Detection of blood in fish muscle by constrained spectral unmixing of hyperspectral images

Skjelvareid, Martin Hansen; Heia, Karsten; Olsen, Svein Ottar; Stormo, Svein Kristian

doi:10.1016/j.jfoodeng.2017.05.029

Cited by 32 publications

(29 citation statements)

References 41 publications

(48 reference statements)

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“…It was reported that PLSR models can be trained using the known variables and then unknown variables can be evaluated directly from spectral information . Nevertheless, the analyst does not really know what the regression coefficients mean when the varables are evaluated, which is the so‐called ‘black box’ of PLSR modelling . Regarding the results of FSMR model, it may be remarkable that R p 2 values are generally better than those obtained by PLSR from 10 wavelengths.…”

Section: Resultsmentioning

confidence: 99%

“…48 Nevertheless, the analyst does not really know what the regression coefficients mean when the varables are evaluated, which is the so-called 'black box' of PLSR modelling. 30 Regarding the results of FSMR model, it may be remarkable that R p 2 values are generally better than those obtained by PLSR from 10 wavelengths. The behavior of models changes dramatically when first and second derivative are used.…”

Section: Spectral Characteristics Overview and Statistics Of Referencmentioning

confidence: 92%

“…Normalization can enhance the spectral features 29 and render spectra that have an equal area under the curve to allow easy comparison of spectral features in the same plot. 30 Regarding MSC, it is a transformation method that compensates for additive and multiplicative effects. 31 The function of SNV is commonly used to remove variability in the relectance spectra caused by light scattering.…”

Section: Model Development and Performance Evaluationmentioning

confidence: 99%

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Real‐time prediction of pre‐cooked Japanese sausage color with different storage days using hyperspectral imaging

et al. 2017

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Section: Resultsmentioning

confidence: 99%

Section: Spectral Characteristics Overview and Statistics Of Referencmentioning

confidence: 92%

Section: Model Development and Performance Evaluationmentioning

confidence: 99%

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Real‐time prediction of pre‐cooked Japanese sausage color with different storage days using hyperspectral imaging

et al. 2017

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“…In [14], a tool for the processing and automatic quality grading in the fish industry is developed based on diffuse reflectance imaging and the subsequent unmixing of the absorption spectra using a constrained least squares model to detect hemoglobin concentration. It is common for the absorption lines to have a Gaussian or Lorentzian distribution shape, so VARPRO is used in the decomposition of the spectra.…”

Section: Medical and Biologicalmentioning

confidence: 99%

Imaging Applications with Variable Projections

Pereyra¹,

Scherer²

2019

AJCM

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We review two important fields of application for the method of Variable Projections (VARPRO): Seismic Prospecting and Medical Imaging. We cover the period since 2002 when a first review was published. Variable Projections is a method for the solution of nonlinear least squares problems where the model is a linear combination of nonlinear functions. Its success is based on the fact that the reduced functional, where the linear parameters are eliminated converges always faster than if the same method of solution is applied to the original problem. More importantly, many of these problems are very hard to solve in their original format and VARPRO has shown its value in many different applications.

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“…For production of lutefisk, the stockfish is soaked in cold water for about a week, which allows the fish to be rehydrated. Then it is immersed in a lye solution (caustic soda) for two to four days, reaching a pH of [11][12]. The last step is to soak the fish again in water in order to remove the lye and make the fish edible.…”

Section: Introductionmentioning

confidence: 99%

Performance of Fluorescence and Diffuse Reflectance Hyperspectral Imaging for Characterization of Lutefisk: A Traditional Norwegian Fish Dish

et al. 2020

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Lutefisk is a traditional Norwegian fish dish made from dried fish, such as cod or other whitefish. In Norway and other Nordic countries, lutefisk is considered among the most popular dishes served during Christmas or other festive occasions. However, to date, little attention has been paid to this product, and available research on the quality, processing, and chemistry of lutefisk is still limited. The quality of this very delicate product, with a high pH value, depends on many factors, such as the initial quality of raw materials (stockfish), the quantity of lye used during the preparation process of lutefisk, and time during soaking in the lye and water, among others, making it challenging to both optimize processing and monitor the quality of lutefisk. In this study, four commercially available lutefisk brands (labelled as A, B, C, and D) were characterized using two online spectroscopic techniques, namely fluorescence and diffuse reflectance hyperspectral imaging, implemented on conveyor belts to mimic industrial applications. The samples were also analyzed by the use of an offline laboratory instrument based on visible/near infrared diffuse reflectance spectroscopy. Three traditional measurements, including texture, water content, and pH, were also conducted on the same samples. Supervised classification PLS-DA models were built with each dataset and relationships between the spectroscopic measurements and the traditional data were investigated using canonical correlations. The spectroscopic methods, especially fluorescence spectroscopy, demonstrated high performance for the discrimination between samples of the different brands, with high correlations between the spectral and traditional measurements. Although more validations of the results of this study are still required, these preliminary findings suggest that the destructive, laborious, and time-consuming traditional techniques can be replaced by rapid and nondestructive online measurements based on hyperspectral imaging used in fluorescence or diffuse reflectance mode.

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Detection of blood in fish muscle by constrained spectral unmixing of hyperspectral images

Cited by 32 publications

References 41 publications

Real‐time prediction of pre‐cooked Japanese sausage color with different storage days using hyperspectral imaging

Real‐time prediction of pre‐cooked Japanese sausage color with different storage days using hyperspectral imaging

Imaging Applications with Variable Projections

Performance of Fluorescence and Diffuse Reflectance Hyperspectral Imaging for Characterization of Lutefisk: A Traditional Norwegian Fish Dish

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