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Invited review: Disentangling residual feed intake—Insights and approaches to make it more fit for purpose in the modern context

Authors :
Vincent Ducrocq
Nicolas Friggens
Pauline Martin
Philippe Faverdin
Génétique Animale et Biologie Intégrative (GABI)
Université Paris-Saclay-AgroParisTech-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)
Physiologie, Environnement et Génétique pour l'Animal et les Systèmes d'Elevage [Rennes] (PEGASE)
AGROCAMPUS OUEST
Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)
Modélisation Systémique Appliquée aux Ruminants (MoSAR)
AgroParisTech-Université Paris-Saclay-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)
APIS-GENE
ANR-15-CE20-0014,Deffilait,Améliorer l'efficacité alimentaire des vaches laitières : comprendre les déterminants grace à de nouveaux outils de phénotypage pour mieux l'évaluer et élaborer des stratégies de sélection génétique en fonction des conditions d'élevage(2015)
European Project: 727213,H2020,H2020-EU.3.2.1.1.,GenTORE(2017)
Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-INSTITUT AGRO Agrocampus Ouest
Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)
Source :
Journal of Dairy Science, Journal of Dairy Science, American Dairy Science Association, 2021, 104 (6), pp.6329-6342. ⟨10.3168/jds.2020-19844⟩, Journal of Dairy Science, 2021, 104 (6), pp.6329-6342. ⟨10.3168/jds.2020-19844⟩
Publication Year :
2021

Abstract

International audience; Residual feed intake (RFI) is an increasingly used trait to analyze feed efficiency in livestock, and in some sectors such as dairy cattle, it is one of the most frequently used traits. Although the principle for calculating RFI is always the same (i.e., using the residual of a regression of intake on performance predictors), a wide range of models are found in the literature, with different predictors, different ways of considering intake, and more recently, different statistical approaches. Consequently, the results are not easily comparable from one study to another as they reflect different biological variabilities, and the relationship between the residual (i.e., RFI) and the underlying true efficiency also differs. In this review, the components of the RFI equation are explored with respect to the underlying biological processes. The aim of this decomposition is to provide a better understanding of which of the processes in this complex trait contribute significantly to the individual variability in efficiency. The intricacies associated with the residual term, as well as the energy sinks and the intake term, are broken down and discussed. Based on this exploration as well as on some recent literature, new forms of the RFI equation are proposed to better separate the efficiency terms from errors and inaccuracies. The review also considers the time period of measurement of RFI. This is a key consideration for the accuracy of the RFI estimation itself, and also for understanding the relationships between short-term efficiency, animal resilience, and long-term efficiency. As livestock production moves toward sustainable efficiency, these considerations are increasingly important to bring to bear in RFI estimations.

Details

ISSN :
00220302
Database :
OpenAIRE
Journal :
Journal of Dairy Science
Accession number :
edsair.doi.dedup.....76b80dc0d30e37949b5d0de20c2f2375
Full Text :
https://doi.org/10.3168/jds.2020-19844