Analysis of feed intake and energy balance of high-yielding first lactating Holstein cows with fixed and random regression models

The difficulties and costs of measuring individual feed intake in dairy cattle are the primary factors limiting the genetic study of feed intake and utilisation, and hence the potential of their subsequent industry-wide applications. However, indirect selection based on heritable, easily measurable, and genetically correlated traits, such as conformation traits, may be an alternative approach to improve feed efficiency. The aim of this study was to estimate genetic and phenotypic correlations among feed intake, production, and feed efficiency traits (particularly residual feed intake; RFI) with routinely recorded conformation traits. A total of 496 repeated records from 260 Holstein dairy cows in different lactations (260, 159 and 77 from first, second and third lactation, respectively) were considered in this study. Individual daily feed intake and monthly BW and body condition scores of these animals were recorded from 5 to 305 days in milk within each lactation from June 2007 to July 2013. Milk yield and composition data of all animals within each lactation were retrieved, and the first lactation conformation traits for primiparous animals were extracted from databases. Individual RFI over 301 days was estimated using linear regression of total 301 days actual energy intake on a total of 301 days estimated traits of metabolic BW, milk production energy requirement, and empty BW change. Pair-wise bivariate animal models were used to estimate genetic and phenotypic parameters among the studied traits. Estimated heritabilities of total intake and production traits ranged from 0.27 ± 0.07 for lactation actual energy intake to 0.45 ± 0.08 for average body condition score over 301 days of the lactation period. RFI showed a moderate heritability estimate (0.20 ± 0.03) and non-significant phenotypic and genetic correlations with lactation 3.5 % fat-corrected milk and average BW over lactation. Among the conformation traits, dairy strength, stature, rear attachment width, chest width and pin width had significant (P < 0.05) moderate to strong genetic correlations with RFI. Combinations of these conformation traits could be used as RFI indicators in the dairy genetic improvement programmes to increase the accuracy of the genetic evaluation of feed intake and utilisation included in the index.

Section: Heritabilitiessupporting

confidence: 71%

Section: Heritabilitiesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Genetic and phenotypic correlations among feed efficiency, production and selected conformation traits in dairy cows

Manafiazar

Goonewardene

Miglior

et al. 2016

“…Direct measures of body energy have been proposed that are chiefly based on individual cow feed intake and milk yield Coffey et al, 2001;Hü ttmann et al, 2009). Such measures, however, are mostly available in research herds because recording individual cow feed intake is practically unfeasible in a commercial population.…”

Section: Introductionmentioning

confidence: 99%

Genetic association between body energy measured throughout lactation and fertility in dairy cattle

Banos

Coffey²

2010

The objective of this study was to quantify the genetic association of body energy assessed throughout lactation with a cow's fertility. Nine direct and indirect body energy traits were defined at different stages of lactation. Four were daily records of energy balance, energy content, cumulative effective energy (CEE) and body condition score (BCS) calculated between lactation days 4 and 311. The other five traits included duration of negative energy balance (DNEB), rate of recovery during DNEB (RNEB), sum of negative energy balance (SNEB), nadir of energy content (NEC) and number of days from calving to NEC. Of these traits, energy balance, DNEB, RNEB and SNEB were primarily based on individual cow feed intake and milk yield, and considered direct measures of body energy. The other traits were calculated from body lipid and protein changes, predicted from BCS and live weight profiles, and were considered indirect measures of body energy. Fertility was defined by number of days between calving and commencement of luteal activity (DLA), first observed oestrus (DH) and conception (DC), and number of services per conception. A total of 957 cows in their first four lactations were considered in the study. Genetic models fitted cubic splines to define longitudinal traits (energy balance, energy content, CEE and BCS) and calculate heritability and genetic correlation with fertility. Daily heritability estimate ranges were 0.10 to 0.34, 0.35 to 0.61, 0.32 to 0.53 and 0.24 to 0.56 for energy balance, energy content, CEE and BCS, respectively, and, in most cases, tended to increase towards the middle of lactation and remain relatively stable thereafter. Of the other body energy traits, heritability of NEC (0.44) was the most notable. Statistically significant ( P , 0.05) genetic correlations of DH with daily energy balance, energy content, CEE and BCS ranged from 20. 16 to 20.28, 20.35 to 20.48, 20.16 to 20.26 and 20.37 to 20.44, respectively. For DC, respective estimates were 20.28 to 20.64, 20.37 to 20.60, 20.30 to 20.48 and 20.29 to 20.53. For DLA, they ranged from 20.47 to 20.56 with energy content and from 20.50 to 20.74 with BCS. Of special interest was the genetic correlation of NEC with DH (20.54) and DC (20.48). Results suggest that indirect measures of body energy have the strongest genetic association with cow fertility. NEC and early lactation (circa day 50) BCS and energy content are the most useful traits for selection in terms of the correlated improvement in a cow's capacity to resume her reproductive activity post partum.

