Name
Title | ||
|---|---|---|
Non-Destructive Detection of Bone Fragments Embedded in Meat Using Hyperspectral Reflectance Imaging Technique. |
Abstract | ||
|---|---|---|
Meat consumption has shifted from a quantitative to a qualitative growth stage due to improved living standards and economic development. Recently, consumers have paid attention to quality and safety in their decision to purchase meat. However, foreign substances which are not normal food ingredients are unintentionally incorporated into meat. These should be eliminated as a hazard to quality or safety. It is important to find a fast, non-destructive, and accurate detection technique of foreign substance in the meat processing industry. Hyperspectral imaging technology has been regarded as a novel technology capable of providing large-scale imaging and continuous observation information on agricultural products and food. In this study, we considered the feasibility of the short-wave near infrared (SWIR) hyperspectral reflectance imaging technique to detect bone fragments embedded in chicken meat. De-boned chicken breast samples with thicknesses of 3, 6, and 9-mm and 5 bone fragments with lengths of about 20-30-mm are used for this experiment. The reflectance spectra (in the wavelength range from 987 to 1701-nm) of the 5 bone fragments embedded under the chicken breast fillet are collected. Our results suggested that these hyperspectral imaging technique is able to detect bone fragments in chicken breast, particularly with the use of a subtraction image (corresponding to image at 1153.8-nm and 1480.2-nm). Thus, the SWIR hyperspectral reflectance imaging technique can be potentially used to detect foreign substance embedded in meat. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.3390/s20144038 | SENSORS |
Keywords | DocType | Volume |
meat,foreign substances,short-wave near infrared,hyperspectral imaging | Journal | 20 |
Issue | ISSN | Citations |
14 | 1424-8220 | 0 |
PageRank | References | Authors |
0.34 | 0 | 7 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jongguk Lim | 1 | 8 | 3.59 |
| Ahyeong Lee | 2 | 0 | 0.68 |
| Jungsook Kang | 3 | 0 | 0.68 |
| Youngwook Seo | 4 | 0 | 0.68 |
| Balgeum Kim | 5 | 0 | 0.68 |
| Giyoung Kim | 6 | 11 | 4.02 |
| Seongmin Kim | 7 | 0 | 0.34 |