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Cow Intake

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The beef cattle industry has adopted expected progeny differences (EPDs) to estimate genetic merit for feed intake (FI), residual feed intake (RFI) and residual average daily gain (RADG). These selection tools are calculated using phenotypic data from growing animals fed a total mixed ration in confinement. Feed intake and efficiency traits are considered to be moderately heritable. For example, Berry and Crowley (2013)[1] reviewed 45 experiments where heritability of average daily gain (ADG), body weight (BW), FI, and RFI were determined in growing animals. The pooled heritabilities across all studies were 0.31, 0.39, 0.40, and 0.33 for ADG, BW, FI, and RFI, respectively, suggesting that substantial genetic improvement can be made in feeder calves for these traits. However, a primary consideration is whether selecting for growing and finishing period efficiency results in improved forage utilization in the cow herd. After all, approximately 70% of feed energy used in the process of beef production is consumed by the cow herd [2], and increasing efficiency of feed utilization in cows should be a primary economic selection criterion. Considerable research has been published over the last 20 years related to feed efficiency traits in growing cattle consuming high-quality diets, however, relatively little is known about the genetics of low-quality forage utilization efficiency in beef cows.

Beef Improvement Federation guidelines require a minimum diet energy concentration of 2.4 Mcal ME/kg feed (DM basis). This is approximately equivalent to 67% total digestible nutrients or 0.43 Mcal of net energy for gain (NEg) per pound of feed. Because this is a minimum requirement, many test diets contain around 70 to 74% TDN or 0.47 to 0.53 Mcal of NEg per pound of feed DM. This degree of diet energy concentration (or digestibility) is equivalent or beyond the absolute peak of forage digestibility in almost any environment. In most grazing systems beef cows spend more than half of the year consuming moderate to low-quality forage ranging from 48 to 60% digestibility. Differences in diet quality combined with differences in physiological maturity represent the potential for a genotype by environment interaction (GxE) regarding genetic potential for feed intake or feed efficiency. In other words, mature animals consuming moderate to low-quality forage diets may rerank compared to their ranking established during a test period that was conducted while they were 8 to 14 months of age, growing rapidly and consuming a high-quality diet. Thus, the factors that must be considered before selecting on existing feed intake and efficiency metrics in the industry (derived from high-quality diets and growing animals) to improve cow feed intake and efficiency are a) evidence of high genetic correlations over time (age and stage of production), and b) high genetic correlations between measures collected using a wide range in diet characteristics.

Stage of Production, Age

In studies where growing animals and cows were provided similar high-quality forage or mixed forage and concentrate rations during both stages, phenotypic correlations for FI are generally positive (0.65 [3], 0.57 [4], 0.78 [5]). Similarly, phenotypic correlations for RFI measured during the post-weaning period and again at three to five years of age are generally positive when high-quality diets are fed during both stages of maturity (0.4[6], 0.39 [7], 0.59 [8], 0.42 [9]). Genetic correlations for FI were moderate to high (0.74 [10], 0.65 [11], 0.69 [12]) when high-quality diets were provided to heifers during the post-weaning period and again during lactation. Under the same circumstances, genetic correlations for RFI were moderate to high in two experiments (0.58 [13], 0.98 [14]). Taken together, these studies indicate that FI and RFI are moderately repeatable across time (age) and stage of production when high-quality diets are provided during each stage of maturity or production. It would seem that repeatability should be reasonable in situations where cows are not frequently subjected to restricted nutrient quality or quantity.

Diet Quality and Age

Studies investigating the relationship of FI or RFI determined during the post-weaning phase and FI or RFI determined in mature cows consuming a moderate or low-quality diet are sparse. Using a 1.5 Mcal NEm/kg diet for heifers and 1.0 Mcal NEm/kg diet for cows, Black et al. (2013)[15] reported a phenotypic correlation of 0.63 for FI. There was no significant correlation for RFI, however. Cassaday (2016)[16] reported lower DMI for mature cows previously classified as medium and low RFI and FI during the post-weaning period. The diet used in this experiment contained 80% (DM basis) processed switchgrass hay and 20% (DM basis) corn condensed distillers solubles. In a recent study, De La Torre et al. (2019)[17] found no difference in hay intake of cows previously classified as high or low RFI as heifers. In contrast, in a large experiment involving 584 purebred dry, open Charolais cows, phenotypic and genetic correlations of 0.36 and 0.83 were reported for residual energy intake. In this study, feed intake was measured during two consecutive periods, beginning with hay and followed by a corn silage diet supplemented with soybean meal. Due to the conflicting nature of these studies, more research is needed to establish a consensus.

Development of tools that can accurately rank mature cattle for low-quality forage intake is a critical step in improving beef production efficiency, carbon footprint, and cow/calf enterprise profitability. Therefore, we encourage continued research comparing intake across different diets, especially those that reflect prevailing conditions in most commercial cattle herds.

