Chemical characterisation of European Emmental cheeses by near infrared spectroscopy using chemometric tools

Karoui, Romdhane; Mouazen, Abdul Mounem; Dufour, Éric; Pillonel, Laurent; Schaller, E.; Baerdemaeker, Josse De; Bosset, J. O.

doi:10.1016/j.idairyj.2005.10.002

Cited by 82 publications

(59 citation statements)

References 27 publications

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“…Close agreement between these results as they related to the precision of the reference method was observed. Despite this study stating that transmittance spectroscopy is more accurate than reflectance, it can be clearly observed from Table 3 that the spectroscopic mode most commonly used in the literature, in the area of cheese compositional analysis, is reflectance mode (Blazquez et al 2004;Lee et al 1997;Pérez-Marín et al 2001;Rodriguez-Otero et al 1994;da Costa Filho and Volery 2005;Karoui et al 2006a;Skeie et al 2006;Downey et al 2005). These authors report predictions with varying degrees of accuracy, but overall, the results are extremely accurate.…”

Section: Transmittance Vs Reflectance Spectroscopy For Determining Comentioning

confidence: 82%

“…Just as it can be seen from Table 3 that reflectance spectroscopy has been used most often in the area of cheese compositional analysis, it can also be quickly noticed that NIR spectroscopy has been used as a tool in this analysis much more frequently than MIR spectroscopy (Blazquez et al 2004;Čurda and Kukačková 2002;Lee et al 1997;Pérez-Marín et al 2001;Rodriguez-Otero et al 1994;Wittrup and Nørgaard 1998;da Costa Filho and Volery 2005;Karoui et al 2006a;Skeie et al 2006;Downey et al 2005). McQueen et al (1995) carried out a comparison of NIR and MIR spectroscopic techniques in obtaining protein, fat, and moisture contents of 24 cheese samples.…”

Section: Nir Vs Mir Spectroscopy For Determining Compositionmentioning

confidence: 99%

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Application of Near and Mid-Infrared Spectroscopy to Determine Cheese Quality and Authenticity

Woodcock

Fagan

O’Donnell

et al. 2007

Food Bioprocess Technol

142

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This paper reviews the current state of development of both near-infrared (NIR) and mid-infrared (MIR) spectroscopic techniques for process monitoring, quality control, and authenticity determination in cheese processing. Infrared spectroscopy has been identified as an ideal process analytical technology tool, and recent publications have demonstrated the potential of both NIR and MIR spectroscopy, coupled with chemometric techniques, for monitoring coagulation, syneresis, and ripening as well as determination of authenticity, composition, sensory, and rheological parameters. Recent research is reviewed and compared on the basis of experimental design, spectroscopic and chemometric methods employed to assess the potential of infrared spectroscopy as a technology for improving process control and quality in cheese manufacture. Emerging research areas for these technologies, such as cheese authenticity and food chain traceability, are also discussed.

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Section: Transmittance Vs Reflectance Spectroscopy For Determining Comentioning

confidence: 82%

Section: Nir Vs Mir Spectroscopy For Determining Compositionmentioning

confidence: 99%

Application of Near and Mid-Infrared Spectroscopy to Determine Cheese Quality and Authenticity

Woodcock

Fagan

O’Donnell

et al. 2007

Food Bioprocess Technol

142

View full text Add to dashboard Cite

show abstract

“…For instance, Karoui et al (2006) reported determination coefficients (R 2 ) of 0.92 for fat and 0.82 for total nitrogen quantification in samples of European Emmental cheese with NIRS. Its PLSR models were obtained with 10 and 7 LVs, respectively.…”

Section: Resultsmentioning

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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“…Setelah dihasilkan koefisien korelasi (R 2 ) dan RPD pada set kalibrasi dan validasi, nilai-nilai tersebut harus memenuhi syarat. Menurut Williams (2003) dalam Karoui et al (2006), nilai R 2 diantara 0.66 dan 0.81 mengindikasikan prediksi mendekati nilai kuantitatif. Nilai diantara 0.82 dan 0.9 menunjukkan prediksi yang baik dan R 2 diatas 0.91 menunjukkan prediksi yang sangat baik.…”

