Estimating feed efficiency: Evaluation of mathematical models to predict individual intakes of steers fed in group pens

Abstract

To evaluate feed efficiency using residual feed intake (RFI), it is necessary to measure and record daily feed intake for each animal. This can be accomplished by housing them in individual pens or by using sophisticated electronic feeders in group pens. All the available options are very expensive and very laborious; therefore, several researchers have developed methods to predict individual DMI of cattle fed in group pens. Three intake models were tested with a data set of 60 Angus × Hereford steers fed a corn-based finishing diet in both group and individual pens. After the first 60 d (period 1) of the study, animals were switched from group to individual pens, and then vice versa for another 60 d (period 2); thus, the entire feeding trial was 120 d long. No difference was observed in DMI between periods for steers fed individually (period 1 = 10.9 kg/d and period 2 = 11.2 kg/d, P = 0.44), but a difference was observed in group pens (period 1 = 12.7 kg/d and period 2 = 10.9 kg/d, P < 0.01). In addition, no difference (P ≥ 0.15) was observed in carcass characteristics, such as HCW, dressing percentage, quality grade, LM area, KPH percentage, yield grade, or backfat between RFI groups (low, medium, and high). Average daily gain and G:F were not different between RFI groups within each period (P ≥ 0.06), but there were period differences (P < 0.001). Models 1 and 2 were based on growth, carcass composition, and nutrient requirements, whereas model 3 was based on the heterogeneity of pen intakes when cattle were rotated through the pens on a daily basis. Models 1 and 2 were forced through the mean observed DMI, so the mean bias was zero, but they were not precise, with a slope bias greater than 50%. Model 3 showed low accuracy (mean bias = 20%), but it was precise, with a slope bias of 21%. Because RFI is the error of the DMI equation, any inaccuracy when estimating intake will lead to a bias in the prediction of RFI. In conclusion, these models could be used to predict mean DMI, but they were not adequate for estimating RFI.

Partitioning of feed intake into maintenance and gain in growing beef cattle: Evaluation of conventional and Bayesian analyses

“…Dry matter intakes, within a study, were overestimated at lesser intakes and underestimated at greater intakes for OLS solutions to Cruz et al (2010) and MARC data for both intercept and 0-intercept models. Cruz et al (2011) reported a similar finding, albeit for pen-fed cattle. When comparing steers (Cruz et al [2010] and MARC) whose ADFI i (observed) was less than average with those with observed ADFI i greater than average, residuals differed from 0 (P < 0.001).…”

Grazed grass herbage intake and performance of beef heifers with predetermined phenotypic residual feed intake classification

“…In this study, using acid insoluble ash as a marker, the absence of a relationship between RFI and total tract digestibility may be related to the nature of the diet offered, as the effect of level of feed intake on digestion is of less magnitude with forage-based diets than with concentrate-based diets (Chilliard et al, 1995). A number of studies where high concentrate diets were offered to cattle have found that diet digestibility was negatively correlated with RFI Nkrumah et al, 2006;McDonald et al, 2010), although some have found no relationship (Cruz et al, 2011). However, whether the association with digestion and RFI is an inherent efficiency or mainly related to a higher passage rate of digesta due to intake is unclear.…”

Integrating Genomics with Nutrition Models to Improve the Prediction of Cattle Performance and Carcass Composition under Feedlot Conditions

“…Because mean BW and ADG usually does not explain all the variation in DMI, we would expect a phenotypic correlation between observed DMI and RFI (0.42 < r < 0.74; [ 15 , 50 ]). Some [ 51 ] have suggested that nutritional models cannot satisfactorily determine individual DMI and RFI of group-fed cattle. Others [ 16 ] have indicated strong correlations (r > 0.89) between RFI and predicted intake difference ( PID = observed DMI—DMR), suggesting that PID would be more capable to identify animals with low DMI and slow ADG as inefficient compared to RFI.…”