journal article·2023-04-24Open access

Estimating Moisture Content of Sausages with Different Types of Casings via Hyperspectral Imaging in Tandem with Multivariate

Chao-Hui Feng, Hirofumi Arai

Applied Sciences· Volume 13· Issue 9

Abstract

The moisture levels in sausages that were stored for 16 days and added with different concentrations of orange extracts to a modification solution were assessed using response surface methodology (RSM). Among the 32 treatment matrixes, treatment 10 presented a higher moisture content than that of treatment 19. Spectral pre-treatments were employed to enhance the model’s robustness. The raw and pre-processed spectral data, as well as moisture content, were fitted to a regression model. The RSM outcomes showed that the interactive effects of [soy lecithin concentration] × [soy oil concentration] and [soy oil concentration] × [orange extract addition] on moisture were significant (p < 0.05), resulting in an R2 value of 78.28% derived from a second-order polynomial model. Hesperidin was identified as the primary component of the orange extracts using high-performance liquid chromatography (HPLC). The PLSR model developed from reflectance data after normalization and 1st derivation pre-treatment showed a higher coefficient of determination in the calibration set (0.7157) than the untreated data (0.2602). Furthermore, the selection of nine key wavelengths (405, 445, 425, 455, 585, 630, 1000, 1075, and 1095 nm) could render the model simpler and allow for easy industrial applications.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Spectroscopy and Chemometric Analyses · Meat and Animal Product Quality · Phytochemicals and Antioxidant Activities

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

School of Regional Innovation and Social Design Engineering, Faculty of Engineering, Kitami Institute of Technology, 165 Koen-cho, Kitami 090-8507, Hokkaido, Japan

RIKEN Centre for Advanced Photonics, RIKEN, 519-1399 Aramaki-Aoba, Aoba-ku, Sendai 980-0845, Miyagi, Japan

Funding

Leading Initiative for Excellent Young Researchers (LEADER) from the Government of Japan Ministry of Education, Culture, Sports, Science and Technology (MEXT) · Japan Society for the Promotion of Science Grant-in-Aid for Early Career Scientists · Sasakawa Scientific Research Grant from The Japan Science Society · Mishima Kaiun Memorial Foundation · Northern Advancement Center for Science & Technology of Hokkaido Japan · President’s Discretionary Grants · Kitami Institute of Technology

References (46)

