Browsing by Author "Thiruchchenthuran S"
Now showing 1 - 2 of 2
Results Per Page
Sort Options
- ItemEvaluation of equations for predicting ileal nutrient digestibility and digestible nutrient content of broiler diets based on their gross chemical composition(Elsevier B V, 2024-06) Thiruchchenthuran S; Lopez-Villalobos N; Zaefarian F; Abdollahi MR; Wester TJ; Pedersen NB; Storm AC; Cowieson AJ; Morel PCHThe coefficient of apparent ileal digestibility (CAID) and ileal digestible contents (IDC) of nutrients of 56 diets using 10 feed ingredients were measured in broilers (21–24 d post-hatch). Diets contained varying inclusion levels of traditional and non-traditional ingredients and differed widely in chemical composition. The chemical composition and in vivo digestibility values were used to establish prediction equations for CAID and IDC of nutrients using stepwise multiple regression. The strength and accuracy of the developed equations were evaluated by root mean square error (RMSE), coefficient of determination (R2), adjusted R2 (adj. R2), and Akaikie's Information Criteria (AIC). The bootstrap method was used to validate the choice of variables by stepwise selection method in the original equation based on their frequencies of selection. Selection of variables was validated if the variables that appear in the original stepwise model were selected in more than 30% of the 1000 bootstrap samples. A close agreement between the original equations and bootstrap resampling was observed for CAID of nitrogen (N) and energy and IDC of energy, starch, and calcium (Ca). Additionally, the original data was subjected to another run of stepwise regression analysis using the selected variables by bootstrapping. The initial regression showed that the CAID of N and energy was highly dependent on crude fibre (CF) and energy contents of the diets. The CAID of energy can be predicted (R2 = 0.89 and RMSE = 0.035) by CF, gross energy (GE), CF2, and starch-to-CF ratio (starch:CF). Calcium content had a positive influence, while phosphorus (P) content had a negative influence on the prediction of CAID of fat. The main variable to predict CAID and IDC of most nutrients was the dietary CF content. Based on the lowest RMSE and AIC, the best predictors for IDC of N were ash, N, fat, CF, CF2, and starch:CF, while the best predictors for IDC of energy were CF, GE, CF2, and starch:CF. The results of the original stepwise regression models and the stepwise regression with the selected variables from the bootstrap results for CAID of N, energy, fat, and DM, as well as IDC of energy, starch, and Ca, were the same with no differences in R2, Adj. R2, RMSE, and AIC. This method can be useful for developing stable and reproducible models using stepwise regression. However, an external validation is needed to confirm the use of these equations in commercial settings.
- ItemValidation of prediction equations to estimate the nutritive value of broiler chicken diets based on their chemical composition(Elsevier BV, Netherlands, 2025-02-18) Thiruchchenthuran S; Zaefarian F; Abdollahi MR; Wester TJ; Morel PCHAn experiment was conducted to validate the accuracy of previously published prediction equations developed to estimate the coefficient of apparent ileal digestibility (CAID) and ileal digestible content (IDC) of nitrogen (N), crude fat, starch, calcium (Ca), phosphorus (P), energy, and dry matter (DM) in broilers using the chemical composition of diets. Twenty new diets were formulated to have a wide range of chemical characteristics relevant to commercial diets. The CAID of N, crude fat, starch, Ca, P, energy, and DM of the diets were determined in broiler growers fed ad libitum from 15 to 22 days post-hatch. The chemical composition and in vivo digestibility values were used to validate the prediction equations developed from a previous study. Comparison between the determined values and predicted values was used to assess the accuracy of prediction equations using the coefficient of determination (R2), root mean square error of prediction, concordance correlation coefficient (CCC), and mean bias (MB). The most accurate prediction was achieved in terms of R2 and CCC for CAID of energy and DM (R2 = 0.57 and 0.66, CCC = 0.45 and 0.47, respectively) as well as for IDC of N, starch, energy, and DM (R2 = 0.90, 1.00, 0.65, and 0.66, CCC = 0.48, 0.97, 0.51, and 0.47, respectively). The R2 and CCC values obtained for CAID of N, crude fat, starch, Ca, and P and IDC of Ca and P were not consistent with the expectation of predictive performance. The R2 for IDC of crude fat was high (0.94), however, CCC was moderate (0.43). The determined MB values showed that some equations underpredicted (CAID and IDC of N, crude fat, starch, energy, and DM) and some overpredicted (CAID of Ca and P and IDC of P) the observed values of in vivo study. In conclusion, the equations obtained for CAID of energy and DM as well as IDC of N, starch, energy, and DM could be considered the best fit according to R2 and CCC. Moreover, this study highlights the importance of validation with external data before applying each prediction equation to practical situations.