gross efficiency (GE) is the most valid definition of efficiency during whole-body exercise. GE is defined as the ratio between mechanical power output and metabolic power input. 3 , 4 Several studies have acknowledged and shown the importance of GE to performance. 1 , 5 – 7 Using the energy flow
Sjors Groot, Lars H.J. van de Westelaken, Dionne A. Noordhof, Koen Levels and Jos J. de Koning
Richard Ebreo, Louis Passfield and James Hopker
Gross efficiency (GE) is defined as the ratio of work generated to the metabolic energy cost and has been shown to be a key component of cycling performance. 1 , 2 The calculation of GE is conventionally determined from steady state measures where energy expenditure from purely aerobic processes
Dennis van Erck, Eric J. Wenker, Koen Levels, Carl Foster, Jos J. de Koning and Dionne A. Noordhof
-controlled ergometer was corrected for the air resistance at each altitude such that the power–speed relationship reflected natural altitude settings. During the entire time trial, the gear ratio was set at 52/12, and participants received feedback on distance. Figure 1 —Experimental protocol of the gross-efficiency
Nicki Winfield Almquist, Gertjan Ettema, James Hopker, Øyvind Sandbakk and Bent R. Rønnestad
sprinting or the cost of the session. The majority of time (∼70%) during 1-day races is spent at an intensity below 70% of VO 2 max. 4 Hours of cycling at such a low intensity gradually increases VO 2 for the same power output (PO; ie, reduced gross efficiency [GE]) in well-trained cyclists. 5 , 6 This
Anna E. Voskamp, Senna van den Bos, Carl Foster, Jos J. de Koning and Dionne A. Noordhof
. Therefore, it would be desirable to know which variables positively influence exercise economy and/or efficiency. One of the variables that seems to negatively influence exercise efficiency is fatigue. 3 Gross efficiency (GE), the most valid definition of exercise efficiency, 4 has been shown to decline
Jos J. de Koning, Dionne A. Noordhof, Tom P. Uitslag, Rianna E Galiart, Christopher Dodge and Carl Foster
Gross efficiency (GE) is coupling power production to propulsion and is an important performance-determining factor in endurance sports. Measuring GE normally requires measuring VO2 during submaximal exercise. In this study a method is proposed to estimating GE during high-intensity exercise.
Nineteen subjects completed a maximal incremental test and 2 GE tests (1 experimental and 1 control test). The GE test consisted of 10 min cycling at 50% peak power output (PPO), 2 min at 25 W, followed by 4 min 100% PPO, 1 min at 25 W, and another 10 min at 50% PPO. GE was determined for the 50%-PPO sections and was, for the second 50%-PPO section, back-extrapolated, using linear regression, to the end of the 100%-PPO bout.
Back-extrapolation of the GE data resulted in a calculated GE of 15.8% ± 1.7% at the end of the 100%-PPO bout, in contrast to 18.3% ± 1.3% during the final 2 min of the first 10-min 50%-PPO bout.
Back-extrapolation seems valuable in providing more insight in GE during high-intensity exercise.
Alfred Nimmerichter, Bernhard Prinz, Kevin Haselsberger, Nina Novak, Dieter Simon and James G. Hopker
While a number of studies have investigated gross efficiency (GE) in laboratory conditions, few studies have analyzed it in field conditions. Therefore, the aim of this study was to analyze the effect of gradient and cadence on GE in field conditions.
Thirteen trained cyclists (mean ± SD age 23.3 ± 4.1 y, stature 177.0 ± 5.5 cm, body mass 69.0 ± 7.2 kg, maximal oxygen uptake [V̇O2max] 68.4 ± 5.1 mL ∙ min–1 ∙ kg–1) completed an incremental graded exercise test to determine ventilatory threshold (VT) and 4 field trials of 6 min duration at 90% of VT on flat (1.1%) and uphill terrain (5.1%) with 2 different cadences (60 and 90 rpm). V̇O2 was measured with a portable gas analyzer and power output was controlled with a mobile power crank that was mounted on a 26-in mountain bike.