“…Therefore, the ability to assess the EB for individual cows in real-time and on farm would be a highly desirable management tool, enabling the dairy farmer to rapidly detect excessive negative EB. Traditional input-output methods to -E-mail: vivim.thorup@agrsci.dk calculate EB require knowledge of individual feed intake (Hü ttmann et al, 2009), which is almost never available on commercial farms. In contrast, automated cow weighing technology, such as walk-over weights, is becoming increasingly common on commercial farms, where it is usually placed in the exit race of the milking parlour or the milking stall (in robotic milking systems).…”

Section: Introductionmentioning

confidence: 99%

Energy balance of individual cows can be estimated in real-time on farm using frequent liveweight measures even in the absence of body condition score

Thorup¹,

Højsgaard²,

Weisbjerg³

et al. 2013

Existing methods for estimating individual dairy cow energy balance typically either need information on feed intake, that is, the traditional input-output method, or frequent measurements of BW and body condition score (BCS), that is, the body reserve changes method (EB body ). The EB body method holds the advantage of not requiring measurements of feed intake, which are difficult to obtain in practice. The present study aimed first to investigate whether the EB body method can be simplified by basing EB body on BW measurements alone, that is, removing the need for BCS measurements, and second to adapt the EB body method for real-time use, thus turning it into a true on-farm tool. Data came from 77 cows (primiparous or multiparous, Danish Holstein, Red or Jersey) that took part in an experiment subjecting them to a planned change in concentrate intake during milking. BW was measured automatically during each milking and real-time smoothed using asymmetric double-exponential weighting and corrected for the weight of milk produced, gutfill and the growing conceptus. BCS assessed visually with 2-week intervals was also smoothed. EB body was calculated from BW changes only, and in conjunction with BCS changes. A comparison of the increase in empty body weight (EBW) estimated from EB body with EBW measured over the first 240 days in milk (DIM) for the mature cows showed that EB body was robust to changes in the BCS coefficients, allowing functions for standard body protein change relative to DIM to be developed for breeds and parities. These standard body protein change functions allow EB body to be estimated from frequent BW measurements alone, that is, in the absence of BCS measurements. Differences in EB body levels before and after changes in concentrate intake were calculated to test the real-time functionality of the EB body method. Results showed that significant EB body increases could be detected 10 days after a 0.2 kg/day increase in concentrate intake. In conclusion, a real-time method for deriving EB body from frequent BW measures either alone or in conjunction with BCS measures has been developed. This extends the applicability of the EB body method, because real-time measures can be used for decision support and early intervention.Keywords: body reserves, energy balance, real-time, smoothing, standard body protein function ImplicationsReal-time estimates of individual energy balance (EB) would enable early intervention in cases of excessive negative EB. The present method allows EB to be estimated solely from changes in BW measured automatically at milking (corrected for milk, foetus and gutfill) or from BW combined with body condition score (BCS) changes. Tested on 77 cows, the method was able to detect EB differences caused by small changes in concentrate amounts eaten. Standard body protein functions were developed, allowing EB to be estimated real-time for individual cows on farm without needing feed intake or BCS measurements. This EB method is a useful on-farm management tool.