Abstract:

The practical early appraisal technique was established in order to accelerate the breeding tea varieties with specific catechins components. In this study, tea plant varieties with high EGCG content and their artificial hybridization F1 were used as material. The non-linear regression forecast model based on functional networks and generalized linear models were applied, and on the basis of field observation net photosynthetic rate of tea plant, the net photosynthetic rate of tea plant leaves of different strains (varieties) was computed. Then the correlation between the tea plants leaves net photosynthetic rate and catechins components and matching of correlation was analyzed. The results showed that the net photosynthetic rate of tea plant leaves had positive correlation with the EC, GCG content, and negative correlation with C, ECG, EGC, EC, EGCG, simple catechins and total catechins. In particular, the negative correlation with the ester-catechins and total catechins was significant. Excluded the impact of the photosynthesis of light, temperature and other factors by the application of the above mentioned models, the tea plant photosynthetic capacity was reacted by the tea plant leaves net photosynthetic rate. The study results indicated that detecting net photosynthetic rate of tea plants provided a basis for early handy appraisal of new tea plant strains with specific catechins components.