Short communication: Estimates of genetic parameters of body condition score in the first 3 lactations using a random regression animal model

Abstract

The objective of this research was to estimate the genetic parameters of body condition score (BCS) in the first 3 lactations in Canadian Holstein dairy cattle using a multiple-lactation random regression animal model. Field staff from Valacta milk recording agency (Sainte-Anne-de-Bellevue, QC, Canada) collected BCS from Québec herds several times throughout each lactation. Approximately 32,000, 20,000, and 11,000 first-, second-, and third-parity BCS were analyzed, respectively, from a total of 75 herds. Body condition score was a moderately heritable trait over the lactation for parity 1, 2, and 3, with average daily heritabilities of 0.22, 0.26, and 0.30, respectively. Daily heritability ranged between 0.14 and 0.26, 0.19 and 0.28, and 0.24 and 0.33 for parity 1, 2, and 3, respectively. Genetic variance of BCS increased with days in milk within lactations. The low genetic variance in early lactation suggests that the evolution of the ability to mobilize tissue reserves in early lactation provided cattle with a major advantage, and is, therefore, somewhat conserved. The increasing genetic variance suggests that more genetic differences were related to how well cows recovered from the negative energy balance state. More specifically, increasing genetic variation as lactation progressed could be a reflection of genetic differences in the ability of cows to efficiently control the rate of mobilization of tissue reserves, which would not be crucial in early lactation. The shape of BCS curves was similar across parities. From first to third parity, differences included the progressively deeper nadir and faster rate of recovery of condition. Daily genetic correlations between parities were calculated from 5 to 305 DIM, and were summed and divided by 301 to obtain average daily genetic correlations. The average daily genetic correlations were 0.84 between parity 1 and 2, 0.83 between parity 1 and 3, and 0.86 between parity 2 and 3. Although not 1, these genetic correlations are still strong, so much of the variation observed in BCS was controlled by the same genes for each of the first 3 lactations. If a genetic evaluation for BCS is developed, regular collection of first-lactation BCS records should be sufficient for genetic evaluation.

Genetic and environmental relationships between body condition score and milk production traits in Canadian Holsteins

“…Estimates of daily heritability, genetic, PE, HY, and residual variances for BCS were very similar to those of Loker et al (2011). Daily BCS heritability was in agreement with other sources, which established that BCS was the least heritable at the beginning of lactation and most heritable in mid to late lactation Berry et al, 2003b;Dechow et al, 2004;Bastin et al, 2010).…”

“…The 0.07 difference in heritability between the current study and that of Bastin et al (2010) could be due to differences in editing of the full data set or to modeling differences. Because a fixed HTD factor was not included in Bastin et al (2010), effect of BCS assessor may have been confounded with the random HY factor in that study, resulting in a lower estimate of heritability for BCS (Loker et al, 2011) compared with the current study.…”

“…A previous study determined that BCS was strongly genetically correlated across the first 3 lactations (Loker et al, 2011). Therefore, only first-parity BCS records were used in the current study.…”

“…As in Loker et al (2011), Legendre polynomials of order 2 were used to describe regression curves for BCS. Only a limited number of BCS records were available per animal (3 on average), and a similar study by Berry et al (2003b) showed little advantage of using Legendre polynomials of order 3 instead of order 2; order 4 was chosen for milk production traits to be similar to the Canadian TD model.…”

Genomic selection for feed efficiency in dairy cattle

“…Conversely, RFI in lactating cows is complicated by additional energy contributed from mobilisation of body tissue to sustain lactation and accretion of body tissue during replenishment. Early lactation is characterised by large changes in body reserves and BCS that is the inverse of the lactation curve (Coffey et al, 2002;Berry et al, 2003;Loker et al, 2011). So, ideally, the model used to calculate RFI in lactating cows should also include an adjustment for body reserves, which is usually achieved by fitting BCS and BCS change as additional covariates.…”