Show source-provided references
1. Simultaneous assessment of various quality attributes and shelf life of packaged bratwurst using hyperspectral imaging10.1016/j.meatsci.2018.06.024 ↗
2. Hyperspectral imaging in tandem with R statistics and image processing for detection and visualisation of pH in Japanese big sausages under different storage conditions10.1111/1750-3841.14024 ↗
3. Real-time prediction of pre-cooked Japanese sausages color with different storage days using hyperspectral imaging10.1002/jsfa.8746 ↗
4. A novel method for evaluating flavanols in grape seeds by near infrared hyperspectral imaging10.1016/j.talanta.2014.01.044 ↗
5. CIELAB—Spectral image matching: An app for merging colorimetric and spectral images for grapes and derivatives10.1016/j.foodcont.2021.108038 ↗
6. Rodríguez-Pulido, F.J., Mora-Garrido, A.B., González-Miret, M.L., and Heredia, F.J. (2022). Research progress in imaging technology for assessing quality in wine grapes and seeds. Foods, 11.10.3390/foods11030254 ↗
7. A decision fusion method based on hyperspectral imaging and electronic nose techniques for moisture content prediction in frozen-thawed pork10.1016/j.lwt.2022.113778 ↗
8. Detection of frozen pork freshness by fluorescence hyperspectral image10.1016/j.jfoodeng.2021.110840 ↗
9. Nondestructive detection and visualization of protein oxidation degree of frozen-thawed pork using fluorescence hyperspectral imaging10.1016/j.meatsci.2022.108975 ↗
10. Classification and characterization of blueberry mechanical damage with time evolution using reflectance, transmittance and interactance imaging spectroscopy10.1016/j.compag.2016.01.015 ↗
11. Prediction of mechanical properties of blueberry using hyperspectral interactance imaging10.1016/j.postharvbio.2015.11.021 ↗
12. Fusion of spectra and texture data of hyperspectral imaging for prediction of myoglobin content in nitrite-cured mutton10.1016/j.foodcont.2022.109332 ↗
13. Rapid evaluation of texture parameters of Tan mutton using hyperspectral imaging with optimization algorithms10.1016/j.foodcont.2022.108815 ↗
14. Rapid identification of lamb freshness grades using visible and near-infrared spectroscopy (Vis-NIR)10.1016/j.jfca.2022.104590 ↗
15. A decision support tool for shelf-life determination of strawberries using hyperspectral imaging technology10.1016/j.biosystemseng.2022.06.013 ↗
16. León-Ecay, S., López-Maestresalas, A., Murillo-Arbizu, M.T., Beriain, M.J., Mendizabal, J.A., Arazuri, S., Carmen, J., Bass, P.D., Colle, M.J., and García, D. (2022). Classification of beef longissimus thoracis muscle tenderness using hyperspectral imaging and chemometrics. Foods, 11.10.3390/foods11193105 ↗
17. Combination of spectral and image information from hyperspectral imaging for the prediction and visualization of the total volatile basic nitrogen content in cooked beef10.1007/s11694-021-00983-x ↗
18. Visualized detection of quality change of cooked beef with condiments by hyperspectral imaging technique10.1007/s10068-022-01115-x ↗
19. Ahmed, M., Reed, D.D., Young, J.M., Eshkabilov, S., Berg, E.P., and Sun, X. (2021). Beef quality grade classification based on intramuscular fat content using hyperspectral imaging technology. Appl. Sci., 11.10.3390/app11104588 ↗
20. Automatic marbling prediction of sliced dry-cured ham using image segmentation, texture analysis and regression10.1016/j.eswa.2022.117765 ↗
21. Feng, C.H., Makino, Y., and García-Martín, J.F. (2020). Hyperspectral imaging coupled with multivariate analysis and image processing for detection and visualisation of colour in cooked sausages stuffed with different modified casings. Foods, 9.10.3390/foods9081089 ↗
22. Estimation of adenosine triphosphate content in ready-to-eat sausages with different storage days, using hyperspectral imaging coupled with R statistics10.1016/j.foodchem.2018.05.029 ↗
23. Hyperspectral imaging for rapid evaluation and visualization of quality deterioration index of vacuum packaged dry-cured sausages10.1016/j.snb.2017.07.006 ↗
24. Potential use of multispectral imaging technology to identify moisture content and water-holding capacity in cooked pork sausages10.1002/jsfa.8659 ↗
25. Feng, C.H., Arai, H., and Rodríguez-Pulido, F.J. (2022). Evaluation of pH in sausages stuffed in a modified casing with orange extracts by hyperspectral imaging coupled with response surface methodology. Foods, 11.10.3390/foods11182797 ↗
26. Evaluation of innovative immersion vacuum cooling with different pressure reduction rates and agitation for cooked sausages stuffed in natural or artificial casing10.1016/j.lwt.2014.04.035 ↗
27. Evaluation of natural hog casings modified by surfactant solutions combined with lactic acid by response surface methodology10.1016/j.lwt.2014.03.012 ↗
28. Incorporation of betel leaf extract provides oxidative stability and improves phytochemical, textural, sensory and antimicrobial activities of buffalo meat sausages10.1016/j.meatsci.2023.109157 ↗
29. Relationship between physicochemical properties and microbial structural distribution of Chinese-style and Salami fermented sausages10.1016/j.fbio.2023.102583 ↗
30. Feng, C.H. (2022). Quality evaluation and mathematical modelling approach to estimate the growth parameters of total viable count in sausages with different casings. Foods, 11.10.3390/foods11050634 ↗
31. Innovatively identifying naringin and hesperidin by using terahertz spectroscopy and evaluating flavonoids extracts from waste orange peels by coupling with multivariate analysis10.1016/j.foodcont.2022.108897 ↗
32. Feng, C.-H., and García Martín, J.F. (2021). The Book of Flavonoids, Nova Science Publishers, Inc.. [1st ed.]. Chapter 1;.10.52305/WGCH6543 ↗
33. Bellavite, P., and Donzelli, A. (2020). Hesperidin and SARS-CoV-2: New light on the healthy function of citrus fruits. Antioxidants, 9.10.20944/preprints202006.0321.v1 ↗
34. Quantification of main phenolic compounds in sweet and bitter orange peel using CE-MS/MS10.1016/j.foodchem.2009.03.003 ↗
35. Molecular immune pathogenesis and diagnosis of COVID-1910.1016/j.jpha.2020.03.001 ↗
36. Feng, C.H., and Arai, H. (2022). Evaluation of hesperidin on sausages stuffed in a new modified casing during long-term storage—A preliminary study. Sustainability, 14.10.3390/su14159071 ↗
37. Influence of particle size on physical, mechanical, thermal, and morphological properties of tamarind- fenugreek mucilage biodegradable films10.1007/s00289-022-04214-1 ↗
38. Evaluation of different solvents on flavonoids extraction efficiency from sweet oranges and ripe and immature Seville oranges10.1111/ijfs.14576 ↗
39. Flavonoid composition of fruit tissues of citrus species10.1271/bbb.70.178 ↗
40. Effects of radix puerariae extracts on physicochemical and sensory quality of precooked pork sausage during cold storage10.1016/j.lwt.2011.11.007 ↗
41. Nutraceutical potential of navel orange peel in diabetes management: The chemical profile, antioxidant, α-glucosidase inhibitory and antiglycation effects of its flavonoids10.1016/j.fbio.2022.101943 ↗
42. Feng, C.H. (2022). Optimizing procedures of ultrasound-assisted extraction of waste orange peels by response surface methodology. Molecules, 27.10.3390/molecules27072268 ↗
43. Lamb muscle discrimination using hyperspectral imaging: Comparison of various machine learning algorithms10.1016/j.jfoodeng.2015.11.024 ↗
44. Selected engineering properties and drying behavior of tendu (diospyros melanoxylon roxb.) fruit10.12944/CRNFSJ.8.2.27 ↗
45. Prediction of pH of fresh chicken breast fillets by VNIR hyperspectral imaging10.1016/j.jfoodeng.2017.03.023 ↗
46. Related versions of the multiplicative scatter correction method for preprocessing spectroscopic data10.1016/0169-7439(95)80098-T ↗