Differences In Gross Efficiency Research Articles

Sex Differences in Physiological Determinants of Performance in Elite Adolescent, Junior, and Senior Cross-Country Skiers.

To compare sex differences in physiological determinants of skiing performance in elite adolescent, junior, and senior cross-country skiers matched for within-age-group performance level. Eight male and 12 female adolescent (15 [1]y), 8 male and 7 female junior (18 [1]y), and 7 male and 6 female senior (28 [5]y) skiers participated. Gross efficiency was calculated during submaximal uphill treadmill roller skiing (approximately 84% of peak oxygen uptake [V˙O2peak]) using the G2 ski-skating technique. Distance covered, V˙O2peak, and maximal accumulated oxygen deficit were established from a 3-minute time-trial. Fifteen-second maximal skiing power was calculated from an incremental treadmill speed test. Finally, upper- and lower-body maximal strength tests were conducted. The 3-minute time-trial distance and maximal skiing power were, respectively, 23% and 15% (adolescent), 24% and 19% (junior), and 17% and 14% (senior) greater for men than women (all groups, P ≤ .01, effect size [ES] = 2.43-4.18; very large). V˙O2peak relative to body mass was 17% (adolescent, P = .002, ES = 1.66, large), 21% (junior, P < .01, ES = 2.60, very large), and 19% (senior, P < .01, ES = 2.35, very large) greater for men than women. The within-age-group sex differences in gross efficiency, relative accumulated oxygen deficit, and strength were not significant, with the exception of greater lower-body strength in male than female juniors (P = .01, ES = 1.26, large). The within-age-group sex difference in skiing performance is of similar magnitude for adolescent, junior, and senior skiers. This difference can likely be attributed to the large to very large sex difference in V˙O2peak within all age-groups.

Low Cadence, High Resistance Creates More Muscle Breakdown than High Cadence, Low Resistance in Well Trained Cyclists during High Intensity Interval Training

Purpose: Research by Laursen (2005:Journal of Strength and Conditioning Research, 19, 527-533) demonstrated the positive effects of High Intensity Interval Training on cycling performance concluding that peripheral (muscular) adaptations were the likely cause of increase in performance. Research also shows the relationship between cadence and gross efficiency in cycling (Ansley, 2009: European Journal of Sport Science, 9, 61-85) however there is no research to determine whether a cadence that has been deemed ‘efficient’ (least metabolic cost) produces an optimal training stimulus (measured as the breakdown of muscle). This research sought to provide cyclists and coaches insight into how they can manipulate cadence during HIIT to obtain a desired acute training response.  Methods: 7 well trained cyclists who compete at least 10 times per year and can sustain at least 4.0 watts per kilogram at maximal aerobic power underwent a high intensity interval training (HIIT) protocol where they maintained 125% Functional Threshold Power (381 ± 56 W) for 40 seconds followed by 20 seconds recovery in a set of 10 repetitions. The participants repeated the test at 3 different cadences, 70, 90 and 110 revolutions per minute (RPM) with at least a 24 hour gap between tests. Before each test, creatine kinase (CK) levels were measured at baseline and immediately at the end of the test. Participants were asked to grade each workout on the pain they felt in their legs on a visual analogue scale (VAS) as well as score a representative perceived effort (RPE) score to represent their overall feeling of effort on every second interval.  Results: Significant difference (p = 0.038) in creatine kinase measurements before and after all the HIIT protocols. The paired T-tests reveal that the difference lies between the 70 and 90RPM protocols (p=.040) with the mean (+48.85) indicating that 70RPM produced the greatest increase in CK levels. There were no significant differences in RPE between the different cadences at any point during the tests: 2 minutes (p=.956), 4 minutes (p=.878), 6 minutes (p=.304), 8 minutes (p=.199) and 10 minutes (p=.140). There were no significant differences between protocols in relation to VAS scores: 2 minutes (p=.325), 4 minutes (p=. 247), 6 minutes (p=.382), 8 minutes (p=.326) and 10 minutes (p=.304) suggesting that the participants did not deem any particular cadence to provide a greater sensation of workload.  Conclusion: A study by Formenti et al (2015: Physiological Reports, 3, 1-10) considered the validity of the American College of Sports Medicine recommended equation for calculating work rate (power) on a cycle ergometer in relation to cadence. The study presented the notion that given a 6 metre distance per pedal revolution, whether an individual pedals at a resistance of about 53 N (product of resistance) and cadence of 30 RPM, or at a resistance of about 13 N and cadence of 120 RPM, the equation would present exactly the same work rate of 160 W, whereas the two physiological responses to exercise would be very different. This research has found there to be an advantage to conducting HIIT at a lower cadence with an increased resistance at 125% of FTP in order to provide greater muscle breakdown in well trained cyclists. This concurs with Ansley et al (2009) who established there to be a difference in gross efficiency when cycling at different cadences in relation to muscular stress, energetic cost and perceived effort however unlike Ansley et al this research found no difference in perceived exertion between the cadences. Although this research has not taken any measurements of energetic/metabolic cost of different cadences, existing research studies (Brisswater, 2000: International Journal of Sports Medicine, 21, 60-64) have been presented within this area and demonstrate a higher metabolic cost to cycling at a higher cadence.

