Journal of the ASABE Vol. 65(3): 491-504 © 2022 American Society of Agricultural and Biological Engineers ISSN 2769-3295 https://doi.org/10.13031/ja.14912 491 CROP IMPROVEMENT FOR CIRCULAR BIOECONOMY SYSTEMS Carlos D. Messina 1,2,* , Fred van Eeuwijk 3 , Tom Tang 2 , Sandra K. Truong 2 , Ryan F. McCormick 2 , Frank Technow 2 , Owen Powell 4 , Laura Mayor 5 , Neal Gutterson 6 , James W. Jones 7 , Graeme L. Hammer 4 , Mark Cooper 4 Collection Research 1 Department of Horticultural Sciences, University of Florida, Gainesville, Florida, USA. 2 Predictive Agriculture, Corteva Agriscience, Johnston, Iowa, USA. 3 Biometris, Wageningen University and Research, Wageningen, Gelderland, Netherlands. 4 Queensland Alliance for Agriculture and Food Innovation, University of Queensland, Saint Lucia, Queensland, Australia. 5 Plant Breeding, Corteva Agriscience, Manhattan, Kansas, USA. 6 Radicle Growth, San Diego, California, USA. 7 Department of Agricultural and Biological Engineering, University of Florida, Gainesville, Florida, USA. * Correspondence: cmessina@ufl.edu, charlie.messina@gmail.com HIGHLIGHTS  We describe and demonstrate a multidimensional framework to integrate environmental and genomic predictors to enable crop improvement for a circular bioeconomy.  A model training procedure based on multiple phenotypes is shown to improve predictive skill.  The decision set comprised of model outputs can inform selection for both productivity and circularity metrics. ABSTRACT. Contemporary agricultural systems are poised to transition from linear to circular, adopting concepts of recy- cling, repurposing, and regeneration. This transition will require changing crop improvement objectives to consider the entire system, and thus provide solutions to improve complex systems for higher productivity, resource use efficiency, and environmental quality. The methods and approaches that underpinned the doubling of yields during the last century may no longer be fully adequate to target crop improvement for circular agricultural systems. Here we propose a multidimensional framework for prediction with outcomes useful to assess both crop performance traits and environmental sustainability of the designed agricultural systems. The study focuses on maize harvestable grain yield and total carbon production, water use, and use efficiency for yield and carbon. The framework builds on the crop growth model whole genome prediction system, which is enabled by advanced phenomics and the integration of symbolic and sub-symbolic artificial intelligence. We demonstrate the approach and prediction accuracy advantages over a standard statistical genomic prediction approach used to breed maize hybrids for yield, flowering time, and kernel set using a dataset comprised of 7004 hybrids, 103 breeding populations, and 62 environments resulting from six years of experimentation in maize drought breeding in the U.S. We propose this framework to motivate a dialogue for how to enable circularity in agriculture through prediction-based systems design. Keywords. Circular bioeconomy, Circular economy, Crop improvement, Crop models, Drought, Gene editing, Genomic prediction, Maize, Plant breeding. ociety and consumers, particularly the new genera- tions, are demanding healthier and sustainably pro- duced food, fiber, and fuel. The traditional high in- put/output agriculture paradigm with low recycling and high emissions, i.e., linear agriculture, is no longer viable to meet sustainability goals (Jordan et al., 2007). A circular economy approach is being advocated as the alternative par- adigm for sustainable intensification (Ellen MacArthur Foun- dation, 2015) while enabling society to combat climate change (Ellen MacArthur Foundation, 2019). Circularity in agriculture, and more generally in food systems, seeks to re- duce inputs and toxic waste, reuse materials and machinery, recycle nutrients not essential for human nutrition, and regen- erate natural and production systems while improving the economic viability of the food and agricultural systems (Ellen MacArthur Foundation, 2015; Jones et al., 2020; Basso et al., 2021). The business and engineering focus of circularity (Geissdoerfer et al., 2017) can be viewed as a set of principles that will enable industry to practice the sustainability narra- tive, and thus meet sustainability goals. The authors have paid for open access for this article. This work is licensed under a Creative Commons Attribution- NonCommercial-NoDerivatives 4.0 International License https://creative commons.org/licenses/by-nc-nd/4.0/ Submitted for review on 18 October 2021 as manuscript number ITSC 14912; approved for publication as an Invited Research Article and as part of the Circular Food and Agricultural Systems Collection by Associate Editor Dr. Kati Migliaccio and Community Editor Dr. Kati Migliaccio of the Information Technology, Sensors, & Control Systems Community of ASABE on 8 March 2022. S