Anaerobic Work Calculated in Cycling Time Trials of Different Length

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

doi:10.1123/ijspp.2014-0035

Cited by 7 publications

(6 citation statements)

References 25 publications

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“…It is assumed that the total energy available from anaerobic resources is finite [5]. The AC is an important parameter for measuring athletic performance during short-distance sports such as 500–4,000 m cycling time trials [6]. While there is no “gold-standard” method to estimate AC, it has been consensually assessed by the maximal accumulated oxygen deficit (MAOD) [4].…”

Section: Introductionmentioning

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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Section: Introductionmentioning

confidence: 99%

Effect of caffeine ingestion on anaerobic capacity quantified by different methods

et al. 2017

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“…Due to the circulatory transit delay from the muscles to the lungs when trained cyclists started exercising moderately (Barstow and Mole, 1991 ), a time-delay of 15 s was applied to the respiratory data, based on previous measures in well-trained cyclists (Mulder et al, 2015 ). The aerobically attributable mechanical power was determined from the metabolic power input, based on the average respiratory data during the 30-s sprint, and GE.…”

Section: Methodsmentioning

confidence: 99%

The Aerobic and Anaerobic Contribution During Repeated 30-s Sprints in Elite Cyclists

et al. 2021

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Although the ability to sprint repeatedly is crucial in road cycling races, the changes in aerobic and anaerobic power when sprinting during prolonged cycling has not been investigated in competitive elite cyclists. Here, we used the gross efficiency (GE)-method to investigate: (1) the absolute and relative aerobic and anaerobic contributions during 3 × 30-s sprints included each hour during a 3-h low-intensity training (LIT)-session by 12 cyclists, and (2) how the energetic contribution during 4 × 30-s sprints is affected by a 14-d high-volume training camp with (SPR, n = 9) or without (CON, n = 9) inclusion of sprints in LIT-sessions. The aerobic power was calculated based on GE determined before, after sprints, or the average of the two, while the anaerobic power was calculated by subtracting the aerobic power from the total power output. When repeating 30-s sprints, the mean power output decreased with each sprint (p < 0.001, ES:0.6–1.1), with the majority being attributed to a decrease in mean anaerobic power (first vs. second sprint: −36 ± 15 W, p < 0.001, ES:0.7, first vs. third sprint: −58 ± 16 W, p < 0.001, ES:1.0). Aerobic power only decreased during the third sprint (first vs. third sprint: −17 ± 5 W, p < 0.001, ES:0.7, second vs. third sprint: 16 ± 5 W, p < 0.001, ES:0.8). Mean power output was largely maintained between sets (first set: 786 ± 30 W vs. second set: 783 ± 30 W, p = 0.917, ES:0.1, vs. third set: 771 ± 30 W, p = 0.070, ES:0.3). After a 14-d high-volume training camp, mean power output during the 4 × 30-s sprints increased on average 25 ± 14 W in SPR (p < 0.001, ES:0.2), which was 29 ± 20 W more than CON (p = 0.008, ES: 0.3). In SPR, mean anaerobic power and mean aerobic power increased by 15 ± 13 W (p = 0.026, ES:0.2) and by 9 ± 6 W (p = 0.004, ES:0.2), respectively, while both were unaltered in CON. In conclusion, moderate decreases in power within sets of repeated 30-s sprints are primarily due to a decrease in anaerobic power and to a lesser extent in aerobic power. However, the repeated sprint-ability (multiple sets) and corresponding energetic contribution are maintained during prolonged cycling in elite cyclists. Including a small number of sprints in LIT-sessions during a 14-d training camp improves sprint-ability mainly through improved anaerobic power.

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“…73,75,76 The structure of the pacing pattern (Figure 1), at least againstthe-clock has been conceptualized as a "landscape" where the interaction of race distance and percentage of the race completed define momentary power output, regardless of whether power output is attributable to aerobic or anaerobic energetic sources. 77,78…”

Section: Patterns Of Pacing Strategymentioning

confidence: 99%

“…The graph resembles a "landscape" and shows that in almost all distances there is an initial peak in power output at the start and a terminal end spurt in all but the shortest distances. 29,77,78 Figure 2 -Schematic of the growth of rating of perceived exertion (RPE) in relation to the percentage of a task completed. Data included are for ambulatory tasks such as walking, running, and cycling, as well as for lifting weights to failure with different levels of resistance.…”

Section: Rating Of Perceived Exertionmentioning

confidence: 99%

Competition Between Desired Competitive Result, Tolerable Homeostatic Disturbance, and Psychophysiological Interpretation Determines Pacing Strategy

Foster

Koning

Hettinga

et al. 2023

International Journal of Sports Physiology and Performance

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Scientific interest in pacing goes back >100 years. Contemporary interest, both as a feature of athletic competition and as a window into understanding fatigue, goes back >30 years. Pacing represents the pattern of energy use designed to produce a competitive result while managing fatigue of different origins. Pacing has been studied both against the clock and during head-to-head competition. Several models have been used to explain pacing, including the teleoanticipation model, the central governor model, the anticipatory-feedback-rating of perceived exertion model, the concept of a learned template, the affordance concept, the integrative governor theory, and as an explanation for “falling behind.” Early studies, mostly using time-trial exercise, focused on the need to manage homeostatic disturbance. More recent studies, based on head-to-head competition, have focused on an improved understanding of how psychophysiology, beyond the gestalt concept of rating of perceived exertion, can be understood as a mediator of pacing and as an explanation for falling behind. More recent approaches to pacing have focused on the elements of decision making during sport and have expanded the role of psychophysiological responses including sensory-discriminatory, affective-motivational, and cognitive-evaluative dimensions. These approaches have expanded the understanding of variations in pacing, particularly during head-to-head competition.

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Anaerobic Work Calculated in Cycling Time Trials of Different Length

Abstract: Anaerobic work calculated during short time trials (<4000 m) with a correction for a declining GE is increased by 30% [25%, 36%] and may represent anaerobic energy contributions during high-intensity exercise better than calculating anaerobic work assuming a constant GE.

Cited by 7 publications

References 25 publications

Effect of caffeine ingestion on anaerobic capacity quantified by different methods

Effect of caffeine ingestion on anaerobic capacity quantified by different methods

The Aerobic and Anaerobic Contribution During Repeated 30-s Sprints in Elite Cyclists

Competition Between Desired Competitive Result, Tolerable Homeostatic Disturbance, and Psychophysiological Interpretation Determines Pacing Strategy

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