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	Visible and near-infrared hyperspectral imaging for cooking loss classification of fresh broiler breast fillets
	Jiang, Hongzhe1; Wang, Wei1; Zhuang, Hong2; Yoon, Seungchul2; Li, Yufeng3,4; Yang, Yi1
刊名	Applied sciences-basel
	2018-02-01
卷号	8期号:2页码:15
关键词	Cooking loss Broiler breast fillet Hyperspectral imaging Vnir Chemometrics
ISSN号	2076-3417
DOI	10.3390/app8020256
通讯作者	Wang, wei(playerwxw@cau.edu.cn) ; Li, yufeng(liyf@ihep.ac.cn)
英文摘要	Cooking loss (cl) is a critical quality attribute directly relating to meat juiciness. the potential of the hyperspectral imaging (hsi) technique was investigated for non-invasively classifying and visualizing the cl of fresh broiler breast meat. hyperspectral images of total 75 fresh broiler breast fillets were acquired by the system operating in the visible and near-infrared (vnir, 400-1000 nm) range. mean spectra were extracted from regions of interest (rois) determined by pure muscle tissue pixels. cl was firstly measured by calculating the weight loss in cooking, and then fillets were grouped into high-cl and low-cl according to the threshold of 20%. the classification methods partial least square-discriminant analysis (pls-da) and radial basis function-support vector machine (rbf-svm) were applied, respectively, to determine the optimal spectral calibration strategy. results showed that the pls-da model developed using the data, that is, first-order derivative (der1) of vnir full spectra, performed best with correct classification rates (ccrs) of 0.90 and 0.79 for the calibration and prediction sets, respectively. furthermore, to simplify the optimal pls-da model and make it practical, effective wavelengths were individually selected using uninformative variable elimination (uve) and competitive adaptive reweighted sampling (cars). through performance comparison, the cars-pls-da combination was identified as the optimal method and the pls-da model built with 18 informative wavelengths selected by cars resulted in good ccrs of 0.86 and 0.79. finally, classification maps were created by predicting cl categories of each pixel in the vnir hyperspectral images using the cars-pls-da model, and the general cl categories of fillets were readily discernible. the overall results were encouraging and showed the promising potential of the vnir hsi technique for classifying fresh broiler breast fillets into different cl categories.
WOS关键词	WATER-HOLDING CAPACITY ; PARTIAL LEAST-SQUARES ; REFLECTANCE SPECTROSCOPY ; NONDESTRUCTIVE DETERMINATION ; CHICKEN MEAT ; MULTIVARIATE CALIBRATION ; SENSORY CHARACTERISTICS ; PREDICTION ; PORK ; QUALITY
WOS研究方向	Chemistry ; Materials Science ; Physics
WOS类目	Chemistry, Multidisciplinary ; Materials Science, Multidisciplinary ; Physics, Applied
语种	英语
出版者	MDPI
WOS记录号	WOS:000427510300108
内容类型	期刊论文
URI标识	http://www.corc.org.cn/handle/1471x/2178103
专题	高能物理研究所
通讯作者	Wang, Wei; Li, Yufeng
作者单位	1.China Agr Univ, Coll Engn, Beijing 100083, Peoples R China 2.USDA ARS, US Natl Poultry Res Ctr, Qual & Safety Assessment Res Unit, 950 Coll Stn Rd, Athens, GA 30605 USA 3.Chinese Acad Sci, State Environm Protect Engn Ctr Mercury Pollut Pr, Beijing 100049, Peoples R China 4.Chinese Acad Sci, Inst High Energy Phys, CAS Key Lab Biol Effects Nanomat & Nanosafety, Beijing 100049, Peoples R China
推荐引用方式 GB/T 7714	Jiang, Hongzhe,Wang, Wei,Zhuang, Hong,et al. Visible and near-infrared hyperspectral imaging for cooking loss classification of fresh broiler breast fillets[J]. Applied sciences-basel,2018,8(2):15.
APA	Jiang, Hongzhe,Wang, Wei,Zhuang, Hong,Yoon, Seungchul,Li, Yufeng,&Yang, Yi.(2018).Visible and near-infrared hyperspectral imaging for cooking loss classification of fresh broiler breast fillets.Applied sciences-basel,8(2),15.
MLA	Jiang, Hongzhe,et al."Visible and near-infrared hyperspectral imaging for cooking loss classification of fresh broiler breast fillets".Applied sciences-basel 8.2(2018):15.

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