Genomic prediction of dry matter intake in dairy cattle from an international data set consisting of research herds in Europe, North America, and Australasia

Abstract The objective of this study was to examine the effects of diet quality on greenhouse gas emissions and dry matter intake (DMI). We used 42 mature, gestating Angus cows (600±69 kg; and BSC 5.3±1.1) with a wide range in DMI EPD (-1.36 to 2.29). Cows were randomly assigned to 2 diet sequences forage-concentrate (FC) or concentrate-forage(CF) determined by the diet they consumed in each period (forage or concentrate). The cows were adapted to the diet and the SmartFeed individual intake units for 14 d followed by 45 d of intake data collection for each period. Body weight was recorded on consecutive weigh days at the beginning and end of each period and then once every two wk for the duration of a period. Cows were exposed to the GreenFeed Emission Monitoring (GEM) system for no less than 9 d during each period. The GEM system was used to measure emissions of carbon dioxide (CO2) and methane (CH4). Only cows with a minimum of 20 total >3-m visits to the GEM were included in the data set. Data were analyzed in a crossover design using GLIMMIX in SASv.9.4. Within the CF sequence there was a significant, positive correlation between TMR DMI and CH4 (r=0.81) and TMR DMI and CO2 (r=0.69), however, gas emissions during the second period on the hay diet were not correlated with hay intake. There was a significant, positive correlation between hay DMI and CO2 (r=0.76) and hay DMI and CH4 (r=0.74) when cows first consumed forage (FC). In comparison to the CF sequence, cows on the FC sequence showed a positive correlation between CO2 and TMR DMI during the second period. There was also a significant positive correlation between hay and TMR DMI when assessed across (r=0.43) or within sequence (FC r=0.41, CF r=0.47).

Download Full-text

Evaluation of the equation for predicting dry matter intake of lactating dairy cows in the Korean feeding standards for dairy cattle

Asian-Australasian Journal of Animal Sciences ◽

10.5713/ajas.20.0684 ◽

2020 ◽

Author(s):

Mingyung Lee ◽

Junsung Lee ◽

Seoyoung Jeon ◽

Seong-Min Park ◽

Kwang-Seok Ki ◽

...

Keyword(s):

Dairy Cattle ◽

Dairy Cows ◽

Dry Matter ◽

Dry Matter Intake ◽

Lactating Dairy Cows

Download Full-text

Invited review: Determination of large-scale individual dry matter intake phenotypes in dairy cattle

Journal of Dairy Science ◽

10.3168/jds.2019-16454 ◽

2019 ◽

Vol 102 (9) ◽

pp. 7655-7663 ◽

Cited By ~ 7

Author(s):

D.J. Seymour ◽

A. Cánovas ◽

C.F. Baes ◽

T.C.S. Chud ◽

V.R. Osborne ◽

...

Keyword(s):

Dairy Cattle ◽

Dry Matter ◽

Large Scale ◽

Dry Matter Intake

Download Full-text

Factors influencing individual predicted total dry matter intake of dairy cattle on farms

Proceedings of the British Society of Animal Science ◽

10.1017/s1752756200005652 ◽

2001 ◽

Vol 2001 ◽

pp. 183-183

Author(s):

H.C.F. Wicks ◽

J.D. Leaver

Keyword(s):

Dairy Cattle ◽

Milk Production ◽

Body Condition ◽

Dry Matter ◽

Dry Matter Intake ◽

Genetic Merit ◽

Factors Influencing ◽

Commercial Farms ◽

Autumn And Winter ◽

Body Condition Scores

The aim was to estimate the influence of genetic merit (£PIN95) and level of concentrate feeding (Cgrp) on predicted total dry matter intake (tDMI) of individual cows, using records collected from commercial farms. The method described by Wicks & Leaver (2000) was used to estimate individual daily dry matter intakes from seven farms, totalling 4282 monthly records over a two-year period. The method was based on milk production records supplemented by body condition scores and height at withers, which were used to calculated the ME requirements of individual animals. All the records were collected, from autumn and winter (July to March) calving cows during the housed period (August to March).

Download Full-text

Investigation of major gene for milk yield, milking speed, dry matter intake, and body weight in dairy cattle

Journal of Applied Genetics ◽

10.1007/bf03194643 ◽

2006 ◽

Vol 47 (4) ◽

pp. 337-343 ◽

Cited By ~ 2

Author(s):

Burak Karacaören ◽

Haja N. Kadarmideen ◽

Luc L. G. Janss

Keyword(s):

Body Weight ◽

Dairy Cattle ◽

Milk Yield ◽

Dry Matter ◽

Major Gene ◽

Dry Matter Intake

Download Full-text

Reliability of breeding values for feed intake and feed efficiency traits in dairy cattle: When dry matter intake recordings are sparse under different scenarios

Journal of Dairy Science ◽

10.3168/jds.2018-16020 ◽

2019 ◽

Vol 102 (8) ◽

pp. 7248-7262 ◽

Cited By ~ 4

Author(s):

E. Negussie ◽

T. Mehtiö ◽

P. Mäntysaari ◽

P. Løvendahl ◽

E.A. Mäntysaari ◽

...

