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Feng CH, Arai H, Rodríguez-Pulido FJ. Evaluating Moisture Content in Immersion Vacuum-Cooled Sausages with Citrus Peel Extracts Using Hyperspectral Imaging. Life (Basel) 2024; 14:647. [PMID: 38792667 PMCID: PMC11122534 DOI: 10.3390/life14050647] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2024] [Revised: 05/10/2024] [Accepted: 05/15/2024] [Indexed: 05/26/2024] Open
Abstract
The moisture content of immersion vacuum-cooled sausages with modified casings containing citrus fruit extracts under different storage conditions was studied using hyperspectral imaging (HSI) associated with chemometrics. Different pre-processing combinations were applied to improve the robustness of the model. The partial least squares regression model, employing the full reflectance spectrum with pre-treatment of the standard normal variate, showed calibration coefficients of determination (Rc2) of 0.6160 and a root mean square error of calibration (RMSEC) of 2.8130%. For the first time, prediction maps developed via HSI visualized the distribution of moisture content in the immersion vacuum-cooled sausages with unique modified casings in response to fluctuating storage conditions. The prediction maps showed exact parts with high water content, which will help us to monitor and prevent mold growth. The combination of HSI with multivariate analysis not only quantifies changes in moisture content but also visually represents them in response to various casing treatments under different storage conditions, illustrating the significant potential for real-time inspection and early mold detection in sausages within the processed meat industry.
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Affiliation(s)
- Chao-Hui Feng
- School of Regional Innovation and Social Design Engineering, Faculty of Engineering, Kitami Institute of Technology, 165 Koen-cho, Kitami 090-8507, Japan;
- RIKEN Centre for Advanced Photonics, RIKEN, 519-1399 Aramaki-Aoba, Aoba-ku, Sendai 980-0845, Japan
| | - Hirofumi Arai
- School of Regional Innovation and Social Design Engineering, Faculty of Engineering, Kitami Institute of Technology, 165 Koen-cho, Kitami 090-8507, Japan;
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Feng CH, Arai H, Rodríguez-Pulido FJ. Assessment of adenosine triphosphate content in sausages stuffed in different modified casing treatments added with orange extracts, utilising hyperspectral imaging combined with multivariate analysis. Front Nutr 2024; 11:1370339. [PMID: 38501071 PMCID: PMC10945020 DOI: 10.3389/fnut.2024.1370339] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2024] [Accepted: 02/21/2024] [Indexed: 03/20/2024] Open
Abstract
Introduction An investigation was conducted using a hyperspectral imaging (HSI) system to non-invasively estimate adenosine triphosphate (ATP) content in vacuum packaged sausages in different modified casing treatments added with orange extracts after a year of storage at 4°C. Methods Various pre-processing combinations were applied to the spectra to enhance the performance of partial least squares regression (PLSR). Results and discussion PLSR models, utilising the full absorbance spectrum with pre-treatment of standard normal variate combined with 1st derivative,exhibited prediction coefficients of determination (Rp2) reaching up to 0.6629. A distribution map developed through MATLAB was employed to display the location and concentration of ATP content in these unique sausages for the first time. The integration of HSI and multivariate analysis not only quantifies but also visually represents the changes in ATP content response to the different casing treatments, demonstrating the significant potential for real-time inspection in the processed meat industry.
