相关系数
食品科学
近红外光谱
均方误差
数学
统计
化学
生物
神经科学
作者
Fangfang Qu,Dong Ren,Yong He,Ping Nie,Lei Lin,Chengyong Cai,Tao Dong
出处
期刊:Meat Science
[Elsevier]
日期:2018-12-01
卷期号:146: 59-67
被引量:27
标识
DOI:10.1016/j.meatsci.2018.07.023
摘要
In this work, the near infrared spectroscopy (NIR) technology was applied to nondestructively evaluate the freshness of pork. The total volatile basic-nitrogen (TVB-N) and pH value of pork were detected as freshness evaluation indicators. A multi-index statistical information fusion (MSIF) modeling method based on variable selection was proposed to evaluate pork freshness. In the experiment, the proposed MSIF was compared with other state-of-the-art variable selection methods. Results showed that the proposed method achieved the best generalization performance and stability. The prediction correlation coefficient (Rval) and root mean square error (RMSEP) of MSIF were: Rval = 0.8618 and RMSEP = 3.910 for TVB-N content, Rval = 0.9379 and RMSEP = 0.1046 for pH value. The research demonstrated that NIR combined with MSIF has the potential for rapid and nondestructive determination of pork freshness, and so hopefully to provide a promising tool for monitoring meat quality and enriching the extracted information from food industry.
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