مقاله انگلیسی رایگان در مورد روش های مختلف تخمینی تولید انرژی بی هوازی – ۲۰۱۸ Frontiers

In short-duration endurance events, such as middledistance running and sprint cross-country skiing, performance is not only related to the rate of aerobic energy supply but also to anaerobic energy provision (Duffield et al., 2005; Losnegard et al., 2012). This is also the case, at least to some extent, during longer-duration endurance events performed over undulating terrains and at fluctuating intensities, since the oxygen uptake (VO˙ 2) demand will at times exceed the maximal oxygen uptake (VO˙ 2max) (Norman et al., 1989; Skiba et al., 2012). In comparison to aerobic energy supply, anaerobic energy supply has a far more limited capacity (i.e., limited amount of energy that can be produced anaerobically) but can provide adenosine triphosphate at a much faster rate than the oxidative pathway. Therefore, the relative contribution of anaerobic energy production decreases with exercise duration (Gastin, 2001). In highly-trained runners, for example, anaerobic metabolism has been shown to account for ∼34 and ∼16% of the total energy turnover during 800-m and 1500-m events (lasting ∼1:53 and ∼3:55 min), respectively (Spencer and Gastin, 2001). In addition to energy supply, the efficacy of converting metabolic energy to external work (i.e., gross efficiency, GE) is an important component of endurance performance (Joyner and Coyle, 2008). Energetic contributions from aerobic pathways during wholebody exercise can easily be quantified using measurements of VO˙ 2, while a direct quantification of the anaerobic energy yield is more complicated and only possible via sophisticated, invasive and expensive technologies (Bangsbo et al., 1990). Therefore, a common approach during whole-body exercise is to indirectly estimate anaerobic energy production using the maximal accumulated oxygen (O2) deficit (MAOD) method (Medbø et al., 1988), which is based on calculating a linear relationship between submaximal VO˙ 2 and speed (or power output) and estimating VO˙ 2 demand at supramaximal speeds by extrapolation.