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Affiliation(s)
- Chao-Hui Feng
- School of Regional Innovation and Social Design Engineering, Faculty of Engineering, Kitami Institute of Technology, Kitami, Hokkaido, Japan
- RIKEN Centre for Advanced Photonics, RIKEN, Sendai, Miyagi, Japan
| | - Hirofumi Arai
- School of Regional Innovation and Social Design Engineering, Faculty of Engineering, Kitami Institute of Technology, Kitami, Hokkaido, Japan
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Hyperspectral Imaging Combined with Chemometrics Analysis for Monitoring the Textural Properties of Modified Casing Sausages with Differentiated Additions of Orange Extracts. Foods 2023; 12:foods12051069. [PMID: 36900582 PMCID: PMC10000443 DOI: 10.3390/foods12051069] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Revised: 02/22/2023] [Accepted: 02/28/2023] [Indexed: 03/06/2023] Open
Abstract
The textural properties (hardness, springiness, gumminess, and adhesion) of 16-day stored sausages with different additions of orange extracts to the modified casing solution were estimated by response surface methodology (RSM) and a hyperspectral imaging system in the spectral range of 390-1100 nm. To improve the model performance, normalization, 1st derivative, 2nd derivative, standard normal variate (SNV), and multiplicative scatter correction (MSC) were applied for spectral pre-treatments. The raw, pretreated spectral data and textural attributes were fit to the partial least squares regression model. The RSM results show that the highest R2 value achieved at adhesion (77.57%) derived from a second-order polynomial model, and the interactive effects of soy lecithin and orange extracts on adhesion were significant (p < 0.05). The adhesion of the PLSR model developed from reflectance after SNV pretreatment possessed a higher calibration coefficient of determination (0.8744) than raw data (0.8591). The selected ten important wavelengths for gumminess and adhesion can simplify the model and can be used for convenient industrial applications.
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Evaluation of pH in Sausages Stuffed in a Modified Casing with Orange Extracts by Hyperspectral Imaging Coupled with Response Surface Methodology. Foods 2022; 11:foods11182797. [PMID: 36140925 PMCID: PMC9497902 DOI: 10.3390/foods11182797] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Revised: 09/04/2022] [Accepted: 09/08/2022] [Indexed: 11/16/2022] Open
Abstract
The pH values of sausages stuffed in natural hog casings with different modifications (soy lecithin, soy oil, orange extracts (OE) from waste orange peels, lactic acid in slush salt, and treatment time) after 16-day 4 °C storage were evaluated for the first time by hyperspectral imaging (350−1100 nm) coupled with response surface methodology (RSM). A partial least squares regression (PLSR) model was developed to relate the spectra to the pH of sausages. Spectral pretreatment, including first derivative, second derivative, multiplicative scatter correction (MSC), standard normal variate (SNV), normalization, and normalization, with different combinations was employed to improve model performance. RSM showed that only soy lecithin and OE interactively affected the pH of sausages (p < 0.05). The pH value decreased when the casing was treated with a higher concentration of soy lecithin with 0.26% OE. As the first and second derivatives are commonly used to eliminate the baseline shift, the PLSR model derived from absorbance pretreated by the first derivative in the full wavelengths showed a calibration coefficient of determination (R2) of 0.73 with a root mean square error of calibration of 0.4283. Twelve feature wavelengths were selected with a comparable R2 value compared with the full wavelengths. The prediction map enables the visualization of the pH evolution of sausages stuffed in the modified casings added with OE.
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Wang S, Das AK, Pang J, Liang P. Real-time monitoring the color changes of large yellow croaker (Larimichthys crocea) fillets based on hyperspectral imaging empowered with artificial intelligence. Food Chem 2022; 382:132343. [PMID: 35152031 DOI: 10.1016/j.foodchem.2022.132343] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2021] [Revised: 01/30/2022] [Accepted: 02/01/2022] [Indexed: 11/29/2022]
Abstract
Vis-NIR hyperspectral imaging (HSI) system combined with artificial neural networks was investigated for the first time to monitor color changes of large yellow croaker (Larimichthys crocea) fillets during low-temperature storage. Feed-forward neural networks (FNN) empowered with the leaky rectified linear unit (Leaky-Relu) have been developed as a non-linear quantitative analysis model. It presented accurate predictive power for color changes based on optimal spectra (with R2P of 0.908, 0.915, and 0.977; and RMSEP of 1.062, 3.315, and 0.082 for L*, a*, and b*, respectively). In final, the simplified FNN-Leaky-Relu model (S-FNN-L) was utilized to visualize the distribution maps of color parameters in the fillets. The results demonstrated the feasibility of HSI could replace the traditional colorimeter to determine the spatial distribution in the color measurement of fish fillets with a rapid and non-invasive technique.
