Projects
This project will deliver large scale phenotyping for eating quality of meat, feed efficiency, and methane emission within the Danish slaughter calf production. With these registrations available it will - for the first time in the Nordic countries - be possible to estimate genomic breeding values (GEBV’s) for the beef bull suitability for use in dairy crossbreeding programs. GEBV’s can be used for selection of the best AI-beef bulls. The result in future will be crossbred slaughter calves with a significant higher genetic level for eating quality of meat, feed efficiency, and methane emission, through the developed GEBV’s for eating quality, feed efficiency and methane emission for Danish Blue, Charolais and Angus AI-bulls. It will provide a strong lift for the whole Danish cattle sector.
The strenght of breeding improvement are that they accumulate. We expect that the crossbred calves after 10 year of selection will show a reduction of 290 kg DMI/calf, a reduced methane emission of 49 kg CO2 equivalents/calf and an increased level of intra muscular fat of 0.36 percentage units. The overall effect of the project is expected to be an increased earning of 238 – 266 billion DKR 10 years after the end of the project. All important players in “the soil to table chain” are involved to ensure implementation beyond the project period. The result will be a better eating quality, lower climate foot print and a better earning for the producer
Department of Food Science is responsible for WP1 – Assessment of eating quality and development of computer image analysis for eating quality traits. (WPL AU-FOOD – Margrethe Therkildsen, Frontmatec, SEGES, DC Beef)
Aim – To deliver cheap phenotypic data on eating quality with high correlation to the “real trait” of a large population of crossbred calves (12,000 calves) in order to describe the phenotype related to eating quality.
1.1 For the 1,000 beef cattle from Animal set 1 the striploin will be removed 48 h post mortem and an image is captured under standardized conditions of each end of the striploin, before the pH and color (Minolta) is measured and a sample is secured for chemical analysis of IMF (Soxhlet) and a sample is aged for additional 5 days before measurement of WBSF. The meat quality traits is used in the optimization of computer image analysis and modelling of the intramuscular fat and texture of the meat including.
1.2 For the 12,000 crossbreed calves from Animal set 2 the eating quality will be measured based on the CIA method developed in WP1.1. The method is controlled based on random sub-samples every half year, which will have the meat quality measured the conventional way.
Funding: GUDP as well as co-funding from all participating partners
Collaborator: SEGES, AU-MBG, Danish Crown, VikingDanmark, VikingGenetics, Alflex, Frontmatec
Description
01/01-2019 → 31/12-2022
Katrine Overgaard Poulsen, Dennis Sandris Nielsen, Ulrik Kræmer Sundekilde & Niels Uldbjerg
• First, we want to determine the variability of breast milk nutrients by application of metabolomics, proteomics and glycomics. The production of human breast milk has a high maternal metabolic cost. Thus, we hypothesise that maternal health attributes (metabolic dysfunction or obesity) influence which breast milk nutrients are made available to the infant.
• Second, we want to establish the microbiome of breast milk. Maternal obesity can lead to an apparent gut microbial ecology and increases the risk of obesity for the child. Thus, we hypothesise that maternal obesity confers distinct microorganisms to the infant.
• Third, we want to identify biological mechanisms for how breast milk nutrients are metabolised in the infants. Infants exclusively breast-feeding offer total compliance. Thus, we hypothesise that by deconstructing breast milk components and markers of infant metabolism through clever analysis of infant urine and feces, we can deduce the bioactivity of breast milk nutrients.Description
18/05-2019 → 18/05-2023
Det overordnede mål med RENEW er at skabe en cirkulær bioøkonomisk forretning ved at udnytte calciumrige sidestrømme fra valleproduktionen til at udvikle et funktionelt calcium ingrediens-koncept, der effektivt kan fremme knoglesundheden.
Særligt den ældre befolkning er i risiko for at miste knoglemasse, og derfor er det essentielt og af stor værdi at udvikle effektive strategier, der kan sikre en effektiv calciumoptagelse hos denne betydeligt voksende befolkningsgruppe. En central målsætning for RENEW er derfor at gennemføre et 1-årigt interventionsstudie med henblik på at dokumentere, at det funktionelle calcium ingrediens kan mindske knogletab i postmenopausale kvinder. Derudover vil RENEW kortlægge om en kombination af det biofunktionelle mælkecalcium med en præbiotisk fiberkilde (inulin) ydermere kan øge calciumoptagelsen og dermed styrke knogleopbygningen. Hypotesen er, at tarmbakteriernes fermentering af kostfibrene vil sikre et tarmmiljø, der fremmer calciumoptagelsen, og en målsætning er også at opnå en detaljeret forståelse for disse aspekter ved at gennemføre metabolomics og microbiom analyser. Ved at kombinere disse data med machine learning teknikker i en omfattende dataanalyse vil vi desuden tilegne os forståelse for hvilke faktorer, der er afgørende for forsøgspersonernes respons. Denne viden vil på sigt være værdifuld i forhold til at udvikle skræddersyede fødevareprodukter.
Description
01/04-2020 → 31/03-2025
Hanne Christine S. Bertram, Axel Kornerup Hansen & Dennis Sandris Nielsen
01/05-2020 → 31/12-2022