Keyword(s):

Dairy Cattle ◽

Feed Intake ◽

Feed Efficiency ◽

Dry Matter ◽

Dry Matter Intake ◽

Breeding Values

Download Full-text

A meta-analysis comparing four measurement methods to determine the relationship between methane emissions and dry-matter intake in New Zealand dairy cattle

Animal Production Science ◽

10.1071/an18573 ◽

2020 ◽

Vol 60 (1) ◽

pp. 96 ◽

Cited By ~ 2

Author(s):

Arjan Jonker ◽

Peter Green ◽

Garry Waghorn ◽

Tony van der Weerden ◽

David Pacheco ◽

...

Keyword(s):

New Zealand ◽

Dairy Cattle ◽

Dry Matter ◽

Measurement Methods ◽

Dry Matter Intake ◽

Residual Variance ◽

Mixed Effect ◽

Ch4 Emissions ◽

Ch4 Production ◽

The Relationship

Enteric methane (CH4) emissions and dry-matter intake (DMI) can be accurately and precisely measured in respiration chambers (RC), whereas automated head chambers (GreenFeed; GF) and the SF6 tracer method can provide estimates of CH4 emissions from grazing cattle. In New Zealand, most dairy cattle graze pasture and, under these conditions, DMI also has to be estimated. The objective of the current study was to compare the relationship between CH4 production and DMI of New Zealand dairy cattle fed forages using the following four measurement methods: RC with measured DMI (RC); sulfur hexafluoride (SF6) with measured DMI (SF6-DMI); SF6 with DMI estimated from prediction equations or indigestible markers (SF6); GF with measured or estimated DMI (GF). Data were collected from published literature from New Zealand trials with growing and lactating dairy cattle fed forage-based diets and data were analysed using a mixed-effect model. The intercept of the linear regression between CH4 production and DMI was not significantly different from zero and was omitted from the model. However, residual variance (observed–predicted values) increased with an increasing DMI, which was addressed by log-transforming CH4 per unit of DMI and this model was used for final data analysis. The accuracy of the four methods for predicting log CH4 per unit of DMI was similar (P = 0.55), but the precision (indicated by residuals) differed (P < 0.001) among methods. The residual standard deviations for SF6, GF and SF6-DMI were 4.6, 3.4 and 2.1 times greater than the residuals for RC. Hence, all methods enabled accurate prediction of CH4 per unit of DMI, but methodology for determining both CH4 and DMI affected their precision (residuals).

Download Full-text

The effect locomotion score and lameness and on dry matter intake and behaviour in dairy cattle

Proceedings of the British Society of Animal Science ◽

10.1017/s1752756200008553 ◽

2002 ◽

Vol 2002 ◽

pp. 199-199

Author(s):

J. K. Margerison ◽

B. Winkler ◽

G. Stephens

Keyword(s):

Dairy Cattle ◽

Feed Intake ◽

Dry Matter ◽

Dry Matter Intake ◽

General Behaviour ◽

Painful Condition ◽

Time Spent Feeding ◽

Locomotion Score ◽

Lying Down

Lameness has been identified as an extremely painful condition (Manson and Leaver, 1988). Studies have found increased locomotion score (LS) and lameness to reduce productivity, while other have found no such reduction (Manson and Leaver, 1988; Kelley et al., 1990; Phillips et al., 1994). Changes in time spent feeding have been associated with changes in LS (Manson and Leaver, 1988) and less time lying down (Hassall, 1993). However, while lame cows change their feeding and general behaviour there is little information regarding the extent and mode of these changes. The objective of this study was to measure the effect of locomotion score on behavior and feed intake.

Download Full-text

Understanding the Effectiveness of Genomic Prediction in Tetraploid Potato

Frontiers in Plant Science ◽

10.3389/fpls.2021.672417 ◽

2021 ◽

Vol 12 ◽

Author(s):

Stefan Wilson ◽

Chaozhi Zheng ◽

Chris Maliepaard ◽

Han A. Mulder ◽

Richard G. F. Visser ◽

...

Keyword(s):

Variable Selection ◽

Phenotypic Variation ◽

Genomic Prediction ◽

Prediction Accuracy ◽

Dry Matter ◽

Dry Matter Content ◽

Tuber Weight ◽

Data Set ◽

Epistatic Effects ◽

Tetraploid Potato

Use of genomic prediction (GP) in tetraploid is becoming more common. Therefore, we think it is the right time for a comparison of GP models for tetraploid potato. GP models were compared that contrasted shrinkage with variable selection, parametric vs. non-parametric models and different ways of accounting for non-additive genetic effects. As a complement to GP, association studies were carried out in an attempt to understand the differences in prediction accuracy. We compared our GP models on a data set consisting of 147 cultivars, representing worldwide diversity, with over 39 k GBS markers and measurements on four tuber traits collected in six trials at three locations during 2 years. GP accuracies ranged from 0.32 for tuber count to 0.77 for dry matter content. For all traits, differences between GP models that utilised shrinkage penalties and those that performed variable selection were negligible. This was surprising for dry matter, as only a few additive markers explained over 50% of phenotypic variation. Accuracy for tuber count increased from 0.35 to 0.41, when dominance was included in the model. This result is supported by Genome Wide Association Study (GWAS) that found additive and dominance effects accounted for 37% of phenotypic variation, while significant additive effects alone accounted for 14%. For tuber weight, the Reproducing Kernel Hilbert Space (RKHS) model gave a larger improvement in prediction accuracy than explicitly modelling epistatic effects. This is an indication that capturing the between locus epistatic effects of tuber weight can be done more effectively using the semi-parametric RKHS model. Our results show good opportunities for GP in 4x potato.

Download Full-text