|Id||Title||Authors||Abstract||Picture||Thematic fields||Recommender||Reviewers||Submission date|
06 Sep 2019
Lactation curve model with explicit representation of perturbations as a phenotyping tool for dairy livestock precision farming.Ben Abdelkrim Ahmed, Puillet Laurence, Gomes Pierre, Martin Olivier https://doi.org/10.1101/661249
Developing smart fitting algorithms to identify random perturbations in time-series dataRecommended by Luis Tedeschi based on reviews by Alberto Atzori, Jennifer Spencer and 1 anonymous reviewer
The ability to adequately characterize the lactation curve of livestock is important not only to ensure proper nutrition of the lactating animal but, among many other benefits, it can assist in diagnosing the incidence of diseases, predicting the quantity of milk production, and comparing animals within the herd for managerial strategies such as culling. Eventually, such smart fitting algorithms can lead to improved genetic selection of more productive animals after genetic-unrelated noises are removed from the data, systematically.
 Johansson, I. (1961). Genetic Aspects of Dairy Cattle Breeding. University of Illinois Press, Urbana, IL.
 Nelder, J. A. (1966). Inverse polynomials, a useful group of multi-factor response functions. Biometrics. 22 (1):128-141. doi: 10.2307/2528220
|Lactation curve model with explicit representation of perturbations as a phenotyping tool for dairy livestock precision farming.||Ben Abdelkrim Ahmed, Puillet Laurence, Gomes Pierre, Martin Olivier||<p>Background Understanding the effects of environment on livestock provides valuable information on how farm animals express their production potential, and on their welfare. Ruminants are often confronted with perturbations that affect their per...||Lactation biology , Mathematical modelling, Precision livestock farming||Luis Tedeschi||2019-06-07 09:38:26||View|