Literature DB >> 25958274

Genetic parameters of cheese yield and curd nutrient recovery or whey loss traits predicted using Fourier-transform infrared spectroscopy of samples collected during milk recording on Holstein, Brown Swiss, and Simmental dairy cows.

A Cecchinato1, A Albera2, C Cipolat-Gotet2, A Ferragina2, G Bittante2.   

Abstract

Cheese yield is the most important technological parameter in the dairy industry in many countries. The aim of this study was to infer (co)variance components for cheese yields (CY) and nutrient recoveries in curd (REC) predicted using Fourier-transform infrared (FTIR) spectroscopy of samples collected during milk recording on Holstein, Brown Swiss, and Simmental dairy cows. A total of 311,354 FTIR spectra representing the test-day records of 29,208 dairy cows (Holstein, Brown Swiss, and Simmental) from 654 herds, collected over a 3-yr period, were available for the study. The traits of interest for each cow consisted of 3 cheese yield traits (%CY: fresh curd, curd total solids, and curd water as a percent of the weight of the processed milk), 4 curd nutrient recovery traits (REC: fat, protein, total solids, and the energy of the curd as a percent of the same nutrient in the processed milk), and 3 daily cheese production traits (daily fresh curd, total solids, and the water of the curd per cow). Calibration equations (freely available upon request to the corresponding author) were used to predict individual test-day observations for these traits. The (co)variance components were estimated for the CY, REC, milk production, and milk composition traits via a set of 4-trait analyses within each breed. All analyses were performed using REML and linear animal models. The heritabilities of the %CY were always higher for Holstein and Brown Swiss cows (0.22 to 0.33) compared with Simmental cows (0.14 to 0.18). In general, the fresh cheese yield (%CYCURD) showed genetic variation and heritability estimates that were slightly higher than those of its components, %CYSOLIDS and %CYWATER. The parameter RECPROTEIN was the most heritable trait in all the 3 breeds, with values ranging from 0.32 to 0.41. Our estimation of the genetic relationships of the CY and REC with milk production and composition revealed that the current selection strategies used in dairy cattle are expected to exert only limited effects on the REC traits. Instead, breeders may be able to exploit genetic variations in the %CY, particularly RECFAT and RECPROTEIN. This last component is not explained by the milk protein content, suggesting that its direct selection could be beneficial for cheese production aptitude. Collectively, our findings indicate that breeding strategies aimed at enhancing CY and REC could be easily and rapidly implemented for dairy cattle populations in which FTIR spectra are routinely acquired from individual milk samples.
Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  cheese yield; dairy breed; genetic parameter; mid-infrared spectroscopy; whey loss

Mesh:

Year:  2015        PMID: 25958274     DOI: 10.3168/jds.2014-8599

Source DB:  PubMed          Journal:  J Dairy Sci        ISSN: 0022-0302            Impact factor:   4.034


  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.  From cow to cheese: genetic parameters of the flavour fingerprint of cheese investigated by direct-injection mass spectrometry (PTR-ToF-MS).

Authors:  Matteo Bergamaschi; Alessio Cecchinato; Franco Biasioli; Flavia Gasperi; Bruno Martin; Giovanni Bittante
Journal:  Genet Sel Evol       Date:  2016-11-16       Impact factor: 4.297

3.  Comparative study on production, reproduction and functional traits between Fleckvieh and Braunvieh cattle.

Authors:  Ludovic-Toma Cziszter; Daniela-Elena Ilie; Radu-Ionel Neamt; Florin-Cristian Neciu; Silviu-Ilie Saplacan; Dinu Gavojdian
Journal:  Asian-Australas J Anim Sci       Date:  2016-11-17       Impact factor: 2.509

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.  Genetic Parameters of Different FTIR-Enabled Phenotyping Tools Derived from Milk Fatty Acid Profile for Reducing Enteric Methane Emissions in Dairy Cattle.

Authors:  Giovanni Bittante; Claudio Cipolat-Gotet; Alessio Cecchinato
Journal:  Animals (Basel)       Date:  2020-09-15       Impact factor: 2.752

6.  Sequence-based genome-wide association study of individual milk mid-infrared wavenumbers in mixed-breed dairy cattle.

Authors:  Kathryn M Tiplady; Thomas J Lopdell; Edwardo Reynolds; Richard G Sherlock; Michael Keehan; Thomas Jj Johnson; Jennie E Pryce; Stephen R Davis; Richard J Spelman; Bevin L Harris; Dorian J Garrick; Mathew D Littlejohn
Journal:  Genet Sel Evol       Date:  2021-07-20       Impact factor: 4.297

7.  Phenotypic and genetic variation of ultraviolet-visible-infrared spectral wavelengths of bovine meat.

Authors:  Giovanni Bittante; Simone Savoia; Alessio Cecchinato; Sara Pegolo; Andrea Albera
Journal:  Sci Rep       Date:  2021-07-06       Impact factor: 4.379

8.  Integration of GWAS, pathway and network analyses reveals novel mechanistic insights into the synthesis of milk proteins in dairy cows.

Authors:  Sara Pegolo; Núria Mach; Yuliaxis Ramayo-Caldas; Stefano Schiavon; Giovanni Bittante; Alessio Cecchinato
Journal:  Sci Rep       Date:  2018-01-12       Impact factor: 4.379

9.  Effect of Abalone Hydrolysates Encapsulated by Double Emulsion on the Physicochemical and Sensorial Properties of Fresh Cheese.

Authors:  HeeJeong Choi; Soo-Jin Kim; Sang-Yoon Lee; Mi-Jung Choi
Journal:  Korean J Food Sci Anim Resour       Date:  2017-04-30       Impact factor: 2.622

10.  Integrated PTR-ToF-MS, GWAS and biological pathway analyses reveal the contribution of cow's genome to cheese volatilome.

Authors:  Sara Pegolo; Matteo Bergamaschi; Flavia Gasperi; Franco Biasioli; Alessio Cecchinato; Giovanni Bittante
Journal:  Sci Rep       Date:  2018-11-19       Impact factor: 4.379

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.