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基于近红外光谱技术评估大豆皮纤维含量的研究

  • 向娜娜 ,
  • 赵江涛 ,
  • 陈丽 ,
  • 夏超笃 ,
  • 王晓琼 ,
  • 陈林 ,
  • 纪昌正
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  • 温氏食品集团股份有限公司, 云浮 527400
向娜娜(1989-),女,安徽淮南人,硕士,从事动物营养与饲料科学研究。E-mail:934569859@qq.com

收稿日期: 2020-07-27

  网络出版日期: 2021-03-18

基金资助

 

Research on Evaluation of Fiber Content in Soybean Hulls Based on Near-Infrared Spectroscopy Technique

  • XIANG Nana ,
  • ZHAO Jiangtao ,
  • CHEN Li ,
  • XIA Chaodu ,
  • WANG Xiaoqiong ,
  • CHEN Lin ,
  • JI Changzheng
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  • Wens Foodstuff Group Co., Ltd., Yunfu 527400, China

Received date: 2020-07-27

  Online published: 2021-03-18

Supported by

 

摘要

本试验主要研究利用近红外光谱技术快速检测大豆皮中纤维相关指标的方法。收集的106份大豆皮样品,分别采用国标GB/T 5009.3—2016、GB/T 6434—2006、GB/T 20806—2006的方法检测水分、粗纤维(CF)、中性洗涤纤维(NDF)的含量及采用农业行业标准NY/T 1459—2007的方法检测酸性洗涤纤维(ADF)的含量,同时结合获得的近红外漫反射光谱进行定量模型的建立和验证。结果表明:大豆皮纤维相关指标的模型决定系数(R2)均大于0.9,模型的均方根误差均小于0.6,相对分析误差(RPD)均大于3.0,其中水分及NDF含量模型的RPD大于4.0。综上表明,本试验建立的近红外预测模型具有较好的精确度和准确性,能够较好地监控大豆皮纤维相关指标的质量,从而保证原料的稳定性和安全性。

本文引用格式

向娜娜 , 赵江涛 , 陈丽 , 夏超笃 , 王晓琼 , 陈林 , 纪昌正 . 基于近红外光谱技术评估大豆皮纤维含量的研究[J]. 动物营养学报, 2021 , 33(3) : 1792 -1800 . DOI: 10.3969/j.issn.1006-267x.2021.03.060

Abstract

The objective of this experiment was to research a method of fiber related indexes in soybean hulls by near-infrared spectroscopy technique. The 106 samples of soybean hulls were collected. The contents of moisture, crude fiber (CF), neutral detergent fiber (NDF) and acid detergent fiber (ADF) were respectively detected by the GB/T 5009.3—2016, GB/T 6434—2006, GB/T 20806—2006 and the agricultural industry standard NY/T 1459—2007. Meanwhile, the near-infrared quantitative model were established and validated combining the near-infrared diffuse reflection spectrum and the chemical values. The results showed that the determination coefficient (R2) of near-infrared model in soybean hull’s fiber related indexes were greater than 0.9, the root mean square error of the model were less than 0.6, the residual predictive deviation (RPD) were greater than 3.0, the RPD of the model in moisture and NDF contents was greater than 4.0. It is indicated that the near-infrared prediction models established with precision and accuracy can better monitor the quality of fiber related indexes in soybean hulls, so as to ensure the stability and safety of raw materials.

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