Volume 17 Issue 4
Aug.  2021
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CHEN Xi, WU Biao, WANG Yan, SUN Xiujun, ZHOU Liqing, LIU Zhihong. Establishment and optimization of micro-reaction system for determination of oyster glycogen content[J]. South China Fisheries Science, 2021, 17(4): 126-132. DOI: 10.12131/20210040
Citation: CHEN Xi, WU Biao, WANG Yan, SUN Xiujun, ZHOU Liqing, LIU Zhihong. Establishment and optimization of micro-reaction system for determination of oyster glycogen content[J]. South China Fisheries Science, 2021, 17(4): 126-132. DOI: 10.12131/20210040
shu

Establishment and optimization of micro-reaction system for determination of oyster glycogen content

  • 1.

    Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences/Key Laboratory of Sustainable Development of Marine Fisheries, Ministry of Agriculture and Rural Affairs, Qingdao 266071, China

  • 2.

    Shanghai Ocean University/National Demonstration Center for Experimental Fisheries Science Education, Shanghai 201306, China

  • 3.

    Laboratory for Marine Fisheries Science and Food Production Processes/Qingdao National Laboratory for Marine Science and Technology, Qingdao 266071, China

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  • Received Date: January 18, 2021
  • Revised Date: April 27, 2021
  • Accepted Date: May 07, 2021
  • Available Online: May 13, 2021
    Graphical Abstract
    • Abstract
  • In this study, soft tissues of fresh oyster (Crassostrea ariakensis) were used as the experimental material for the determination of glycogen, and the optimal reaction conditions were determined by analyzing the absorbance values obtained with different anthrone sulfuric acid ratios and at different reaction times. Then the lowest detection limit, stability and accuracy of this method were evaluated, and a trace detection system for oyster glycogen was established. The established micro-reaction system had a volume of 300 μL including 200 μL of 0.2% anthrone sulfuric acid solution and 100 μL of sample solution, and the reaction time in boiling water bath was 10 min. The minimum detection limit of glucose was 0.001 5 mg·mL−1 and the coefficient of variation of the standard curve was less than 4%, indicating the high detection sensitivity and good repeatability of the method. In addition, after the reaction completed, absorbance basically remained unchanged within 120 min at room temperature, proving the high stability of this reaction. The recovery rate of glucose from six tissues including oyster mantle, gill, lip, gonad, hepatopancreas and adductor muscle were between 95.3% and 105.8%, indicating that this method has high accuracy. Thus, the established method for the determination of oyster glycogen has high repeatability, stability and accuracy, having the advantages of low reagent consumption, simple operation and low cost per sample. It is suitable for batch determination of glycogen in a large amount of samples. This study provides an effective technical method for quickly and efficiently determining glycogen in oyster samples.
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    • References (32)
  • [1]
    陈骞, 杨瑞金, 顾聆琳. 牡蛎糖原的研究 (II)——牡蛎糖原的分子结构[J]. 食品科学, 2005, 26(7): 43-46. doi: 10.3321/j.issn:1002-6630.2005.07.005
    [2]
    陈骞. 牡蛎糖原的提取与抗疲劳活性研究[D]. 无锡: 江南大学, 2005: 10.
    [3]
    丛日浩. 长牡蛎快速生长品系选育及重要功能基因与生长和糖原含量相关性研究[D]. 青岛: 中国海洋大学, 2014: 24.
    [4]
    汪何雅, 杨瑞金, 王璋. 牡蛎的营养成分及蛋白质的酶法水解[J]. 水产学报, 2003, 27(2): 163-168.
    [5]
