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The objective of this experiment was to develop a new computer-controlled simulated digestion system to predict the digestible energy (DE) and metabolizable energy (ME) of unconventional plant protein meals for growing pigs. Nine meals tested included 1 source of rapeseed meal, 4 sources of cottonseed meal, 2 sources of sunflower meal, and 2 sources of peanut meal. Twenty growing pigs (Duroc × [Landrace × Large White]) with an initial body weight (BW) of 41.7 ± 2.6 kg were allotted to a replicated 10 × 3 incomplete Latin square design to determine the DE and ME of 1 basal diet and 9 experimental diets formulated with 9 unconventional plant protein meals. The DE and ME values of unconventional plant protein meals were calculated by the difference method. The in vitro digestible energy (IVDE) of 1 basal diet, 9 experimental diets, and 9 unconventional plant protein meals were determined with 5 replicates of each sample in a complete randomized arrangement. The IVDE/DE or IVDE/ME ranged from 0.96 to 0.98 or 1.00 to 1.01, and the correlation coefficient between IVDE and DE or ME was 0.97 or 0.98 in 10 experimental diets. Accordingly, the IVDE/DE or IVDE/ME ranged from 0.86 to 1.05 or 0.96 to 1.20, and the correlation coefficient between IVDE and DE or ME was 0.92 or 0.91 in 9 unconventional plant protein meals. The coefficient of variation (CV) of IVDE was less than that of DE and ME in the experimental diets (0.43%, 0.80%, and 0.97% for CV of IVDE, DE and ME, respectively) and unconventional plant protein meals (0.92%, 4.84%, and 6.33% for CV of IVDE, DE and ME, respectively). The regression equations to predict DE from IVDE in 10 experimental diets and 9 unconventional plant protein meals were DE = 0.8851 × IVDE +539 (R2 = 0.9411, residual standard deviation [RSD] = 23 kcal/kg DM, P

Two experiments were conducted to study the accuracy of predicting true metabolizable energy (TME) of ingredients for ducks from in vitro digestible energy (IVDE) determined with a computer-controlled simulated digestion system. Experiment 1 was to establish TME prediction models from the IVDE of 9 energy feed ingredients and 12 protein feed ingredients using regression analysis. Experiment 2 was to validate the accuracy of the predicted ME of 10 ingredients randomly selected from Exp. 1. Ten diets were formulated with 2 to 6 of 10 ingredients. Dietary in vivo TME values were compared with calculated values based on the TME predicted in Exp. 1. In Exp. 1, the correlation coefficients between TME and IVDE were 0.9339 (P

Two experiments were conducted to validate the sensitivity and accuracy of in vitro digestible energy (IVDE) determined with a computer-controlled simulated digestion system (CCSDS) to predict metabolizable energy (ME) of diets for roosters. In experiment 1, soybean hulls were added to a basal diet (calibration diet 1) at 2.06, 4.12, 6.17, 8.23, 10.28, 12.32, or 14.37% of the diets (calibration diets 2–8) to produce an interval of approximately 80 kcal ME/kg. The sensitivity was measured by comparing the determined and actual IVDE of the diets. With these data, a linear model was developed to predict ME from IVDE. In experiment 2, validation diets were identical except they were composed of different cereal ingredients. For each diet, the correlations and ratios between IVDE and ME were analyzed to test the sensitivity of IVDE to predict ME across different ingredients. In experiment 1, a slope of 0.9899 was calculated in a linear regression of determined IVDE on actual IVDE (R2 = 0.9998; P 0.97; P

