Cargando…

Profiling the Aerobic Window of Horses in Response to Training by Means of a Modified Lactate Minimum Speed Test: Flatten the Curve

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-d...

Descripción completa

Detalles Bibliográficos
Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8982777/
https://www.ncbi.nlm.nih.gov/pubmed/35392373
http://dx.doi.org/10.3389/fphys.2022.792052
_version_ 1784681863475888128
author 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
author_facet 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
author_sort De Maré, Lorie
collection PubMed
description 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(1).(5/2/4) and (LMS-test) area under the curve (AUC(>/<LMS)), LMS and Aerobic Window (AW) via angular vs. threshold method. Statistics for comparison: a paired t-test was applied, except for LMS: paired Wilcoxon test; (p < 0.05). The Pearson correlation (r > 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(1).(5/2/4). The width of the AW increased significantly while the AUC(</>LMS) and LMS decreased post-training (flattening U-curve). The LMS BL steady-state is reached earlier and maintained longer after training. BL(max) was significantly lower for LMS vs. SET. The 40° angular method is the optimal approach. The correlation between LMS and V(MLSS) was significantly better compared to the SET. The VLa(4) 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.
format Online
Article
Text
id pubmed-8982777
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-89827772022-04-06 Profiling the Aerobic Window of Horses in Response to Training by Means of a Modified Lactate Minimum Speed Test: Flatten the Curve 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 Front Physiol Physiology 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(1).(5/2/4) and (LMS-test) area under the curve (AUC(>/<LMS)), LMS and Aerobic Window (AW) via angular vs. threshold method. Statistics for comparison: a paired t-test was applied, except for LMS: paired Wilcoxon test; (p < 0.05). The Pearson correlation (r > 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(1).(5/2/4). The width of the AW increased significantly while the AUC(</>LMS) and LMS decreased post-training (flattening U-curve). The LMS BL steady-state is reached earlier and maintained longer after training. BL(max) was significantly lower for LMS vs. SET. The 40° angular method is the optimal approach. The correlation between LMS and V(MLSS) was significantly better compared to the SET. The VLa(4) 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. Frontiers Media S.A. 2022-03-22 /pmc/articles/PMC8982777/ /pubmed/35392373 http://dx.doi.org/10.3389/fphys.2022.792052 Text en Copyright © 2022 De Maré, Boshuizen, Vidal Moreno de Vega, de Meeûs, Plancke, Gansemans, Van Nieuwerburgh, Deforce, de Oliveira, Hosotani, Oosterlinck and Delesalle. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Physiology
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
Profiling the Aerobic Window of Horses in Response to Training by Means of a Modified Lactate Minimum Speed Test: Flatten the Curve
title Profiling the Aerobic Window of Horses in Response to Training by Means of a Modified Lactate Minimum Speed Test: Flatten the Curve
title_full Profiling the Aerobic Window of Horses in Response to Training by Means of a Modified Lactate Minimum Speed Test: Flatten the Curve
title_fullStr Profiling the Aerobic Window of Horses in Response to Training by Means of a Modified Lactate Minimum Speed Test: Flatten the Curve
title_full_unstemmed Profiling the Aerobic Window of Horses in Response to Training by Means of a Modified Lactate Minimum Speed Test: Flatten the Curve
title_short Profiling the Aerobic Window of Horses in Response to Training by Means of a Modified Lactate Minimum Speed Test: Flatten the Curve
title_sort profiling the aerobic window of horses in response to training by means of a modified lactate minimum speed test: flatten the curve
topic Physiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8982777/
https://www.ncbi.nlm.nih.gov/pubmed/35392373
http://dx.doi.org/10.3389/fphys.2022.792052
work_keys_str_mv AT demarelorie profilingtheaerobicwindowofhorsesinresponsetotrainingbymeansofamodifiedlactateminimumspeedtestflattenthecurve
AT boshuizenberit profilingtheaerobicwindowofhorsesinresponsetotrainingbymeansofamodifiedlactateminimumspeedtestflattenthecurve
AT vidalmorenodevegacarmen profilingtheaerobicwindowofhorsesinresponsetotrainingbymeansofamodifiedlactateminimumspeedtestflattenthecurve
AT demeeusconstance profilingtheaerobicwindowofhorsesinresponsetotrainingbymeansofamodifiedlactateminimumspeedtestflattenthecurve
AT planckelukas profilingtheaerobicwindowofhorsesinresponsetotrainingbymeansofamodifiedlactateminimumspeedtestflattenthecurve
AT gansemansyannick profilingtheaerobicwindowofhorsesinresponsetotrainingbymeansofamodifiedlactateminimumspeedtestflattenthecurve
AT vannieuwerburghfilip profilingtheaerobicwindowofhorsesinresponsetotrainingbymeansofamodifiedlactateminimumspeedtestflattenthecurve
AT deforcedieter profilingtheaerobicwindowofhorsesinresponsetotrainingbymeansofamodifiedlactateminimumspeedtestflattenthecurve
AT deoliveirajeaneduardo profilingtheaerobicwindowofhorsesinresponsetotrainingbymeansofamodifiedlactateminimumspeedtestflattenthecurve
AT hosotaniguilherme profilingtheaerobicwindowofhorsesinresponsetotrainingbymeansofamodifiedlactateminimumspeedtestflattenthecurve
AT oosterlinckmaarten profilingtheaerobicwindowofhorsesinresponsetotrainingbymeansofamodifiedlactateminimumspeedtestflattenthecurve
AT delesallecatherine profilingtheaerobicwindowofhorsesinresponsetotrainingbymeansofamodifiedlactateminimumspeedtestflattenthecurve