Abstract
Background
Locating the optimal varieties for coffee cultivation is increasingly considered a key condition for sustainable production and marketing. Variety performance varies when it comes to susceptibility to coffee leaf rust and other diseases, adaptation to climate change and high cup quality for specialty markets. But because of poor organization and the lack of a professional coffee seed sector, most existing coffee farms (and even seed lots and nurseries) do not know which varieties they are using. DNA fingerprinting of coffee planting material will contribute to professionalize the coffee seed sector.
Objective
The objective of this paper is i) to check in a large scale the robustness of the existing coffee DNA fingerprinting method based on eight Single Sequence Repeats markers (SRR) and ii) to describe how it can help in moving the needle towards a more professional seed sector.
Method
2533 samples representing all possible genetic background of Arabica varieties were DNA fingerprinted with 8 SRR markers. The genetic diversity was analyzed and the genetic conformity to varietal references was assessed.
Results
The DNA fingerprinting method proved to be robust in authenticating varieties and trace back the history of C. arabica breeding and of the movement of C. arabica varieties. The genetic conformity of two important coffee varieties, Marseillesa and Gesha, proved to be 91% and 39% respectively.
Conclusions
DNA fingerprinting provides different actors in the coffee sector with a powerful new tool—farmers can verify the identity of their cultivated varieties, coffee roasters can be assured that marketing claims related to varieties are correct, and most of all, those looking to establish the a more professional and reliable coffee seed sector have a reliable new monitoring tool to establish and check genetic purity of seed stock and nursery plants.
Highlights
While C. arabica is primarily self-pollinating, even fixed line varieties appear to be drifting away from their original genetic reference due to uncontrolled cross pollination. A set of 8 SSR markers applied to the largest possible genetically diverse set of samples prove to discriminate between a wide range of varieties Figures confirm that genetic non conformity of coffee varieties can represent up to 61% of checked samples.
The Digital Fingerprinting Method for Static Images Based on Weighted Hamming Metric and on Weighted Container Model
