The development and evaluation of a mathematical nutrition model to predict digestible energy intake of broodmares based on body condition changes.
Abstract: Mathematical nutrition models have been developed for beef and dairy cattle to estimate dietary energy intake needed to change BCS. Similar technology has not been used to improve nutrition and feeding strategies for horses. An accurate equine nutrition model may enhance feeding management and reduce the costs of unnecessary overfeeding and promote an optimal level of fatness to achieve reproductive efficiency. The objectives of this study were to develop and evaluate a mathematical nutrition model capable of accurately predicting dietary energy changes to alter BW, rump fat (RF) thickness, and overall body fat (BF), which is needed to maximize profitability and productivity of mares. Model structure was similar to a previously developed model for cattle, and literature data for Quarter Horse mares were used to parameterize the horse model in predicting DE requirement associated with BCS changes. Evaluation of the horse model was performed using an independent dataset comprising 20 nonlactating Quarter Horse mares. Pretrial BCS was used to assign mares to 1 of 4 treatment groups and fed to alter BCS by 1 unit as follows: from 4 to 5 (Group 1), 5 to 4 (Group 2), 6 to 7 (Group 3), and 7 to 6 (Group 4). The BCS, RF thickness, and BW were measured for each mare before the commencement of the feeding trial and once per week thereafter for the duration of a 30-d feeding trial. Initial and target BCS, percent BF, and BW data were collected from each mare and inputted into the model. Mares were individually fed according to the DE suggestions proposed by the model to achieve the targeted BCS change within 30 d. The coefficient of determination of observed and model-predicted values (model precision) was 0.907 (P < 0.001) for BCS, 0.607 (P < 0.001) for percent BF, and 0.94 (P < 0.001) for BW. The BCS was highly correlated to percent BF (r = 0.808; P = 0.01). We concluded the reparameterized model was reliable to predict changes in BW and BCS, but more work is needed to improve the predictions of initial and final body composition.
Publication Date: 2013-02-19 PubMed ID: 23422008DOI: 10.2527/jas.2011-4659Google Scholar: Lookup
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Summary
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The article discusses the creation and testing of a mathematical nutrition model designed to predict the dietary energy changes needed in broodmares to alter their body weight and fat levels, in order to optimise their productivity and profitability.
Objective of Research
- The primary objective of this research study was to design and evaluate a mathematical nutrition model for broodmares. This model was intended to accurately predict dietary energy intake changes necessary to alter a mare’s body weight (BW), rump fat (RF) thickness, and total body fat (BF).
- The aim of this model was to help enhance feeding management practices, lower costs associated with overfeeding, and ensure mares maintain an optimal level of fatness for efficient reproduction.
Research Method
- The model structure employed was similar to that previously developed for beef and dairy cattle. Data specific to Quarter Horse mares was utilised for parameterising the equine model to predict the Digestible Energy (DE) requirement associated with Body Condition Score (BCS) changes.
- For the evaluation phase, an independent dataset comprising 20 nonlactating Quarter Horse mares was used. These mares were segmented into 4 groups based on their pretrial BCS, with each group designed to undergo a 1-unit BCS change through feeding alteration over a 30-day period.
Research Findings
- The nutrition model accurately predicted changes in BCS and body weight. The precision of the model was high, as indicated by a coefficient of determination of 0.907 for BCS and 0.94 for body weight.
- However, the model’s capacity to accurately predict percentage of body fat was slightly lower, with a coefficient of determination of 0.607.
- There was a strong correlation found between BCS and percentage body fat, with a correlation coefficient of 0.808.
Conclusions
- According to the results obtained, the researchers concluded that the reparameterized model was effective in predicting changes in body weight and BCS.
- However, the prediction of initial and final body composition needs improvement. The less precise prediction of the percentage of body fat suggests that further research and model refinement is required to increase the accuracy of these measurements.
Cite This Article
APA
Cordero VV, Cavinder CA, Tedeschi LO, Sigler DH, Vogelsang MM, Arnold CE.
(2013).
The development and evaluation of a mathematical nutrition model to predict digestible energy intake of broodmares based on body condition changes.
J Anim Sci, 91(5), 2169-2177.
https://doi.org/10.2527/jas.2011-4659 Publication
Researcher Affiliations
- Department of Animal Science, Texas A&M University, College Station, TX 77843-2471, USA.
MeSH Terms
- Animal Husbandry / methods
- Animal Nutritional Physiological Phenomena
- Animals
- Body Composition
- Diet / veterinary
- Energy Intake
- Energy Metabolism
- Female
- Horses / physiology
- Models, Biological
- Nutritional Status
- Reproduction
Citations
This article has been cited 5 times.- Baker LA, Burrows AM, Nonella KJ, Pipkin JL, Holmes LD, McEvers TJ, Tennant TC, Tisdale ZM, Voyles AH, Lawrence TE. Relationship between live body condition score and carcass fat measures in equine. Transl Anim Sci 2020 Oct;4(4):txaa179.
- Ebert M, Moore-Colyer MJS. The energy requirements of performance horses in training. Transl Anim Sci 2020 Apr;4(2):txaa032.
- Much ML, Leatherwood JL, Zoller JL, Bradbery AN, Martinez RE, Keegan AD, Lamprecht ED, Wickersham TA. Influence of diet fortification on body composition and apparent digestion in mature horses consuming a low-quality forage. Transl Anim Sci 2020 Jan;4(1):1-9.
- Zoller JL, Cavinder CA, Sigler D, Tedeschi LO, Harlin J. Development of a mathematical model for predicting digestible energy intake to meet desired body condition parameters in exercising horses. J Anim Sci 2019 Apr 29;97(5):1945-1955.
- Shumilov D, Heymsfield SB, Redman LM, Smith SR, Bray GA, Kalluri K, Dey J. New compartment model analysis of lean-mass and fat-mass growth with overfeeding. Nutrition 2016 May;32(5):590-600.
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