冷鲜羊肉品质的高光谱成像无损检测

杨菊梅; 贺晓光; 王松磊; 丁佳兴; 强锋; 王芹志

doi:10.13386/j.issn1002-0306.2016.22.008

冷鲜羊肉品质的高光谱成像无损检测

宁夏大学农学院

详细信息

作者简介:
杨菊梅(1991-),女,在读硕士研究生,研究方向:农产品无损检测,E-mail:1255499035@qq.com。;

贺晓光(1963-),男,教授,主要从事食品加工与食品机械方面的教学和科研工作,E-mail:13995015705@163.com。;

中图分类号: TS251.53
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出版历程
- 收稿日期: 2016-05-19

Nondestructive detection of quality of chilled mutton using hyperspectral imaging technique

School of Agriculture,Ningxia University

摘要

摘要: 利用400¹000 nm可见近红外高光谱成像系统对冷鲜羊肉蛋白质含量、嫩度、p H进行无损检测研究。采集冷鲜羊肉表面的高光谱散射图像,提取样本感兴趣区域的反射光谱曲线获得原始数据。先对原始光谱预处理并建立偏最小二乘回归（PLSR）模型,优选最佳预处理方法,后采用正自适应加权算法（CARS）和连续投影算法（SPA）提取特征波长,建立不同特征波长下各品质参数的PLSR预测模型。结果表明:利用原始光谱建立的冷鲜羊肉蛋白质、嫩度和p H的PLSR模型均优于经过光谱预处理所建PLSR模型;在不同波长下建立预测模型,OS-PLSR光谱模型对冷鲜羊肉蛋白质含量预测效果最佳,Rp=0.869,RMSEP=0.097;建立的SPA-PLSR光谱预测模型对p H预测效果理想,Rp=0.958,RMSEP=0.067;CARS-PLSR光谱预测模型对嫩度的预测能力较高,Rp=0.862,RMSEP=0.706。研究表明:利用可见近红外高光谱技术对冷鲜羊肉品质进行快速无损检测是可行的。
- 高光谱成像技术 /
- 冷鲜羊肉 /
- 品质 /
- 无损检测 /
- 偏最小二乘回归
Abstract: Visible / near infrared hyperspectral imaging system ranging from 400 nm to 1000 nm was investigated for non- destructive determination of protein content,p H value and tenderness in chilled mutton. Collected the hyperspectral scattering image of chilled mutton and extracted the reflectance spectrum at range of interest.Firstly,the partial least squares regression( PLSR) model was established by the pretreatment of original spectrum to prefer the best pretreatment method. Then,the successive projections algorithm( SPA) and competitive adaptive reweighed sampling( CARS) were used to select characteristic wavelengths,the PLSR prediction models of protein content,p H value and tenderness under the characteristic wavelengths were set up and analyzed. The results showed that using original spectrum to establish OS- PLSR models for predicting protein content,p H value and tenderness were better than the PLSR models constructed by pretreatment spectrum; the PLSR prediction model of protein content under full wavelengths has the best effect,the correlation coefficient of prediction( Rp) and the predict root mean square error( RMSEP) were 0.869 and 0.097. The result of SPA- PLSR model for predicting p H value was ideal and RP value was 0.958,RMSEP value was 0.067. The result of CARS- PLSR model for predicting tenderness has high predictive power and the RP value was 0.862,RMSEP value was 0.706.Therefore,visible / near infrared hyperspectral imaging technology is feasible for non- destructive determination of protein content,p H value and tenderness in chilled mutton.
- hyperspectral imaging technique /
- chilled mutton /
- quality /
- nondestructive detection /
- partial least squares regression

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