RESUMEN
After harvest, fruit remain metabolically active and continue to ripen. The main goal of postharvest storage is to slow down the metabolic activity of the detached fruit. In many cases, this is accomplished by storing fruit at low temperature in combination with low oxygen (O2) and high carbon dioxide (CO2) partial pressures. However, altering the normal atmospheric conditions is not without any risk and can induce low-O2 stress. This review focuses on the central carbon metabolism of apple fruit during postharvest storage, both under normal O2 conditions and under low-O2 stress conditions. While the current review is focused on apple fruit, most research on the central carbon metabolism, low-O2 stress, and O2 sensing has been done on a range of different model plants (e.g., Arabidopsis, potato, rice, and maize) using various plant organs (e.g., seedlings, tubers, roots, and leaves). This review pulls together this information from the various sources into a coherent overview to facilitate the research on the central carbon metabolism in apple fruit exposed to postharvest low-O2 stress.
RESUMEN
BACKGROUND: In general, enzyme activity is estimated from spectrophotometric data, by taking the slope of the linear part of the progress curve describing the rate of change in the substrate or product monitored. As long as the substrate concentrations are sufficiently high to saturate the enzyme and, the velocity of the catalyzed reaction is directly proportional to the enzyme concentration. Under these premises, this velocity can be taken as a measure of the amount of active enzyme present. Estimation of the enzyme activity through linear regression of the data should only be applied when linearity is true, which is often not the case or has not been checked. RESULTS: In this paper, we propose a more elaborate method, based on a kinetic modelling approach, to estimate the in vitro specific enzyme activity from spectrophotometric assay data. As a case study, kinetic models were developed to estimate the activity of the enzymes pyruvate decarboxylase and alcohol dehydrogenase extracted from 'Jonagold' apple (Malus x domestica Borkh. cv. 'Jonagold'). The models are based on Michaelis-Menten and first order kinetics, which describe the reaction mechanism catalyzed by the enzymes. CONCLUSIONS: In contrast to the linear regression approach, the models can be used to estimate the enzyme activity regardless of whether linearity is achieved since they integrally take into account the complete progress curve. The use of kinetic models to estimate the enzyme activity can be applied to all other enzymes as long as the underlying reaction mechanism is known. The kinetic models can also be used as a tool to optimize the enzyme assays by systematically studying the effect of the various design parameters.
