Dilmini Alahakoon started working with VitisGen2 while employed in the Fennell lab for her PhD in August 2016 at South Dakota State University as a graduate research assistant. She is interested in grapevine phenology which plays a key role in grapevine breeding and is working in several QTL mapping projects under the guidance of Dr. Fennell. She used her prior knowledge and experience from a masters degree in biostatistics and certificate in data science to figure out phenotype and genotype association of studied populations.
What got you interested in grapevine genetics?
I was born in Sri Lanka and my father ran a rice cultivation where I had my first experience in agriculture. Later in my undergraduate at the University of Peradeniya, I learned the science behind tropical agriculture and crop farming. While working with the Department of Agriculture in Sri Lanka, I realized the importance of statistics to evaluate crop performance and completed my master’s in biostatistics. Inspired by the Fennell lab that uses statistics heavily in grapevine crop improvement, I joined SDSU and VitisGen2 for my PhD in 2016. Now I am working with grapevine populations to improve cold hardiness by studying phenomics and identifying quantitative trait loci.
What is your role with the VitisGen2 project?
My main role is monitoring and evaluating grapevine phenomics for the VitisGen2, mostly for freezing tolerance, bud break, and root architecture and QTL identification. We collect data every season for multiple years, so I love pattern recognition and analyzing those data for lab discussions. In addition, I help set up experiments, sample and data collection, data analyzing and maintaining field and greenhouses for the VitisGen2 team at the Fennell lab.
What are some major challenges faced by the industry/researchers, and how will your work address them?
One of the main challenges in phenomics is accuracy in phenotyping. Without an accurate phenotype measure, it is impossible to identify QTLs, the last step of the long process of phenotyping, and can give misleading results with other statistical analysis. Therefore, I usually follow a well-organized protocol for phenotyping especially for qualitative data to avoid wasting time, money, and efforts. Another key point is that we never forget to increase the size of the population including number of replicates. Introduction of new technology for genotyping and statistical analyzing methods are additional strategies in our team. All these approaches will help to improve the accuracy of QTL identification of a large grapevine population.
What is the most exciting thing you’ve learned or done since starting work with VitisGen2?
The most exciting thing I learned with VitisGen2 is high-throughput phenotyping of root architecture traits. Phenomics of grape root architecture is challenging especially for rooted cuttings. Since we scanned young root systems using a 2D scanner, I questioned the correlation of scanned results with real root systems that highly influenced for QTL analysis. With the results we observed, we can recommend this method of studying grape phenomics for grape geneticists.
How would you describe your job to a kindergartener?
My job is just like the crayon maker. Crayon makers invent different colors of crayons that have attractive shapes, sizes, shine or fruity smells using existing crayons. Likewise, I work with a large group of people to do the same thing but with grapes. I work hard to select the best for the community. When needed, we use our mathematical knowledge to figure out some big problems.