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1000 Titel
  • A Novel Estimation of Unobserved Pig Growth Traits for the Purposes of Precision Feeding Methods
1000 Autor/in
  1. Misiura, Maciej M. |
  2. Filipe, Joao A. N. |
  3. Kyriazakis, Ilias |
1000 Erscheinungsjahr 2021
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2021-07-29
1000 Erschienen in
1000 Quellenangabe
  • 8:689206
1000 Copyrightjahr
  • 2021
1000 Embargo
  • 2022-01-31
1000 Lizenz
1000 Verlagsversion
  • https://doi.org/10.3389/fvets.2021.689206 |
  • https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8360350/ |
1000 Publikationsstatus
1000 Begutachtungsstatus
1000 Abstract/Summary
  • <jats:p>Recent technological advances make it possible to deliver feeding strategies that can be tailored to the needs of individual pigs in order to optimise the allocation of nutrient resources and contribute toward reducing excess nutrient excretion. However, these efforts are currently hampered by the challenges associated with: (1) estimation of unobserved traits from the available data on bodyweight and feed consumption; and (2) characterisation of the distributions and correlations of these unobserved traits to generate accurate estimates of individual level variation among pigs. Here, alternative quantitative approaches to these challenges, based on the principles of inverse modelling and separately inferring individual level distributions within a Bayesian context were developed and incorporated in a proposed precision feeding modelling framework. The objectives were to: (i) determine the average and distribution of individual traits characterising growth potential and body composition in an empirical population of growing-finishing barrows and gilts; (ii) simulate the growth and excretion of nitrogen and phosphorus of the average pig offered either a commercial two-phase feeding plan, or a precision feeding plan with daily adjustments; and (iii) simulate the growth and excretion of nitrogen and phosphorus across the pig population under two scenarios: a two-phase feeding plan formulated to meet the nutrient requirements of the average pig or a precision feeding plan with daily adjustments for each and every animal in the population. The distributions of mature bodyweight and ratio of lipid to protein weights at maturity had median (IQR) values of 203 (47.8) kg and 2.23 (0.814) kg/kg, respectively; these estimates were obtained without any prior assumptions concerning correlations between the traits. Overall, it was found that a proposed precision feeding strategy could result in considerable reductions in excretion of nitrogen and phosphorus (average pig: 8.07 and 9.17% reduction, respectively; heterogenous pig population: 22.5 and 22.9% reduction, respectively) during the growing-finishing period from 35 to 120 kg bodyweight. This precision feeding modelling framework is anticipated to be a starting point toward more accurate estimation of individual level nutrient requirements, with the general aim of improving the economic and environmental sustainability of future pig production systems.</jats:p>
1000 Sacherschließung
lokal Veterinary Science
lokal pigs
lokal nitrogen excretion
lokal phosphorus excretion
lokal Bayesian inference
lokal body composifion
lokal precision feeding
lokal individual traits
1000 Liste der Beteiligten
  1. https://frl.publisso.de/adhoc/uri/TWlzaXVyYSwgTWFjaWVqIE0u|https://frl.publisso.de/adhoc/uri/RmlsaXBlLCBKb2FvIEEuIE4u|https://frl.publisso.de/adhoc/uri/S3lyaWF6YWtpcywgSWxpYXM=
1000 Hinweis
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1000 Label
1000 Förderer
  1. Horizon 2020 Framework Programme |
  2. Rural and Environment Science and Analytical Services Division |
1000 Fördernummer
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  2. -
1000 Förderprogramm
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  2. -
1000 Dateien
1000 Förderung
  1. 1000 joinedFunding-child
    1000 Förderer Horizon 2020 Framework Programme |
    1000 Förderprogramm -
    1000 Fördernummer -
  2. 1000 joinedFunding-child
    1000 Förderer Rural and Environment Science and Analytical Services Division |
    1000 Förderprogramm -
    1000 Fördernummer -
1000 Objektart article
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1000 @id frl:6475056.rdf
1000 Erstellt am 2024-04-11T14:13:11.990+0200
1000 Erstellt von 322
1000 beschreibt frl:6475056
1000 Zuletzt bearbeitet 2024-04-29T11:29:52.590+0200
1000 Objekt bearb. Mon Apr 29 11:29:52 CEST 2024
1000 Vgl. frl:6475056
1000 Oai Id
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