Abstract:
Enviromics is the field of applied data science that integrates databases of environmental factors into biostatistics and quantitative genetics. It can leverage plant ecophysiology knowledge to bridge the gaps about environment interactions with systems biology (genes, transcripts, proteins, and metabolites), which also boosts the ability to understand and model the phenotypic plasticity of the main agronomic traits. Recently, the plant breeding community has experienced reduced costs for acquiring environmental sensors to be installed in the field trials while increasing the reliability and resolution of the remote sensing techniques. The combination of those two factors has started the spring of enviromics-aided breeding in recent years. However, the use of environmental information in plant breeding is not a novelty approach developed a few years ago, but a core of efforts originated in the last 60 years, yet some basic ideas traced back to early 20th century attempts to establish a relationship between phenotypic and environmental variation. This review highlights the main concepts surrounding the construction of the “modern enviromics science”, tracing back to its origins in the last decades. Finally, we present how this field has helped integrate different data sources in prediction-based models or build one framework.
Keywords:
Prediction-based breeding; breeding analytics; envirotyping; genotype x environment
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