Application of a SUGAR model to analyse sugar accumulation in peach cultivars that differ in glucose–fructose ratio
Wu , B.H. (Chinese Academy of Science, Beijing(Chine). Institute of Botany) | Quilot-Turion , Bénédicte (INRA (France). UR 1052 Génétique et Amélioration des Fruits et Légumes) | Génard , Michel (INRA , Avignon (France). UR 1115 Unité de recherche Plantes et Systèmes de Culture Horticoles) | Li , S.H. (Chinese Academy of Science, Beijing(Chine). Institute of Botany) | Zhao , J.B. (Beijing Academy of Agriculture and Forestry Sciences, Beijing(Chine). Institute of Forestry and Fruit) | Yang , J. (Chinese Academy of Science, Beijing(Chine). Institute of Botany) | Wang , Y.Q. (Chinese Academy of Science, Beijing(Chine). Institute of Botany)
A SUGAR model, which was established to predict the partitioning of carbon into sucrose, glucose, fructose and sorbitol in fruit mesocarp of peach cultivars (Prunus persica (L.) Batch) with normal glucose: fructose ratio (G:F) of 0·8–1·5, was evaluated and extended for peach cultivars with a high G:F ratio of 1·5–7·8. The extended model (SUGARb) is more generic and assumes a high G:F ratio to be due to preferential transformation of sorbitol into glucose, preferential utilization of fructose or preferential conversion of fructose into glucose. The simulated seasonal variations in sugars via the SUGARb-model-matched experimental data for three normal and three high G:F cultivars well, and accurately exhibited G:F ratio characteristics. The relative rates of sucrose transformation into glucose and fructose differed according to cultivar but not according to G:F status. Compared with hexosephosphate interconversion, a lower production rate of fructose than glucose from sorbitol, and/or a higher utilization rate of fructose than that of glucose might be preferential alternatives for forming high G:F ratios in the high G:F cultivars studied in the present study, which is discussed in the light of recent results on enzyme activities
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Эту запись предоставил National Institute for Agricultural Research