Literature DB >> 22440358

Effectiveness of mid-infrared spectroscopy to predict fatty acid composition of Brown Swiss bovine milk.

M De Marchi1, M Penasa, A Cecchinato, M Mele, P Secchiari, G Bittante.   

Abstract

Mid-infrared spectroscopy (MIR) is used to predict fatty acid (FA) composition of individual milk samples (n=267) of Brown Swiss cows. FAs were analyzed by gas chromatography as a reference method. Samples were scanned (4000 to 900 cm-1) by MIR, and predictive models were developed using modified partial least squares regressions with full cross-validation. The methods using a first derivative or multiplicative scatter corrected plus first derivative resulted, on average, in the best predictions. Coefficients of correlation between measured and predicted C8:0, C10:0, C12:0, C14:0, anteiso-C17:0, c9-C18:1, and medium- and long-chain FA, and saturated, monounsaturated and unsaturated FA ranged from 0.71 to 0.77, suggesting that prediction models can be implemented in milk recording schemes to routinely collect information on FA composition from the whole Brown Swiss population for breeding purposes.

Entities:  

Year:  2011        PMID: 22440358     DOI: 10.1017/S1751731111000747

Source DB:  PubMed          Journal:  Animal        ISSN: 1751-7311            Impact factor:   3.240


  11 in total

1.  Bayesian regression models outperform partial least squares methods for predicting milk components and technological properties using infrared spectral data.

Authors:  A Ferragina; G de los Campos; A I Vazquez; A Cecchinato; G Bittante
Journal:  J Dairy Sci       Date:  2015-09-18       Impact factor: 4.034

2.  Genome-wide association mapping for milk fat composition and fine mapping of a QTL for de novo synthesis of milk fatty acids on bovine chromosome 13.

Authors:  Hanne Gro Olsen; Tim Martin Knutsen; Achim Kohler; Morten Svendsen; Lars Gidskehaug; Harald Grove; Torfinn Nome; Marte Sodeland; Kristil Kindem Sundsaasen; Matthew Peter Kent; Harald Martens; Sigbjørn Lien
Journal:  Genet Sel Evol       Date:  2017-02-13       Impact factor: 4.297

3.  Multi-population GWAS and enrichment analyses reveal novel genomic regions and promising candidate genes underlying bovine milk fatty acid composition.

Authors:  G Gebreyesus; A J Buitenhuis; N A Poulsen; M H P W Visker; Q Zhang; H J F van Valenberg; D Sun; H Bovenhuis
Journal:  BMC Genomics       Date:  2019-03-06       Impact factor: 3.969

Review 4.  The evolving role of Fourier-transform mid-infrared spectroscopy in genetic improvement of dairy cattle.

Authors:  K M Tiplady; T J Lopdell; M D Littlejohn; D J Garrick
Journal:  J Anim Sci Biotechnol       Date:  2020-04-17

5.  Estimation of Fatty Acids in Intramuscular Fat of Beef by FT-MIR Spectroscopy.

Authors:  María José Beriain; Francisco C Ibañez; Edurne Beruete; Inmaculada Gómez; Miguel Beruete
Journal:  Foods       Date:  2021-01-13

6.  Fatty Acid Prediction in Bovine Milk by Attenuated Total Reflection Infrared Spectroscopy after Solvent-Free Lipid Separation.

Authors:  Christopher Karim Akhgar; Vanessa Nürnberger; Marlene Nadvornik; Margit Velik; Andreas Schwaighofer; Erwin Rosenberg; Bernhard Lendl
Journal:  Foods       Date:  2021-05-11

7.  Unravelling genetic variation underlying de novo-synthesis of bovine milk fatty acids.

Authors:  Tim Martin Knutsen; Hanne Gro Olsen; Valeria Tafintseva; Morten Svendsen; Achim Kohler; Matthew Peter Kent; Sigbjørn Lien
Journal:  Sci Rep       Date:  2018-02-01       Impact factor: 4.379

8.  Prediction of Milk Coagulation Properties and Individual Cheese Yield in Sheep Using Partial Least Squares Regression.

Authors:  Massimo Cellesi; Fabio Correddu; Maria Grazia Manca; Jessica Serdino; Giustino Gaspa; Corrado Dimauro; Nicolò Pietro Paolo Macciotta
Journal:  Animals (Basel)       Date:  2019-09-07       Impact factor: 2.752

9.  Genetic Analysis of Milk Production Traits and Mid-Infrared Spectra in Chinese Holstein Population.

Authors:  Chao Du; Liangkang Nan; Lei Yan; Qiuyue Bu; Xiaoli Ren; Zhen Zhang; Ahmed Sabek; Shujun Zhang
Journal:  Animals (Basel)       Date:  2020-01-15       Impact factor: 2.752

Review 10.  Infrared Spectrometry as a High-Throughput Phenotyping Technology to Predict Complex Traits in Livestock Systems.

Authors:  Tiago Bresolin; João R R Dórea
Journal:  Front Genet       Date:  2020-08-20       Impact factor: 4.599

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