Section: Kalibrasi Spektrum Nir Kelapa Sawitunclassified

“…Penggunaan DG1 menghasilkan R 2 (kalibrasi) bernilai 0.84, R 2 (validasi) bernilai 0.77 dan RPD 2.06.Sehingga dengan nilai R 2 yang baik dan RPD lebih dari 2, dapat dikatakan model PLS yang dibentuk baik untuk menentukan nilai aktual total karoten. DG1 merupakan metode untuk mengkalkulasi turunan orde pertama atau orde yang lebih besar yang meliputi faktor smoothing didalamnya, sehingga dapat menentukan seberapa besar variable yang berdekatan untuk memprediksi pendekatan polinomial pada suatu turunan (Karoui et al 2006).…”

Section: Kandungan Kimiaunclassified

Prediction of Oil Palm Fresh Fruit Bunch (FFB) Water Content and Total Carotene Using NIR Spectroscopy

Iqbal¹,

Herodian²,

Widodo³

2014

JTEP

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PendahuluanPenentuan kematangan Tandan Buah Segar (TBS) sawit di perkebunan sangat mempengaruhi rendemen dalam produksi minyak sawit. Apabila minyak pada buah mentah atau lewat matang ikut diekstraksi, maka dapat menurunkan hasil rendemen. Salah satu upaya peningkatan rendemen minyak yaitu dengan dengan mengoptimalkan kegiatan penentuan kematangan buah, karena sampai saat ini masih menggunakan metode konvensional yaitu dengan melihat secara visual. TBS dikatakan layak panen apabila sudah menjatuhkan brondol (buah kecil) sebanyak 10-15 butir. Kenyataan di lapangan, terdapat TBS yang sulit menjatuhkan brondol atau brondol tersangkut di sela pelepah. Penentuan secara konvensional ini juga sangat bergantung pada pengalaman, kondisi psikis serta pengetahuan pemanen saat menentukan kematangan buah. Technical Paper Pendugaan Kadar Air dan Total Karoten Tandan Buah Segar (TBS) Kelapa Sawit Menggunakan NIR Spektroskopi Keywords: Fresh Fruit Bunch (FFB) maturity, NIR spectra, calibration model, water content, total carotene AbstrakTujuan dari penelitian ini adalah untuk membangun model kalibrasi dari kadar air dan total karotenyang dapat dijadikan standar kematangan buah. Terdapat tiga tahapan pada penelitian ini, pertama akuisisi spektrum Near Infrared (NIR) pada 60 sampel menggunakan NIRFlex N-500. Langkah selanjutnya adalah pengujiankadar air dan total karoten tiap sampel secara destruktif. Langkah terakhir adalah pembuatan model kalibrasi menggunakan metode (Partial Least Square) PLS dan menerapkan pretreatment data Standard Normal Variate (SNV), normalisasi (N01), dan First Derivative Savitzky-Golay 9 titik (DG1). Hasil menunjukkan bahwa kadar air dapat diprediksi dengan baik menggunakan SNV dengan R 2 (kalibrasi) = 0.89 dan R 2 (validasi) = 0.88 dan RPD = 2.84. Total karoten juga dapat diprediksi dengan baik menggunakan DG1 dengan R 2 (kalibrasi) = 0.84 dan R 2 (validasi) = 0.77 dan RPD = 2.06.

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Chemical characterisation of European Emmental cheeses by near infrared spectroscopy using chemometric tools

Cited by 82 publications

References 27 publications

Application of Near and Mid-Infrared Spectroscopy to Determine Cheese Quality and Authenticity

Application of Near and Mid-Infrared Spectroscopy to Determine Cheese Quality and Authenticity

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

Prediction of Oil Palm Fresh Fruit Bunch (FFB) Water Content and Total Carotene Using NIR Spectroscopy

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