Advanced Research Journal of Biochemistry Vol. 4 (1) pp. 168-178, January, 2019.  © Advanced Scholars Journals

Full Length Research Paper

Study on effective berry-independent method for grapevine evaluation 

*Zhao Yong, Xiamo H. A and Cheng M. O.

College of Food and Nutritional Engineering, China Agricultural University, Beijing 100083, China.

* Corresponding author. Email: [email protected]

Accepted 10 December, 2018

Abstract

The quality and characteristics of grape are fundamentally determined by its biochemical components. Quantitative detection of these components in berries is a classic method to evaluate grapevine resources. However, fruits are not always available for the new generated grape plantlets due to their long juvenile stage (3 to 4 years), as well as for many other potential valuable germplasm resources, such as wild grapes. Therefore, an effective berry-independent method for grapevine evaluation should have great significance. Data were provided from both leaves and berries for 2 groups of grapevine: one group is 12 genotype different varieties or species from environmental similar collections; the other group is one variety of wine grape with 18 different treatments. After quantitative correlation tests, 9 in total 11 detected parameters in genotype different (GD) group and 5 in 9 detected parameters in treatment different (TD) group, respectively, were significantly correlated between leaf and berry, respectively were found. Higher correlation coefficients were found in GD group than in TD group. Parameters of leaf reducing sugar, total flavonoids and superoxide anion scavenging capacity were found significantly correlated to berry, in both groups. These parameters with significant correlation may potentially be used as metabolite markers to estimate the qualities and characters of some new grapevine germplasm, by using the obtained data from leaves. The prospects of this leave-dependent evaluation method have also been discussed in this report.

Key words: Leaf-dependent berry evaluation, leaf/berry quantitative correlation, parameter pair, inter-parameters pair.