Rate My Professor Vivi Arief

Dr. Vivi Arief is a Lecturer in Biometry in the School of Agriculture and Food Sustainability, Faculty of Science, at the University of Queensland. She was awarded a PhD in plant breeding and quantitative genetics from the University of Queensland in 2011 and holds a Master's (Coursework) in Agricultural Studies from the same institution. Her research specializations include the analysis and interpretation of data from large-scale plant breeding experiments, application of pattern analysis such as clustering and ordination procedures for plant breeding data, genome-wide association analysis using plant breeding data, application of genomic selection in plant breeding, and QU-GENE simulation for plant breeding strategies.

Arief continues her academic career at the University of Queensland, contributing to crop science through quantitative genetics, plant breeding, and biometrics. She has received funding for projects including Analytics for the Australian Grains Industry from the Grains Research & Development Corporation (2023–2027), Pre-breeding for cold tolerance and improved agronomy for high water productivity rice from the AgriFutures Rice Program (2021–2026), Data Partnerships Initiative from the Grains Research & Development Corporation (2023), and Cooperative Development of QU-GENE Simulation Platform for cross-pollinating Forage Species from AgResearch (2018–2020). Key publications encompass 'Design and analysis of multi-year field trials for annual crops' (Arief, DeLacy, and Basford, 2020), 'Selecting superior genotypes to enhance yield and fruit quality in Australian passion fruit' (Sun et al., 2025), 'Evaluation of Water Use Efficiency in Mungbean using the Inverted-Bottle Pot System' (Zhong et al., 2024), 'Simulations of multiple breeding strategy scenarios in common bean for assessing genomic selection accuracy and model updating' (Chiaravallotti et al., 2024), and 'Simulations of rate of genetic gain in dry bean breeding programs' (Lin et al., 2023). Her scholarship, cited over 2000 times, advances plant breeding methodologies and genetic gain predictions.