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Prediction of fatty acid composition in intact and minced fat of European autochthonous pigs breeds by near infrared spectroscopy.
Parrini, Silvia; Sirtori, Francesco; Candek-Potokar, Marjeta; Charneca, Rui; Crovetti, Alessandro; Kusec, Ivona Djurkin; Sanchez, Elena González; Cebrian, Mercedes Maria Izquierdo; Garcia, Ana Haro; Karolyi, Danijel; Lebret, Benedicte; Ortiz, Alberto; Panella-Riera, Nuria; Petig, Matthias; Jesus da Costa Pires, Preciosa; Tejerina, David; Razmaite, Violeta; Aquilani, Chiara; Bozzi, Riccardo.
Affiliation
  • Parrini S; Department of Agriculture, Food, Environment and Forestry, University of Florence, Piazzale delle Cascine 18, 50144, Florence, Italy.
  • Sirtori F; Department of Agriculture, Food, Environment and Forestry, University of Florence, Piazzale delle Cascine 18, 50144, Florence, Italy. francesco.sirtori@unifi.it.
  • Candek-Potokar M; Kmetijski Institut Slovenije, Hacquetova ulica 17, 1000, Ljubljana, Slovenia.
  • Charneca R; MED - Mediterranean Institute for Agriculture, Environment and Development and CHANGE - Global Change and Sustainability Institute, Departamento de Zootecnia, Escola de Ciências e Tecnologia, Universidade de Évora, Pólo da Mitra, Ap. 94, 7006-554, Évora, Portugal.
  • Crovetti A; Department of Agriculture, Food, Environment and Forestry, University of Florence, Piazzale delle Cascine 18, 50144, Florence, Italy.
  • Kusec ID; Department for Animal Production and Biotechnology, Faculty of Agrobiotechnical Sciences Osijek, Vladimira Preloga 1, Osijek, Croatia.
  • Sanchez EG; Department of Animal Production and Food Science, School of Agricultural Engineering, University of Extremadura, Avda. Adolfo Suarez, s/n, 06007, Badajoz, Spain.
  • Cebrian MMI; Centre of Scientific and Technological Research of Extremadura, CICYTEX, Badajoz, Spain.
  • Garcia AH; Department of Nutrition and Sustainable Animal Production, Estacion Experimental del Zaidin, Spanish National Research Council, CSIC, Profesor Albareda 1, 18008, Granada, Spain.
  • Karolyi D; Department of Animal Science, University of Zagreb Faculty of Agriculture, Svetosimunska cesta 25, 10000, Zagreb, Croatia.
  • Lebret B; PEGASE, INRAE, Institut Agro, 35590, Saint-Gilles, France.
  • Ortiz A; Centre of Scientific and Technological Research of Extremadura, CICYTEX, Badajoz, Spain.
  • Panella-Riera N; IRTA-Monells, Finca Camps i Armet, s/n, 17121, Monells, Spain.
  • Petig M; BESH, Haller Str. 20, 74549, Wolpertshausen, Germany.
  • Jesus da Costa Pires P; Center for Research and Development in Agri-Food Systems and Sustainability (CISAS), Polytechnic Institute of Viana do Castelo. Praça General Barbosa, 4900-347, Viana do Castelo, Portugal.
  • Tejerina D; Centre of Scientific and Technological Research of Extremadura, CICYTEX, Badajoz, Spain.
  • Razmaite V; Animal Science Institute, Lithuanian University of Health Sciences, 82317, Baisogala, Lithuania.
  • Aquilani C; Department of Agriculture, Food, Environment and Forestry, University of Florence, Piazzale delle Cascine 18, 50144, Florence, Italy.
  • Bozzi R; Department of Agriculture, Food, Environment and Forestry, University of Florence, Piazzale delle Cascine 18, 50144, Florence, Italy.
Sci Rep ; 13(1): 7874, 2023 05 15.
Article in En | MEDLINE | ID: mdl-37188692
The fatty acids profile has been playing a decisive role in recent years, thanks to technological, sensory and health demands from producers and consumers. The application of NIRS technique on fat tissues, could lead to more efficient, practical, and economical in the quality control. The study aim was to assess the accuracy of Fourier Transformed Near Infrared Spectroscopy technique to determine fatty acids composition in fat of 12 European local pig breeds. A total of 439 spectra of backfat were collected both in intact and minced tissue and then were analyzed using gas chromatographic analysis. Predictive equations were developed using the 80% of samples for the calibration, followed by full cross validation, and the remaining 20% for the external validation test. NIRS analysis of minced samples allowed a better response for fatty acid families, n6 PUFA, it is promising both for n3 PUFA quantification and for the screening (high, low value) of the major fatty acids. Intact fat prediction, although with a lower predictive ability, seems suitable for PUFA and n6 PUFA while for other families allows only a discrimination between high and low values.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Fatty Acids, Omega-3 / Fatty Acids Type of study: Prognostic_studies / Risk_factors_studies Limits: Animals Language: En Journal: Sci Rep Year: 2023 Type: Article Affiliation country: Italy

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Fatty Acids, Omega-3 / Fatty Acids Type of study: Prognostic_studies / Risk_factors_studies Limits: Animals Language: En Journal: Sci Rep Year: 2023 Type: Article Affiliation country: Italy