Integration of spectral and textural data for enhancing hyperspectral prediction of K value in pork meat

Cheng, Weiwei; Sun, Da‐Wen; Pu, Hongbin; Liu, Yuwei

doi:10.1016/j.lwt.2016.05.003

Cited by 100 publications

(23 citation statements)

References 65 publications

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“…Adenosine triphosphate (ATP)—related decomposition products were analyzed according to the method described in Cheng, Sun, and Pu (), Cheng, Sun, Pu, and Zhu () with some modifications. 5 grams of minced fish was homogenized for 30 s with 10 ml of 0.6 mol/L perchloric acid at 4 °C.…”

Section: Methodsmentioning

confidence: 99%

“…Therefore, shelf‐life extension of fish is an important issue for food quality and safety assurance in the industry. The industry not only requires processing techniques such as cooling (Desmond, Kenny, Ward, & Sun, ; Hu & Sun, ; McDonald & Sun, ; McDonald, Sun, & Kenny, ; Sun, ; Sun & Eames, ; Sun & Zheng, ; Wang & Sun, ), freezing (Cheng, Sun, Pu, & Liu, ; Cheng, Sun, Pu, & Wei, ; Cheng, Sun, Zhu, & Zhang, ; Kiani, Sun, Delgado, & Zhang, ; Kiani, Zhang, Delgado, & Sun, ; Ma et al, ; Pu, Sun, Ma, & Cheng, ; Qu, Sun, Cheng, & Pu, ; Xie, Sun, Xu, & Zhu, , Xie, Sun, Zhu, & Pu, ), and drying (Delgado & Sun, ; Ma, Sun, Qu, & Pu, ; Pu & Sun, ; Sun, ; Sun & Woods, ; Yang, Sun, & Cheng, ), but also needs packaging methods for extending the shelf‐life of perishable foods.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Quality comparison of grass carp and salmon fillets packaged in modified atmosphere with different composite films

Zhu

Hai

Gao

et al. 2018

J Food Process Engineering

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Grass carp fillets (without dark meat) and salmon fillets were stored in modified atmosphere packaging (MAP) with a gas mixture of 10% O2, 60% CO2, and 30% N2 for up to 12 days at 4 °C. Effects of three commercial MAP composite films, that is, F1 from Sealed Air, F2 from Amcor, and F3 from Bemis, on contents of CO2 and O2, and quality indicators including total viable count (TVC), total volatile basic nitrogen (TVB‐N), thiobarbituric acid (TBA), K value, pH, and color difference were investigated. It was observed that O2 content, pH, and TBA in grass carp fillets were higher than those of salmon fillets, while CO2 content and color difference were lower. F1 could maintain the quality of both fillets better than F2 and F3, with F3 being the worst. Principal component analysis showed the scores of F1, F2, and F3 for packaging grass carp and salmon fillets were 24.840, 26.570, and 25.162, and 24.863, 27.086, and 24.878, respectively, with F1 being the best for keeping the quality. The relationship between rate constant k and film oxygen permeability for describing kinetic change of TVC and TVB‐N during MAP storage for both fillets were also determined in the study. Practical applications Grass carp and salmon are very common species of fish with the largest reported production internationally. As highly perishable products, the extension of their shelf‐life is an important issue for in the industry. Modified atmosphere packaging (MAP) is an effective method for extending the shelf life of fresh foods. This study compared three commercial MAP composite films, that is, F1 from Sealed Air, F2 from Amcor, and F3 from Bemis, on contents of CO2 and O2, and quality indicators including total viable count (TVC), total volatile basic nitrogen (TVB‐N), thiobarbituric acid (TBA), K value, pH, and color difference for grass carp fillets (without dark meat) and salmon fillets stored in MAP, and indicated that F1 with composition of PP/Tie/Nylon6/EVOH/Nylon6/Tie/LLDPE was the best for keeping their quality. The current results should provide valuable information for the industry and retailers to supply high quality fresh aquatic products to the consumers.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Quality comparison of grass carp and salmon fillets packaged in modified atmosphere with different composite films