The objective of this study was to predict the apparent total tract digestibility (ATTD) of gross energy (GE), digestible energy (DE), and metabolizable energy (ME) of cereals and byproducts using an in vitro digestion procedure automatically progressed in a computer-controlled simulated digestion system (CCSDS) for growing pigs. In in vivo test to determine the ATTD of GE, DE and ME of feed ingredients, 15 barrows (30.2 ± 2.4 kg of initial body weight) were allotted to a 15 × 6 Youden square design with 15 experimental diets in 6 periods to give 6 replicates per diet. Diets included a corn-soybean meal-based basal diet and 14 test diets formulated with 14 samples of cereals and byproducts. The in vitro digestible energy (IVDE) and IVDE/GE were determined using CCSDS with 5 replicates for each sample. Principal components analysis showed that similar positions of samples were observed on a two-dimensional plot of PC1 and PC2 extracted from chemical composition and each of DE, ME, or IVDE. The ratios of IVDE to DE or ME among 14 samples ranged from 87.7–110.4 % and 91.1–112.9 %, but ranged from 97.8–103.5 % or 100.2–105.7 % when both paddy rice and wheat shorts were excluded in consideration of lever effect. Models to predict DE and ME from IVDE were DE = 0.7428 × IVDE + 945 (R² = 0.71, root mean square error (RMSE) = 157 kcal/kg DM, P < 0.01), ME = 0.7465 × IVDE + 839 (R² = 0.76, RMSE=139 kcal/kg DM, P < 0.01) when 14 samples were included, but regression equations were DE = 0.6924 × IVDE + 1173 (R² = 0.91, RMSE = 49 kcal/kg DM, P < 0.01) and ME = 0.6876 × IVDE + 1098 (R² = 0.95, RMSE = 34 kcal/kg DM, P < 0.01) when paddy rice and wheat shorts were excluded. Our results indicate that IVDE determined with a novel CCSDS can precisely predict the DE and ME of cereals and byproducts with lower fiber content (ADF < 6.01 % DM) for growing pigs. • A novel in vitro simulated digestion (IVSD) method was developed for growing pigs. • Digestible (DE) or metabolizable energy (ME) of cereals varied from 3100 to 4200 kcal/kg DM. • Similar trend was observed in in vitro and in vivo available energy among 14 cereals. • The DE and ME of cereals can be precisely predicted by the IVSD method. [ABSTRACT FROM AUTHOR]

Two experiments were conducted to de-velop a computer-controlled digestion system to simu-late the digestion process of duck for predicting the concentration of ME and the metabolizability of gross energy (GE) in corn. In a calibration experiment, 30 corn-based calibration samples with a previously pub-lished ME concentration in 2008 were used to develop the prediction models for in vivo energetic values. The linear relationships were established between in vivo ME concentration and in vitro digestible energy (IVDE) concentration, and between in vivo metabolizability of GE (ME/GE) and in vitro digestibility of GE (IVDE/ GE), respectively. In a validation experiment, 6 sources of corn with previously published ME concentration in 2008 randomly selected from the primary corn-growing regions of China were used to validate the prediction models established in the calibration experiment. The results showed that in calibration samples, the IVDE concentration was positively correlated with the AME (r = 0.9419), AME„ (r = 0.9480), TME (r = 0.9403), and TMEn concentration (r = 0.9473). Similarly, the IVDE/GE was positively correlated with the AME/GE (r = 0.95987), AMEn/GE (r = 0.9641), TME/GE (r = 0.9588), and TMEn/GE (r = 0.9637). The coefficient of determination greater than 0.88 and 0.91, and residual SD less than 45 kcal/kg of DM and 1.01% were ob-served in the prediction models for ME concentrations and ME/GE, respectively. Twenty-nine out of 30 cali-bration samples showed differences less than 100 kcal/ kg of DM and 2.4% between determined and predict-ed values for 4 ME (AME, AMEn, TME, and TMEn) and for 4 ME/GE (AME/GE, AMEn/GE. TME/GE, and TMEn/GE), respectively. Using prediction mod-els developed from 30 calibration samples, 6 validation samples further showed differences less than 100 kcal/ kg of DM and 2% between determined and predicted values for ME and ME/GE, respectively. Therefore, the computer-controlled simulated digestion system can be used to predict the ME and ME/GE of corn for ducks with acceptable accuracy. [ABSTRACT FROM AUTHOR]

