scholarly journals Energy System Contribution during 1500M Running in Untrained and Endurance-Trained Asian Male College Students

2021 ◽  
Vol 23 (2) ◽  
pp. 9-18
Author(s):  
Govindasamy Balasekaran ◽  
Loh Mun Keong ◽  
Viknesh Veeramuthu ◽  
Yong Tze Woon ◽  
Visvasuresh Victor Govindaswamy ◽  
...  
Keyword(s):  
Body Fat ◽  
Maximal Oxygen Consumption ◽  
Energy System ◽  
Oxygen Deficit ◽  
Accumulated Oxygen Deficit ◽  
Anaerobic Energy ◽  
The Mean ◽  
The Times ◽  
Study Participants ◽  
Aerobic And Anaerobic

OBJECTIVES To compare the aerobic and anaerobic energy system contribution during 1500m running between collegiate untrained (UT) and endurance trained (ET) subjects.METHODS Five Asian UT (age: 23.8 ± 0.4 yrs, body fat %: 15.9 ± 5.7 %, height: 174.0 ± 4.1 cm, weight: 65.5 ± 4.1 kg) and 5 Asian ET male participants (age: 24.4 ± 3.9 yrs, body fat %: 12.9 ± 6.9 %, height: 169.4 ± 5.1 cm, weight: 60.6 ± 8.1 kg) participated in this study. Participants attended 3 sessions to determine their body composition, submaximal and maximal oxygen consumption (VO<sub>2max</sub>) test, 1500m track running session (RS) and 1500m treadmill RS. The maximally accumulated oxygen deficit (MAOD) method was used to calculate energy system contribution.RESULTS The times for the 1500m track run for the UT and ET were 428.0 ± 48.7 and 331.6 ± 14.0 seconds (p=0.004) respectively. There were no significant differences in VO<sub>2</sub> between the 1500m track and treadmill RS indicating the participants ran to their personal best times for both trials. The mean VO<sub>2max</sub>(mL•kg<sup>-1</sup>•min<sup>-1</sup>) were significantly different between UT (45.1 ± 5.0) and ET participants (58.3 ± 2.2) (p=0.002). The mean relative contributions of the aerobic and anaerobic energy system during 1500m running were significantly different for the UT, 65.4 ± 7.0%, 34.6 ± 7.0 and ET, 75.7 ± 1.5%, 24.3 ± 1.5 % (p =0.011).CONCLUSIONS The point of equal contribution of the aerobic and the anaerobic systems occurred after thirty to forty seconds of intensive exhaustive running after which the aerobic contribution continues to increase while the anaerobic contribution decreases with increasing duration. By the end of 60th second of exhaustive running, the ET mean aerobic contribution is 71.5% compared to the UT’s 58.6%. This finding suggests a greater reliance on the aerobic energy system by the ET.

Development of Race Profiles for the Performance of a Simulated 2000-m Rowing Race

2003 ◽  
Vol 28 (4) ◽  
pp. 536-546 ◽  
Author(s):  
Michael D. Kennedy ◽  
Gordon J. Bell
Keyword(s):  
Critical Power ◽  
Elite Athletes ◽  
Maximal Oxygen Consumption ◽  
Oxygen Deficit ◽  
Male And Female ◽  
Pacing Strategy ◽  
Accumulated Oxygen Deficit ◽  
Before And After ◽  
The Mean ◽  
And Gender

The purpose of this study was to determine the race profile for a 2000-m simulated rowing race as well as the effect of training and gender on the race profile. Nineteen men and 19 women undertook a 2000-m simulated rowing race before and after 10 weeks of a typical off-season training program for rowing. Velocity was calculated every 200 m and the deviation in velocities from the mean race velocity (MRV) was plotted every 200 m to produce race profiles for each gender before and after training. The three fastest male rowers varied approximately 0.02 m•s−1 from the MRV after training and displayed a constant-pace model. The fastest female rowers displayed an all-out strategy after training, producing large deviations from MRV. Average squared deviations from the mean (SDM) determined that all groups except the fastest females had a reduction in MRV deviation after training. These results suggest that the optimal race profile for a simulated 2000-m rowing race may be different between genders. Training reduces SDM and influences both male and female pacing patterns such that both exhibit a pacing strategy that is more similar to that of elite athletes in other events of similar and shorter duration. Key words: maximal oxygen consumption, critical power, pacing strategy, critical velocity, accumulated oxygen deficit