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Affiliation(s)
- Shengnan Wang
- College of Food Science, Fujian Agriculture and Forestry University, Fuzhou 350002, PR China
| | - Avik Kumar Das
- Department of Civil and Environmental Engineering, Hong Kong University of Science and Technology, Hong Kong Special Administrative Region
| | - Jie Pang
- College of Food Science, Fujian Agriculture and Forestry University, Fuzhou 350002, PR China
| | - Peng Liang
- College of Food Science, Fujian Agriculture and Forestry University, Fuzhou 350002, PR China.
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Optimizing Procedures of Ultrasound-Assisted Extraction of Waste Orange Peels by Response Surface Methodology. Molecules 2022; 27:molecules27072268. [PMID: 35408666 PMCID: PMC9000381 DOI: 10.3390/molecules27072268] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2022] [Revised: 03/20/2022] [Accepted: 03/30/2022] [Indexed: 02/06/2023] Open
Abstract
The simultaneous effects of three continuous factors: solvent concentration (50−100%), treated times (25−85 min), treated temperatures (25−55 °C), and two categorical factors: type of solvents (methanol or ethanol) and ultrasonic frequency (28 kHz or 40 kHz) on ultrasonic-assisted extraction yield from waste orange peels were evaluated and optimized by response surface methodology. Fourier Transform Infrared (FTIR) spectroscopy with a wavelength of 500 cm−1 to 4000 cm−1 was employed to rapidly identify the orange extracts. The significant polynomial regression models on crude extraction, sediments after evaporation, and precipitation yield were established (p < 0.05). Results revealed that solvent concentration affected crude extraction and precipitation yield linearly (p < 0.01). The optimal and practical ultrasound-assisted extraction conditions for increasing the precipitation yield were using 61.42% methanol with 85 min at 55 °C under 40 kHz ultrasonic frequency. The spectra of extracts showed a similar fingerprint of hesperidin.
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Developing a computer vision system for real-time color measurement – A case study with color characterization of roasted rice. J FOOD ENG 2022. [DOI: 10.1016/j.jfoodeng.2021.110821] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
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8
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Feng CH, Otani C, Ogawa Y. Innovatively identifying naringin and hesperidin by using terahertz spectroscopy and evaluating flavonoids extracts from waste orange peels by coupling with multivariate analysis. Food Control 2022. [DOI: 10.1016/j.foodcont.2022.108897] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
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9
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Özdoğan G, Lin X, Sun DW. Rapid and noninvasive sensory analyses of food products by hyperspectral imaging: Recent application developments. Trends Food Sci Technol 2021. [DOI: 10.1016/j.tifs.2021.02.044] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/14/2023]
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10
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Hyperspectral Imaging Coupled with Multivariate Analysis and Image Processing for Detection and Visualisation of Colour in Cooked Sausages Stuffed in Different Modified Casings. Foods 2020; 9:foods9081089. [PMID: 32785172 PMCID: PMC7466231 DOI: 10.3390/foods9081089] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2020] [Revised: 08/04/2020] [Accepted: 08/07/2020] [Indexed: 11/16/2022] Open
Abstract
A hyperspectral imaging system was for the first time exploited to estimate the core colour of sausages stuffed in natural hog casings or in two hog casings treated with solutions containing surfactants and lactic acid in slush salt. Yellowness of sausages stuffed in natural hog casings (control group, 20.26 ± 4.81) was significantly higher than that of sausages stuffed in casings modified by submersion for 90 min in a solution containing 1:30 (w/w) soy lecithin:distilled water, 2.5% wt. soy oil, and 21 mL lactic acid per kg NaCl (17.66 ± 2.89) (p < 0.05). When predicting the lightness and redness of the sausage core, a partial least squares regression model developed from spectra pre-treated with a second derivative showed calibration coefficients of determination (Rc2) of 0.73 and 0.76, respectively. Ten, ten, and seven wavelengths were selected as the important optimal wavelengths for lightness, redness, and yellowness, respectively. Those wavelengths provide meaningful information for developing a simple, cost-effective multispectral system to rapidly differentiate sausages based on their core colour. According to the canonical discriminant analysis, lightness possessed the highest discriminant power with which to differentiate sausages stuffed in different casings.
