The Decline in Gross Efficiency in Relation to Cycling Time-Trial Length

Noordhof, Dionne A.; Mulder, Roy C.M.; Malterer, Katherine R.; Foster, Carl; Koning, Jos J. de

doi:10.1123/ijspp.2014-0034

Cited by 31 publications

(41 citation statements)

References 26 publications

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“…In a previous study by Björklund et al (2011), both elite-and moderately-trained cross-country skiers showed no drift inVO 2 while completing a continuous variable-intensity test comprising of 5-6 bouts with 3-min high-intensity exercise (90% ofVO 2max ), each interspersed with 6 min of exercise at 70% ofVO 2max using the DS sub-technique. The slow component ofVO 2 is partly explained by a loss in muscular efficiency (Jones et al, 2011), therefore, it is likely to assume that a 4-min supramaximal exercise would result in a declining GE similar to that observed for cycle ergometry exercise (de Koning et al, 2013;Noordhof et al, 2015). However, unpublished data from our laboratory on well-trained cross-country skiers showed no differences in GE before and after a 3-min uphill DS time trial.…”

Section: Methodological Discussionmentioning

confidence: 67%

“…Therefore, also the exercise mode should be considered when assuming potential changes in GE with increasing power output. Moreover, recent studies on well-trained cyclists have shown that GE declines during supramaximal cycle ergometry (de Koning et al, 2013;Noordhof et al, 2015), if this also applies to the both subtechniques studied in the current study, remains to be evaluated in future studies. However, based on the GE data presented in Figure 2 for DP and DS, it is unlikely that GE would have increased during the supramaximal time trial for both DP and DS.…”

Section: The Difference In Anaerobic Capacity Estimated With the Maodmentioning

confidence: 87%

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

Andersson

Noordhof

Lögdal

2020

Front. Sports Act. Living

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Anaerobic capacity is an important performance-determining variable of sprint cross-country skiing. Nevertheless, to date, no study has directly compared the anaerobic capacity, determined using the maximal accumulated oxygen deficit (MAOD) method and gross efficiency (GE) method, while using different skiing sub-techniques.Purpose: To compare the anaerobic capacity assessed using two different MAOD approaches (including and excluding a measured y-intercept) and the GE method during double poling (DP) and diagonal stride (DS) cross-country skiing.Methods: After an initial familiarization trial, 16 well-trained male cross-country skiers performed, in each sub-technique on separate occasions, a submaximal protocol consisting of eight 4-min bouts at intensities between ∼47-78% ofVO 2peak followed by a 4-min roller-skiing time trial, with the order of sub-technique being randomized. Linear and polynomial speed-metabolic rate relationships were constructed for both sub-techniques, while using a measured y-intercept (8+Y LIN and 8+Y POL ) or not (8-Y LIN and 8-Y POL ), to determine the anaerobic capacity using the MAOD method. The average GE (GE AVG ) of all eight submaximal exercise bouts or the GE of the last submaximal exercise bout (GE LAST ) were used to calculate the anaerobic capacity using the GE method. Repeated measures ANOVA were used to test differences in anaerobic capacity between methods/approaches.Results: A significant interaction was found between computational method and skiing sub-technique (P < 0.001, η 2 = 0.51) for the anaerobic capacity estimates. The different methodologies resulted in significantly different anaerobic capacity values in DP (P < 0.001, η 2 = 0.74) and in DS (P = 0.016, η 2 = 0.27). The 8-Y POL model resulted in the smallest standard error of the estimate (SEE, 0.24 W·kg −1 ) of the MAOD methods in DP, while the 8-Y LIN resulted in a smaller SEE value than the 8+Y LIN model (0.17 vs. 0.33 W·kg −1 ) in DS. The 8-Y LIN and GE LAST resulted in the closest agreement in anaerobic capacity values in DS (typical error 2.1 mL O 2 eq·kg −1 ). Andersson et al. Estimating Anaerobic Energy ProductionConclusions: It is discouraged to use the same method to estimate the anaerobic capacity in DP and DS sub-techniques. In DP, a polynomial MAOD method (8-Y POL ) seems to be the preferred method, whereas the 8-Y LIN , GE AVG , and GE LAST can all be used for DS, but not interchangeable, with GE LAST being the least time-consuming method.

