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酒糟主要成分含量的近红外反射光谱快速分析
  • ISSN号:1000-1298
  • 期刊名称:《农业机械学报》
  • 时间:0
  • 分类:S123[农业科学—农业基础科学] O657.33[理学—分析化学;理学—化学]
  • 作者机构:[1]中国农业大学工学院,北京100083
  • 相关基金:国家自然科学基金资助项目(31072062)、科技部国际合作资助项目(2010DFA34540)和欧盟第七框架资助项目(FPT-265702,QSAFFE)
中文摘要:

从全国21个省份收集78个代表性酒糟样品,采用国标方法测定了其成分含量并进行了统计分析,结果显示粗纤维、粗灰分和粗蛋白3种成分质量分数分布范围分别为1.60%~37.54%、0.74%~26.85%和12.01%~38.69%,标准偏差分别为8.33%、5.21%和7.11%,样品成分含量差异较大。利用NIRS建立了其粗纤维、粗灰分和粗蛋白质量分数的定量分析模型,定标决定系数分别为0.98、0.91和0.96,定标标准误差分别为1.19%、1.58%和1.61%,验证决定系数分别为0.98、0.92和0.96,预测标准误差分别为1.20%、1.57%和1.60%,相对分析误差分别为7.38、3.75和4.98,模型预测精度较高,可以用于实际检测分析。

英文摘要:

Dried distillers' grains were rich in nutrition, which used as protein feed materials, and could give some benefit to supplement feed deficit and reduce feed cost. Totally 78 dried distillers' grains samples were collected from 21 provinces of China. Crude fiber, crude ash and crude protein contents were detected in laboratory by standard methods. The statistic analysis showed that the distribution range of crude fiber, crude ash and crude protein contents were 1.60% - 37.54%, 0.74% -26. 85% and 12.01% - 38.69% , respectively, the standard distribution value of them were 8.33% , 5.21% and 7.11% , respectively. The big differences in components content were mainly caused by the remaining rice hull during drying and separating process. Quantitative evaluation models were established to determinate crude fiber, crude ash and crude protein content of dried distillers' grains by NIRS methods. The results of NIRS analysis showed that this method could provide rapidly quantitative prediction for crude fiber, crude ash and crude protein contents in dried distillers' grains, the coefficient of determination in calibration were 0.98, 0.91 and 0.96, respectively; the standard error in calibration were 1. 19% , 1.58% and 1.61%., respectively; the coefficient of determination in validation were 0.98, 0.92 and 0.96, respectively; the standard error in validation were 1.20% , 1.57% and 1.60% , respectively, and the ratio of performance to standard deviation were 7.38, 3.75 and 4.98, respectively. The prediction values of these models are accurate.

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期刊信息
  • 《农业机械学报》
  • 中国科技核心期刊
  • 主管单位:中国科学技术协会
  • 主办单位:中国农业机械学会 中国农业机械化科学研究院
  • 主编:任露泉
  • 地址:北京德胜门外北沙滩一号6号信箱
  • 邮编:100083
  • 邮箱:njxb@caams.org.cn
  • 电话:010-64882610 64867367
  • 国际标准刊号:ISSN:1000-1298
  • 国内统一刊号:ISSN:11-1964/S
  • 邮发代号:2-363
  • 获奖情况:
  • 荣获中国科协优秀期刊二等奖,1997~2000年连续4年获中国科协择优资金,被列入中国期刊方阵,中国期刊方阵“双效”期刊
  • 国内外数据库收录:
  • 美国化学文摘(网络版),英国农业与生物科学研究中心文摘,荷兰文摘与引文数据库,美国工程索引,美国剑桥科学文摘,日本日本科学技术振兴机构数据库,中国中国科技核心期刊,中国北大核心期刊(2004版),中国北大核心期刊(2008版),中国北大核心期刊(2011版),中国北大核心期刊(2014版),中国北大核心期刊(2000版)
  • 被引量:42884