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11
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Feng CH, Otani C. Terahertz spectroscopy technology as an innovative technique for food: Current state-of-the-Art research advances. Crit Rev Food Sci Nutr 2020; 61:2523-2543. [PMID: 32584169 DOI: 10.1080/10408398.2020.1779649] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
Abstract
With the dramatic development of source and detector components, terahertz (THz) spectroscopy technology has recently shown a renaissance in various fields such as medical, material, biosensing and pharmaceutical industry. As a rapid and noninvasive technology, it has been extensively exploited to evaluate food quality and ensure food safety. In this review, the principles and processes of THz spectroscopy are first discussed. The current state-of-the-art applications of THz and imaging technologies focused on foodstuffs are then discussed. The advantages and challenges are also covered. This review offers detailed information for recent efforts dedicated to THz for monitoring the quality and safety of various food commodities and the feasibility of its widespread application. THz technology, as an emerging and unique method, is potentially applied for detecting food processing and maintaining quality and safety.
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Affiliation(s)
- Chao-Hui Feng
- RIKEN Centre for Advanced Photonics, RIKEN, Sendai, Japan
| | - Chiko Otani
- RIKEN Centre for Advanced Photonics, RIKEN, Sendai, Japan.,Department of Physics, Tohoku University, Sendai, Miyagi, Japan
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Weng S, Yu S, Guo B, Tang P, Liang D. Non-Destructive Detection of Strawberry Quality Using Multi-Features of Hyperspectral Imaging and Multivariate Methods. SENSORS (BASEL, SWITZERLAND) 2020; 20:E3074. [PMID: 32485900 PMCID: PMC7308843 DOI: 10.3390/s20113074] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/11/2020] [Revised: 05/26/2020] [Accepted: 05/26/2020] [Indexed: 02/07/2023]
Abstract
Soluble solid content (SSC), pH, and vitamin C (VC) are considered as key parameters for strawberry quality. Spectral, color, and textural features from hyperspectral reflectance imaging of 400-1000 nm was to develop the non-destructive detection approaches for SSC, pH, and VC of strawberries by integrating various multivariate methods as partial least-squares regression (PLSR), support vector regression, and locally weighted regression (LWR). SSC, pH, and VC of 120 strawberries were statistically analyzed to facilitate the partitioning of data sets, which helped optimize the model. PLSR, with spectral and color features, obtained the optimal prediction of SSC with determination coefficient of prediction (Rp2) of 0.9370 and the root mean square error of prediction (RMSEP) of 0.1145. Through spectral features, the best prediction for pH was obtained by LWR with Rp2 = 0.8493 and RMSEP = 0.0501. Combination of spectral and textural features with PLSR provided the best results of VC with Rp2 = 0.8769 and RMSEP = 0.0279. Competitive adaptive reweighted sampling and uninformative variable elimination (UVE) were used to select important variables from the above features. Based on the important variables, the accuracy of SSC, pH, and VC prediction both gain the promotion. Finally, the distribution maps of SSC, pH, and VC over time were generated, and the change trend of three quality parameters was observed. Thus, the proposed method can nondestructively and accurately determine SSC, pH, and VC of strawberries and is expected to design and construct the simple sensors for the above quality parameters of strawberries.
