Nondestructive determination of freshness indicators for tilapia fillets stored at various temperatures by hyperspectral imaging coupled with RBF neural networks

Shi, Ce; Qian, Jiang; Zhu, Wenying; Huan, Liu; Han, Shuai D.; Yang, Xinting

doi:10.1016/j.foodchem.2018.09.092

Cited by 63 publications

(26 citation statements)

References 22 publications

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“…Shi et al . 31 also reported that the sensory analysis of tilapia fillets correlates well with the chemical and especially microbial analysis. In addition, variation range of sensory score for calibration set was 18.9 (10.2–29.1) and for prediction set was 18.6 (10.6–29.0).…”

Section: Resultsmentioning

confidence: 79%

“…In the other word the best prediction performance was obtained for K value and the weakest one was acquired for TVC value. Different chemometric analysis, fish Species, and experimental condition could explain the disagreement between various research findings 31 .…”

Section: Resultsmentioning

confidence: 99%

“…However, Shi et al . 31 used optimal wavelengths from hyperspectral imaging (HSI) selected by successive projections algorithm (SPA) and radial basis function neural network to predict various freshness factor in tilapia fillets. Their results showed that the relative error of TVB-N, TVC and K value between predicted and experimental values were 5.66, 6.29 and −4.84%.…”

Section: Resultsmentioning

confidence: 99%

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Prediction of various freshness indicators in fish fillets by one multispectral imaging system

Khoshnoudi‐Nia

Moosavi‐Nasab

2019

Sci Rep

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In current study, a simple multispectral imaging (430–1010 nm) system along with linear and non-linear regressions were used to assess the various fish spoilage indicators during 12 days storage at 4 ± 2 °C. The indicators included Total-Volatile Basic Nitrogen (TVB-N) and Psychrotrophic Plate Count (PPC) and sensory score in fish fillets. immediately, after hyperspectral imaging, the reference values (TVB-N, PPC and sensory score) of samples were obtained by traditional method. To simplify the calibration models, nine optimal wavelengths were selected by genetic algorithm. The prediction performance of various chemometric models including partial least-squares regression (PLSR), multiple-linear regression (MLR), least-squares support vector machine (LS-SVM) and back-propagation artificial neural network (BP-ANN) were compared. All models showed acceptable performance for simultaneous predicting of PPC, TVB-N and sensory score (R2P ≥ 0.853 and RPD ≥ 2.603). Non-linear models were considered better quantitative model to predict all of three freshness indicators in fish fillets. Among the three spoilage indices, the best predictive power was obtained for PPC value and the weakest one was acquired for TVB-N content prediction. The best model for prediction TVB-N (R2p = 0.862; RMSEP = 3.542 and RPD = 2.678) and sensory score (R2p = 0.912; RMSEP = 1.802 and RPD = 3.33) belonged to GA-LS-SVM and for prediction of PPC value was BP-ANN (R2p = 0.921; RMSEP = 0.504 and RPD = 3.64). Therefore, developing multispectral imaging system based on LS-SVM model seems to be suitable for simultaneous prediction of all three indicators (R2P > 0.862 and RPD > 2.678). Further studies needed to improve the accuracy and applicability of HSI system for predicting freshness of rainbow-trout fish.

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Section: Resultsmentioning

confidence: 79%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

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Prediction of various freshness indicators in fish fillets by one multispectral imaging system

Khoshnoudi‐Nia

Moosavi‐Nasab

2019

Sci Rep

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“…K values were determined according to the method described by Shi et al. (). Standard adenosine triphosphate (ATP), adenosine diphosphate (ADP), adenosine monophosphate (AMP), inosine monophosphate (IMP), hypoxanthine (Hx), and inosine (HxR)) were purchased from Sangon Biotech Co., Ltd (Shanghai, China).…”

Section: Methodsmentioning

confidence: 99%

“…Tilapia ( Oreochromis niloticus ), farmed in more than 100 countries around the world, is the second most commonly aquaculture fish worldwide (FAO, ). Tilapia is tremendously popular among consumers in Asia, North Africa and the Central and South Americas given its savory taste, low price, and high essential amino acid, unsaturated fatty acid, vitamin, and mineral contents (Shi et al., ). Global total farmed tilapia production was 4,199,567 tons (FAO, ).…”

Section: Introductionmentioning

confidence: 99%

Tartary Buckwheat Extract and Chitosan Coated Tilapia (Oreochromis Niloticus) Fillets Determine Their Shelf Life

Yang

Zhou

Wang

et al. 2019

Journal of Food Science

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The preservation effects of tartary buckwheat extract (T) and chitosan (C) coatings on the physicochemical (pH value, thiobarbituric acid value, Peroxide value (PV), total volatile basic nitrogen (TVB‐N), K value, surface color and the texture profiles), bacteriological (total viable counts (TVC) and psychrotrophic bacteria counts (PBC)), and sensory characteristics of tilapia (Oreochromis niloticus) fillets storage at 0 °C for 18 days were evaluated. The fillets coated with 0.5% T + 1.0% C, 1.0% T + 1.0% C and 1.5% T + 1.0% C maintained better quality and had longer shelf life with respect to samples coated with chitosan alone and the control. Base on the limit values of TVB‐N, K value, TVC and sensory preference scores, the shelf life of control fillets was 6 days. By contrast, shelf life of 9 days for 0.5% T + 1.0% C‐coated fillets, 12 days for 1.0% T + 1.0% C treated‐fillets, and 15 days for 1.5% T + 1.0% C‐treated fillets were obtained. Therefore, TBE combined with chitosan coatings have the potential to extend the shelf life of tilapia fillets during storage at 0 °C. Practical Application This study provides basic theory regarding the application of TBE to fish preservation. The edible coating of TBE combined with chitosan has potential use in developing activity food preservation coating.

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Visible Light Imaging

Ali

Hashim

2021

Electromagnetic Technologies in Food Science

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Nondestructive determination of freshness indicators for tilapia fillets stored at various temperatures by hyperspectral imaging coupled with RBF neural networks

Cited by 63 publications

References 22 publications

Prediction of various freshness indicators in fish fillets by one multispectral imaging system

Prediction of various freshness indicators in fish fillets by one multispectral imaging system

Tartary Buckwheat Extract and Chitosan Coated Tilapia (Oreochromis Niloticus) Fillets Determine Their Shelf Life

Visible Light Imaging

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