Browsing by Author "Kahanda, Indika"

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Data-Driven Improvement to Institutional Repository Discoverability and Use
(Institute of Museum and Library Services, 2018-09) Arlitsch, Kenning; Kahanda, Indika; OBrien, Patrick; Shanks, Justin D.; Wheeler, Jonathan
The Montana State University (MSU) Library, in partnership with the MSU School of Computing, the University of New Mexico Library and DuraSpace, seeks a $49,998 Planning Grant from the Institute of Museum and Library Services through its National Leadership Grant program under its National Digital Platform project category to develop a sustainability plan for the Repositories Analytics & Metrics Portal that will keep its dataset open and available to all researchers. The proposal also includes developing a preliminary institutional repositories (IR) reporting model; a search engine optimization (SEO) audit and remediation plan for IR; and exploring whether machine learning can improve the quality of IR content metadata.The project team expects work conducted in this planning grant to make the case for advanced research projects that will be high-impact and worthy of funding.
Genetic dissection of natural variation in oilseed traits of camelina by whole-genome resequencing and QTL mapping
(Wiley, 2021-06) Li, Huang; Hu, Xiao; Lovell, John T.; Grabowski, Paul P.; Mamidi, Sujan; Chen, Cindy; Amirebrahimi, Mojgan; Kahanda, Indika; Mumey, Brendan; Barry, Kerrie; Kudrna, David; Schmutz, Jeremy; Lachowiec, Jennifer; Lu, Chaofu
Camelina [Camelina sativa (L.) Crantz] is an oilseed crop in the Brassicaceae family that is currently being developed as a source of bioenergy and healthy fatty acids. To facilitate modern breeding efforts through marker-assisted selection and biotechnology, we evaluated genetic variation among a worldwide collection of 222 camelina accessions. We performed whole-genome resequencing to obtain single nucleotide polymorphism (SNP) markers and to analyze genomic diversity. We also conducted phenotypic field evaluations in two consecutive seasons for variations in key agronomic traits related to oilseed production such as seed size, oil content (OC), fatty acid composition, and flowering time. We determined the population structure of the camelina accessions using 161,301 SNPs. Further, we identified quantitative trait loci (QTL) and candidate genes controlling the above field-evaluated traits by genome-wide association studies (GWAS) complemented with linkage mapping using a recombinant inbred line (RIL) population. Characterization of the natural variation at the genome and phenotypic levels provides valuable resources to camelina genetic studies and crop improvement. The QTL and candidate genes should assist in breeding of advanced camelina varieties that can be integrated into the cropping systems for the production of high yield of oils of desired fatty acid composition.