References

  1. Berry, D. P., and J. J. Crowley. “CELL BIOLOGY SYMPOSIUM: Genetics of Feed Efficiency in Dairy and Beef cattle1.” Journal of Animal Science, vol. 91, no. 4, Jan. 2013, pp. 1594–1613., doi:10.2527/jas.2012-5862.
  2. Gregory, K. E. "Beef Cattle Type for Maximum Efficiency "Putting It All Together"." Journal of Animal Science, vol. 34, no. 5, 1972, pp. 881-884.
  3. Freetly, H.C., Kuehn, L.A., Thallman, R.M., Snelling, W.M. 2016. Feed intake and production efficiency of beef cows [abstract]. Journal of Animal Science. 94 (E-Supplement 5):114.
  4. Cassady, C. J., et. al. "Effects of timing and duration of test period and diet type on intake and feed efficiency of Charolais-sired cattle." Journal of Animal Science, vol. 94, no. 11, Jan. 2016, pp. 4748–4758., doi:10.2527/jas.2016-0633.
  5. Hardie, Lydia. “The Genetic Basis and Improvement of Feed Efficiency in Lactating Holstein Dairy Cattle.” Journal of Dairy Science, vol. 100, no. 11, 12 July 2017, pp. 9061–9075., doi:10.31274/etd-180810-5553.
  6. Archer, J. A., et. al. 2002, ‘Genetic Variation in Feed Intake and Efficiency of Mature Beef Cows and Relationships with Postweaning Measurements’, 7th World Congress on Genetics Applied to Livestock Production, Montpellier, France, 19-23 August.
  7. Arthur, Paul F., and Robert M. Herd. “Genetic Improvement of Feed Efficiency.” Feed Efficiency in the Beef Industry, Oct. 2012, pp. 93–103., doi:10.1002/9781118392331.ch7.
  8. Lawrence, P., Kenny, D. A., Earley, B., and McGee, M. “Grazed grass herbage intake and performance of beef heifers with predetermined phenotypic residual feed intake classification.” Animal, vol. 6, no. 10, Mar. 2012, pp.1648-1661., doi:10.1017/S1751731112000559.
  9. Hafla, A. N., et al. “Relationships between Postweaning Residual Feed Intake in Heifers and Forage Use, Body Composition, Feeding Behavior, Physical Activity, and Heart Rate of Pregnant Beef Females.” Journal of Animal Science, vol. 91, no. 11, Jan. 2013, pp. 5353–5365., doi:10.2527/jas.2013-6423.
  10. Nieuwhof, G.j., et al. “Genetic Relationships between Feed Intake, Efficiency and Production Traits in Growing Bulls, Growing Heifers and Lactating Heifers.” Livestock Production Science, vol. 32, no. 3, 1992, pp. 189–202., doi:10.1016/s0301-6226(12)80001-7.
  11. Freetly, H.C., Kuehn, L.A., Thallman, R.M., Snelling, W.M. 2016. Feed intake and production efficiency of beef cows [abstract]. Journal of Animal Science. 94 (E-Supplement 5):114.
  12. Archer, J. A., et. al. 2002, ‘Genetic Variation in Feed Intake and Efficiency of Mature Beef Cows and Relationships with Postweaning Measurements’, 7th World Congress on Genetics Applied to Livestock Production, Montpellier, France, 19-23 August.
  13. Nieuwhof, G.j., et al. “Genetic Relationships between Feed Intake, Efficiency and Production Traits in Growing Bulls, Growing Heifers and Lactating Heifers.” Livestock Production Science, vol. 32, no. 3, 1992, pp. 189–202., doi:10.1016/s0301-6226(12)80001-7.
  14. Archer, J. A., et. al. 2002, ‘Genetic Variation in Feed Intake and Efficiency of Mature Beef Cows and Relationships with Postweaning Measurements’, 7th World Congress on Genetics Applied to Livestock Production, Montpellier, France, 19-23 August.
  15. Black, T. E., et al. “Relationships among Performance, Residual Feed Intake, and Temperament Assessed in Growing Beef Heifers and Subsequently as 3-Year-Old, Lactating Beef cows1.” Journal of Animal Science, vol. 91, no. 5, Jan. 2013, pp. 2254–2263., doi:10.2527/jas.2012-5242.
  16. Cassady, C. J., et. al. "Effects of timing and duration of test period and diet type on intake and feed efficiency of Charolais-sired cattle." Journal of Animal Science, vol. Cassady, C. J., et al. “Effects of Timing and Duration of Test Period and Diet Type on Intake and Feed Efficiency of Charolais-Sired cattle.” Journal of Animal Science, vol. 94, no. 11, Jan. 2016, pp. 4748–4758., doi:10.2527/jas.2016-0633.
  17. Torre, A. De La, et al. “Digestibility Contributes to between-Animal Variation in Feed Efficiency in Beef Cows.” Animal, 2019, pp. 1–9., doi:10.1017/s1751731119001137.