Detecting the QTL-Allele System of Seed Oil Traits Using Multi-Locus Genome-Wide Association Analysis for Population Characterization and Optimal Cross Prediction in Soybean.

MLA

Zhang, Yinghu, et al. “Detecting the QTL-Allele System of Seed Oil Traits Using Multi-Locus Genome-Wide Association Analysis for Population Characterization and Optimal Cross Prediction in Soybean.” Frontiers in Plant Science, vol. 9, Dec. 2018, p. 1793. EBSCOhost, https://doi.org/10.3389/fpls.2018.01793.

APA

Zhang, Y., He, J., Wang, H., Meng, S., Xing, G., Li, Y., Yang, S., Zhao, J., Zhao, T., & Gai, J. (2018). Detecting the QTL-Allele System of Seed Oil Traits Using Multi-Locus Genome-Wide Association Analysis for Population Characterization and Optimal Cross Prediction in Soybean. Frontiers in Plant Science, 9, 1793. https://doi.org/10.3389/fpls.2018.01793

Chicago

Zhang, Yinghu, Jianbo He, Hongwei Wang, Shan Meng, Guangnan Xing, Yan Li, Shouping Yang, Jinming Zhao, Tuanjie Zhao, and Junyi Gai. 2018. “Detecting the QTL-Allele System of Seed Oil Traits Using Multi-Locus Genome-Wide Association Analysis for Population Characterization and Optimal Cross Prediction in Soybean.” Frontiers in Plant Science 9 (December): 1793. doi:10.3389/fpls.2018.01793.