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Invited review: Disentangling residual feed intake—Insights and approaches to make it more fit for purpose in the modern context
- 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.
- Subjects :
- Computer science
media_common.quotation_subject
Context (language use)
Residual
03 medical and health sciences
Eating
[MATH.MATH-ST]Mathematics [math]/Statistics [math.ST]
feed efficiency
Genetics
Econometrics
Production (economics)
Animals
resilience
030304 developmental biology
media_common
2. Zero hunger
0303 health sciences
individual variation
Body Weight
0402 animal and dairy science
04 agricultural and veterinary sciences
040201 dairy & animal science
Animal Feed
Regression
Term (time)
[SDV.GEN.GA]Life Sciences [q-bio]/Genetics/Animal genetics
Phenotype
Trait
biological processes
Animal Science and Zoology
Cattle
Psychological resilience
Residual feed intake
Food Science
Subjects
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