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Estimating the daily nutritive value of bermudagrass for grazing livestock

      ABSTRACT

      Objective

      Our objective was to develop models to estimate the CP, NDF, lignin, and ash concentrations of bermudagrass [Cynodondactylon (L.) Pers.] forage daily throughout the grazing season and use them to estimate TDN daily. We hypothesized that the CP, NDF, lignin, ash, and TDN concentrations might change daily.

      Materials and Methods

      Coastal bermudagrass forage CP, NDF, lignin, and ash concentrations spanning several years were obtained from Overton, Texas. The forage samples used comprised hand-plucked plant parts intended to estimate animal-selected diets. We developed an empirical model for each nutritive variable with the day of the year (DOY) as a predictor. By incorporating these models into a pre-existing summative equation, we estimated the daily values of TDN. These nutritive value models were evaluated using the Willmott index, modeling efficiency, root mean squared error, and R2 as the measures of fit.

      Results and Discussion

      Bermudagrass CP concentration had a negative, curvilinear association with DOY, whereas lignin and NDF concentrations were positively, curvilinearly related to DOY. The ash concentration had a negative, linear association with DOY. The likely causal factors for these relationships were plant maturity and weather conditions, especially temperature. The Willmott index, modeling efficiency, and R2 values were greater than 0.87, 0.64, and 0.65, respectively. The root mean squared error and percent error values were less than 3.1 and 11%, respectively. These values indicated that the nutritive value models were reliable.

      Implications and Applications

      We showed that the CP, NDF, lignin, ash, and TDN values of bermudagrass forage changed daily. By incorporating these trends into a nutritive value prediction system, accurate estimates of daily TDN could be made. These nutritive value models could be a valuable asset in forage-animal modeling for more accurately studying the effects of various management strategies and environmental factors on forage nutritive value and animal performance.

      Key words

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