The Anaerobic Capacity of Cross-Country Skiers: The Effect of Computational Method and Skiing Sub-technique

Physiological responses and performance factors for double-poling and diagonal-stride treadmill roller-skiing time-trial exercise

PURPOSE

To compare physiological responses between a self-paced 4-min double-poling (DP) time-trial (TTDP) versus a 4-min diagonal-stride (DS) time-trial (TTDS). The relative importance of peak oxygen uptake ([Formula: see text]O2peak), anaerobic capacity, and gross efficiency (GE) for projection of 4-min TTDP and TTDS roller-skiing performances were also examined.

METHODS

Sixteen highly trained male cross-country skiers performed, in each sub-technique on separate occasions, an 8 × 4-min incremental submaximal protocol, to assess individual metabolic rate (MR) versus power output (PO) relationships, followed by a 10-min passive break and then the TTDP or TTDS, with a randomized order between sub-techniques.

RESULTS

In comparison to TTDS, the TTDP resulted in 10 ± 7% lower total MR, 5 ± 4% lower aerobic MR, 30 ± 37% lower anaerobic MR, and 4.7 ± 1.2 percentage points lower GE, which resulted in a 32 ± 4% lower PO (all P < 0.01). The [Formula: see text]O2peak and anaerobic capacity were 4 ± 4% and 30 ± 37% lower, respectively, in DP than DS (both P < 0.01). The PO for the two time-trial (TT) performances were not significantly correlated (R2 = 0.044). Similar parabolic pacing strategies were used during both TTs. Multivariate data analysis projected TT performance using [Formula: see text]O2peak, anaerobic capacity, and GE (TTDP, R2 = 0.974; TTDS, R2 = 0.848). The variable influence on projection values for [Formula: see text]O2peak, anaerobic capacity, and GE were for TTDP, 1.12 ± 0.60, 1.01 ± 0.72, and 0.83 ± 0.38, respectively, and TTDS, 1.22 ± 0.35, 0.93 ± 0.44, and 0.75 ± 0.19, respectively.

CONCLUSIONS

The results show that a cross-country skier's "metabolic profile" and performance capability are highly sub-technique specific and that 4-min TT performance is differentiated by physiological factors, such as [Formula: see text]O2peak, anaerobic capacity, and GE.

The effect of exercise hyperpnea on gross efficiency and anaerobic capacity estimates during a 3-min cycle time trial

This study aimed to analyze the effect of exercise-induced hyperpnea on gross efficiency (GE) and anaerobic capacity estimates during a self-paced 3-min supramaximal cycle time trial (TT). Fourteen highly trained male cyclists performed 7 × 4-min submaximal stages, a 6-min passive rest, a 3-min TT, a 5-min passive rest, and a 6-min submaximal stage. Three models were based on the 7 × 4-min linear regression extrapolation method, using 1) the conventional model (7-Y_LIN); 2) the same 7-Y_LIN model but correcting for the additional ventilatory cost (i.e., hyperpnea) (7-Y_LIN-V-cor); and 3) accounting for linearly declining GE during the TT (7-Y_LIN-D). The other three models were based on GE from the last submaximal stage, using the conventional model (GE_LAST) and the same modifications as described for 7+Y_LIN, i.e., 1) GE_LAST, 2) GE_LAST-V-cor, and 3) GE_LAST-D. The GE_LAST model generated 18% higher values of anaerobic capacity than the 7-Y_LIN model (P < 0.05). During the TT, the hyperpnea-corrected model (i.e., 7-Y_LIN-V-cor or GE_LAST-V-cor) generated, compared with the respective conventional model (i.e., 7-Y_LIN or GE_LAST), ∼0.7 percentage points lower GE and ∼11% higher anaerobic capacity (all, P < 0.05). The post-TT GE was 1.9 percentage points lower (P < 0.001) and the 7-Y_LIN-D or GE_LAST-D model generated, compared with the respective conventional model, a lower GE (∼1.0 percentage points) and ∼17% higher anaerobic capacity during the TT (all, P < 0.05). In conclusion, the correction for a declining GE due to hyperpnea during a supramaximal TT resulted in an increased required total metabolic rate and anaerobic energy expenditure compared with the conventional models.NEW & NOTEWORTHY This study demonstrates that GE declines during a 3-min supramaximal cycle TT, which is possibly related to the hyperpneic response during supramaximal exercise. The finding from this study also provides novel insight into how the increased ventilatory energy cost from exercise-induced hyperpnea contributes to decreased GE, increased required total metabolic rate, and increased anaerobic energy expenditure during supramaximal exercise. Therefore, conventional linear models for estimating anaerobic capacity are likely to generate underestimated values.

