Estimation of genetic parameters for predicted nitrogen use efficiency and losses in early lactation of Holstein cows

Abstract

The objective of this study was to estimate genetic parameters of predicted N use efficiency (PNUE) and N losses (PNL) as proxies of N use and loss for Holstein cows. Furthermore, we have assessed approximate genetic correlations between PNUE, PNL, and dairy production, health, longevity, and conformation traits. These traits are considered important in many countries and are currently evaluated by the International Bull Evaluation Service (Interbull). The values of PNUE and PNL were obtained by using the combined milk midinfrared (MIR) spectrum, parity, and milk yield-based prediction equations on test-day MIR records with days in milk (DIM) between 5 and 50 d. After editing, the final data set comprised 46,163 records of 21,462 cows from 154 farms in 5 countries. Each trait was divided into primiparous and multiparous (including second to fifth parity) groups. Genetic parameters and breeding values were estimated by using a multitrait (2-trait, 2-parity classes) repeatability model. Herd-year-season of calving, DIM, age of calving, and parity were used as fixed effects. Random effects were defined as parity (within-parity permanent environment), nongenetic cow (across-parity permanent environment), additive genetic animal, and residual effects. The estimated heritability of PNUE and PNL in the first and later parity were 0.13, 0.12, 0.14, and 0.13, and the repeatability values were 0.49, 0.40, 0.55, and 0.43, respectively. The estimated approximate genetic correlations between PNUE and PNL were negative and high (from −0.89 to −0.53), whereas the phenotypic correlations were also negative but relatively low (from −0.45 to −0.11). At a level of reliability of more than 0.30 for all novel traits, a total of 504 bulls born after 1995 had also publishable Interbull multiple-trait across-country estimated breeding values (EBV). The approximate genetic correlations between PNUE and the other 30 traits of interest, estimated as corrected correlations between EBV of bulls, ranged from −0.46 (udder depth) to 0.47 (milk yield). Obtained results showed the complex genetic relationship between efficiency, production, and other traits: for instance, more efficient cows seem to give more milk, which is linked to deeper udders, but seem to have lower health, fertility, and longevity. Additionally, the approximate genetic correlations between PNL, lower values representing less loss of N, and the 30 other traits, were from −0.32 (angularity) to 0.57 (direct calving ease). Even if further research is needed, our results provided preliminary evidence that the PNUE and PNL traits used as proxies could be included in genetic improvement programs in Holstein cows and could help their management.

Defining a nitrogen efficiency index in Holstein cows and assessing its potential effect on the breeding program of bulls

“…Daily milk yield (MY), protein percentage (PP), and MU were restricted to the range of 1 to 90 kg, 1 to 7%, and 2 to 70 mg/dL, respectively. The filtering procedure used for NINT was the same as that explained by Chen et al (2021c). In brief, 2 criteria are considered in the filtering procedure: (1) the standardized Mahalanobis distance between the new predicted spectrum and the calibration data set is ≤3, (2) the predicted value of NINT is within the range of 3 standard deviations (SD) of the mean.…”

“…A 6-trait (3 features in 2 parity classes) repeatability animal model was used to estimate the (co)variance components. The used model was based on that presented by Chen et al (2021c) to a different set of 6 traits:…”

“…where y was a vector of NINT1, MTPN1, MUNY1, NINT2+, MTPN2+, and MUNY2+. In each trait, all effects in this model were the same as Chen et al (2021c). In brief, h was a vector of fixed effect of herdyear-season of calving; b was a vector of fixed regression coefficients for standardization DIM and its quadratic; q was a vector of fixed regression coefficients of the standardization age of calving, defined as a constant, linear and quadratic regression defined inside parities (from first to fifth parity); c was a vector of nongenetic cow random effect; p was a vector of nongenetic cow × parity random effect, this effect was only modeled for NINT2+, MTPN2+, and MUNY2+, as they allowed to distinguish records for the same cow but occurring during different parities (from second to fifth parity); a was a vector of the random additive genetic effect; e was a vector of random residual effect.…”

“…The economic importance of genetic improvement for efficiency traits in cattle is recognized by the world's cattle producers (Brito et al, 2020). Measuring and improving efficiency is not only beneficial to the protection of the environment, but also beneficial to the farm, can promote the sustainable economic development of dairy production (Chen et al, 2021c), and strengthen its social acceptability. In the process of studying efficiency, researchers put forward various indicators representing dairy cow efficiency which can be defined very broadly.…”

“…However, there are relatively few studies on N use efficiency (NUE) of dairy cows, except for those addressing milk urea con-Defining a nitrogen efficiency index in Holstein cows and assessing its potential effect on the breeding program of bulls Y. Chen, 1 H. Atashi, 1,2 C. Grelet, 3 S. Vanderick, 1 H. Hu, 1 and N. Gengler 1 * centration (MU) or MUN as implicit proxies (Bobbo et al, 2020;Chen et al, 2021b). To our knowledge, only we have recently performed the genetic analyses of predicted NUE for dairy cows in early lactation (Chen et al, 2021c). Moreover, the NUE by cattle is very low (20-44%) and could be improved (Cantalapiedra-Hijar et al, 2018;Grelet et al, 2020).…”