De Maré Lorie, Boshuizen Berit, Vidal Moreno de Vega Carmen, de Meeûs Constance, Plancke Lukas, Gansemans Yannick, Van Nieuwerburgh Filip, Deforce Dieter, de Oliveira Jean Eduardo, Hosotani Guilherme, Oosterlinck Maarten, Delesalle Catherine
Department of Translational Physiology, Infectiology and Public Health, Research Group of Comparative Physiology, Faculty of Veterinary Medicine, Ghent University, Merelbeke, Belgium.
Equine Hospital Wolvega, Oldeholtpade, Netherlands.
Front Physiol. 2022 Mar 22;13:792052. doi: 10.3389/fphys.2022.792052. eCollection 2022.
There is a great need for objective external training load prescription and performance capacity evaluation in equestrian disciplines. Therefore, reliable standardised exercise tests (SETs) are needed. Classic SETs require maximum intensities with associated risks to deduce training loads from pre-described cut-off values. The lactate minimum speed (LMS) test could be a valuable alternative. Our aim was to compare new performance parameters of a modified LMS-test with those of an incremental SET, to assess the effect of training on LMS-test parameters and curve-shape, and to identify the optimal mathematical approach for LMS-curve parameters. Six untrained standardbred mares (3-4 years) performed a SET and LMS-test at the start and end of the 8-week harness training. The SET-protocol contains 5 increments (4 km/h; 3 min/step). The LMS-test started with a 3-min trot at 36-40 km/h [until blood lactate (BL) > 5 mmol/L] followed by 8 incremental steps (2 km/h; 3 min/step). The maximum lactate steady state estimation (MLSS) entailed >10 km run at the LMS and 110% LMS. The GPS, heartrate (Polar), and blood lactate (BL) were monitored and plotted. Curve-parameters (R core team, 3.6.0) were (SET) VLa. and (LMS-test) area under the curve (AUC), LMS and Aerobic Window (AW) angular vs. threshold method. Statistics for comparison: a paired -test was applied, except for LMS: paired Wilcoxon test; ( < 0.05). The Pearson correlation ( > 0.80), Bland-Altman method, and ordinary least products (OLP) regression analyses were determined for test-correlation and concordance. Training induced a significant increase in VLa.. The width of the AW increased significantly while the AUC and LMS decreased post-training (flattening U-curve). The LMS BL steady-state is reached earlier and maintained longer after training. BL was significantly lower for LMS vs. SET. The 40° angular method is the optimal approach. The correlation between LMS and V was significantly better compared to the SET. The VLa is unreliable for equine aerobic capacity assessment. The LMS-test allows more reliable individual performance capacity assessment at lower speed and BL compared to SETs. The LMS-test protocol can be further adapted, especially post-training; however, inducing modest hyperlactatemia prior to the incremental LMS-stages and omitting inclusion of a per-test recovery contributes to its robustness. This LMS-test is a promising tool for the development of tailored training programmes based on the AW, respecting animal welfare.
马术运动领域非常需要客观的外部训练负荷规定和运动能力评估。因此，需要可靠的标准化运动测试（SETs）。传统的SETs需要最大强度并伴有风险，以便从预先设定的临界值推断训练负荷。乳酸最低速度（LMS）测试可能是一种有价值的替代方法。我们的目的是比较改良LMS测试的新性能参数与递增SET的参数，评估训练对LMS测试参数和曲线形状的影响，并确定LMS曲线参数的最佳数学方法。六匹未经训练的标准bred母马（3 - 4岁）在为期8周的挽具训练开始和结束时进行了SET和LMS测试。SET方案包含5个递增阶段（4 km/h；每个阶段3分钟）。LMS测试从以36 - 40 km/h的速度小跑3分钟开始（直到血乳酸（BL）> 5 mmol/L），然后是8个递增阶段（2 km/h；每个阶段3分钟）。最大乳酸稳态估计（MLSS）需要在LMS速度和110% LMS速度下进行>10 km的跑步。监测并绘制了GPS、心率（Polar）和血乳酸（BL）数据。曲线参数（R核心团队，3.6.0）为（SET）VLa.以及（LMS测试）曲线下面积（AUC）、LMS和有氧窗口（AW）角度与阈值法。比较统计：除LMS采用配对Wilcoxon检验外，其他采用配对t检验；（< 0.05）。确定了Pearson相关性（> 0.80）、Bland - Altman方法和普通最小乘积（OLP）回归分析用于测试相关性和一致性。训练导致VLa.显著增加。训练后，AW的宽度显著增加，而AUC和LMS降低（U形曲线变平）。训练后，LMS的BL稳态达到得更早且维持时间更长。LMS的BL显著低于SET。40°角度法是最佳方法。与SET相比，LMS与V之间的相关性显著更好。VLa.对于评估马的有氧能力不可靠。与SETs相比，LMS测试能够在更低速度和BL水平下更可靠地评估个体运动能力。LMS测试方案可以进一步调整，特别是在训练后；然而，在递增的LMS阶段之前诱导适度的高乳酸血症并省略每次测试后的恢复阶段有助于提高其稳健性。这种LMS测试是一种有前景的工具，可用于基于AW制定量身定制的训练计划，同时尊重动物福利。
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