No differences un gross efficiency between dominant and non-dominant legs during one-legged conterweighted cycling

Background: Recently, the use of a counterweight during one-legged cycling has been advocated as a training methodology to enhance the metabolic and oxidative potential of skeletal muscle. However, to date, no study has investigated whether training using either the dominant or the non-dominant leg affects the physiological response to a bout of exercise. Thus, the aim of this study was to assess whether cycling gross efficiency was affected by using either the dominant or the non-dominant leg during counterweighted cycling. Methods: The experiment was performed on 7 occasions, separated by at least 48 h, with 11 competitive cyclists (mean ± SD; age: 31.0 ± 7.7 years; body mass: 70.6 ± 10.8 kg; height: 175.8 ± 8.1 cm; VO2peak: 64.0 ± 9.0 ml.kg-1.min-1). At the first occasion, cyclists’ anthropometry and lateral preference (Waterloo Footedness Questionnaire) were assessed. Then, participants performed a graded exercise test to exhaustion (25 W.min-1). In the following sessions, one-legged cycling exercise was performed with dominant and non-dominant legs, in different workloads (60 or 100 W), cadences (60, 75 or 90 rev.min-1) and counterweights (non-counterweighted, 2.5 or 5 kg) — 2 cycling bouts per session (one for each limb) with a 40-min passive recovery between them. Bouts consisted of 18 min at a constant workload with each target cadence for 6 min. Workloads, cadences and counterweights were randomly assigned. All tests were performed on a standard road bike fitted with a powermeter crank (Professional, SRM, Julich, Germany) and attached to a Computrainer (ProLab, RacerMate, Seattle, USA). Twenty-second gas exchanges were recorded thoroughly by open-circuit indirect calorimetry (VO2000, Medgraphics, St. Paul, USA). The average of the last 3 min of each condition was used for gross efficiency calculations as the ratio of the power output to the power input, multiplied by 100. Data normality was confirmed with a Shapiro-Wilk test. A repeated-measures three-way ANOVA was used for each workload to compare gross efficiency within conditions, followed by Bonferroni pairwise comparisons if P≤0.05. Results: Results are summarized in table 1. One participant did not complete all conditions and his data were therefore included only at 60 W. No significant main effect of the leg was found at 60 (F=0.024; P=0.879) or 100 W (F=3.617; P=0.086). However, a significant main effect of the cadence was found at 60 (F=40.213; P<0.001) and 100 W (F=54.509; P<0.001). A main effect of the counterweight was found at 100 (F=3.879; P=0.038), but not at 60 W (F=2.439; P=0.115). No significant interactions were found, except for counterweight versus cadence at 60 W (F=2.843; P=0.038). Bonferroni pairwise comparisons showed significant differences between 60 and 90 (P<0.001) and between 75 and 90 rev.min-1 (P<0.001) at both 60 and 100 W, but not between other conditions. Discussion: The results of this study demonstrate that the use of either the dominant or the non-dominant leg during one-legged cycling does not affect cycling gross efficiency. As shown in bilateral cycling studies, higher cadences decrease gross efficiency. In addition, as work rate increased from 60 to 100 W a main effect of the counterweight on gross efficiency was found, possibly reflecting biomechanical advantages of the counterweighted-cycling model. However, due to high between-subject variability in gross efficiency, a bigger sample is required to confirm this assumption. A significant interaction of counterweight versus cadence at 60 W suggests that the optimal counterweight for one-legged cycling might vary across conditions, warranting further investigation. Conclusion: No difference in gross efficiency was found between dominant and non-dominant legs when adopting a counterweighted-cycling model.

The Effects of Training on Gross Efficiency in Cycling: A Review

There has been much debate in the recent scientific literature regarding the possible ability to increase gross efficiency in cycling via training. Using cross-sectional study designs, researchers have demonstrated no significant differences in gross efficiency between trained and untrained cyclists. Reviewing this literature provides evidence to suggest that methodological inadequacies may have played a crucial role in the conclusions drawn from the majority of these studies. We present an overview of these studies and their relative shortcomings and conclude that in well-controlled and rigorously designed studies, training has a positive influence upon gross efficiency. Putative mechanisms for the increase in gross efficiency as a result of training include, muscle fibre type transformation, changes to muscle fibre shortening velocities and changes within the mitochondria. However, the specific mechanisms by which training improves gross efficiency and their impact on cycling performance remain to be determined.

