Screening Germplasm Resources of Tea Plant with Less Bitterness and Astringency Index

The aim of this study was to identify tea varieties with less bitterness and astringency index that could be used as important sources for breeding and in the production of high quality tea. We studied 36 cultivars or lines which had been preserved in Tea Germplasm Garden of Fujian. The contents of catechins in spring tea shoots, summer tea shoots and autumn tea shoots in 36 varieties and lines were analyzed by HPLC. Analysis of these tea varieties and lines revealed that the catechins contained in the tea shoots in different seasons are highly variable. The content of ester-catechins in spring and summer tea shoots was higher than that of autumn, while non-ester-catechins did not showed the same characteristic. The content of EGCG showed an extremely significant positive correlation with T1 （T1 = EGC ＋ EGCG ＋ GCG ＋ EGC）, an extremely significant negative correlation with DL-C, the content of EGC showed the same characteristic. Among them, 10 cultivars with less bitterness and astringency index （the annual average bitterness and astringency index 〈 8.0） were considered good candidates as important breeding materials tbr tea infusion quality improvement.

A Review on the Identification Indicators of Tea Germplasm

Tea plant is cross pollinated plant, it forms a variety of the tea Germplasm constantly in the long-term breeding process. Tea Germplasm resources are the material foundation for improving varieties and also the basic research which is good for developing and expanding tea well-bred varieties in tea field, especially in quality selection and biotechnology research. Furthermore, excellent tea germplasm is primary condition for tea breeding and quality. Therefore, identification and screening excellent tea germplasm become particularly important. We need accelerate develop high-quality tea varieties, and it need to base on exploring and studying tea germplasm. This paper reviews the research progress of tea germplasm on identification from morphological characteristic, biological characteristic, quality characteristic, resistance and heredity. However, there are still some problems on identification and screening of tea germplasm, no effective methods have been found so far which apply on early identification and genetic engineering, so we should make intensive and long lasting study tea germplasm and analyze systematically various identification, which are benefit for breeding high-quality seeds, shortening the breeding period and summing the new way of breeding. We expect them to play the key roles and provide the theory basis for genetic improvement, classification and breeding in tea plant.

Local multifractal detrended fluctuation analysis for tea breeds identification

In recent years, the popular multifractal detrended fluctuation analysis （MF-DFA） is extended to two-dimensional （2D） version, which has been applied in some field of image processing. In this paper, based on the 2D MF-DFA, a novel multifractal estimation method for images, which we called the local multifractal detrended fluctuation analysis （LMF-DFA）, is proposed to recognize and distinguish 20 types of tea breeds. A set of new multifractal descriptors, namely the local multifractal fluctuation exponents is defined to portray the local scaling properties of a surface. After collecting 10 tea leaves for each breed and photographing them to standard images, the LMF-DFA method is used to extract characteristic parameters for the images. Our analysis finds that there are significant differences among the different tea breeds＇ characteristic parameters by analysis of variance. Both the proposed LMF-DFA exponents and another classic parameter, namely the exponent based on capacity measure method have been used as features to distinguish the 20 tea breeds. The comparison results illustrate that the LMF-DFA estimation can differentiate the tea breeds more effectively and provide more satisfactory accuracy.