Anaerobic work capacity in cycling: the effect of computational method

PURPOSE

To compare the anaerobic work capacity (AnWC, i.e., attributable anaerobic mechanical work) assessed using four different approaches/models applied to time-trial (TT) cycle-ergometry exercise.

METHODS

Fifteen male cyclists completed a 7 × 4-min submaximal protocol and a 3-min all-out TT (TTAO). Linear relationships between power output (PO) and submaximal metabolic rate were constructed to estimate TT-specific gross efficiency (GE) and AnWC, using either a measured resting metabolic rate as a Y-intercept (7 + YLIN) or no measured Y-intercept (7-YLIN). In addition, GE of the last submaximal bout (GELAST) was used to estimate AnWC, and critical power (CP) from TTAO (CP3´AO) was used to estimate mechanical work above CP (W', i.e., "AnWC").

RESULTS

Average PO during TTAO was 5.43 ± 0.30 and CP was 4.48 ± 0.23 W∙kg-1. The TT-associated GE values were ~ 22.0% for both 7 + YLIN and 7-YLIN and ~ 21.1% for GELAST (both P < 0.001). The AnWC were 269 ± 60, 272 ± 55, 299 ± 61, and 196 ± 52 J∙kg-1 for the 7 + YLIN, 7-YLIN, GELAST, and CP3´AO models, respectively (7 + YLIN and 7-YLIN versus GELAST, both P < 0.001; 7 + YLIN, 7-YLIN, and GELAST versus CP3´AO, all P < 0.01). For the three pair-wise comparisons between 7 + YLIN, 7-YLIN, and GELAST, typical errors in AnWC values ranged from 7 to 11 J∙kg-1, whereas 7 + YLIN, 7-YLIN, and GELAST versus CP3´AO revealed typical errors of 55-59 J∙kg-1.

CONCLUSION

These findings demonstrate a substantial disagreement in AnWC between CP3´AO and the other models. The 7 + YLIN and 7-YLIN generated 10% lower AnWC values than the GELAST model, whereas 7 + YLIN and 7-YLIN generated similar values of AnWC.

Maximizing recovery time between knock-out races improves sprint cross-country skiing performance

BACKGROUND

In a sprint cross-country (XC) ski competition, the difference in recovery times separating the first and the second semi-final (SF) heats from the final (F) may affect performance. The aim of the current study was to compare the effects of longer vs. shorter recovery periods prescribed between the 3 knock-out races of a simulated sprint XC ski competition involving a prologue (P), quarter-final (QF), SF, and F.

METHODS

Eleven well-trained XC ski athletes completed 2 simulated sprint XC ski competitions on a treadmill involving 4 × 883-m roller-ski bouts at a 4° incline using the gear 3 ski-skating sub-technique. The first 3 bouts were completed at a fixed speed (P_FIX, QF_FIX, and SF_FIX) corresponding to ∼96% of each individual's previously determined maximal effort. The final bout was performed as a self-paced sprint time trial (F_STT). Test conditions differed by the time durations prescribed between the QF_FIX, SF_FIX, and F_STT, which simulated real-world XC ski competition conditions using maximum (MAX-REC) or minimum (MIN-REC) recovery periods.

RESULTS

The F_STT was completed 5.4 ± 5.5 s faster (p = 0.009) during MAX-REC (179.2 ± 18.1 s) compared to MIN-REC (184.6 ± 20.0 s), and this was linked to a significantly higher power output (p = 0.010) and total metabolic rate (p = 0.009). The pre F_STT blood lactate (BLa) concentration was significantly lower during MAX-REC compared to MIN-REC (2.5 ± 0.8 mmol/L vs. 3.6 ± 1.6 mmol/L, respectively; p = 0.027), and the pre-to-post F_STT increase in BLa was greater (8.8 ± 2.1 mmol/L vs. 7.1 ± 2.3 mmol/L, respectively; p = 0.024). No other differences for MAX-REC vs. MIN-REC reached significance (p > 0.05).

CONCLUSION

Performance in a group of well-trained XC skiers is negatively affected when recovery times between sprint heats are minimized which, in competition conditions, would occur when selecting the last QF heat. This result is combined with a higher pre-race BLa concentration and a reduced rise in BLa concentration under shorter recovery conditions. These findings may help inform decision making when XC skiers are faced with selecting a QF heat within a sprint competition.

