Chemical composition of meat cured products is important for its nutritional value, technological, and sensory quality. Conventional chemical analyses are time-consuming, expensive, and destructive. Advantages of NIR spectroscopy are its speed, simplicity, lowcost and the possibility to determine a large number of different parameters simultaneously in a large number of samples. This technology could be used to produce a nutritional label for each product adding value to high market price niche products. The aim of this study is to assess the ability of near infrared spectroscopy to predict chemical composition of Tuscan seasoned pig products. One hundred and two seasoned products were sampled (43 "cuore di spalla", 26 Prosciutto Toscano PDO and 33 "capocollo") and the following chemical components were determined: protein, intramuscular fat, ashes, saturated fatty acid, monounsaturated fatty acid, polyunsaturated fatty acid, omega-3 and omega-6 fatty acids. NIR spectra were acquired using a Thermo-FIsher Antaris II instrument; spectral data processing was performed by using TQ Analyst 8.6.12 software. Partial least squares (PLS) regression was applied in the calibration and the validation models; the models were fully cross-validated using the “leave-one-out” method. Calibration and cross validation models were developed for each product individually and grouping all the available data. Calibration correlation coefficients showed satisfying values (minimum R2=0.73), while cross-validation correlation coefficients, despite being generally acceptable, showed lower values (minimum R2=0.42). The highest R2 was found for fat content (correlation R2= 0.96, cross-validation R2= 0.95). The use of grouped data improved the predictive ability of FT-NIR; minimum R2 were 0.93 and 0.85 in calibration and cross-validation respectively. Our results, even if obtained on a reduced sample, showed how FT-NIRS could be used in routine analyses of pig seasoned products.

Predictive ability of FT-NIRS of meat quality in pork seasoned products / Crovetti, A.; Sirtori, F; Aquilani, C.; Franci, O.; Bozzi, R.. - In: ARCHIVOS DE ZOOTECNIA. - ISSN 0004-0592. - STAMPA. - 67:(2018), pp. 151-154. (Intervento presentato al convegno IX International Symposium on Mediterranean Pig tenutosi a Portalegre (Portugal) nel 3-5 Novembre 2016) [10.21071/AZ.V67ISUPPLEMENT.3593].

Predictive ability of FT-NIRS of meat quality in pork seasoned products

CROVETTI, ALESSANDRO;SIRTORI, FRANCESCO;AQUILANI, CHIARA;FRANCI, ORESTE;BOZZI, RICCARDO
2018

Abstract

Chemical composition of meat cured products is important for its nutritional value, technological, and sensory quality. Conventional chemical analyses are time-consuming, expensive, and destructive. Advantages of NIR spectroscopy are its speed, simplicity, lowcost and the possibility to determine a large number of different parameters simultaneously in a large number of samples. This technology could be used to produce a nutritional label for each product adding value to high market price niche products. The aim of this study is to assess the ability of near infrared spectroscopy to predict chemical composition of Tuscan seasoned pig products. One hundred and two seasoned products were sampled (43 "cuore di spalla", 26 Prosciutto Toscano PDO and 33 "capocollo") and the following chemical components were determined: protein, intramuscular fat, ashes, saturated fatty acid, monounsaturated fatty acid, polyunsaturated fatty acid, omega-3 and omega-6 fatty acids. NIR spectra were acquired using a Thermo-FIsher Antaris II instrument; spectral data processing was performed by using TQ Analyst 8.6.12 software. Partial least squares (PLS) regression was applied in the calibration and the validation models; the models were fully cross-validated using the “leave-one-out” method. Calibration and cross validation models were developed for each product individually and grouping all the available data. Calibration correlation coefficients showed satisfying values (minimum R2=0.73), while cross-validation correlation coefficients, despite being generally acceptable, showed lower values (minimum R2=0.42). The highest R2 was found for fat content (correlation R2= 0.96, cross-validation R2= 0.95). The use of grouped data improved the predictive ability of FT-NIR; minimum R2 were 0.93 and 0.85 in calibration and cross-validation respectively. Our results, even if obtained on a reduced sample, showed how FT-NIRS could be used in routine analyses of pig seasoned products.
2018
PROCEEDINGS IX Simposio Internacional sobre el Cerdo Mediterráneo
IX International Symposium on Mediterranean Pig
Portalegre (Portugal)
Crovetti, A.; Sirtori, F; Aquilani, C.; Franci, O.; Bozzi, R.
File in questo prodotto:
File Dimensione Formato  
Resumo_1428_94632.pdf

accesso aperto

Descrizione: Riassunto comunicazione
Tipologia: Pdf editoriale (Version of record)
Licenza: Tutti i diritti riservati
Dimensione 71.05 kB
Formato Adobe PDF
71.05 kB Adobe PDF
Predictive ability of FT-NIRS in the assessment of chemical composition of pork seasoned products.pdf

accesso aperto

Tipologia: Pdf editoriale (Version of record)
Licenza: Open Access
Dimensione 271.02 kB
Formato Adobe PDF
271.02 kB Adobe PDF

I documenti in FLORE sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1071644
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 2
  • ???jsp.display-item.citation.isi??? ND
social impact