Maximal accumulated oxygen deficit in thoroughbred horses

1995 ◽  
Vol 78 (4) ◽  
pp. 1564-1568 ◽  
Author(s):  
M. D. Eaton ◽  
D. L. Evans ◽  
D. R. Hodgson ◽  
R. J. Rose
Keyword(s):  
Aerobic Capacity ◽  
Anaerobic Capacity ◽  
Oxygen Deficit ◽  
Open Flow ◽  
Thoroughbred Horses ◽  
Accumulated Oxygen Deficit ◽  
The Mean ◽  
The Difference ◽  
Aerobic And Anaerobic ◽  
O2 Deficit

Thoroughbred horses have a high aerobic capacity, approximately twice that of elite human athletes. Whereas the aerobic capacity of horses can be accurately measured, there have been no measurements of anaerobic capacity. The aim of this study was to determine whether maximal accumulated O2 deficit (MAOD) could be measured in horses and used as an estimate of anaerobic capacity, as in human athletes. Six fit Thoroughbred horses were used with the exercise protocol utilizing a treadmill set at a 10% incline. O2 uptake VO2 was measured via an open-flow system for seven submaximal speeds (3–9 m/s), and maximal VO2 (135 +/- 3 ml.kg-1.min-1) was determined. The horses performed three tests at 105 and 125% and six tests at 115% of maximal VO2. The MAOD test was performed with the treadmill accelerated rapidly from 1.5 m/s (mean acceleration time 8 s) to the calculated speed (11–14 m/s). VO2 was measured every 10 or 15 s, and the test ended when the horse no longer kept pace with the treadmill. The mean run times were 165, 98, and 57 s for intensities of 105, 115, and 125% maximal VO2. The mean MAOD values were 31 +/- 2, 30 +/- 1, and 32 +/- 2 (SE) ml O2 eq/kg for the three intensities (P > 0.05). The proportion of energy derived from aerobic and anaerobic sources was calculated from the difference between calculated O2 demand and the VO2 curve. There was no correlation between MAOD and maximal VO2.(ABSTRACT TRUNCATED AT 250 WORDS)

Aerobic and Anaerobic Power Distribution During Cross-Country Mountain Bike Racing

2020 ◽  
pp. 1-6
Author(s):  
Bernhard Prinz ◽  
Dieter Simon ◽  
Harald Tschan ◽  
Alfred Nimmerichter
Keyword(s):  
Power Output ◽  
Power Distribution ◽  
Anaerobic Power ◽  
Energy System ◽  
Mountain Bike ◽  
Mean Power ◽  
Anaerobic Energy ◽  
Cross Country ◽  
Mean Power Output ◽  
Aerobic And Anaerobic

Purpose: To determine aerobic and anaerobic demands of mountain bike cross-country racing. Methods: Twelve elite cyclists (7 males;  = 73.8 [2.6] mL·min-1·kg−1, maximal aerobic power [MAP] = 370 [26] W, 5.7 [0.4] W·kg−1, and 5 females;  = 67.3 [2.9] mL·min−1·kg−1, MAP = 261 [17] W, 5.0 [0.1] W·kg−1) participated over 4 seasons at several (119) international and national races and performed laboratory tests regularly to assess their aerobic and anaerobic performance. Power output, heart rate, and cadence were recorded throughout the races. Results: The mean race time was 79 (12) minutes performed at a mean power output of 3.8 (0.4) W·kg−1; 70% (7%) MAP (3.9 [0.4] W·kg−1 and 3.6 [0.4] W·kg−1 for males and females, respectively) with a cadence of 64 (5) rev·min−1 (including nonpedaling periods). Time spent in intensity zones 1 to 4 (below MAP) were 28% (4%), 18% (8%), 12% (2%), and 13% (3%), respectively; 30% (9%) was spent in zone 5 (above MAP). The number of efforts above MAP was 334 (84), which had a mean duration of 4.3 (1.1) seconds, separated by 10.9 (3) seconds with a mean power output of 7.3 (0.6) W·kg−1 (135% [9%] MAP). Conclusions: These findings highlight the importance of the anaerobic energy system and the interaction between anaerobic and aerobic energy systems. Therefore, the ability to perform numerous efforts above MAP and a high aerobic capacity are essential to be competitive in mountain bike cross-country.

