Consumption of beetroot juice (BRJ) supplements has become popular among athletes because beets tend to be rich in nitrate (NO3 −), which can enhance exercise performance by increasing nitric oxide production. The NO3 − content of beets can vary significantly, however, making it difficult to know how much NO3 − any product actually contains. Samples from 45 different lots of 24 different BRJ products from 21 different companies were therefore analyzed for NO3 − (and nitrite [NO2 −]) concentration using high-performance liquid chromatography. The NO3 − and NO2 − content (i.e., amount per serving) was then calculated based on either (a) the manufacturer’s recommended serving size (for prepackaged/single dose products) or (b) as used in previous studies, a volume of 500 ml (for BRJ sold in bulk containers). There was moderate-to-large variability in NO3 − content between samples of the same product, with a mean coefficient of variation of 30% ± 26% (range 2–83%). There was even greater variability between products, with a ∼50-fold range in NO3 − content between the lowest and highest. Only five products consistently provided ≥5 mmol of NO3 −/serving, which seems to be the minimal dose required to enhance exercise performance in most individuals. NO2 − contents were generally low (i.e., ≤0.5% compared with NO3 −), although two products contained 10% and 14%. The results of this study may be useful to athletes and their support staff contemplating which (if any) BRJ product to utilize. These data may also offer insight into variability in the literature with respect to the effects of BRJ on exercise performance.
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Edgar J. Gallardo and Andrew R. Coggan
Ernest G. Rimer, Linda R. Peterson, Andrew R. Coggan, and James C. Martin
Muscle-shortening velocity and hence power have been shown to increase in the presence of nitric oxide (NO). NO availability increases after consuming nitrate (NO3 -). Ingestion of NO3 -rich beetroot juice (BRJ) has increased muscle power in untrained adults.
This study determined whether NO3 - supplementation could acutely enhance maximal power in trained athletes.
In this double-blind, crossover study, 13 trained athletes performed maximal inertial-load cycling trials (3–4 s) immediately before (PRE) and after (POST) consuming either NO3 -rich (NO3) or NO3 -depleted (PLA) BRJ to assess acute changes (ie, within the same day) in maximal power (PMAX) and optimal pedaling rate (RPMopt). Participants also performed maximal isokinetic cycling (30 s) to assess performance differences after supplementation.
2 x 2 repeated-measures ANOVA indicated a greater increase in PMAX from PRE to POST NO3 (PRE 1160 ± 301 W to POST 1229 ± 317 W) than with PLA (PRE 1191 ± 298 W to POST 1213 ± 300 W) (P = .009; η p 2 = 0.45). A paired t-test verified a greater relative change in PMAX after NO3 (6.0% ± 2.6%) than with PLA (2.0% ± 3.8%) (P = .014; d = 1.21). RPMopt remained unchanged from PRE (123 ± 14 rpm) to POST PLA (122 ± 14 rpm) but increased from PRE (120 ± 14 rpm) to POST NO3 (127 ± 13 rpm) (P = .043; η p 2 = 0.30). There was no relative change in RPMopt after PLA (–0.3% ± 4.1%), but there was an increase after NO3 (6.5% ± 11.4%) (P = .049; d = 0.79). No differences were observed between the 30-s isokinetic trials.
Acute NO3 - supplementation can enhance maximal muscle power in trained athletes. These findings may particularly benefit power-sport athletes who perform brief explosive actions.
Andrew R. Coggan, Robert J. Spina, Wendy M. Kohrt, Dennis M. Bier, and John O. Holloszy
We hypothesized that when plasma glucose availability is maintained by carbohydrate (CHO) ingestion, trained cyclists can utilize plasma glucose at very high rates during the later stages of prolonged exercise (10). To test this hypothesis, a well-trained male cyclist was studied during exercise to fatigue at 70%
James C. Martin, Douglas L. Milliken, John E. Cobb, Kevin L. McFadden, and Andrew R. Coggan
This investigation sought to determine if cycling power could be accurately modeled. A mathematical model of cycling power was derived, and values for each model parameter were determined. A bicycle-mounted power measurement system was validated by comparison with a laboratory ergometer. Power was measured during road cycling, and the measured values were compared with the values predicted by the model. The measured values for power were highly correlated (R 2 = .97) with, and were not different than, the modeled values. The standard error between the modeled and measured power (2.7 W) was very small. The model was also used to estimate the effects of changes in several model parameters on cycling velocity. Over the range of parameter values evaluated, velocity varied linearly (R 2 > .99). The results demonstrated that cycling power can be accurately predicted by a mathematical model.