Four experiments were conducted to evaluate the effectiveness of a computer-controlled simulated digestion system (CCSDS) for predicting apparent metabolizable energy (AME) and true metabolizable energy (TME) using in vitro digestible energy (IVDE) content of feeds for roosters. In Exp. 1, the repeatability of the IVDE assay was tested in corn, wheat, rapeseed meal, and cottonseed meal with 3 assays of each sample and each with 5 replicates of the same sample. In Exp. 2, the additivity of IVDE concentration in corn, soybean meal, and cottonseed meal was tested by comparing determined IVDE values of the complete diet with values predicted from measurements on individual ingredients. In Exp. 3, linear models to predict AME and TME based on IVDE were developed with 16 calibration samples. In Exp. 4, the accuracy of prediction models was tested by the differences between predicted and determined values for AME or TME of 6 ingredients and 4 diets. In Exp. 1, the mean CV of IVDE was 0.88% (range = 0.20 to 2.14%) for corn, wheat, rapeseed meal, and cottonseed meal. No difference in IVDE was observed between 3 assays of an ingredient, indicating that the IVDE assay is repeatable under these conditions. In Exp. 2, minimal differences (<21 kcal/ kg) were observed between determined and calculated IVDE of 3 complete diets formulated with com, soybean meal, and cottonseed meal, demonstrating that the IVDE values are additive in a complete diet. In Exp. 3, linear relationships between AME and IVDE and between TME and IVDE were observed in 16 calibration samples: AME = 1.062 x IVDE - 530 (R² = 0.97, residual standard deviation [RSD] = 146 kcal/kg, P < 0.001) and TME = 1.050 x IVDE - 16 {R² = 0.97, RSD = 148 kcal/kg, P < 0.001). Differences of less than 100 kcal/kg were observed between determined and predicted values in 10 and 9 of the 16 calibration samples for AME and TME, respectively. In Exp. 4, differences of less than 100 kcal/kg between determined and predicted values were observed in 3 and 4 of the 6 ingredient samples forAME and TME, respectively, and all 4 diets showed the differences of less than 25 kcal/kg between determined and predicted AME or TME. Our results indicate that the CCSDS is repeatable and additive. This system accurately predicted AME or TME on 17 of the 26 samples and may be a promising method to predict the energetic values of feed for poultry. [ABSTRACT FROM AUTHOR]