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

2021 ◽  
Vol 3 ◽  
Author(s):  
Dionne A. Noordhof ◽  
Marius Lyng Danielsson ◽  
Knut Skovereng ◽  
Jørgen Danielsen ◽  
Trine M. Seeberg ◽  
...  
Keyword(s):  
Correlation Coefficients ◽  
Energy Systems ◽  
Energy System ◽  
Oxygen Deficit ◽  
Time To Exhaustion ◽  
Energy Reserves ◽  
Energy Contribution ◽  
Significant Difference ◽  
Anaerobic Energy ◽  
And Performance

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 (rs = 0.58–0.71, p &lt; 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.

scholarly journals Assessment of two methods to determine the relative contributions of the aerobic and anaerobic energy systems in racehorses

2019 ◽  
Vol 126 (5) ◽  
pp. 1390-1398 ◽  
Author(s):  
Stephanie L. Bond ◽  
Persephone Greco-Otto ◽  
Raymond Sides ◽  
Grace P. S. Kwong ◽  
Renaud Léguillette ◽  
...  
Keyword(s):  
Exercise Intensity ◽  
Fixed Effects ◽  
Lactate Concentration ◽  
Relative Energy ◽  
Oxygen Deficit ◽  
Controlled Study ◽  
Supramaximal Exercise ◽  
Thoroughbred Racehorses ◽  
Anaerobic Energy ◽  
Aerobic And Anaerobic

A prospective, randomized, controlled study was designed to determine relative aerobic and anaerobic (lactic and alactic) contributions at supramaximal exercise intensities using two different methods. Thoroughbred racehorses ( n = 5) performed a maximal rate of oxygen consumption (V̇o2max) test and three supramaximal treadmill runs (105, 115, and 125% V̇o2max). Blood lactate concentration (BL) was measured at rest, every 15 s during runs, and 2, 5, 10, 20, 30, 40, 50, and 60 min postexercise. In method 1, oxygen demand was calculated for each supramaximal intensity based on the V̇o2max test, and relative aerobic and anaerobic contributions were calculated from measured V̇o2 and the accumulated oxygen deficit. In method 2, aerobic contribution was calculated using the trapezoidal method to determine V̇o2 during exercise. A monoexponential model was fitted to the postexercise V̇o2 curve. Alactic contribution was calculated using the coefficients of this model. Lactate anaerobic contribution was calculated by multiplying the peak to resting change in BL by 3. Linear mixed-effects models were used to examine the effects of exercise intensity and method (as fixed effects) on measured outcomes ( P ≤ 0.05). Relative aerobic and anaerobic contributions were not different between methods ( P = 0.20). Horses’ mean contributions were 81.4, 77.6, and 72.5% (aerobic), and 18.5, 22.3, and 27.4% (anaerobic) at 105, 115, and 125% V̇o2max, respectively. Individual alactic anaerobic energy was not different between supramaximal exercise intensities ( P = 0.43) and was negligible, contributing a mean of 0.11% of the total energy. Relative energy contributions can be calculated using measured V̇o2 and BL in situations where the exercise intensity is unknown. Understanding relative metabolic demands could help develop tailored training programs. NEW & NOTEWORTHY Relative energy contributions of horses can be calculated using measured V̇o2 and BL in situations where the exercise intensity is unknown. Horses’ mean contributions were 81.4, 77.6, and 72.5% (aerobic), and 18.5, 22.3, and 27.4% (anaerobic) at 105, 115, and 125% of V̇o2max, respectively. Individual alactic capacity was unaltered between supramaximal exercise intensities and accounted for a mean contribution of 0.11% of energy use.

Mechanical Efficiency of Treadmill Running Exercise: Effect of Anaerobic-Energy Contribution at Various Speeds

2012 ◽  
Vol 7 (4) ◽  
pp. 382-389 ◽  
Author(s):  
Daniel A. Keir ◽  
Raphaël Zory ◽  
Céline Boudreau-Larivière ◽  
Olivier Serresse
Keyword(s):  
Oxygen Uptake ◽  
Mechanical Efficiency ◽  
Peak Oxygen Uptake ◽  
Treadmill Running ◽  
Oxygen Deficit ◽  
Accumulated Oxygen Deficit ◽  
Anaerobic Energy ◽  
Exercise Effect ◽  
Kinematic Analyses ◽  
All Speeds

Objectives:Mechanical efficiency (ME) describes the ratio between mechanical (PMECH) and metabolic (PMET) power. The purpose of the study was to include an estimation of anaerobic energy expenditure (AnE) into the quantification of PMET using the accumulated oxygen deficit (AOD) and to examine its effect on the value of ME in treadmill running at submaximal, maximal, and supramaximal running speeds.Methods:Participants (N = 11) underwent a graded maximal exercise test to determine velocity at peak oxygen uptake (vVO2peak). On 4 separate occasions, subjects ran for 6 min at speeds corresponding to 50%, 70%, 90%, and 110% of vVO2peak. During each testing session, PMET was measured from pulmonary oxygen uptake (VO2p) using opencircuit spirometry and was quantified in 2 ways: from VO2p and an estimate of AnE (from the AOD method) and from VO2p only. PMECH was determined from kinematic analyses.Results:ME at 50%, 70%, 90%, and 110% of vVO2peak was 59.9% ± 11.9%, 55.4% ± 12.2%, 51.5% ± 6.8%, and 52.9% ± 7.5%, respectively, when AnE was included in the calculation of PMET. The exclusion of AnE yielded significantly greater values of ME at all speeds: 62.9% ± 11.4%, 62.4% ± 12.6%, 55.1% ± 6.2%, and 64.2% ± 8.4%; P = .001 (for 50%, 70%, 90%, and 110% of vVO2peak, respectively).Conclusions:The data suggest that an estimate of AnE should be considered in the computation of PMET when determining ME of treadmill running, as its exclusion leads to overestimations of ME values.