Validity and Reliability of Hydraulic-Analogy Bioenergetic Models in Sprint Roller Skiing

Purpose: To develop a method for individual parameter estimation of four hydraulic-analogy bioenergetic models and to assess the validity and reliability of these models' prediction of aerobic and anaerobic metabolic utilization during sprint roller-skiing. Methods: Eleven elite cross-country skiers performed two treadmill roller-skiing time trials on a course consisting of three flat sections interspersed by two uphill sections. Aerobic and anaerobic metabolic rate contributions, external power output, and gross efficiency were determined. Two versions each (fixed or free maximal aerobic metabolic rate) of a two-tank hydraulic-analogy bioenergetic model (2TM-fixed and 2TM-free) and a more complex three-tank model (3TM-fixed and 3TM-free) were programmed into MATLAB. The aerobic metabolic rate (MR _ae ) and the accumulated anaerobic energy expenditure (E _an,acc ) from the first time trial (STT1) together with a gray-box model in MATLAB, were used to estimate the bioenergetic model parameters. Validity was assessed by simulation of each bioenergetic model using the estimated parameters from STT1 and the total metabolic rate (MR _tot ) in the second time trial (STT2). Results: The validity and reliability of the parameter estimation method based on STT1 revealed valid and reliable overall results for all the four models vs. measurement data with the 2TM-free model being the most valid. Mean differences in model-vs.-measured MR _ae ranged between -0.005 and 0.016 kW with typical errors between 0.002 and 0.009 kW. Mean differences in E _an,acc at STT termination ranged between -4.3 and 0.5 kJ and typical errors were between 0.6 and 2.1 kJ. The root mean square error (RMSE) for 2TM-free on the instantaneous STT1 data was 0.05 kW for MR _ae and 0.61 kJ for E _an,acc , which was lower than the other three models (all P < 0.05). Compared to the results in STT1, the validity and reliability of each individually adapted bioenergetic model was worse during STT2 with models underpredicting MR _ae and overpredicting E _an,acc vs. measurement data (all P < 0.05). Moreover, the 2TM-free had the lowest RMSEs during STT2. Conclusion: The 2TM-free provided the highest validity and reliability in MR _ae and E _an,acc for both the parameter estimation in STT1 and the model validity and reliability evaluation in the succeeding STT2.

Anaerobic Capacity in Running: The Effect of Computational Method

Introduction

To date, no study has compared anaerobic capacity (AnC) estimates computed with the maximal accumulated oxygen deficit (MAOD) method and the gross energy cost (GEC) method applied to treadmill running exercise.

Purpose

Four different models for estimating anaerobic energy supply during treadmill running exercise were compared.

Methods

Fifteen endurance-trained recreational athletes performed, after a 10-min warm-up, five 4-min stages at ∼55-80% of peak oxygen uptake, and a 4-min time trial (TT). Two linear speed-metabolic rate (MR) regression models were used to estimate the instantaneous required MR during the TT (MR _{TT_req} ), either including (5+Y _LIN ) or excluding (5-Y _LIN ) a measured Y-intercept. Also, the average GEC (GEC _AVG ) based on all five submaximal stages, or the GEC based on the last submaximal stage (GEC _LAST ), were used as models to estimate the instantaneous MR _{TT_req} . The AnC was computed as the difference between the MR _{TT_req} and the aerobic MR integrated over time.

Results

The GEC remained constant at ∼4.39 ± 0.29 J⋅kg^-1⋅m^-1 across the five submaximal stages and the TT was performed at a speed of 4.7 ± 0.4 m⋅s^-1. Compared with the 5-Y _LIN , GEC _AVG , and GEC _LAST models, the 5+Y _LIN model generated a MR _{TT_req} that was ∼3.9% lower, with corresponding anaerobic capacities from the four models of 0.72 ± 0.20, 0.74 ± 0.16, 0.74 ± 0.15, and 0.54 ± 0.14 kJ⋅kg^-1, respectively (F _1.07,42 = 13.9, P = 0.002). The GEC values associated with the TT were 4.22 ± 0.27 and 4.37 ± 0.30 J⋅kg^-1⋅m^-1 for 5+Y _LIN and 5-Y _LIN , respectively (calculated from the regression equation), and 4.39 ± 0.28 and 4.38 ± 0.27 J⋅kg^-1⋅m^-1 for GEC _AVG and GEC _LAST , respectively (F _1.08,42 = 14.6, P < 0.001). The absolute typical errors in AnC ranged between 0.03 and 0.16 kJ⋅kg^-1 for the six pair-wise comparisons and the overall standard error of measurement (SEM) was 0.16 kJ⋅kg^-1.

