Cite
Multivariate genomic analysis and optimal contributions selection predicts high genetic gains in cooking time, iron, zinc, and grain yield in common beans in East Africa
MLA
Renu Saradadevi, et al. “Multivariate Genomic Analysis and Optimal Contributions Selection Predicts High Genetic Gains in Cooking Time, Iron, Zinc, and Grain Yield in Common Beans in East Africa.” The Plant Genome, vol. 14, no. 3, Nov. 2021. EBSCOhost, https://doi.org/10.1002/tpg2.20156.
APA
Renu Saradadevi, Clare Mukankusi, Li Li, Winnyfred Amongi, Julius Peter Mbiu, Bodo Raatz, Daniel Ariza, Steve Beebe, Rajeev K. Varshney, Eric Huttner, Brian Kinghorn, Robert Banks, Jean Claude Rubyogo, Kadambot H. M. Siddique, & Wallace A. Cowling. (2021). Multivariate genomic analysis and optimal contributions selection predicts high genetic gains in cooking time, iron, zinc, and grain yield in common beans in East Africa. The Plant Genome, 14(3). https://doi.org/10.1002/tpg2.20156
Chicago
Renu Saradadevi, Clare Mukankusi, Li Li, Winnyfred Amongi, Julius Peter Mbiu, Bodo Raatz, Daniel Ariza, et al. 2021. “Multivariate Genomic Analysis and Optimal Contributions Selection Predicts High Genetic Gains in Cooking Time, Iron, Zinc, and Grain Yield in Common Beans in East Africa.” The Plant Genome 14 (3). doi:10.1002/tpg2.20156.