Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
4.2
3.0
Journals
Animals
Special Issues
From Milk to Cheese: Phenotypic and Genetic Background of Milk...
share announcement

From Milk to Cheese: Phenotypic and Genetic Background of Milk and Cheese Related Traits

A special issue of Animals (ISSN 2076-2615). This special issue belongs to the section "Animal Genetics and Genomics".

Deadline for manuscript submissions: closed (31 December 2021) | Viewed by 7723

Special Issue Editors

Dr. Giorgia Stocco

E-Mail Website
Guest Editor
Department of Veterinary Science, University of Parma, Via del Taglio 10, I-43126 Parma, Italy
Interests: dairy science; milk quality; milk minerals; coagulation properties; dairy products; cheese-making
Dr. Claudio Cipolat-Gotet

E-Mail Website
Guest Editor
Department of Veterinary Science, University of Parma, Via del Taglio 10, 43126 Parma, Italy
Interests: dairy cattle; milk quality; milk coagulation properties; cheese-making; infrared spectroscopy
Dr. Michela Ablondi

E-Mail Website
Guest Editor
Department of Veterinary Science, University of Parma, Via del Taglio 10, I-43126 Parma, Italy
Interests: cattle breeding; animal genetics; statistical genetics; genomics; quantitative genetics; genetic diversity; horse genetics
Special Issues, Collections and Topics in MDPI journals
Dr. Pietro Paschino

E-Mail Website
Guest Editor
Department of Veterinary Medicine, University of Sassari, Via Vienna 2, I-07100 Sassari, Italy
Interests: animal production; ruminant nutrition; dairy science; milk quality; milk coagulation properties; dairy products
Dr. Christos Dadousis

E-Mail Website
Guest Editor
Department of Agriculture, Food, Environment and Forestry, University of Firenze, I-50144 Firenze, Italy
Interests: animal breeding & genetics; quantitative genetics; statistical genetics/genomics; dairy and meat science
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

World milk production is almost entirely derived from cattle, buffaloes, goats, and sheep. The largest part of this milk is used for cheese production. Actually, cheese yield is the key factor for the profitability of dairy industries, and it is the result of a complex process in which several factors are involved, from herd management aspects and animal features, to milk composition, milk pre-treatments, and cheese-making conditions. Deeper studies on the phenotypic and genetic aspects of milk and cheese are fundamental in order to boost the dairy industry at farm, breeding, and dairy plant levels. Currently, available tools, such as infrared spectroscopy technologies, allow the collection of novel phenotypes in milk in a fast and cost-effective way, from both bulk and individual milk. However, exploiting this information at an animal level would open the way for genetic analysis, and thereby for selective breeding. The aims of this Special Issue are mainly to: 1) investigate further the relationships among milk and cheese-related traits in the 4 main dairy species, 2) consider the predictability of novel milk components, technological traits of milk, and different measures of cheese yield, and 3) study the genetic background of novel milk and cheese-related traits.

Dr. Giorgia Stocco
Dr. Claudio Cipolat-Gotet
Dr. Michela Ablondi
Dr. Pietro Paschino
Dr. Christos Dadousis
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Animals is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • milk composition
  • minerals
  • proteins
  • milk coagulation
  • cheese-making
  • cheese yield
  • infrared spectroscopy
  • genomics
  • quantitative genetics

Published Papers (3 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

14 pages, 1072 KiB  
Article
Genome-Wide Identification of Candidate Genes for Milk Production Traits in Korean Holstein Cattle
by Sangwook Kim, Byeonghwi Lim, Joohyeon Cho, Seokhyun Lee, Chang-Gwon Dang, Jung-Hwan Jeon, Jun-Mo Kim and Jungjae Lee
Animals 2021, 11(5), 1392; https://doi.org/10.3390/ani11051392 - 13 May 2021
Cited by 12 | Viewed by 2886
Abstract
We performed a genome-wide association study and fine mapping using two methods (single marker regression: frequentist approach and Bayesian C (BayesC): fitting selected single nucleotide polymorphisms (SNPs) in a Bayesian framework) through three high-density SNP chip platforms to analyze milk production phenotypes in [...] Read more.
We performed a genome-wide association study and fine mapping using two methods (single marker regression: frequentist approach and Bayesian C (BayesC): fitting selected single nucleotide polymorphisms (SNPs) in a Bayesian framework) through three high-density SNP chip platforms to analyze milk production phenotypes in Korean Holstein cattle (n = 2780). We identified four significant SNPs for each phenotype in the single marker regression model: AX-311625843 and AX-115099068 on Bos taurus autosome (BTA) 14 for milk yield (MY) and adjusted 305-d fat yield (FY), respectively, AX-428357234 on BTA 18 for adjusted 305-d protein yield (PY), and AX-185120896 on BTA 5 for somatic cell score (SCS). Using the BayesC model, we discovered significant 1-Mb window regions that harbored over 0.5% of the additive genetic variance effects for four milk production phenotypes. The concordant significant SNPs and 1-Mb window regions were characterized into quantitative trait loci (QTL). Among the QTL regions, we focused on a well-known gene (diacylglycerol O-acyltransferase 1 (DGAT1)) and newly identified genes (phosphodiesterase 4B (PDE4B), and anoctamin 2 (ANO2)) for MY and FY, and observed that DGAT1 is involved in glycerolipid metabolism, fat digestion and absorption, metabolic pathways, and retinol metabolism, and PDE4B is involved in cAMP signaling. Our findings suggest that the candidate genes in QTL are strongly related to physiological mechanisms related to the fat production and consequent total MY in Korean Holstein cattle. Full article
(This article belongs to the Special Issue From Milk to Cheese: Phenotypic and Genetic Background of Milk and Cheese Related Traits)
►▼ Show Figures

