Mathematics Colloquium: The Future of Statistical Bioinformatics and Genomics in the Automated World of Agriculture
4:10pm SPARK 335
World population is expected to reach 9.6 billion by 2050, and crop yields are not keeping pace fast enough to avoid widespread food shortages. Modern molecular breeding programs are extremely effective, and can generate annual yield increases of around 4%. However, it is not scalable due to both the human labor and expertise required. Employing robots in agriculture has great potential to address chronic issues that are challenging food systems in the developing world. While quantitative trait locus (QTL) mapping associates molecular with variation in traits, there are new challenges for the statistical bioinformatics and genomics communities in how data are collected, stored and analyzed with respect to understanding relationships between genetic composition and phenotype. Using automation, the expectation is a dramatic increase, factor of 100+, in the number of individuals in the breeding population that can be evaluated. Artificial intelligence based technologies and analysis allow rapid evaluation, and thus make molecular breeding adaptive to environmental and other changes. Automated phenotyping is a transformational technology that can be applied worldwide.