Zhu

Hai

Gao

et al. 2018

J Food Process Engineering

Self Cite

View full text Add to dashboard Cite

show abstract

“…Entropy measures the textural uniformity of the image. Correlation is the measurement of the spatial arrangement of gray levels [29,[36][37][38]. The procedure of texture variable extraction was carried out using ENVI 4.8 (Exelis Visual Information Solutions, Boulder, CO, USA).…”

Section: Extraction Of Texture Datamentioning

confidence: 99%

“…In order to obtain more information from the chicken filets and to improve prediction models performance, some researchers [29,39] have attempted to integrate two complementary information models of hyperspectral image (spectral and spatial data), and good potential was shown. Generally, data fusion can be categorized into three methods-pixel level fusion, feature level fusion, and decision level fusion [40]: Pixel level fusion is a direct method that integrates the original data from various data sources and requires immense data calculation; feature level fusion requires the extraction of feature variables and then fuses the feature variables using statistical approaches, such as arithmetic combinations, filters, and regression variable substitution; and decision level fusion is a method that integrates the extracted data by applying decision rules [40,41].…”

Section: Fusion Of Spectra and Texture Datamentioning

confidence: 99%

“…Spectral information can effectively reflect the chemical components within the meat [25][26][27], while spatial information can evaluate important physical qualities of meat, such as size, shape, texture, etc. In particular, texture can be used as an effective tool for reflecting the surface information of chicken breast filets, such as the distribution of muscle fibers, fat, and fascia [28,29]. Some studies have tested the fusion of spectral and spatial information of HSI for predicting the WHC of fish and red meat [8,30], and the results demonstrated that the prediction accuracy can be improved.…”

Section: Introductionmentioning

confidence: 99%

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Fusion of Spectra and Texture Data of Hyperspectral Imaging for the Prediction of the Water-Holding Capacity of Fresh Chicken Breast Filets

Wang

Zhuang

et al. 2018

Applied Sciences

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This study investigated the fusion of spectra and texture data of hyperspectral imaging (HSI, 1000-2500 nm) for predicting the water-holding capacity (WHC) of intact, fresh chicken breast filets. Three physical and chemical indicators-drip loss, expressible fluid, and salt-induced water gain-were measured to be different WHC references of chicken meat. Different partial least squares regression (PLSR) models were established with corresponding input variables including the full spectra, key wavelengths, and texture variables, as well as the fusion data of key wavelengths and the corresponding texture variables, respectively. The results demonstrated that for drip loss and expressible fluid, texture data was an effective supplement to spectra data, and fusion data as an input variable could effectively improve the predictive ability of the independent prediction set (Rp = 0.80, RMSEp = 0.80; Rp = 0.56, RMSEp = 2.10). While the best model to predict salt-induced water gain was based on key wavelengths (Rp = 0.69, RMSEp = 18.04), this was mainly because salt-induced water gain was measured on mince samples, which lacked the important physical structure to represent the texture information of meat. Our results of this study demonstrated the potential to further improve the evaluation of the WHC of chicken meat by HSI.

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CNN in Food Industry: Current Practices and Future Trends

Tripathy

Salaria²,

Ambastha³

2022

Artificial Intelligence: A Real Opportunity in the Food Industry

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Integration of spectral and textural data for enhancing hyperspectral prediction of K value in pork meat

Cited by 100 publications

References 65 publications

Quality comparison of grass carp and salmon fillets packaged in modified atmosphere with different composite films

Quality comparison of grass carp and salmon fillets packaged in modified atmosphere with different composite films

Fusion of Spectra and Texture Data of Hyperspectral Imaging for the Prediction of the Water-Holding Capacity of Fresh Chicken Breast Filets

CNN in Food Industry: Current Practices and Future Trends

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