Correlated Response in Feed Efficiency Accompanying Selection for Milk Yield in Jerseys

Gross feed efficiency (milk energy output divided by energy consumed) was measured in 232 Jersey cows resulting from direct selection for milk yield and a control line of 121 daughters of 20 Jersey bulls taken randomly from commercial artificial insemination sampling programs in 1967. Data were collected between 1971 and 1982 from primiparous cows in middle to late lactation in 21 feeding trials of 28 d. Cows were fed hay and silage ad libitum plus grain according to production at the rate of 1kg grain/3kg milk. Models for least squares analyses included trial, line, days in milk, and either body weight change (model 1) or energy balance (model 2), estimated as the difference between energy requirements and actual energy intake. Body weight change was an insignificant source of variation, and gross feed efficiency did not differ between genetic lines using model 1. Significant line differences in gross efficiency were obtained after adjusting for energy balance; however, problems of multi-collinearity invalidates meaningful inference. Results indicate genetic lines of Jerseys did not differ in gross feed efficiency when fed according to yield and suggest selection has not affected efficiency of direct conversion of nutrients into milk.

Quantitative digestion of fresh herbage by sheep: I. The sites of digestion of organic matter, energy, readily fermentable carbohydrate, structural carbohydrate, and lipid

SummarySheep prepared either with a rumen cannula, or with a rumen cannula plus re-entrant cannulae in the duodenum and ileum were fed fresh ‘Ruanui’ perennial ryegrass (R), ‘Manawa’ short-rotation ryegrass (M) and white clover (C) at dry-matter intakes ranging from 450 to 1000 g/24 h.The re-entrant cannulated sheep were given paper impregnated with chromic oxide (Cr2O3) once daily via the rumen fistula as a marker; recoveries of Cr2O3 at the duodenum, ileum and faeces were approximately 75, 69 and 100% respectively. Regressions of Cr2O3-corrected digesta constituent flows (g/24 h) on intake were constructed and from these were calculated the sites of digestion of OM, gross energy, readily fermentable carbohydrate, structural carbohydrate and lipid between the stomach, small intestine and large intestine.There were differences between pasture species in partition of OM and energy digestion. With M, digestion in the stomach was significantly less (P &lt; 0·01) and digestion in the small intestine was significantly more (P &lt; 0·05) than with either R or C. These partitions of OM and energy digestion changed with level of feed intake. A substantial proportion (9–18%) of the digestible OM and energy was apparently digested in the large intestine with all three herbages.With all three herbages approximately 93% of the digestible readily fermentable carbohydrate and 90% of the digestible structural carbohydrate was digested in the stomach region.Reasons for differences in gross efficiency of utilization between the pasture species in the order C &gt; M &gt; R were examined.

Selection for weaning weight in Merino sheep. 3. Maintenance requirements and the efficiency of conversion of feed to wool in mature ewes

Net and gross efficiencies of wool growth have been estimated for ewes from three Trangie selection flocks, one selected for high weaning weight (Weight Plus), one for low weaning weight (Weight Minus), and a random control flock. Weight Plus ewes had 15 and 11 per cent heavier body weights than Weight Minus ewes at maintenance and unlimited levels of feeding respectively. At each level, feed intake was proportional to body weight both between and within flocks. In addition, the feed costs of a unit gain and loss of body weight were the same for each flock at each level of feeding. The Weight Plus ewes grew 7 and 10 per cent more wool than Weight Minus ewes at maintenance and unlimited levels of feeding. Consequently, there was only a small difference between the flocks in efficiency of conversion of feed to wool at maintenance, and there was no difference on unlimited intake. These results indicate that there is no genetic correlation between weaning weight and efficiency of conversion of feed to wool. At the three levels of controlled feeding (543, 725, 902 grams of dry matter a day) there were no differences in gross efficiency of wool growth, either between flocks or between levels within flocks, despite differing changes in body weight. During unlimited feeding, gross efficiency of wool growth was lower than that during controlled feeding. This was due to a reduced response in wool growth, as feed costs per unit body weight change were constant. As both production and feed intake changed in proportion to body weight, it is concluded that attention to weaning weight has little place in a Merino breeding program aimed at increasing wool production. However, selection for high weaning weight may be a useful tool in selecting ewes for crossbreeding because of the associated increases in milk production and lamb growth rate.

138. Effect of Breed, Size of Cow, Yield of Milk and Stage of Lactation upon Efficiency of Milk Production

The records of 2400 cows on test at the London Dairy Show between the years 1922 and 1934 have been examined for the relationship between the gross physiological efficiency of milk production and the factors of breed, size of cow within a breed, actual yield of milk and stage of lactation. (“Gross Efficiency” is here the ratio of energy in the milk to the energy in the digestible nutrients consumed.)(1) It is shown that among the best representatives of the various dairy breeds there is little difference in gross efficiency of milk production. The lactation stimulus has been bred approximately in proportion to the size of the breed.(2) Cows, in spite of their greater weight, are more efficient than heifers, and animals milked thrice daily than those milked twice daily.(3) Within the breed there is a slight though definite tendency for gross efficiency to decrease with increase in live weight.(4) Greater than any of the foregoing differences in gross efficiency is that which exists within a breed due to differences in actual milk yield.(5) Stage of lactation has also much to do with gross efficiency. There is a steady decline in efficiency with advance in lactation from 38·75 to 29·25 per cent.