Literature DB >> 24663164

Developing a computer-controlled simulated digestion system to predict the concentration of metabolizable energy of feedstuffs for rooster.

F Zhao1, L Q Ren, B M Mi, H Z Tan, J T Zhao, H Li, H F Zhang, Z Y Zhang.   

Abstract

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 corn, 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 × IVDE - 530 (R(2) = 0.97, residual standard deviation [RSD] = 146 kcal/kg, P < 0.001) and TME = 1.050 × IVDE - 16 (R(2) = 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 for AME 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.

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Year:  2014        PMID: 24663164     DOI: 10.2527/jas.2013-6636

Source DB:  PubMed          Journal:  J Anim Sci        ISSN: 0021-8812            Impact factor:   3.159


  10 in total

Review 1.  Artificial gut and the applications in poultry: A review.

Authors:  Nishchal K Sharma; Shu-Biao Wu; Natalie K Morgan; Tamsyn M Crowley
Journal:  Anim Nutr       Date:  2022-03-26

2.  Solid-state fermentation of distilled dried grain with solubles with probiotics for degrading lignocellulose and upgrading nutrient utilization.

Authors:  Cheng Wang; Weifa Su; Yu Zhang; Lihong Hao; Fengqin Wang; Zeqing Lu; Jian Zhao; Xuelian Liu; Yizhen Wang
Journal:  AMB Express       Date:  2018-11-26       Impact factor: 3.298

3.  β-xylosidase and β-mannosidase in combination improved growth performance and altered microbial profiles in weanling pigs fed a corn-soybean meal-based diet.

Authors:  Shaoshuai Liu; Chang Ma; Ling Liu; Dong Ning; Yajing Liu; Bing Dong
Journal:  Asian-Australas J Anim Sci       Date:  2019-02-14       Impact factor: 2.509

4.  Sensitivity of in vitro digestible energy determined with computer-controlled simulated digestion system and its accuracy to predict dietary metabolizable energy for roosters.

Authors:  Y Yu; F Zhao; J Chen; Y Zou; S L Zeng; S B Liu; H Z Tan
Journal:  Poult Sci       Date:  2020-10-07       Impact factor: 3.352

Review 5.  Methodologies for energy evaluation of pig and poultry feeds: A review.

Authors:  Jean Noblet; Shu-Biao Wu; Mingan Choct
Journal:  Anim Nutr       Date:  2021-10-09

6.  An automatically progressed computer-controlled simulated digestion system to predict digestible and metabolizable energy of unconventional plant protein meals for growing pigs.

Authors:  Zhongyuan Du; Yuming Wang; Mingqiang Song; Shuli Zeng; Lixiang Gao; Jiangtao Zhao; Feng Zhao
Journal:  Anim Nutr       Date:  2022-04-26

7.  Optimization of Compound Ratio of Exogenous Xylanase and Debranching Enzymes Supplemented in Corn-Based Broiler Diets Using In Vitro Simulated Gastrointestinal Digestion and Response Surface Methodology.

Authors:  Wei Wu; Huajin Zhou; Yanhong Chen; Chunyue Li; Yuming Guo; Jianmin Yuan
Journal:  Animals (Basel)       Date:  2022-10-01       Impact factor: 3.231

Review 8.  Methodological aspects of determining phosphorus digestibility in swine: A review.

Authors:  Yue She; Defa Li; Shuai Zhang
Journal:  Anim Nutr       Date:  2017-02-21

9.  Historical flaws in bioassays used to generate metabolizable energy values for poultry feed formulation: a critical review.

Authors:  Shu-Biao Wu; Mingan Choct; Gene Pesti
Journal:  Poult Sci       Date:  2019-12-30       Impact factor: 3.352

10.  The feasibility of enzyme hydrolysate gross energy for formulating duck feeds.

Authors:  J Wei; M Xie; J Tang; Y B Wu; Q Zhang; S S Hou
Journal:  Poult Sci       Date:  2020-04-25       Impact factor: 3.352

  10 in total

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