title: Characterizing individual differences in animal responses to a nutritional challenge: Toward improved robustness measures.
abstract: The aim of this paper was to explore the variation between individuals in the response to and recovery from a nutritional challenge, the repeatability of responses between lactation stages, and the use of shape-clustering methods to classify similar individuals. Sixteen dairy goats were exposed to a 2-d nutritional challenge (underfeeding) at 2 different stages of lactation. Each challenge consisted of a 7-d control period with standard total mixed ration (TMR), 2d of straw-only feeding, and a 10-d recovery period on the TMR. All feeds were offered ad libitum, as was water. The first challenge was in late lactation on primiparous goats (mean days in milk=249), and the second challenge was carried out on the same goats early in the following lactation (mean days in milk=28). The main energetic response traits dry matter intake (DMI), milk yield, body weight, milk fat and protein contents, and plasma glucose, fatty acids (NEFA), β-hydroxybutyrate (BHB), urea, and insulin, were measured daily throughout. A clustering procedure linked to a piecewise mixed model was used to characterize different types of response. As expected, straw feeding caused a large decline in DMI and milk yield, and substantial increases in milk fat and milk protein composition, relative to the prechallenge period on the control TMR. For both DMI and milk yield, the slope of the response, and hence the size of the drop, was strongly related to the prechallenge values, indicating that these 2 measures were tightly constrained by the challenge. Regression slopes between lactation stages for responses to the same nutritional challenge were significant for DMI, milk protein content, plasma BHB and urea, and body weight, indicating that within-animal responses in late and early lactation were repeatable. The clustering procedure generally performed well, classifying both scaling differences and differences in shape. The extent of reranking of cluster designations between late lactation and the following early lactation period was examined. For milk yield, DMI, body weight, and urea, relatively little reranking occurred; the numbers of goats not changing class number were 10, 12, 10, and 13, respectively. In contrast, for milk contents of fat and protein, and also for BHB, no clear association was found between late and early lactation class numbers. For NEFA and glucose, these comparisons were not relevant because either the vast majority of goats were in 1 cluster (NEFA) or because an outlier goat skewed the cluster designation (glucose in late lactation). For insulin, 9 out of 16 goats kept the same rank.
authors.affiliation: INRA UMR 791 Modélisation Systémique Appliquée aux Ruminants, 16 Rue Claude Bernard, F-75005 Paris, France; AgroParisTech UMR 791 Modélisation Systémique Appliquée aux Ruminants, 16 Rue Claude Bernard, F-75005 Paris, France. Electronic address: nicolas.friggens@agroparistech.fr.
authors.forename: N C
authors.initials: NC
authors.lastname: Friggens
authors.affiliation: INRA UMR 791 Modélisation Systémique Appliquée aux Ruminants, 16 Rue Claude Bernard, F-75005 Paris, France; AgroParisTech UMR 791 Modélisation Systémique Appliquée aux Ruminants, 16 Rue Claude Bernard, F-75005 Paris, France.
authors.forename: C
authors.initials: C
authors.lastname: Duvaux-Ponter
authors.affiliation: UMR AgroParisTech/INRA MIA 518, 16 Rue Claude Bernard, 75005 Paris, France.
authors.forename: M P
authors.initials: MP
authors.lastname: Etienne
authors.affiliation: UMR AgroParisTech/INRA MIA 518, 16 Rue Claude Bernard, 75005 Paris, France; UMR de Génétique Végétale, INRA/Univ. Paris-Sud/CNRS, 91190 Gif-Sur-Yvette, France.
authors.forename: T
authors.initials: T
authors.lastname: Mary-Huard
authors.affiliation: INRA UMR 791 Modélisation Systémique Appliquée aux Ruminants, 16 Rue Claude Bernard, F-75005 Paris, France; AgroParisTech UMR 791 Modélisation Systémique Appliquée aux Ruminants, 16 Rue Claude Bernard, F-75005 Paris, France.
authors.forename: P
authors.initials: P
authors.lastname: Schmidely
mesh_terms: D020155:3-Hydroxybutyric Acid / Q000097:blood; D000824:Animal Nutritional Physiological Phenomena; D000818:Animals; D001835:Body Weight / Q000502:physiology; D005227:Fatty Acids / Q000097:blood / Q000378:metabolism; D005260:Female; D006041:Goats / Q000502:physiology*; D007328:Insulin / Q000378:metabolism; D007774:Lactation / Q000502:physiology*; D008892:Milk / Q000737:chemistry / Q000378:metabolism; D008894:Milk Proteins / Q000032:analysis* / Q000737:chemistry / Q000378:metabolism
chemical_list: D005227:Fatty Acids; D007328:Insulin; D008894:Milk Proteins; D020155:3-Hydroxybutyric Acid
keywords: adaptive capacity; clustering method; dairy goat; lactation; resilience