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Section: Methodological Discussionmentioning

confidence: 67%

Section: The Difference In Anaerobic Capacity Estimated With the Maodmentioning

confidence: 87%

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

Andersson

Noordhof

Lögdal

2020

Front. Sports Act. Living

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“…The decrease in GE during prolonged submaximal and supramaximal exercise is associated with fatigue and appears to depend on the length and intensity of the exercise. 53 Ignoring this decrease will result in underestimation of anaerobic capacity. Thus, it is very important to determine GE at the highest possible exercise intensity and to gain knowledge about the decrease in GE during exercise.…”

Section: Ge During Supramaximal Exercisementioning

confidence: 99%

Determining Anaerobic Capacity in Sporting Activities

Noordhof¹,

Skiba²,

Koning³

2013

International Journal of Sports Physiology and Performance

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Anaerobic capacity/anaerobically attributable power is an important parameter for athletic performance, not only for short high-intensity activities but also for breakaway efforts and end spurts during endurance events. Unlike aerobic capacity, anaerobic capacity cannot be easily quantified. The 3 most commonly used methodologies to quantify anaerobic capacity are the maximal accumulated oxygen deficit method, the critical power concept, and the gross efficiency method. This review describes these methods, evaluates if they result in similar estimates of anaerobic capacity, and highlights how anaerobic capacity is used during sporting activities. All 3 methods have their own strengths and weaknesses and result in more or less similar estimates of anaerobic capacity but cannot be used interchangeably. The method of choice depends on the research question or practical goal.

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“…The rationale of this method assumes that gross efficiency remains similar between submaximal and supramaximal exercises, and also remains constant throughout the supramaximal exercise bout [5]. However, although the efficiency of the anaerobic metabolism is higher than that of the aerobic metabolism during high-intensity exercise [44], gross efficiency (calculated as the sum of the rates of anaerobic and aerobic ATP production divided by external work) might be reduced during supramaximal exercise compared to submaximal exercise, and also reduced over time during the supramaximal bout [45, 46]. In addition, when gross efficiency might be underestimated at exercise intensities lower than GET, and, thus, AC overestimated [5].…”

Section: Discussionmentioning

confidence: 99%

Effect of caffeine ingestion on anaerobic capacity quantified by different methods

et al. 2017

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We investigated whether caffeine ingestion before submaximal exercise bouts would affect supramaximal oxygen demand and maximal accumulated oxygen deficit (MAOD), and if caffeine-induced improvement on the anaerobic capacity (AC) could be detected by different methods. Nine men took part in several submaximal and supramaximal exercise bouts one hour after ingesting caffeine (5 mg·kg-1) or placebo. The AC was estimated by MAOD, alternative MAOD, critical power, and gross efficiency methods. Caffeine had no effect on exercise endurance during the supramaximal bout (caffeine: 131.3 ± 21.9 and placebo: 130.8 ± 20.8 s, P = 0.80). Caffeine ingestion before submaximal trials did not affect supramaximal oxygen demand and MAOD compared to placebo (7.88 ± 1.56 L and 65.80 ± 16.06 kJ vs. 7.89 ± 1.30 L and 62.85 ± 13.67 kJ, P = 0.99). Additionally, MAOD was similar between caffeine and placebo when supramaximal oxygen demand was estimated without caffeine effects during submaximal bouts (67.02 ± 16.36 and 62.85 ± 13.67 kJ, P = 0.41) or when estimated by alternative MAOD (56.61 ± 8.49 and 56.87 ± 9.76 kJ, P = 0.91). The AC estimated by gross efficiency was also similar between caffeine and placebo (21.80 ± 3.09 and 20.94 ± 2.67 kJ, P = 0.15), but was lower in caffeine when estimated by critical power method (16.2 ± 2.6 vs. 19.3 ± 3.5 kJ, P = 0.03). In conclusion, caffeine ingestion before submaximal bouts did not affect supramaximal oxygen demand and consequently MAOD. Otherwise, caffeine seems to have no clear positive effect on AC.

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The Decline in Gross Efficiency in Relation to Cycling Time-Trial Length

Abstract: GE decreases during time-trial exercise. Unfortunately, the cause of the decrease remains uncertain. Future modeling studies should consider using a declining instead of a constant GE. In sport situations, the declining GE has to be taken into account when selecting a pacing strategy.

Cited by 31 publications

References 26 publications

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

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

Determining Anaerobic Capacity in Sporting Activities

Effect of caffeine ingestion on anaerobic capacity quantified by different methods

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