Effect of divergence in residual feed intake on feeding behavior, blood metabolic variables, and body composition traits in growing beef heifers1

Abstract

This study examined the relationship of feed efficiency and performance with feeding behavior, blood metabolic variables, and various body composition measurements in growing beef heifers. Individual DMI and growth were measured in yearling Limousin x Holstein-Friesian heifers [n = 86; initial BW = 191.8 (SD = 37) kg] fed a TMR diet comprising 70:30 concentrate:corn silage on a DM basis (ME of 2.65 Mcal/kg of DM; DM of 580 g/kg) for 82 d. Meal duration (min/d) and meal frequency (events/d) were calculated for each animal on a daily basis using an Insentec computerized feeding system. Physical measurements as well as ultrasonic fat and muscle depths were recorded on 3 equally spaced occasions during the experimental period. Blood samples were collected by jugular venipuncture on 4 equally spaced occasions and analyzed for plasma concentrations of IGF-I, insulin, leptin, and various metabolites. Phenotypic residual feed intake (RFI) was calculated for all animals as the residuals from a multiple regression model regressing DMI on ADG and midtest BW(0.75). Overall, ADG, DMI, feed conversion ratio (FCR), and RFI were 1.51 (SD = 0.13), 6.74 (SD = 0.99), 4.48 (SD = 0.65), and 0.00 (SD = 0.48) kg/d, respectively. Residual feed intake was positively correlated with DMI (r = 0.47) and FCR (r = 0.46), but not with ADG or midtest BW. Positive correlations (ranging from r = 0.27 to r = 0.63) were estimated between ultrasonic measures of final lumbar fat and lumbar fat accretion over the test period and DMI, FCR, and RFI. The inclusion of gain in lumbar fat to the base RFI model increased R(2) (0.77 vs. 0.80) value for the degree of variation in DMI not explained by midtest BW and ADG alone. The Pearson rank correlation between RFI and carcass-adjusted RFI (RFI(c)) was high (r = 0.93). From the plasma analytes measured, NEFA (r = -0.21; P < 0.05) and beta-hydroxybutyrate (r = 0.37; P < 0.05) concentrations were correlated with RFI. Plasma leptin (r = 0.48), glucose:insulin (r = -0.23), NEFA (r = -0.32), and beta-hydroxybutyrate (r = 0.25) were associated with FCR. However, systemic IGF-I and insulin were unrelated (P > 0.05) to any measure of feed efficiency. The feeding behavior traits of eating rate, daily feeding events, and nonfeeding events were positively correlated (P < 0.05) with RFI and RFI(c). This multifactorial study provides new information on some of the biological processes responsible for variation in feed efficiency in beef cattle.

Pigs that are divergent in feed efficiency, differ in intestinal enzyme and nutrient transporter gene expression, nutrient digestibility and microbial activity

“…This is comparable to results found in RFI selection lines in both Iowa State University in the United States and INRA in France, where both selected large white pigs over multiple generations and 33% of variation in ADFI was due to RFI (Young and Dekkers, 2012). This is lower, however, than the value found in two breeds of beef cattle, where 77% of variation in feed intake was due to RFI (Kelly et al, 2010). In the current study, RFI was not associated with the phenotypic measurements of ADG (r = −0.06), MBW (r = −0.11) or BW (r = 0.05), which is to be expected due to the concept of RFI and the results from previous studies (Mani et al, 2013).…”

Relationship between residual feed intake and enteric methane emission in Nellore cattle

“…77% for heifers fed corn silage and a concentrate diet (Kelly et al, 2010). Apparently, in the present study, the coefficient of determination of the model used for the estimation of RFI is not associated with the dietary energy density, as reported by Fitzsimons et al (2013).…”

Effect of post-weaning residual feed intake classification on grazed grass intake and performance in pregnant beef heifers

“…Low RFI fat heifers had similar (P !0.10) feeding duration, head down time, and feeding event frequency compared with high RFI fat heifers. However, significantly lower feeding event frequency (events/day; Kelly et al 2010a;Basarab et al 2011), eating rate (g min (1 ; Kelly et al 2010a), and feeding duration (min d…”