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Kronfeld, D. S., Custalow, S. E., Ferrante, P. L., Taylor, L. E., Wilson, J. A., & Tiegs, W. (1998). Acid-base responses of fat-adapted horses: relevance to hard work in the heat. Appl. Anim. Behav. Sci., 59(1-3), 61–72.
Abstract: Feeding and training may affect acid-base responses to strenuous exercise. Acidosis usually correlates with higher blood lactate concentrations during intense exercise, but alkalosis has been found in several studies of horses, and higher lactate responses during sprints have been found in fat adapted horses. To elucidate these unexpected findings, we applied a comprehensive physicochemical approach to evaluate acid-base responses during exercise in fat adapted horses. In incremental tests and repeated sprints, changes in blood [H+] were dependent upon corresponding changes in pCO2 but not strong ion difference (SID, the algebraic sum of ions of sodium, potassium, chloride and lactate). The influence of changes in [Lac-] were largely offset by changes in [Na+], [K+] and [Cl-], so that SID was unchanged and did not contribute to the exercise induced acidemia, so it may be inaccurate to term this a lacticacidosis. During repeated sprints, central venous [H+] increased (acidosis) but arterial [H+] decreased (alkalosis). These changes were consistent with concurrent changes in venous and arterial pCO2 but not SID. Fat adaptation decreased mixed venous pCO2 during repeated sprints, which is consistent with the lower respiratory quotient associated with fat oxidation. Less pulmonary work to eliminate CO2 could benefit horses under hot and humid conditions, especially those with mildly reduced pulmonary function. The blood lactate response was decreased during aerobic tests but increased during anaerobic tests on fat adapted horses. Fat adaptation appears to facilitate the metabolic regulation of glycolysis, by sparing glucose and glycogen at work of low intensity, but by promoting glycolysis when power is needed for high intensity exercise. The blood lactate response to repeated sprints was increased more by the combination of fat adaptation and oral supplementation of sodium bicarbonate than by the sum of the responses to fat alone or bicarbonate alone. This synergism suggests that need for further studies of the interaction of fat adaptation with dietary cation-anion balance, especially under hot conditions. These results integrate harmoniously with previous findings of lower feed intake and fecal output, lower loads of heat and CO2, lower water losses in the feces and by evaporation, and less spontaneous activity and reactivity in fat adapted horses. Thus fat adaptation confers several advantages on horses and presumably other equids used for hard work, especially in the heat.
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Staniar, W. B., Kronfeld, D. S., Hoffman, R. M., Wilson, J. A., & Harris, P. A. (2004). Weight prediction from linear measures of growing Thoroughbreds. Equine Vet J, 36(2), 149–154.
Abstract: REASON FOR PERFORMING STUDY: Monitoring weight of foals is a useful management practice to aid in maximising athletic potential while minimising risks associated with deviations from normal growth. OBJECTIVE: To develop predictive equations for weight, based on linear measurements of growing Thoroughbreds (TBs). METHODS: Morphometric equations predicting weight from measurements of the trunk and legs were developed from data of 153 foals. The accuracy, precision and bias of the best fitting equation were compared to published equations using a naive data set of 22 foals. RESULTS: Accuracy and precision were maximised with a broken line relating calculated volumes (V(t + l)) to measured weights. Use of the broken line is a 2 step process. V(t + l) is calculated from linear measures (m) of girth (G), carpus circumference (C), and length of body (B) and left forelimb (F). V(t + I) = ([G2 x B] + 4[C2 x F]) 4pi. If V(t + l) < 0.27 m3, weight is estimated: Weight (kg) = V(t + l) x 1093. If V(t + l) > or = 0.27 m3: Weight (kg) = V(t + l) x 984 + 24. The broken line was more accurate and precise than 3 published equations predicting the weight of young TBs. CONCLUSIONS: Estimation of weight using morphometric equations requires attention to temporal changes in body shape and density; hence, a broken line is needed. Including calculated leg volume in the broken line model is another contributing factor to improvement in predictive capability. POTENTIAL RELEVANCE: The broken line maximises its value to equine professionals through its accuracy, precision and convenience.
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