The objective of this experiment was to develop a new computer-controlled simulated digestion system to predict the digestible energy (DE) and metabolizable energy (ME) of unconventional plant protein meals for growing pigs. Nine meals tested included 1 source of rapeseed meal, 4 sources of cottonseed meal, 2 sources of sunflower meal, and 2 sources of peanut meal. Twenty growing pigs (Duroc × [Landrace × Large White]) with an initial body weight (BW) of 41.7 ± 2.6 kg were allotted to a replicated 10 × 3 incomplete Latin square design to determine the DE and ME of 1 basal diet and 9 experimental diets formulated with 9 unconventional plant protein meals. The DE and ME values of unconventional plant protein meals were calculated by the difference method. The in vitro digestible energy (IVDE) of 1 basal diet, 9 experimental diets, and 9 unconventional plant protein meals were determined with 5 replicates of each sample in a complete randomized arrangement. The IVDE/DE or IVDE/ME ranged from 0.96 to 0.98 or 1.00 to 1.01, and the correlation coefficient between IVDE and DE or ME was 0.97 or 0.98 in 10 experimental diets. Accordingly, the IVDE/DE or IVDE/ME ranged from 0.86 to 1.05 or 0.96 to 1.20, and the correlation coefficient between IVDE and DE or ME was 0.92 or 0.91 in 9 unconventional plant protein meals. The coefficient of variation (CV) of IVDE was less than that of DE and ME in the experimental diets (0.43%, 0.80%, and 0.97% for CV of IVDE, DE and ME, respectively) and unconventional plant protein meals (0.92%, 4.84%, and 6.33% for CV of IVDE, DE and ME, respectively). The regression equations to predict DE from IVDE in 10 experimental diets and 9 unconventional plant protein meals were DE = 0.8851 × IVDE +539 ( R 2  = 0.9411, residual standard deviation [RSD] = 23 kcal/kg DM, P  < 0.01) and DE = 0.9880 × IVDE + 166 ( R 2  = 0.8428, RSD = 182 kcal/kg DM, P  < 0.01), respectively. There was no statistical difference in the slopes ( P  = 0.82) or intercepts ( P  = 1.00) of these 2 equations. Thus, 10 diets and 9 unconventional plant protein meals were pooled to establish the regression equation of DE on IVDE as: DE = 0.9813 × IVDE +187 ( R 2  = 0.9120, RSD = 118 kcal/kg DM, P  < 0.01). The regression equations to predict ME from IVDE in 10 experimental diets and 9 unconventional plant protein meals were ME = 0.9559 × IVDE +146 ( R 2  = 0.9697, RSD = 18 kcal/kg DM, P  < 0.01) and ME = 0.9388 × IVDE + 3 ( R 2  = 0.8282, RSD = 182 kcal/kg DM, P  < 0.01), respectively. There was no statistical difference in slopes ( P  = 0.97) but significant difference between the intercepts ( P  = 0.02) of these 2 equations. Our results indicate IVDE has similar response to the DE but different response to the ME in 10 experimental diets and 9 unconventional plant protein meals. Therefore, IVDE is more suitable to predict DE than ME of diets and unconventional plant protein meals for growing pigs., Competing Interests: We declare that we have no financial and personal relationships with other people or organizations that can inappropriately influence our work, and there is no professional or other personal interest of any nature or kind in any product, service and/or company that could be construed as influencing the content of this paper., (© 2022 Chinese Association of Animal Science and Veterinary Medicine. Publishing services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd.)

Two experiments were conducted to validate the sensitivity and accuracy of in vitro digestible energy (IVDE) determined with a computer-controlled simulated digestion system (CCSDS) to predict metabolizable energy (ME) of diets for roosters. In experiment 1, soybean hulls were added to a basal diet (calibration diet 1) at 2.06, 4.12, 6.17, 8.23, 10.28, 12.32, or 14.37% of the diets (calibration diets 2-8) to produce an interval of approximately 80 kcal ME/kg. The sensitivity was measured by comparing the determined and actual IVDE of the diets. With these data, a linear model was developed to predict ME from IVDE. In experiment 2, validation diets were identical except they were composed of different cereal ingredients. For each diet, the correlations and ratios between IVDE and ME were analyzed to test the sensitivity of IVDE to predict ME across different ingredients. In experiment 1, a slope of 0.9899 was calculated in a linear regression of determined IVDE on actual IVDE (R 2  = 0.9998; P < 0.01). The ratio of determined IVDE to actual IVDE was 0.9878. The ratio of IVDE to apparent metabolizable energy (AME) and to nitrogen-corrected AME (AMEn) was 1.03 and 1.05, respectively. The linear models to predict ME from IVDE were AME = 0.8449 × IVDE + 451 (R 2  = 0.9812, residual standard deviation [RSD] = 28 kcal/kg; P < 0.01) and AMEn = 0.8357 × IVDE + 436 (R 2  = 0.9821, RSD = 27 kcal/kg; P < 0.01). In experiment 2, a significant simple correlation was observed between the IVDE and AME or AMEn of validation diets (r > 0.97; P < 0.01). The ratio of IVDE to AME and to AMEn was 1.04 and 1.05, respectively. Predicted and determined AME or AMEn of 8 validation diets differed by less than 100 kcal/kg. The regression of determined AME or AMEn against predicted AME or AMEn (R 2  ≥ 0.9466; P < 0.01) resulted in an overlapped line where Y = X. These results suggest the IVDE determined with CCSDS is highly sensitive and can be used to accurately predict the ME of diets for roosters across a wide range of cereal grains., (Copyright © 2020. Published by Elsevier Inc.)