| Using a combination of spectral and textural data to measure water-holding capacity in fresh chicken breast fillets | |
| Jia, Beibei1; Wang, Wei1; Yoon, Seung-Chul2; Zhuang, Hong2; Li, Yu-Feng3 | |
| 刊名 | Applied sciences-basel
 |
| 2018-03-01 | |
| 卷号 | 8期号:3页码:11 |
| 关键词 | Chicken breast fillet Water-holding capacity (whc) Gray-level co-occurrencematrix (glcm) Texture Partial least square-discriminant analysis (pls-da) |
| ISSN号 | 2076-3417 |
| DOI | 10.3390/app8030343 |
| 通讯作者 | Wang, wei(playerwxw@cau.edu.cn) ; Li, yu-feng(liyf@ihep.ac.cn) |
| 英文摘要 | The aim here was to explore the potential of visible and near-infrared (vis/nir) hyperspectral imaging (400-1000 nm) to classify fresh chicken breast fillets into different water-holding capacity (whc) groups. initially, the extracted spectra and image textural features, as well as the mixed data of the two, were used to develop partial least square-discriminant analysis (pls-da) classification models. smoothing, a first derivative process, and principle component analysis (pca) were carried out sequentially on the mean spectra of all samples to deal with baseline offsets and identify outlier data. six samples located outside the confidence ellipses of 95% confidence level in the score plot were defined as outliers. a pls-da model based on the outlier-free spectra provided a correct classification rate (ccr) value of 78% in the prediction set. then, seven optimal wavelengths selected using a successive projections algorithm (spa) were used to develop a simplified pls-da model that obtained a slightly reduced ccr with a value of 73%. moreover, the gray-level co-occurrence matrix (glcm) was implemented on the first principle component image (with 98.13% of variance) of the hyperspectral image to extract textural features (contrast, correlation, energy, and homogeneity). the ccr of the model developed using textural variables was less optimistic with a value of 59%. compared to results of models based on spectral or textural data individually, the performance of the model based on the mixed data of optimal spectral and textural features was the best with an improved ccr of 86%. the results showed that the spectral and textural data of hyperspectral images together can be integrated in order to measure and classify the whc of fresh chicken breast fillets. |
| WOS关键词 | NEAR-INFRARED SPECTROSCOPY ; SUCCESSIVE PROJECTIONS ALGORITHM ; DISCRIMINANT-ANALYSIS ; QUALITY ATTRIBUTES ; VARIABLE SELECTION ; SALMON FILLET ; MEAT ; PREDICTION ; PORK ; CLASSIFICATION |
| 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:000428369400026 |
| 内容类型 | 期刊论文 |
| URI标识 | http://www.corc.org.cn/handle/1471x/2177553 |
| 专题 | 高能物理研究所 |
| 通讯作者 | Wang, Wei; Li, Yu-Feng |
| 作者单位 | 1.China Agr Univ, Coll Engn, Beijing 100083, Peoples R China 2.USDA ARS, Qual & Safety Assessment Res Unit, US Natl Poultry Res Ctr, 950 Coll Stn Rd, Athens, GA 30605 USA 3.Chinese Acad Sci, Inst High Energy Phys, Multidisciplinary Initiat Ctr, Beijing 100049, Peoples R China |
| 推荐引用方式 GB/T 7714 | Jia, Beibei,Wang, Wei,Yoon, Seung-Chul,et al. Using a combination of spectral and textural data to measure water-holding capacity in fresh chicken breast fillets[J]. Applied sciences-basel,2018,8(3):11. |
| APA | Jia, Beibei,Wang, Wei,Yoon, Seung-Chul,Zhuang, Hong,&Li, Yu-Feng.(2018).Using a combination of spectral and textural data to measure water-holding capacity in fresh chicken breast fillets.Applied sciences-basel,8(3),11. |
| MLA | Jia, Beibei,et al."Using a combination of spectral and textural data to measure water-holding capacity in fresh chicken breast fillets".Applied sciences-basel 8.3(2018):11. |
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