Simões H G, Hiyane W C, Sotero R C, Pardono E, Puga G M, Lima L C J, Campbell C S G
Unit of Physical Activity and Health, Catholic University of Brasilia, Brasìlia, DF, Brazil.
J Sports Med Phys Fitness. 2009 Mar;49(1):14-8.
The lactate minimum (LM) protocol has been used to assess aerobic fitness and to predict exercise intensity associated with the maximal blood lactate steady state. The aim of this study was to compare different methods to identify the lactate minimum velocity (LMV) on cycling.
Fourteen male cyclists (26.8+/-4.5 years; 173.2+/-6.1 cm; 67.3+/-5.2 kg; 5,8+/-2.9 years of training) performed the LM test in a velodrome. The protocol consisted of an all out 2 km time trial to elevate blood lactate (bLAC), followed by 8 min of recovery and then 6 bouts of 2 km starting 5 kmxh(-1) below the individual mean velocity for the 6 km performance. The velocity was incremented by 1 kmxh(-1) at each bout with 25 microL of capillary blood being collected for bLAC measurements (YSI 2700 STAT). The LMV was identified visually (vLMV), and by applying a second grade polynomial function on 6 (pLMV(6)) and 3 (pLMV(3)) incremental bouts. Additionally, a method where the bLACx work velocity(-1) quotients (LMVQ) were plotted against the correspondent velocity during the incremental test, identified the LMV by considering 6 (LMVQ(6)) or 3 bouts (LMVQ(3)).
ANOVA showed no differences between vLMV (33.1+/-2.5 kmxh(-1)), pLMV(6) (32.9+/-2.5 kmxh(-1)), pLMV(3) (33.2+/-2.3 kmxh(-1)), LMVQ(6) (32.8+/-2.5 kmxh(-1)) and LMVQ(3) (33.4+/-2.3 kmxh(-1)), with high correlation among them.
It was possible to identify the LMV by the methods proposed in the present study, even when the results of only 3 bouts of the test were modeled by polynomial function. Such an approach enables a more practical and economical test in addition to minimizing the discomfort due to several blood collections.
乳酸最低值(LM)方案已被用于评估有氧适能,并预测与最大血乳酸稳态相关的运动强度。本研究的目的是比较不同方法来确定自行车运动中的乳酸最低速度(LMV)。
14名男性自行车运动员(年龄26.8±4.5岁;身高173.2±6.1厘米;体重67.3±5.2千克;训练年限5.8±2.9年)在自行车赛车场进行了LM测试。测试方案包括一次全力2公里计时赛以提高血乳酸(bLAC)水平,随后8分钟恢复,然后进行6组2公里骑行,起始速度比个人6公里成绩的平均速度低5公里·小时⁻¹。每组速度递增1公里·小时⁻¹,每次递增时采集25微升毛细血管血用于bLAC测量(YSI 2700 STAT)。通过视觉确定LMV(vLMV),并通过对6组(pLMV(6))和3组(pLMV(3))递增骑行数据应用二次多项式函数来确定。此外,在递增测试过程中,将bLAC×工作速度⁻¹商值(LMVQ)与相应速度作图,通过考虑6组(LMVQ(6))或3组(LMVQ(3))来确定LMV。
方差分析显示vLMV(33.1±2.5公里·小时⁻¹)、pLMV(6)(32.9±2.5公里·小时⁻¹)、pLMV(3)(33.2±2.3公里·小时⁻¹)、LMVQ(6)(32.8±2.5公里·小时⁻¹)和LMVQ(3)(33.4±2.3公里·小时⁻¹)之间无差异,且它们之间具有高度相关性。
即使仅用3组测试数据通过多项式函数建模,本研究提出的方法也能够确定LMV。这种方法除了能将多次采血带来的不适降至最低外,还能使测试更具实用性和经济性。