Conclusion

These findings demonstrate a generally high disagreement in estimated anaerobic capacities between models and show that the inclusion of a measured Y-intercept in the linear regression (i.e., 5+Y _LIN ) is likely to underestimate the MR _{TT_req} and the GEC associated with the TT, and hence the AnC during maximal 4-min treadmill running.

The Dynamics of the Anaerobic Energy Contribution During a Simulated Mass-Start Competition While Roller-Ski Skating on a Treadmill

The purposes of this study were: 1) to investigate the anaerobic energy contribution during a simulated cross-country (XC) skiing mass-start competition while roller-ski skating on a treadmill; 2) to investigate the relationship between the recovery of the anaerobic energy reserves and performance; and 3) to compare the gross efficiency (GE) method and maximal accumulated oxygen deficit (MAOD) to determine the anaerobic contribution. Twelve male XC skiers performed two testing days while roller skiing on a treadmill. To collect submaximal data necessary for the GE and MAOD method, participants performed a resting metabolism measurement, followed by low-intensity warm up, 12 submaximal 4-min bouts, performed using three different skating sub-techniques (G2 on a 12% incline, G3 on 5% and G4 on 2%) on three submaximal intensities on day 1. On day 2, participants performed a 21-min simulated mass-start competition on varying terrain to determine the anaerobic energy contribution. The speed was fixed, but when participants were unable to keep up, a 30-s rest bout was included. Performance was established by the time to exhaustion (TTE) during a sprint at the end of the 21-min protocol. Skiers were ranked based on the number of rest bouts needed to finish the protocol and TTE. The highest GE of day 1 for each of the different inclines/sub-techniques was used to calculate the aerobic and anaerobic contribution during the simulated mass start using the GE method and two different MAOD approaches. About 85–90% of the required energy during the simulated mass-start competition (excluding downhill segments) came from the aerobic energy system and ~10–15% from the anaerobic energy systems. Moderate to large Spearman correlation coefficients were found between recovery of anaerobic energy reserves and performance rank (r_s = 0.58–0.71, p < 0.025). No significant difference in anaerobic work was found between methods/approaches (F_(1.2,8.5) = 3.2, p = 0.10), while clear individual differences existed. In conclusion, about 10–15% of the required energy during the periods of active propulsion of a 21-min simulated mass-start competition came from the anaerobic energy systems. Due to the intermittent nature of XC skiing, the recovery of anaerobic energy reserves seems highly important for performance. To assess the anaerobic contribution methods should not be used interchangeably.

Physiological responses and cycle characteristics during double-poling versus diagonal-stride roller-skiing in junior cross-country skiers

Purpose

This study aimed to compare physiological factors and cycle characteristics during cross-country (XC) roller-skiing at matched inclines and speeds using the double-poling (DP) and diagonal-stride (DS) sub-techniques in junior female and male XC skiers.

Methods

Twenty-three well-trained junior XC skiers (11 women, 12 men; age 18.2 ± 1.2 yr.) completed two treadmill roller-skiing tests in a randomized order using either DP or DS. The exercise protocols were identical and included a 5 min warm-up, 4 × 5 min submaximal stages, and an incremental test to exhaustion, all performed at a 5° incline.

Results

No significant three-way interactions were observed between sex, submaximal exercise intensity, and sub-technique. For the pooled sample, higher values were observed for DP versus DS during submaximal exercise for the mean oxygen uptake kinetics response time (33%), energy cost (18%), heart rate (HR) (9%), blood lactate concentration (5.1 versus 2.1 mmol·L⁻¹), rating of perceived exertion (12%), and cycle rate (25%), while cycle length was lower (19%) (all P < 0.001). During the time-to-exhaustion (TTE) test, peak oxygen uptake (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{V}$$\end{document}V˙O₂peak), peak HR, and peak oxygen pulse were 8%, 2%, and 6% lower, respectively, for DP than DS, with a 29% shorter TTE during DP (pooled data, all P < 0.001).

Conclusion

In well-trained junior XC skiers, DP was found to exert a greater physiological load than DS during uphill XC roller-skiing at submaximal intensities. During the TTE test, both female and male athletes were able to ski for longer and reached markedly higher \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{V}$$\end{document}V˙O₂peak values when using DS compared to DP.