Cargando…
An automatically progressed computer-controlled simulated digestion system to predict digestible and metabolizable energy of unconventional plant protein meals for growing pigs
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 cottonse...
Autores principales: | , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
KeAi Publishing
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9207295/ https://www.ncbi.nlm.nih.gov/pubmed/35785257 http://dx.doi.org/10.1016/j.aninu.2022.02.004 |
_version_ | 1784729493798125568 |
---|---|
author | Du, Zhongyuan Wang, Yuming Song, Mingqiang Zeng, Shuli Gao, Lixiang Zhao, Jiangtao Zhao, Feng |
author_facet | Du, Zhongyuan Wang, Yuming Song, Mingqiang Zeng, Shuli Gao, Lixiang Zhao, Jiangtao Zhao, Feng |
author_sort | Du, Zhongyuan |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-9207295 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | KeAi Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-92072952022-06-30 An automatically progressed computer-controlled simulated digestion system to predict digestible and metabolizable energy of unconventional plant protein meals for growing pigs Du, Zhongyuan Wang, Yuming Song, Mingqiang Zeng, Shuli Gao, Lixiang Zhao, Jiangtao Zhao, Feng Anim Nutr Original Research Article 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. KeAi Publishing 2022-04-26 /pmc/articles/PMC9207295/ /pubmed/35785257 http://dx.doi.org/10.1016/j.aninu.2022.02.004 Text en © 2022 Chinese Association of Animal Science and Veterinary Medicine. Publishing services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Original Research Article Du, Zhongyuan Wang, Yuming Song, Mingqiang Zeng, Shuli Gao, Lixiang Zhao, Jiangtao Zhao, Feng An automatically progressed computer-controlled simulated digestion system to predict digestible and metabolizable energy of unconventional plant protein meals for growing pigs |
title | An automatically progressed computer-controlled simulated digestion system to predict digestible and metabolizable energy of unconventional plant protein meals for growing pigs |
title_full | An automatically progressed computer-controlled simulated digestion system to predict digestible and metabolizable energy of unconventional plant protein meals for growing pigs |
title_fullStr | An automatically progressed computer-controlled simulated digestion system to predict digestible and metabolizable energy of unconventional plant protein meals for growing pigs |
title_full_unstemmed | An automatically progressed computer-controlled simulated digestion system to predict digestible and metabolizable energy of unconventional plant protein meals for growing pigs |
title_short | An automatically progressed computer-controlled simulated digestion system to predict digestible and metabolizable energy of unconventional plant protein meals for growing pigs |
title_sort | automatically progressed computer-controlled simulated digestion system to predict digestible and metabolizable energy of unconventional plant protein meals for growing pigs |
topic | Original Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9207295/ https://www.ncbi.nlm.nih.gov/pubmed/35785257 http://dx.doi.org/10.1016/j.aninu.2022.02.004 |
work_keys_str_mv | AT duzhongyuan anautomaticallyprogressedcomputercontrolledsimulateddigestionsystemtopredictdigestibleandmetabolizableenergyofunconventionalplantproteinmealsforgrowingpigs AT wangyuming anautomaticallyprogressedcomputercontrolledsimulateddigestionsystemtopredictdigestibleandmetabolizableenergyofunconventionalplantproteinmealsforgrowingpigs AT songmingqiang anautomaticallyprogressedcomputercontrolledsimulateddigestionsystemtopredictdigestibleandmetabolizableenergyofunconventionalplantproteinmealsforgrowingpigs AT zengshuli anautomaticallyprogressedcomputercontrolledsimulateddigestionsystemtopredictdigestibleandmetabolizableenergyofunconventionalplantproteinmealsforgrowingpigs AT gaolixiang anautomaticallyprogressedcomputercontrolledsimulateddigestionsystemtopredictdigestibleandmetabolizableenergyofunconventionalplantproteinmealsforgrowingpigs AT zhaojiangtao anautomaticallyprogressedcomputercontrolledsimulateddigestionsystemtopredictdigestibleandmetabolizableenergyofunconventionalplantproteinmealsforgrowingpigs AT zhaofeng anautomaticallyprogressedcomputercontrolledsimulateddigestionsystemtopredictdigestibleandmetabolizableenergyofunconventionalplantproteinmealsforgrowingpigs AT duzhongyuan automaticallyprogressedcomputercontrolledsimulateddigestionsystemtopredictdigestibleandmetabolizableenergyofunconventionalplantproteinmealsforgrowingpigs AT wangyuming automaticallyprogressedcomputercontrolledsimulateddigestionsystemtopredictdigestibleandmetabolizableenergyofunconventionalplantproteinmealsforgrowingpigs AT songmingqiang automaticallyprogressedcomputercontrolledsimulateddigestionsystemtopredictdigestibleandmetabolizableenergyofunconventionalplantproteinmealsforgrowingpigs AT zengshuli automaticallyprogressedcomputercontrolledsimulateddigestionsystemtopredictdigestibleandmetabolizableenergyofunconventionalplantproteinmealsforgrowingpigs AT gaolixiang automaticallyprogressedcomputercontrolledsimulateddigestionsystemtopredictdigestibleandmetabolizableenergyofunconventionalplantproteinmealsforgrowingpigs AT zhaojiangtao automaticallyprogressedcomputercontrolledsimulateddigestionsystemtopredictdigestibleandmetabolizableenergyofunconventionalplantproteinmealsforgrowingpigs AT zhaofeng automaticallyprogressedcomputercontrolledsimulateddigestionsystemtopredictdigestibleandmetabolizableenergyofunconventionalplantproteinmealsforgrowingpigs |