This study aimed to profile the physiological characteristics of junior sprint kayak athletes (n = 21, VO2max 4.1 ± 0.7 L/min, training experience 2.7 ± 1.2 y) and to establish the relationship between physiological variables (VO2max, VO2 kinetics, muscle-oxygen kinetics, paddling efficiency) and sprint kayak performance. VO2max, power at VO2max, power:weight ratio, paddling efficiency, VO2 at lactate threshold, and whole-body and muscle oxygen kinetics were determined on a kayak ergometer in the laboratory. Separately, on-water time trials (TT) were completed over 200 m and 1000 m. Large to nearly perfect (−.5 to −.9) inverse relationships were found between the physiological variables and on-water TT performance across both distances. Paddling efficiency and lactate threshold shared moderate to very large correlations (−.4 to −.7) with 200- and 1000-m performance. In addition, trivial to large correlations (−.11 to −.5) were observed between muscle-oxygenation parameters, muscle and whole-body oxygen kinetics, and performance. Multiple regression showed that 88% of the unadjusted variance for the 200-m TT performance was explained by VO2max, peripheral muscle deoxygenation, and maximal aerobic power (P < .001), whereas 85% of the unadjusted variance in 1000-m TT performance was explained by VO2max and deoxyhemoglobin (P < .001). The current findings show that well-trained junior sprint kayak athletes possess a high level of relative aerobic fitness and highlight the importance of the peripheral muscle metabolism for sprint kayak performance, particularly in 200-m races, where finalists and nonfinalists are separated by very small margins. Such data highlight the relative aerobic-fitness variables that can be used as benchmarks for talent-identification programs or monitoring longitudinal athlete development. However, such approaches need further investigation.
Thiago Oliveira Borges, Ben Dascombe, Nicola Bullock and Aaron J. Coutts
Thiago Oliveira Borges, Nicola Bullock, David Aitken and Aaron J. Coutts
This study compared 3 commercially available ergometers for within- and between-brands difference to a first-principle calibration rig.
All ergometers underestimated true mean power, with errors of 27.6% ± 3.7%, 4.5% ± 3.5%, and 22.5% ± 1.9% for the KayakPro, WEBA, and Dansprint, respectively. Within-brand ergometer power differences ranged from 17 ± 9 to 22 ± 11 W for the KayakPro, 3 ± 4 to 4 ± 4 W for the WEBA, and 5 ± 3 to 5 ± 4 W for the Dansprint. The linear-regression analysis showed that most kayak ergometers have a stable coefficient of variation (0.9–1.7%) with a moderate effect size.
Taken collectively, these findings show that different ergometers present inconsistent outcomes. Therefore, we suggest that athlete testing be conducted on the same ergometer brand, preferably the same ergometer. Optimally, that ergometer should be calibrated using a first-principle device before any athlete testing block.
Peter Peeling, Gregory R. Cox, Nicola Bullock and Louise M. Burke
We assessed the ingestion of a beetroot juice supplement (BR) on 4-min laboratory-based kayak performance in national level male (n = 6) athletes (Study A), and on 500 m on-water kayak time-trial (TT) performance in international level female (n = 5) athletes (Study B). In Study A, participants completed three laboratory-based sessions on a kayak ergometer, including a 7 × 4 min step test, and two 4 min maximal effort performance trials. Two and a half hours before the warm-up of each 4 min performance trial, athletes received either a 70 ml BR shot containing ~4.8 mmol of nitrate, or a placebo equivalent (BRPLA). The distance covered over the 4 min TT was not different between conditions; however, the average VO2 over the 4 min period was significantly lower in BR (p = .04), resulting in an improved exercise economy (p = .05). In Study B, participants completed two field-based 500 m TTs, separated by 4 days. Two hours before each trial, athletes received either two 70 ml BR shots containing ~9.6 mmol of nitrate, or a placebo equivalent (BRPLA). BR supplementation significantly enhanced TT performance by 1.7% (p = .01). Our results show that in national-level male kayak athletes, commercially available BR shots (70 ml) containing ~4.8 mmol of nitrate improved exercise economy during laboratory-based tasks predominantly reliant on the aerobic energy system. Furthermore, greater volumes of BR (140 ml; ~9.6 mmol nitrate) provided to international-level female kayak athletes resulted in enhancements to TT performance in the field.
Thiago Oliveira Borges, Nicola Bullock, David Aitken, Gregory R. Cox and Aaron J. Coutts
Purpose: To compare the metabolic cost of paddling on different commercially available kayak ergometers using a standardized kayak incremental exercise protocol. Methods: Six male sprint kayak athletes undertook an incremental exercise protocol on 3 different kayak ergometers utilizing a randomized counterbalanced pair-matched design. Results: Mean maximal aerobic power on the WEBA ergometer (265  W) was significantly higher than on the Dansprint (238  W) and KayakPro® (247  W, P < .01, effect size [ES] = 0.80). At the fifth stage, absolute oxygen consumption on the WEBA (3.82 [0.25] L·min−1) was significantly lower (P < 0.05, ES = 0.20) than KayakPro and Dansprint (4.10 [0.28] and 4.08 [0.27] L·min−1, respectively). Blood lactate concentration response at the sixth stage was significantly lower for the WEBA (3.5 [0.8] mmol·L−1), compared with KayakPro and Dansprint (5.4 [1.2] and 5.6 [1.5] mmol·L−1, P = .012, ES = 0.20). Stroke rate was significantly higher, without any effect of pacing during the submaximal stages for the Dansprint, compared with the WEBA (P < .001, ES = 0.28) and KayakPro (P < .001, ES = 0.38). A pacing effect was present at the maximal stage for all ergometers. Conclusions: This study demonstrated that paddling on different kayak ergometers when controlling power output elicits different metabolic and work outputs. It is recommended that scientists and coaches avoid testing on different ergometers and regularly calibrate these devices. Moreover, when an ergometer has been calibrated against a first principle device, it is necessary to consider calibration of various drag settings, due to their impact on stroke rate. Further research should explore the relationship between drag settings and stroke rate.