Moisture, solids-non-fat and fat analysis in butter by near infrared spectroscopy

Hermida, Marcelo Antonio Martínez; González, José Manuel; Sánchez, M. Jesús; Rodríguez-Otero, J. L.

doi:10.1016/s0958-6946(01)00039-5

Cited by 43 publications

(38 citation statements)

References 11 publications

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“…Near-infrared (NIR) spectrometry as a technique used for on-line and off-line analyses in food industries has been reviewed [35]. In recent years, NIR has become popular for process monitoring in many industries such as the dairy industry, in part because of the relative simplicity of the equipment required to record a spectrum [1,2,4,7,15,23,25,29,38,41]. In addition, the relatively low absorption coefficients exhibited by many species in the NIR region implies that bulk samples can often be examined by NIR directly without the need for dilution in some inert, non-absorbing medium, as might be required for study in the fundamental mid-infrared (MIR) region.…”

Section: Introductionmentioning

confidence: 99%

Mid-infrared spectrometry: A tool for the determination of chemical parameters in Emmental cheeses produced during winter

Karoui

Mouazen

Dufour

et al. 2005

Lait

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-The study investigates the potential use of the mid-infrared (MIR) spectroscopy in transmission mode for determining some chemical parameters of European Emmental cheeses. A total of 91 Emmental cheeses produced during the winter in Austria (n = 4), Finland (n = 6), Germany (n = 13), France (n = 30) and Switzerland (n = 38) were investigated. Fat, total nitrogen (TN), watersoluble nitrogen (WSN), non-protein nitrogen (NPN), sodium chloride (NaCl) and pH were analysed by the reference methods. The MIR transmission of different cheeses was also measured by a Nicolet Magna 750 IR spectrometer in a measurement range of 4000-600 cm -1 . Partial least square analysis together with the leave-one-out cross-validation technique was used to develop calibration models for different cheese parameters. The best results for NPN (R 2 = 0.85; ratio of standard deviation to root mean square error of prediction (RPD) = 2.58), pH (R 2 = 0.82; RPD = 2.34), WSN (R 2 = 0.80; RPD = 2.26), NaCl (R 2 = 0.70; RPD = 1.91), fat (R 2 = 0.69; RPD = 1.87), TN (R 2 = 0.62; RPD = 1.60), WSN/TN (R 2 = 0.83; RPD = 2.81) and WSN/NPN (R 2 = 0.57; RPD = 1.52) were obtained when the spectra were subjected to the first derivation and smoothing after maximum normalisation. It can be concluded that MIR-transmission spectroscopy can be considered as a suitable technique for the prediction of NPN, pH, WSN and WSN/TN of European Emmental cheeses with different origins. The NaCl, TN, WSN/NPN and fat can also be estimated, but with much lower precision.Emmental cheese / mid-infrared spectroscopy / calibration / partial least square method Résumé -La spectroscopie moyen infrarouge : un outil pour la détermination des paramètres chimiques des fromages Emmental de production hivernale. Cette étude traite du potentiel d'utilisation de la spectroscopie moyen infrarouge en mode transmission pour la détermination de certains paramètres chimiques des fromages Emmental européens. Un total de 91 fromages Emmental de production hivernale, provenant de : Autriche (n = 4), Finlande (n = 6), Allemagne (n = 13), France (n = 30) et Suisse (n = 38) ont été analysés. La matière grasse, l'azote total, l'azote soluble, l'azote non protéique, le chlorure de sodium et le pH ont été déterminés par les méthodes de réfé-rences. La spectroscopie moyen infrarouge en mode transmission a été, également, appliquée aux différents fromages en utilisant un spectromètre (Nicolet Magna 750) et ce, entre 4000-600 cm -1 . La méthode aux moindres carrés partiels avec validation croisée a été utilisée pour développer des modèles de calibration, et ce pour tous les paramètres chimiques. Les meilleurs résultats pour l'azote non protéique (R 2 = 0,85 ; ratio de la déviation moyenne à la racine carré de prédiction (RPD) = 2,58), pH (R 2 = 0,82 ; RPD = 2,34), azote soluble (R 2 = 0,80 ; RPD = 2,26), chlorure de sodium (R 2 = 0,70 ; RPD = 1,91), matière grasse (R 2 = 0,69 ; RPD = 1,87), azote total (R 2 = 0,62 ; RPD = 1,60), rapport azote soluble/azote total (R 2 = 0,83; RPD = 2,81) et du rap...

