小鼠体成分无损分析方法的开发及其在功能性食品评价中的应用
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- 英文论文题名：Development of a noninvasive analysis method of body composition in mice and its application in evaluation of functional foods
- 论文作者：李晨阳 ; 朱蓓薇 ; 谭明乾
- 英文论文作者：Li Chenyang ; Zhu Beiwei ; Tan Mingqian ; School of food science and technology ; Dalian Polytechnic University ; National Engineering Research Center of Seafood
- 年：2016
- 作者机构：大连工业大学食品学院国家海洋食品工程技术研究中心;
- 论文关键词：体成分 ; 低场核磁共振 ; 无损 ; 化学方法 ; 预测 ; 偏最小二乘回归法 ; 主成分回归法
- 英文论文关键词：body composition ; LF-NMR ; noninvasive ; chemical method ; prediction ; PLSR ; PCR
- 会议召开时间：2016-11-09
- 会议录名称：中国食品科学技术学会第十三届年会论文摘要集
- 英文会议录名称：Abstracts of the 13th Annual Meeting of CIFST
- 语种：中文
- 分类号：TS218
- 学会代码：ZGSP
- 会议名称：中国食品科学技术学会第十三届年会
- 会议地点：中国北京
- 主办单位：中国食品科学技术学会
- 学会名称：中国食品科学技术学会
- 页数：2
- 文件大小：107k
- 原文格式：O
- 会议级别：全国
摘要
本研究利用低场核磁共振(NMR)技术开发一种小鼠体成分(体液、脂肪、瘦肉)含量无损分析的新方法,并应用该方法检测岩藻多糖对小鼠体成分变化的影响。以传统的全身化学分析方法,包括干燥法,索氏提取法,凯氏定氮法,灼烧法测定的样品体成分含量作为参考值,利用低场核磁共振技术结合偏最小二乘回归法(PLSR)和主成分回归法(PCR)分别建立了样品体液、脂肪、瘦肉含量的预测模型。通过该模型每周对喂食不同组分食品的小鼠进行体成分含量检测。结果显示,PLSR和PCR预测模型:校正集的相关系数(R_(cal)~2)和交互验证集的相关系数(R_(val)~2)均大于0.98,且标准误差值较低,说明该模型的稳定性较好,通过该模型可以准确预测小鼠体液,脂肪和瘦肉含量,并发现岩藻多糖对小鼠体内脂肪含量有显著影响。
The aim of this study was to develop a new method for prediction of body composition(body fluid,fat,lean mass)content in mice,based on the technology of low field nuclear magnetic resonance(NMR) to test the influence of fucoidin for body composition in mice.The reference data results determined by the traditional whole-body chemical analysis methods which include drying method,Soxhlet extractor method,Kjeldahl method and burning method,and the calibration and validation models of body fluid,fat and lean mass were developed by the NMR combined with the partial least square regression(PLSR)and principal component regression(PCR),respectively.Body composition of mice being fed different food components has been detected by this model.The results indicated that PCR and PLSR prediction model,calibration model and validation model correlation coefficient R2 were greater than 0.98 with a lower standard error value.Moreover,fucoidin have a significant effect on the fat content of mice.
The aim of this study was to develop a new method for prediction of body composition(body fluid,fat,lean mass)content in mice,based on the technology of low field nuclear magnetic resonance(NMR) to test the influence of fucoidin for body composition in mice.The reference data results determined by the traditional whole-body chemical analysis methods which include drying method,Soxhlet extractor method,Kjeldahl method and burning method,and the calibration and validation models of body fluid,fat and lean mass were developed by the NMR combined with the partial least square regression(PLSR)and principal component regression(PCR),respectively.Body composition of mice being fed different food components has been detected by this model.The results indicated that PCR and PLSR prediction model,calibration model and validation model correlation coefficient R2 were greater than 0.98 with a lower standard error value.Moreover,fucoidin have a significant effect on the fat content of mice.
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