GE was significantly affected by cadence (20.6% ± 1.7% vs 18.1% ± 1.3% at 60 and 90 rpm, respectively; P < .001) and terrain (20.0% ± 1.5% vs 18.7% ± 1.7% at flat and uphill cycling, respectively; P = .029). The end-exercise V̇O2 was 2536 ± 352 and 2594 ± 329 mL/min for flat and uphill cycling, respectively (P = .489). There was a significant difference in end-exercise V̇O2 between 60 (2352 ± 193 mL/min) and 90 rpm (2778 ± 431 mL/min) (P < .001).
These findings support previous laboratory-based studies demonstrating reductions in GE with increasing cadence and gradient that might be attributed to changes in muscle-activity pattern.
Dionne A. Noordhof, Thijs Schoots, Derk H. Hoekert and Jos J. de Koning
The purpose of this study was to test the assumption that gross efficiency (GE) at sea level (SL) is representative of GE at altitude (AL). It was hypothesized that an increased cost of ventilation and heart rate, combined with a higher respiratory-exchange ratio, at AL might result in a decrease in GE.
Trained men (N = 16) completed 2 maximal incremental tests and 2 GE tests, 1 at SL and 1 at an acute simulated AL of 1500 m (hypobaric chamber). GE was determined during submaximal exercise at 45%, 55%, and 65% of the altitude-specific power output attained at VO2max.
GE determined at the highest submaximal exercise intensity with a mean RER ≤1.0, matched for both conditions, was significantly lower at AL (AL 20.7% ± 1.1% and SL 21.4% ± 0.8%, t 15 = 2.9, P < .05).
These results demonstrate that moderate AL resulted in a significantly lower GE during cycling exercise than SL. However, it might be that the lower GE at AL is caused by the lower absolute exercise intensity.
Dionne A. Noordhof, Roy C.M. Mulder, Katherine R. Malterer, Carl Foster and Jos J. de Koning
To evaluate whether gross efficiency (GE), determined during submaximal cycling, is lower after time trials and if the magnitude of the decrease differs in relation to race distance. Secondary purposes were to study the rate of the decline in GE and whether changes in muscle-fiber recruitment could explain the decline.
Cyclists completed 9 GE tests consisting of submaximal exercise performed before and after time trials of different length (500 m, 1000 m, 2000 m, 4000 m, 15,000 m, and 40,000 m). In addition, subjects performed time trials as if they were a 1000-m, 4000-m, or 40,000-m time trial during which they were stopped at 50% of the final time of the preceding “full” time trial. Power output, gas exchange, and EMG were measured continuously throughout the GE tests.
A significant interaction effect between distance and time was found for GE (P = .001). GE was significantly lower immediately after the time trials than before (P < .05), and the decline in GE differed between distances (P < .001). GE seemed to decline linearly during the relatively short trials, while it declined more hyperbolically during the 40,000-m. A significant effect of time (P = .04) on mean EMG amplitude was found. However, post hoc comparisons showed no significant differences in mean EMG amplitude between the different time points (before and after the time trials).
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.
William M. Bertucci, Andrew C. Betik, Sebastien Duc and Frederic Grappe
This study was designed to examine the biomechanical and physiological responses between cycling on the Axiom stationary ergometer (Axiom, Elite, Fontaniva, Italy) vs. field conditions for both uphill and level ground cycling. Nine cyclists performed cycling bouts in the laboratory on an Axiom stationary ergometer and on their personal road bikes in actual road cycling conditions in the field with three pedaling cadences during uphill and level cycling. Gross efficiency and cycling economy were lower (–10%) for the Axiom stationary ergometer compared with the field. The preferred pedaling cadence was higher for the Axiom stationary ergometer conditions compared with the field conditions only for uphill cycling. Our data suggests that simulated cycling using the Axiom stationary ergometer differs from actual cycling in the field. These results should be taken into account notably for improving the precision of the model of cycling performance, and when it is necessary to compare two cycling test conditions (field/laboratory, using different ergometers).