Figure 1

9 pages, 255 KiB  
Article
Evaluation of Different Test-Day Milk Recording Protocols by Wood’s Model Application for the Estimation of Dairy Goat Milk and Milk Constituent Yield
by Vincenzo Landi, Aristide Maggiolino, Angela Salzano, Salvatore Claps, Pasquale De Palo, Domenico Rufrano, Giuseppina Pedota and Gianluca Neglia
Animals 2021, 11(4), 1058; https://doi.org/10.3390/ani11041058 - 08 Apr 2021
Viewed by 1642
Abstract
Goats have important social and economic roles in many countries because of their ability to survive and be productive in marginal areas. The overarching aim of this study was to compare the application of Wood’s model to different test-day milk recording protocols for [...] Read more.
Goats have important social and economic roles in many countries because of their ability to survive and be productive in marginal areas. The overarching aim of this study was to compare the application of Wood’s model to different test-day milk recording protocols for estimation of total milk, fat, and protein yield in dairy goats. A total of 465 goats were used (Garganica, 78; Girgentana, 81; Jonica, 76; Maltese, 77; Red Mediterranean, 76; Saanen, 77). Milk yield was recorded every 15 days throughout lactation of 210 days, for a total of 14 collection days, during both morning and afternoon milking sessions. Milk samples were collected and analyzed for protein and fat. The fat-corrected milk was standardized at 35g fat/kg of milk. Wood models showed high R2 values, and thus good fitting, in all the considered breeds. Wood model applied to first, second, fourth, and sixth month recordings (C) and ICAR estimation showed total milk yield very close to Wood’s model applied to all 14 recordings (A) (p > 0.38). Differently, Wood’s model applied to the first, second, third, and fourth month recording (B) estimation showed great differences (p < 0.01). This could be applied for farms that had the necessity to synchronize flock groups for kidding in order to produce kid meat. In farms that apply the estrus induction and/or synchronization for kidding, it would be possible to perform only four test-day milk recordings and to apply the Wood’s model on them in order to obtain the estimation of total milk, fat, and protein yield during lactation for animals inscribed, or to be inscribed, to the genealogical book. Full article
(This article belongs to the Special Issue From Milk to Cheese: Phenotypic and Genetic Background of Milk and Cheese Related Traits)
13 pages, 2561 KiB  
Article
Association Analysis between SPP1, POFUT1 and PRLR Gene Variation and Milk Yield, Composition and Coagulation Traits in Sarda Sheep
by Maria Luisa Dettori, Michele Pazzola, Elena Petretto and Giuseppe Massimo Vacca
Animals 2020, 10(7), 1216; https://doi.org/10.3390/ani10071216 - 17 Jul 2020
Cited by 4 | Viewed by 2332
Abstract
Many studies focus on the identification of genomic regions that undergo selective processes, where evidence of selection is revealed and positional candidate genes are identified. The aim of the research was to evaluate the association between positional candidate genes, namely secreted phosphoprotein 1 [...] Read more.
Many studies focus on the identification of genomic regions that undergo selective processes, where evidence of selection is revealed and positional candidate genes are identified. The aim of the research was to evaluate the association between positional candidate genes, namely secreted phosphoprotein 1 (SPP1, sheep chromosome Ovis aries OAR6, 36.651–36.658 Mb), protein O-fucosyltransferase 1 (POFUT1, OAR13, 61.006–61.027 Mb) and prolactin receptor (PRLR, OAR16, 38.969–39.028 Mb) with milk yield, composition and coagulation traits. Eight single nucleotide polymorphisms (SNPs) mapping to the three genes were genotyped in 380 Sarda dairy sheep. Statistical analysis revealed an association between SNP rs161844011 at SPP1 (chromosome position Oar_v3 OAR6:36651870, gene region exon 7) and somatic cell score, while POFUT1 SNP rs424501869 (OAR13:61007495, intron 1) was associated with curd firmness both 45 and 60 min after rennet addition (p = 0.015 and p = 0.007, respectively). SNP rs400874750 at PRLR gene (OAR16:39004070, intron 2) had a significant association with lactose content (p = 0.020), somatic cell score (p = 0.038), rennet coagulation time (p = 0.018) and curd firming time (p = 0.047). The outcome of this research confirmed predictions based on genomic studies, producing new information regarding the SPP1, POFUT1 and PRLR genes, which may be useful for future breeding schemes. Full article
(This article belongs to the Special Issue From Milk to Cheese: Phenotypic and Genetic Background of Milk and Cheese Related Traits)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-3
Back to TopTop