Agriculture today faces increasing pressure due to climate variability and the need to feed a growing population. Maize plays a crucial role by providing food, feed, and fuel both in and out of the US, but it contributes significantly to environmental issues such as nitrous oxide emissions and nutrient runoff. Improving the sustainability of maize production requires rethinking our current methods and leveraging quantitative genetics and genomics to develop the foundations for more resilient cropping systems. This dissertation begins by investigating intraspecific competition dynamics in maize, focusing on neighboring row competition and variety mixtures. These experiments demonstrate that competitive effects explain 1-3% of yield variance, suggesting that plant breeders have successfully selected against competitive traits in maize. Further, variety mixtures show no significant impact on yield stability, offering a potential strategy for reducing risk while maintaining yield in modern breeding programs. The second part tackles the challenge of determining gene model annotation quality. To address this, reelGene, a machine-learning pipeline that evaluates the functionality of gene models, was developed. In a study of 1.8 million maize transcript models, 28% were found to be nonfunctional or misannotated, highlighting the ability of reelGene to provide a more robust set of genes for downstream analyses. reelGene also allows for a greater understanding of genome biology and shows that most species-specific genes are nonfunctional. Finally, this dissertation examines the molecular evolution of perenniality by analyzing 749 Poaceae genomes, covering numerous perennial-to-annual transitions. The analysis uncovers a 9.3-fold enrichment for the loss of nucleotide conservation in annuals compared to perennials, indicating that the transition from perennial to annual life histories is largely driven by the loss of perennial-related gene function. Using a phylogenetic mixed model, key pathways are identified that are differentially constrained between annuals and perennials as well as for species with and without rhizomes. This research provides critical insights into how we can redesign cropping systems to be more resilient and resource-efficient, leveraging genetic diversity and perennial-like traits to improve yield stability and reduce environmental impact in maize-based agriculture.