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Feng CH, Makino Y. Colour analysis in sausages stuffed in modified casings with different storage days using hyperspectral imaging – A feasibility study. Food Control 2020. [DOI: 10.1016/j.foodcont.2019.107047] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
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14
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Falkovskaya A, Gowen A. Literature review: spectral imaging applied to poultry products. Poult Sci 2020; 99:3709-3722. [PMID: 32616267 PMCID: PMC7597839 DOI: 10.1016/j.psj.2020.04.013] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2020] [Accepted: 04/03/2020] [Indexed: 12/30/2022] Open
Abstract
Consumption of poultry products is increasing worldwide, leading to an increased demand for safe, fresh, high-quality products. To ensure consumer safety and meet quality standards, poultry products must be routinely checked for fecal matter, food fraud, microbiological contamination, physical defects, and product quality. However, traditional screening methods are insufficient in providing real-time, nondestructive, chemical and spatial information about poultry products. Novel techniques, such as hyperspectral imaging (HSI), are being developed to acquire real-time chemical and spatial information about products without destruction of samples to ensure safety of products and prevent economic losses. This literature review provides a comprehensive overview of HSI applications to poultry products. The studies used for this review were found using the Google Scholar database by searching the following terms and their synonyms: “poultry” and “hyperspectral imaging”. A total of 67 studies were found to meet the criteria. After all relevant literature was compiled, studies were grouped into categories based on the specific material or characteristic of interest to be detected, identified, predicted, or quantified by HSI. Studies were found for each of the following categories: food fraud, fecal matter detection, microbiological contamination, physical defects, and product quality. Key findings and technological advancements were briefly summarized and presented for each category. Since the first application to poultry products 20 yr ago, HSI has been shown to be a successful alternative to traditional screening methods.
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Affiliation(s)
- Anastasia Falkovskaya
- UCD School of Biosystems and Food Engineering, University College Dublin, Belfield, Dublin 4, Ireland.
| | - Aoife Gowen
- UCD School of Biosystems and Food Engineering, University College Dublin, Belfield, Dublin 4, Ireland
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Leng Y, Sun Y, Wang X, Hou J, Zhao X, Zhang Y. Electrical impedance estimation for pork tissues during chilled storage. Meat Sci 2020; 161:108014. [DOI: 10.1016/j.meatsci.2019.108014] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2019] [Revised: 09/24/2019] [Accepted: 11/18/2019] [Indexed: 01/30/2023]
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16
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Weng S, Yu S, Dong R, Pan F, Liang D. Nondestructive detection of storage time of strawberries using visible/near-infrared hyperspectral imaging. INTERNATIONAL JOURNAL OF FOOD PROPERTIES 2020. [DOI: 10.1080/10942912.2020.1716793] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
Affiliation(s)
- Shizhuang Weng
- National Engineering Research Center for Agro-Ecological Big Data Analysis & Application, Anhui University, Hefei, China
| | - Shuan Yu
- National Engineering Research Center for Agro-Ecological Big Data Analysis & Application, Anhui University, Hefei, China
| | - Ronglu Dong
- Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, China
| | - Fangfang Pan
- National Engineering Research Center for Agro-Ecological Big Data Analysis & Application, Anhui University, Hefei, China
| | - Dong Liang
- National Engineering Research Center for Agro-Ecological Big Data Analysis & Application, Anhui University, Hefei, China
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Feng CH, Wang W, Makino Y, García-Martín JF, Alvarez-Mateos P, Song XY. Evaluation of storage time and temperature on physicochemical properties of immersion vacuum cooled sausages stuffed in the innovative casings modified by surfactants and lactic acid. J FOOD ENG 2019. [DOI: 10.1016/j.jfoodeng.2019.03.023] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
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18
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Feng CH, Makino Y, Yoshimura M, Rodríguez-Pulido FJ. Estimation of adenosine triphosphate content in ready-to-eat sausages with different storage days, using hyperspectral imaging coupled with R statistics. Food Chem 2018; 264:419-426. [PMID: 29853396 DOI: 10.1016/j.foodchem.2018.05.029] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2017] [Revised: 04/29/2018] [Accepted: 05/03/2018] [Indexed: 12/15/2022]
Abstract
A hyperspectral imaging (HSI) system (380-1000 nm) was investigated for non-invasively estimating adenosine triphosphate (ATP) content in ready-to-eat sausages during 5 days storage at 35 °C. A set of pretreated combinations were carried out on preprocessing the spectra to improve the performance of partial least squares regression (PLSR). According to the regression coefficient values, ten important wavelengths (385, 390, 395, 505, 580, 670, 745, 780, 855, and 955 nm) were selected in this study. PLSR models developed using full wavelengths and optimal wavelengths showed the prediction coefficient of determination (rp2) up to 0.8324 and 0.8606, respectively. The concentration and location of the ATP content in sausages were for the first time displayed via chemical imaging developed by R statistics. Combining HSI and multivariate analysis can quantify and visualize ATP dynamic changes during storage and a great potential in the processed meat industry for real-time inspection.
