Estimates of Botanical Composition of Diets from Analyses of Chemical Components or NIRS Among Cattle Fed Binary Mixtures of Cornstalk and Noncornstalk Residue

Estimates of diet quality from samples of mechanically harvested corn residues likely under-predict nutrient density in diets selected by grazing cattle. Our objective was to determine if measures of chemical composition or near-infrared reflectance spectroscopy (NIRS) of diet samples collected from ruminally cannulated cows could allow accurate estimates of diet selection among cows fed binary mixtures of cornstalk and noncornstalk (i.e., husk and leaf) residues. Six ruminally cannulated cows were placed in a 6 × 6 Latin square to evaluate predictions of diet intake. After complete ruminal evacuation, cows were fed 1-kg meals (DM-basis) containing different combinations of cornstalk and noncornstalk residues in ratios of 0:100, 20:80, 40:60, 60:40, 80:20, 100:0. Diet samples from each meal were collected by removal of ruminal contents after 1-h and were either machine-rinsed, hand-rinsed or unrinsed to evaluate effects of endogenous compounds on predictions of diet composition. Diet samples were analyzed for NDF, ADF, acid detergent insoluble ash (ADIA), ADL, CP and NIRS to calculate diet composition. Greater amounts of rinsing increased NDF and ADF content and decreased ADIA and CP content of diet samples (P < 0.01). Rinsing tended to increase (P < 0.06) ADL content of diet samples. Differences in concentration between cornstalk and noncornstalk residues within each chemical component were standardized by calculating a coefficient of variation (CV). Accuracy and precision of estimates of diet composition were analyzed by regressing predicted diet composition and known diet composition. Predictions of diet composition were improved by increasing differences in concentration of chemical components between cornstalk and noncornstalk residues up to a CV of 22.6 ± 5.4%. Predictions of diet composition from unrinsed ADIA and machine-rinsed NIRS had the greatest accuracy (slope = 0.98 and 0.95, respectively) and large coefficients of determination (r² = 0.86 and 0.74 respectively). Subsequently, a field trial was performed to evaluate predictions of diet composition in cattle grazing corn residue. Five cows were placed in 1 of 10 paddocks (6.1 AUM/ha) and allowed to continuously graze or to strip-graze (4.7% of BW/12 h) corn residues. Predictions of diet composition from ADIA, ADL and NIRS did not differ (P = 0.99), and estimates of cornstalk intake tended to be greater (P = 0.09) in strip-grazed compared to continuously grazed cows. These data suggest that diet composition can be predicted by chemical components or NIRS by ruminal collection of diet samples among cattle grazing binary mixtures of forage.