    王海艳. 中国近海常见牡蛎分子系统演化和分类的研究[D]. 青岛: 中国科学院海洋研究所, 2004: 9.
    [6]
    MENG J, SONG K, LI C, et al. Genome-wide association analysis of nutrient traits in the oyster Crassostrea gigas: genetic effect and interaction network[J]. BMC Genom, 2019, 20(1): 625. doi: 10.1186/s12864-019-5971-z
    [7]
    刘雨. 长牡蛎高糖原含量新品系能量代谢及养殖模式研究[D]. 上海: 上海海洋大学, 2017: 18.
    [8]
    刘思玮. 长牡蛎糖原代谢酶基因多态性与生长及糖原含量相关性研究[D]. 青岛: 中国海洋大学, 2013: 28.
    [9]
    李春燕. 牡蛎营养品质等重要经济性状的遗传定位与基因解析[D]. 青岛: 中国科学院海洋研究所, 2017: 29.
    [10]
    王卫军, 杨建敏, 董迎辉, 等. 长牡蛎 (Crassostrea gigas) 鲜样组织八种成分含量近红外 (NIR) 模型的建立[J]. 海洋与湖沼, 2015, 46(4): 845-852.
    [11]
    杨柳, 郭海云, 邵长健, 等. 糖原检测方法研究进展[J]. 现代生物医学进展, 2018, 18(1): 175-179.
    [12]
    高珊, 童英, 熊晓燕, 等. 蒽酮法与试剂盒法测定糖原含量的比较研究[J]. 首都公共卫生, 2011, 5(1): 38-40. doi: 10.3969/j.issn.1673-7830.2011.01.018
    [13]
    LEYVA A, QUINTANA A, SANCHEZ M, et al. Rapid and sensitive anthrone-sulfuric acid assay in microplate format to quantify carbohydrate in biopharmaceutical products: method development and validation[J]. Biologicals, 2008, 36(2): 134-141. doi: 10.1016/j.biologicals.2007.09.001
    [14]
    韩烨, 马永强, 王鑫, 等. 微量滴定蒽酮法测定甜玉米芯可溶性糖含量方法的建立[J]. 食品科技, 2019, 44(11): 327-334.
    [15]
    张述伟, 宗营杰, 方春燕, 等. 蒽酮比色法快速测定大麦叶片中可溶性糖含量的优化[J]. 食品研究与开发, 2020, 41(7): 196-200.
    [16]
    竺巧玲, 俞薇. 蒽酮-硫酸法测定蛋糕总糖含量的研究[J]. 食品安全质量检测学报, 2014, 5(5): 1519-1523.
    [17]
    CARROLL K N, LONGLEY W, ROE J. The determination of glycogen in liver and muscle by use of anthrone reagent[J]. J Biol Chem, 1956, 220(2): 583-593. doi: 10.1016/S0021-9258(18)65284-6
    [18]
    MORRIS D L. Quantitative determination of carbohydrates with dreywood's anthrone reagent.[J]. Science, 1948, 107(2775): 254. doi: 10.1126/science.107.2775.254
    [19]
    WANG W, YANG J, LI Q, et al. Development of calibration models for rapid determination of chemical composition of Pacific oyster (Crassostrea gigas) by near infrared reflectance spectroscopy[J]. J Shellfish Res, 2015, 34(2): 303-309. doi: 10.2983/035.034.0212
    [20]
    HALDAR D, SEN D, GAYEN K. Development of spectrophotometric method for the analysis of multi-component carbohydrate mixture of different moieties[J]. Appl Biochem Biotechnol, 2016, 181(4): 1-19.
    [21]
    李艳艳, 郑萍. 蒽酮-硫酸比色法测定松花粉中粗多糖的含量[J]. 云南师范大学学报 (自然科学版), 2017, 37(4): 58-63.
    [22]
    吴怡迪. 福建牡蛎铜和锌富集能力的遗传参数评估及其与糖原含量关系初探[D]. 厦门: 厦门大学, 2017: 65.
    [23]
    朱迪, 谭丹, 侯靖宇, 等. 紫外分光光度法和蒽酮-硫酸法测定参芎葡萄糖注射液中总糖含量[J]. 贵阳医学院学报, 2015, 40(4): 349-351, 355.
    [24]
    谢心文, 门磊, 孙怡, 等. 蒽酮-硫酸法测定复方木鸡颗粒中粗多糖[J]. 中成药, 2019, 41(7): 1685-1687. doi: 10.3969/j.issn.1001-1528.2019.07.039
    [25]
    赵轶鹏, 赵新勇. 植物体可溶性糖测定方法的优化[J]. 安徽农业科学, 2018, 46(4): 184-185. doi: 10.3969/j.issn.0517-6611.2018.04.056
    [26]
    徐美蓉, 李晓蓉, 李婷. 响应面分析优化蒽酮硫酸法测定葡萄叶片中可溶性糖的含量[J]. 甘肃农业科技, 2017, 503(11): 25-29. doi: 10.3969/j.issn.1001-1463.2017.11.008
    [27]
    孙晓燕, 蔡昌利, 徐丽莉, 等. 多糖含量测定方法的比较[J]. 现代中药研究与实践, 2015, 29(3): 58-62.
    [28]
    李文砚, 韦持章, 孔方南, 等. 蒽酮法测定木奶果果实中可溶性糖含量的研究[J]. 中国园艺文摘, 2015, 31(12): 7-8, 28. doi: 10.3969/j.issn.1672-0873.2015.12.003
    [29]
    刘桂茹. 不同硫酸蒽酮比色定糖法的比较[J]. 天津农业科学, 2016, 22(3): 5-7, 22. doi: 10.3969/j.issn.1006-6500.2016.03.002
    [30]
    张妙霞, 孔祥生, 郭秀璞, 等. 蒽酮法测定可溶性糖显色条件的研究[J]. 洛阳农专学报, 1997(4): 24-28.
    [31]
    李晓旭, 李家政. 优化蒽酮比色法测定甜玉米中可溶性糖的含量[J]. 保鲜与加工, 2013, 13(4): 24-27. doi: 10.3969/j.issn.1009-6221.2013.04.006
    [32]
    任婧, 李景富, 张佳, 等. 基于蒽酮硫酸比色法建立一种快速测定果糖含量的方法[J]. 黑龙江科学, 2017, 8(10): 82-85. doi: 10.3969/j.issn.1674-8646.2017.10.038
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