An organism’s phenome results from genotype (nature), environment and management effects (nurture) and their interactions, as well as measurement error. For over 30 years, DNA sequencing and genomics tools have advanced genotyping to where genomes can now be routinely saturated with measurements. In contrast, most focus in high throughput phenotyping, and phenomics to date has been on automating previously known “traits” as measurable and interpretable phenotypes; akin to focusing on measuring a single DNA marker rather than measuring a saturated genome. 

Tools such as unoccupied aerial systems (UAS, aka UAVs, drones) collecting temporal phenomic measurements in the field now allow novel methods in plant breeding and new insights into plant biology. Viewing phenomics as a platform for discovery, similar to genomics, opens new methods for capturing phenomena in nature and nurture. To date, our experience with phenomic prediction from UAS in maize breeding for cumulative, complex phenotypes such as grain yield suggests it’s possible to predict organismal performance in untested environments; in fact possibly better than gold-standard genomic methods. Surprising insights into biology have also been made in through these activities predicting plant disease and resistance, evaluating genotypic resilience to stress, and identifying early season growth periods for crop improvement that have not been able to be selected. 

Method development and data analytics in phenomics are large investments, but worth making. Successfully measuring the phenome will impact every aspect of science and society, in biological disciplines from germplasm curators, physiologists to breeders, to education, the courtroom and policy.