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Section: Introductionmentioning

confidence: 99%

Mid-infrared spectrometry: A tool for the determination of chemical parameters in Emmental cheeses produced during winter

Karoui

Mouazen

Dufour

et al. 2005

Lait

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“…NIR spectroscopic analysis of dairy products such as milk [4,5], meat [6], butter [7], and others [8] have been reported. In contrast, few examples of application of Raman spectroscopy to quantitative analysis and quality control in the food industry have been reported [9,10].…”

Section: Introductionmentioning

confidence: 99%

Determination of oil and water content in olive pomace using near infrared and Raman spectrometry. A comparative study

Muik

Lendl

Molina‐Díaz

et al. 2004

Analytical and Bioanalytical Chemistry

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Near infrared (NIR) reflectance and Raman spectrometry were compared for determination of the oil and water content of olive pomace, a by-product in olive oil production. To enable comparison of the spectral techniques the same sample sets were used for calibration (1.74-3.93% oil, 48.3-67.0% water) and for validation (1.77-3.74% oil, 50.0-64.5% water). Several partial least squares (PLS) regression models were optimized by cross-validation with cancellation groups, including different spectral pretreatments for each technique. Best models were achieved with first-derivative spectra for both oil and water content. Prediction results for an independent validation set were similar for both techniques. The values of root mean square error of prediction (RMSEP) were 0.19 and 0.20-0.21 for oil content and 2.0 and 1.8 for water content, using Raman and NIR, respectively. The possibility of improving these results by combining the information of both techniques was also tested. The best models constructed using the appended spectra resulted in slightly better performance for oil content (RMSEP 0.17) but no improvement for water content.

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“…Usually, this association dispenses sample pretreatments, which favors the development of easily-executed routines and the analysis of a large number of samples in few minutes (Hermida et al 2001;Silva et al 2009). …”

Section: Introductionmentioning

confidence: 99%

“…Since then, many papers have described the use of NIRS in food analysis, including the quality control of wheat flour of milling industry (Miralbés 2004), the chemical composition of butter (Hermida et al 2001), cocoa powder (Veselá et al 2007), and grass silage (Villamarín et al 2002), and the nutritional evaluation of cereals (Soares et al 1998) and feed for rabbits (Xiccato et al 1999(Xiccato et al , 2003. Work related to quality control of cheeses include the determination of whey fat (Castillo et al 2005), the determination of total solids and protein content in cheese curd (Sultaneh and Rohm 2007), the prediction of major components in commercial cheese (González-Martín et al 2008), and the prediction of fatty acid composition of fresh and freeze-dried cheeses (Lucas et al 2008).…”

Section: Introductionmentioning

confidence: 99%

Determination of fat, protein and moisture in ricotta cheese by near infrared spectroscopy and multivariate calibration

2013

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Near-infrared reflectance spectroscopy (NIRS) with partial least squares regression (PLSR) was used to determine levels of fat, protein and moisture in ricotta cheese without complex sample preparation. Spectra of 19 conventional and low-fat ricotta samples from different manufacturers were collected in duplicate, with 33 of the 38 spectra used as a calibration set and the remaining 5 spectra used as an external validation set. The best results were obtained by processing the spectral region between 1,100 and 2,500 nm. Multivariate models with six latent variables (LVs) showed good prediction capability for fat and protein determinations, with average relative errors (Er) of 6.37 % and 5.95 %, respectively. For moisture, a more robust model was obtained with 4 LVs, showing better prevision capacity and Er of 1.91 %.

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Moisture, solids-non-fat and fat analysis in butter by near infrared spectroscopy

Cited by 43 publications

References 11 publications

Mid-infrared spectrometry: A tool for the determination of chemical parameters in Emmental cheeses produced during winter

Mid-infrared spectrometry: A tool for the determination of chemical parameters in Emmental cheeses produced during winter

Determination of oil and water content in olive pomace using near infrared and Raman spectrometry. A comparative study

Determination of fat, protein and moisture in ricotta cheese by near infrared spectroscopy and multivariate calibration

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