Method-Induced Differences of Energy Contributions in Women’s Kayaking

2018 ◽  
Vol 13 (1) ◽  
pp. 9-13
Author(s):  
Yongming Li ◽  
Margot Niessen ◽  
Xiaoping Chen ◽  
Ulrich Hartmann
Keyword(s):  
Relative Energy ◽  
Oxygen Deficit ◽  
Energy Calculation ◽  
Longitudinal Assessment ◽  
Energy Contribution ◽  
Training Experience ◽  
Incremental Exercise Test ◽  
Accumulated Oxygen Deficit ◽  
Anaerobic Energy ◽  
Gas Metabolism

Context: Different relative aerobic energy contribution (WAER%) has been reported for the 2 women’s Olympic kayaking disciplines (ie, 200 and 500 m). Purpose: To investigate whether the adopted method of energy calculation influences the value of WAER% during kayaking time trials. Methods: Eleven adolescent female kayakers (age 14 ± 1 y, height 172 ± 4 cm, body mass 65.4 ± 4.2 kg, VO2peak 42.6 ± 4.9 mL·min−1·kg−1, training experience 1.5 ± 0.3 y) volunteered to participate in 1 incremental exercise test and 2 time trials (40 and 120 s) on the kayak ergometer. A portable spirometric system was used to measure gas metabolism. Capillary blood was taken from the ear lobe during and after the tests and analyzed for lactate afterward. The method of modified maximal accumulated oxygen deficit (m-MAOD) and the method based on the fast component of oxygen-uptake off-kinetics (PCr-La-O2) were used to calculate the energy contributions. Results: The anaerobic energy portions from m-MAOD were lower than those from PCr-La-O2 in the 40-s (41.9 ± 8.8 vs 52.8 ± 4.0 kJ, P > .05) and 120-s (64.1 ± 27.9 vs 68.2 ± 10.0 kJ, P > .05) time trials, which induced differences of WAER% between m-MAOD and PCr-La-O2 (36.0% vs 30.0% in 40 s, P > .05; 60.9% vs 57.5% in 120 s, P > .05). Conclusions: The reported different WAER% in women’s Olympic kayaking could be partly attributed to the adopted method of energy calculation (ie, m-MAOD vs PCr-La-O2). A fixed method of energy calculation is recommended during the longitudinal assessment on the relative energy contribution in women’s Olympic kayaking.

Maximal accumulated oxygen deficit in running and cycling

2011 ◽  
Vol 36 (6) ◽  
pp. 831-838 ◽  
Author(s):  
David W. Hill ◽  
Jakob L. Vingren
Keyword(s):  
Anaerobic Capacity ◽  
Oxygen Demand ◽  
Cycle Ergometer ◽  
Work Rate ◽  
Oxygen Deficit ◽  
Post Exercise ◽  
Accumulated Oxygen Deficit ◽  
The Mean ◽  
Curvilinear Relationships ◽  
The Relationship

The purpose of this study was to compare values of maximal accumulated oxygen deficit (MAOD; a measure of anaerobic capacity) in running and cycling. Twenty-seven women and 25 men performed exhaustive treadmill and cycle ergometer tests of ∼3 min, ∼5 min, and ∼7 min duration. Oxygen demands were estimated assuming a linear relationship between demand and intensity and also using upwardly curvilinear relationships. When oxygen demand was estimated using speed (with exponent 1.05), values for MAOD for the three running tests were virtually identical; the mean of the three values was 78 ± 7 mL·kg–1. Use of an oxygen demand that was estimated using work rate (with exponent 1.00) generated the most similar values for MAOD from the three cycling tests (mean of 59 ± 6 mL·kg–1). Consistent with the higher (p < 0.05) MAOD in running, peak post-exercise blood lactate concentrations were also higher (p < 0.05) in running (13.9 ± 2.2 mmol·L–1) than in cycling (12.6 ± 2.4 mmol·L–1). The results suggest that the relationship between oxygen demand and running speed is upwardly curvilinear for the speeds used to measure MAOD; the relationship between demand and cycle ergometer work rate is linear; MAOD is greater in running than in cycling.

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