Literature DB >> 30715345

Development of a mathematical model for predicting digestible energy intake to meet desired body condition parameters in exercising horses.

Jennifer L Zoller1, Clay A Cavinder2, Dennis Sigler1, Luis O Tedeschi1, Julie Harlin3.   

Abstract

Maintaining optimal body condition is an important concern for horse owners and managers as it can affect reproductive efficiency, athletic ability, and overall health of the horse; however, information regarding dietary requirements to maintain or alter BCS in the horse is limited. A recently developed model had high accuracy in predicting the energy required to alter BCS in the horse. However, the model was restricted to sedentary mares, while many horses are subject to physical work. The objective of this study was to expand the scope of that model to include exercising horses by incorporating previously published estimates of exercise energy expenditure and then testing the expanded model. Stock type horses (n = 24) were grouped by initial BCS (3.0 to 6.5) and assigned to treatments of light (L), heavy (H), or no-exercise control (C). Horses were fed according to the model recommendations to increase (I) or decrease (D) two BCS within 60 d. Thus, six treatments were obtained: HD, HI, LD, LI, CD, CI. Mean DE intake Mcal/d for each group was HD = 19.3 ± 0.90, HI = 29 ± 0.84, LD = 13.2 ± 0.54, LI = 23.1 ± 1.39, CD = 12.1 ± 0.79, and CI = 21.9 ± 0.94. BCSs were evaluated by three independent appraisers, days 0 and 60 values were used to calculate the average BCS change for HD = -0.88 ± 0.24, HI = 1.13 ± 0.24, LD = -1.5 ± 0.29, LI = 0.88 ± 0.38, CD = -1.38 ± 0.13, and CI = 1.35 ± 0.14. Statistical comparison of final observed and model predicted values revealed acceptable precision when predicting BCS and BW respectively in control horses (r2 = 0.91, 0.98) but less precision when predicting body fat (BF) (r2 = 0.51). Model precision for BCS, BW, and BF respectively in lightly (r2 = 0.29, 0.85, 0.57) and heavily (r2 = 0.04, 0.84, 0.13) exercised horses was low. Model accuracy was acceptable across all treatments when predicting BW (Cb = 0.97, 0.96, 0.98). However, accuracy varied when predicting BCS (Cb = 0.82, 0.89, 0.41) and BF (Cb = 0.80, 0.55, 0.87) for the control, light, and heavy exercise groups, respectively. These results indicate that the revised model is acceptable for sedentary horses but the predictability of the model was insensitive to the exercising horse, therefore the exercise energy expenditure formulas incorporated into the model require revision. Packaging this model in a format that facilitates industry application could lead to more efficient feeding practices of sedentary horses, generating health, and economic benefit. Further investigation into energy expenditure of exercising horses could yield a model with broader applications.
© The Author(s) 2019. Published by Oxford University Press on behalf of the American Society of Animal Science. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Entities:  

Keywords:  body condition score; equine; exercise; nutrition model

Mesh:

Year:  2019        PMID: 30715345      PMCID: PMC6488313          DOI: 10.1093/jas/skz041

Source DB:  PubMed          Journal:  J Anim Sci        ISSN: 0021-8812            Impact factor:   3.159


  10 in total

1.  Relationship between body composition, blood volume and maximal oxygen uptake.

Authors:  C F Kearns; K H McKeever; H John-Alder; T Abe; W F Brechue
Journal:  Equine Vet J Suppl       Date:  2002-09

2.  Assessment of body fat in the pony: part II. Validation of the deuterium oxide dilution technique for the measurement of body fat.

Authors:  A H A Dugdale; G C Curtis; E Milne; P A Harris; C Mc Argo
Journal:  Equine Vet J       Date:  2011-03-04       Impact factor: 2.888

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Authors:  H F Hintz; S J Roberts; S W Sabin; H F Schryver
Journal:  J Anim Sci       Date:  1971-01       Impact factor: 3.159

4.  Relationship between condition score, physical measurements and body fat percentage in mares.

Authors:  D R Henneke; G D Potter; J L Kreider; B F Yeates
Journal:  Equine Vet J       Date:  1983-10       Impact factor: 2.888

5.  Accounting for energy and protein reserve changes in predicting diet-allowable milk production in cattle.

Authors:  L O Tedeschi; S Seo; D G Fox; R Ruiz
Journal:  J Dairy Sci       Date:  2006-12       Impact factor: 4.034

6.  The development and evaluation of a mathematical nutrition model to predict digestible energy intake of broodmares based on body condition changes.

Authors:  V V Cordero; C A Cavinder; L O Tedeschi; D H Sigler; M M Vogelsang; C E Arnold
Journal:  J Anim Sci       Date:  2013-02-19       Impact factor: 3.159

7.  Effect of body condition, body weight and adiposity on inflammatory cytokine responses in old horses.

Authors:  Amanda A Adams; Madhu P Katepalli; Katharina Kohler; Stephanie E Reedy; J P Stilz; Mandi M Vick; Barry P Fitzgerald; Laurie M Lawrence; David W Horohov
Journal:  Vet Immunol Immunopathol       Date:  2008-10-31       Impact factor: 2.046

8.  Obesity and diet affect glucose dynamics and insulin sensitivity in Thoroughbred geldings.

Authors:  R M Hoffman; R C Boston; D Stefanovski; D S Kronfeld; P A Harris
Journal:  J Anim Sci       Date:  2003-09       Impact factor: 3.159

9.  Effect of treadmill incline and speed on metabolic rate during exercise in thoroughbred horses.

Authors:  M D Eaton; D L Evans; D R Hodgson; R J Rose
Journal:  J Appl Physiol (1985)       Date:  1995-09

10.  Body fat of stock-type horses predicted by rump fat thickness and deuterium oxide dilution and validated by near-infrared spectroscopy of dissected tissues.

Authors:  E N Ferjak; C A Cavinder; D D Burnett; C Mc Argo; T T N Dinh
Journal:  J Anim Sci       Date:  2017-10       Impact factor: 3.159

  10 in total

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