Accuracy of near infrared spectroscopy for prediction of chemical composition, salt content and free amino acids in dry-cured ham

Prevolnik, M.; Škrlep, Martin; Janeš, Lucija; Velikonja-Bolta, Š.; Škorjanc, Dejan; Čandek-Potokar, Marjeta

doi:10.1016/j.meatsci.2011.01.007

Cited by 68 publications

(46 citation statements)

References 27 publications

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“…However, no application of NIR spectroscopy for this purpose has been documented although the method was recently used for numerous different analyses on dry-cured hams (for review see Prieto et al, 2009). Moreover, several successful applications of NIR spectroscopy in a combination with ANN were reported in meat production and technology (a review of Prevolnik, Škrlep, et al, 2011) and the results of the present study represent another promising example.…”

Section: Classification Resultsmentioning

confidence: 88%

“…Several chemical constituents (moisture, intramuscular fat, protein, non-protein nitrogen, salt content, the percentage of salt per dry mater and proteolysis index) of dry-cured ham muscle biceps femoris were determined by means of internal NIR spectroscopy calibration models published in Prevolnik, Škrlep, Janeš, Velikonja-Bolta, Škorjanc & Čandek-Potokar (2011). Data are presented in Table 1.…”

Section: Dry-cured Ham Chemical Compositionmentioning

confidence: 99%

“…Different models were prepared varying the net size, i.e. the a Assessed with NIR spectroscopy using internal calibration models (Prevolnik, Škrlep, et al, 2011) number of neurons in x and y direction (8 × 8, 10 × 10 and 12 × 12) and number of epochs (10, 30, 50, 70, 100, 150, 200 and 300), while the other net parameters remained constant (no toroid boundary conditions, triangular type of neighbourhood correction, minimal and maximal learning rates 0.01 and 0.5, respectively). In this step of analysis, besides the input variables (262 spectral data points), the target or output variables were also needed.…”

Section: Development and Validation Of Modelsmentioning

confidence: 99%

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Classification of dry-cured hams according to the maturation time using near infrared spectra and artificial neural networks

et al. 2014

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An attempt to classify dry-cured hams according to the maturation time on the basis of near infrared (NIR) spectra was studied. The study comprised 128 samples of biceps femoris (BF) muscle from dry-cured hams matured for 10 (n = 32), 12 (n = 32), 14 (n = 32) or 16 months (n = 32). Samples were minced and scanned in the wavelength range from 400 to 2500 nm using spectrometer NIR System model 6500 (Silver Spring, MD, USA). Spectral data were used for i) splitting of samples into the training and test set using 2D Kohonen artificial neural networks (ANN) and for ii) construction of classification models using counterpropagation ANN (CP-ANN). Different models were tested, and the one selected was based on the lowest percentage of misclassified test samples (external validation). Overall correctness of the classification was 79.7%, which demonstrates practical relevance of using NIR spectroscopy and ANN for dry-cured ham processing control.

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Section: Classification Resultsmentioning

confidence: 88%

Section: Dry-cured Ham Chemical Compositionmentioning

confidence: 99%

Section: Development and Validation Of Modelsmentioning

confidence: 99%

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Classification of dry-cured hams according to the maturation time using near infrared spectra and artificial neural networks

et al. 2014

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“…The authors found the mean content of this compound in raw material to be 243.3 mg/100 g on average and in ham after ripening the amount of l-glutamic acid ranged from 300.39 to 482.81 mg/100 g of the product. Similar research was conducted by Prevolnik et al (2011). The authors investigated the occurrence of amino acids in dry-cured hams.…”

Section: Nutritional Valuementioning

confidence: 80%

Influence of the origin on selected determinants of the quality of pork meat products

Garbowska¹,

Radzymińska²,

Jakubowska³

2013

Czech J. Food Sci.

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Garbowska B., Radzymińska M., Jakubowska D. (2013): Influence of the origin on selected determinants of the quality of pork meat products. Czech J. Food Sci., 31: 547-552.In recent years, great attention has been paid to the quality of eaten meat and its products. There have been launched a lot of promotional campaigns aimed at providing opportunities for the consumption of traditional products. Based on the experiment, a significantly higher protein content was found in sausages produced by large producers (24.73 ± 1.98%). The fat content was significantly higher in traditional ham (16.25 ± 14.47%), compared with local ham (4.38 ± 2.26%) and the mass (9.29 ± 5.25%). The samples of traditional and local ham had a significantly higher salt content (3.31 ± 0.72 and 2.90 ± 0.54%, respectively). No dye compounds were detected in any of the tested samples. There were no statistically significant differences in hydroxyproline and l-glutamic acid content between traditional and conventional samples of meat products. Analysis of nitrate (V and III) showed a statistically significant difference in the average contents of these compounds. Significantly higher levels of nitrates were revealed only in traditional ham samples (12.60 ± 8.08 mg NaNO(V)/kg and 17.53 ± 27.91 mg NaNO(III)/kg of the product, respectively), wherein there was a large variation in the content of these compounds in the samples.

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“…In case of brine (Lin and Brown, 1992), the concentrations of NaCI in aqueous solutions have been determined with the use of NIR spectra 1100 -1900 nm and the models developed with linear and nonlinear regression could be applied for quantitative analysis of NaCl in the laboratory or can be readily adapted for continuous monitoring in process control. For dry-cured ham (Prevolnik et al, 2011), the samples were scanned in the wavelength range 400 to 2500 nm in reflectance mode. The best model for salt content and salt percentage in moisture/dry matter provided the coefficients of determination (R 2 CV ) > 0.90 and the ratio of standard error of validation to the standard deviation (RPD) > 3.0.…”

Section: Introductionmentioning

confidence: 99%

Feasibility of Evaluation of Salt Content in Canned Sardine in Oil by Near Infrared Spectroscopy

Srikornkarn

Sirisomboon

2014

Agriculture and Agricultural Science Procedia

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Accuracy of near infrared spectroscopy for prediction of chemical composition, salt content and free amino acids in dry-cured ham

Cited by 68 publications

References 27 publications

Classification of dry-cured hams according to the maturation time using near infrared spectra and artificial neural networks

Classification of dry-cured hams according to the maturation time using near infrared spectra and artificial neural networks

Influence of the origin on selected determinants of the quality of pork meat products

Feasibility of Evaluation of Salt Content in Canned Sardine in Oil by Near Infrared Spectroscopy

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