鳞片进行酸浸操作则导致δ13C测值降低,同位素混合模型可以较好地解释预处理方式对鱼体组织δ13C测值的影响。这两种预处理方式均导致鱼体组织δ15N测值有所升高,暗示部分氮同位素信号的损失。根据鱼类生长过程中稳定同位素的动态平衡模型,建立了肌肉与鳞片碳氮同位素的理论替代关系,证实鳞片有望作为肌肉的替代物进行氮同位素分析。本研究为探讨大黄鱼稳定同位素组成的异质性提供了关键基础数据,对理解不同组织间的代谢动态具有参考价值,并为非致死性取样技术在鱼类稳定同位素研究中的应用提供了科学依据。
  • 图  1  大黄鱼样品预处理前后δ13C值和δ15N值的变化(a~d)及各组织有机碳δ13C与体长L的关系(e~f)(虚线为拟合直线;阴影为95%置信区间)

    Fig.  1  Changes in δ13C and δ15N values before and after pretreatment of large yellow croaker samples (a~d) and the relationship between organic carbon δ13C and body length L in various tissues (e~f) (dashed line represents fitted line; shaded area represents 95% confidence interval)

    图  2  大黄鱼不同组织的(a)碳含量、(b)氮含量及(c)碳氮比

    Fig.  2  (a) Carbon content, (b) nitrogen content, and (c) carbon to nitrogen ratio in different tissues of yellow croaker

    图  3  增加约束条件后各校正模型的拟合效果

    Fig.  3  The fitting effect of each calibration model after adding constraints

    图  4  同位素混合模型在不同端元值下对鳞片酸浸前后δ13C数据的拟合效果

    Fig.  4  The fitting effect of isotope mixing model on δ13C data of scales before and after acid leaching at different endmember values

    图  5  大黄鱼不同组织间δ13C值和δ15N值的关系(虚线为拟合直线;阴影为95%置信区间)

    Fig.  5  Relationship between δ13C and δ15N among different tissues of yellow croaker (dashed line represents fitted line; shaded area represents 95% confidence interval)

    图  6  大黄鱼肌肉和鳞片的氨基酸组成差异(鳞片氨基酸数据来自罗红宇[21];肌肉氨基酸数据来自颜孙安等[22]、李松等[23]、郭全友等[24]、吴燕燕等[25]、徐大凤等[26]的平均值;图中未列出占比<1%的氨基酸,包括色氨酸、半胱氨酸、谷氨酰胺和天冬酰胺)

    Fig.  6  Differences in amino acid composition between muscles and scales of yellow croaker (scale amino acid data from Luo Hongyu[21]; muscle amino acid data from the average values of Yan S et al.[22], Li S et al.[23], Guo Q et al.[24], Wu Y et al.[25], Xu D et al.[26]; amino acids with a proportion of less than 1% are not listed in the figure, including tryptophan, cysteine, glutamine and asparagine)

    表  1  样品碳氮同位素δ值及C∶N比值统计数据

    Tab.  1  Statistical data of δ values of carbon and nitrogen isotopes and C∶N ratio of samples

    样品类别δ13C / ‰δ15N / ‰C∶N
    平均值标准差最小值最大值平均值标准差最小值最大值平均值标准差最小值最大值
    肌肉−21.11.1−22.5−19.812.50.311.712.96.801.375.098.96
    去脂肌肉−16.70.2−17.0−16.314.00.213.614.53.740.173.323.90
    鳞片−13.60.7−14.5−12.311.60.510.812.23.530.083.403.66
    酸浸鳞片−14.20.5−14.7−13.211.90.511.412.73.370.023.353.42
    下载: 导出CSV

    表  2  脂质校正模型拟合结果

    Tab.  2  Fitting results of lipid correction model

    编号模型无边界条件约束有边界条件约束
    abcR2AICcabcR2AICc
    1Δ = a + b · δ13C−14.22−0.88/0.9628.10NDNDNDNDND
    2Δ = a + b · C∶N−0.110.66/0.9128.86−4.271.23/0.1231.18
    3Δ = a + b · δ13C + c · C∶N−9.39−0.570.270.9931.71NDNDNDNDND
    4Δ = a + b · (C∶N)−18.87−29.34/0.9029.029.83−36.28/0.8429.50
    5Δ = a + b · (C∶N + c) −126.54−735.3426.450.9233.6410.49−43.860.490.8134.44
    6Δ = a + b · ln(C∶N)−4.104.48/0.9128.88−8.966.94/0.6030.41
      注:/ 表示不存在该参数;ND表示无数据。Note: / indicates that the parameter does not exist; ND indicates no data.
    下载: 导出CSV
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  • 收稿日期:  2024-12-28
  • 修回日期:  2025-04-18
  • 网络出版日期:  2025-05-26

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