Prediction of fatty acid composition in intact and minced fat of European autochthonous pigs breeds by Near infrared spectroscopy

Author:

Parrini Silvia1,Sirtori Francesco1,Čandek-Potokar Marjeta2,Charneca Rui3,Crovetti Alessandro1,Kušec Ivona Djurkin4,Sanchez Elena González5,Cebrian Mercedes Maria Izquierdo6,Garcia Ana Haro7,Karolyi Danijel8,Lebret Benedicte9,Ortiz Alberto6,Panella-Riera Nuria10,Petig Matthias11,Pires Preciosa Jesus da Costa12,Tejerina David6,Razmaite Violeta13,Aquilani Chiara1,Bozzi Riccardo1

Affiliation:

1. University of Florence

2. Kmetijski Inštitut Slovenije

3. Universidade de Évora

4. Faculty of Agrobiotechnical Sciences Osijek Vladimira

5. Department of Animal Production and Food Science, School of Agricultural Engineering, University of Extremadura

6. Centre of Scientific and Technological Research of Extremadura, CICYTEX

7. Spanish National Research Council, CSIC

8. University of Zagreb Faculty of Agriculture

9. PEGASE, INRAE, Institut Agro

10. IRTA-Monells

11. BESH

12. Center of Research and development in Agrifood System and Sustainability, Refóios do Lima

13. Lithuanian University of Health Sciences

Abstract

Abstract 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, n3 PUFA, n6 PUFA and for the screening (high, medium, 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.

Publisher

Research Square Platform LLC

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3