Comparison of portable spectral imaging (443–726 nm) and RGB imaging for predicting poultry product “use-by” status through packaging film

Q3 Chemistry Journal of Spectral Imaging Pub Date : 2021-10-21 DOI:10.1255/jsi.2021.a6
Anastasia Swanson, A. Herrero-Langreo, A. Gowen
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引用次数: 2

Abstract

The objective of this study is to compare portable visible spectral imaging (443–726 nm) and conventional RGB imaging for detecting products stored beyond the recommended “use-by” date and predicting the number of days poultry products have been stored. Packages of chicken thighs with skin on were stored at 4 °C and imaged daily in pack through plastic lidding film using spectral and RGB imaging over 10 days. K-nearest neighbour (KNN) models were built to detect poultry stored beyond its recommended “use-by” date and partial least squares regression (PLSR) models were built to predict the storage day of samples. Model overfitting in the spectral PLSR model was prevented using a geostatistical approach to estimate the number of latent variables (LV). All models were built at the object level by using mean spectra and colour values per image. The KNN model built using spectral images (acc. = 93 %, sen. = 75 %, spec. = 100 %) was more suitable than the model built using RGB images (acc. = 80 %, sen. = 42 %, spec. = 96 %) for detecting poultry stored beyond its “use-by” date. The PLSR model built using spectral images (R2 = 0.78 RMSEC = 0.92, RMSEV = 1.11, RMSEP = 1.34 day) was more suitable than the model built using RGB images (R2 = 0.60, RMSEC = 1.66, RMSEV = 1.67, RMSEP = 1.92 day) for predicting storage day of poultry products.
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便携式光谱成像(443-726 nm)与RGB成像通过包装薄膜预测家禽产品“待用”状态的比较
本研究的目的是比较便携式可见光谱成像(443-726 nm)和传统RGB成像在检测超过推荐“保质期”的产品和预测家禽产品已储存天数方面的应用。带皮的鸡腿包装在4°C下保存,每天在包装中通过塑料盖膜进行光谱和RGB成像,持续10天。建立k -最近邻(KNN)模型来检测超过推荐“使用”日期的家禽,并建立偏最小二乘回归(PLSR)模型来预测样本的储存日期。使用地质统计学方法估计潜在变量(LV)的数量,可以防止谱PLSR模型中的模型过拟合。通过每张图像的平均光谱和颜色值,在目标水平上建立所有模型。利用光谱图像(acc)建立KNN模型。= 93%, sen = 75%, spec = 100%)比使用RGB图像(acc;= 80%, sen = 42%, spec = 96%)用于检测超过“使用”日期的家禽。利用光谱图像构建的PLSR模型(R2 = 0.78, RMSEC = 0.92, RMSEV = 1.11, RMSEP = 1.34 d)比利用RGB图像构建的模型(R2 = 0.60, RMSEC = 1.66, RMSEV = 1.67, RMSEP = 1.92 d)更适合预测家禽产品存贮天数。
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来源期刊
Journal of Spectral Imaging
Journal of Spectral Imaging Chemistry-Analytical Chemistry
CiteScore
3.90
自引率
0.00%
发文量
11
审稿时长
22 weeks
期刊介绍: JSI—Journal of Spectral Imaging is the first journal to bring together current research from the diverse research areas of spectral, hyperspectral and chemical imaging as well as related areas such as remote sensing, chemometrics, data mining and data handling for spectral image data. We believe all those working in Spectral Imaging can benefit from the knowledge of others even in widely different fields. We welcome original research papers, letters, review articles, tutorial papers, short communications and technical notes.
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