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Affiliation(s)
- Chao-Hui Feng
- Graduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1, Yayoi, Bunkyo-ku, Tokyo 113-8657, Japan; College of Pharmacy and Biological Engineering, Chengdu University, Chengdu, Sichuan 610106, China; College of Food Sciences, Sichuan Agricultural University, Yucheng District, Ya'an, Sichuan, China.
| | - Yoshio Makino
- Graduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1, Yayoi, Bunkyo-ku, Tokyo 113-8657, Japan.
| | - Masatoshi Yoshimura
- Graduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1, Yayoi, Bunkyo-ku, Tokyo 113-8657, Japan
| | - Francisco J Rodríguez-Pulido
- Food Color & Quality Laboratory, Department of Nutrition and Food Science, Facultad de Farmacia, Universidad de Sevilla, 41012, Spain
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Feng CH, Makino Y, Yoshimura M, Thuyet DQ, García-Martín JF. Hyperspectral Imaging in Tandem with R Statistics and Image Processing for Detection and Visualization of pH in Japanese Big Sausages Under Different Storage Conditions. J Food Sci 2017; 83:358-366. [PMID: 29278665 DOI: 10.1111/1750-3841.14024] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2017] [Revised: 11/18/2017] [Accepted: 12/01/2017] [Indexed: 01/06/2023]
Abstract
The potential of hyperspectral imaging with wavelengths of 380 to 1000 nm was used to determine the pH of cooked sausages after different storage conditions (4 °C for 1 d, 35 °C for 1, 3, and 5 d). The mean spectra of the sausages were extracted from the hyperspectral images and partial least squares regression (PLSR) model was developed to relate spectral profiles with the pH of the cooked sausages. Eleven important wavelengths were selected based on the regression coefficient values. The PLSR model established using the optimal wavelengths showed good precision being the prediction coefficient of determination (Rp2 ) 0.909 and the root mean square error of prediction 0.035. The prediction map for illustrating pH indices in sausages was for the first time developed by R statistics. The overall results suggested that hyperspectral imaging combined with PLSR and R statistics are capable to quantify and visualize the sausages pH evolution under different storage conditions. PRACTICAL APPLICATION In this paper, hyperspectral imaging is for the first time used to detect pH in cooked sausages using R statistics, which provides another useful information for the researchers who do not have the access to Matlab. Eleven optimal wavelengths were successfully selected, which were used for simplifying the PLSR model established based on the full wavelengths. This simplified model achieved a high Rp2 (0.909) and a low root mean square error of prediction (0.035), which can be useful for the design of multispectral imaging systems.
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Affiliation(s)
- Chao-Hui Feng
- Graduate School of Agricultural and Life Sciences, The Univ. of Tokyo, 1-1-1, Yayoi, Bunkyo-ku, Tokyo 113-8657, Japan.,Coll. of Food Science, Sichuan Agricultural Univ., Yucheng District, Ya'an, Sichuan, China.,Coll. of Pharmacy and Biological Engineering, Chengdu Univ., Chengdu, Sichuan 610106, China
| | - Yoshio Makino
- Graduate School of Agricultural and Life Sciences, The Univ. of Tokyo, 1-1-1, Yayoi, Bunkyo-ku, Tokyo 113-8657, Japan
| | - Masatoshi Yoshimura
- Graduate School of Agricultural and Life Sciences, The Univ. of Tokyo, 1-1-1, Yayoi, Bunkyo-ku, Tokyo 113-8657, Japan
| | - Dang Quoc Thuyet
- Graduate School of Agricultural and Life Sciences, The Univ. of Tokyo, 1-1-1, Yayoi, Bunkyo-ku, Tokyo 113-8657, Japan
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