Conventional breeding approaches and technologies have improved many agronomical traits in the past decades, including quality, disease resistance, yield and environmental adaptation traits. Innovations in plant science such as next-generation sequencing (NGS) technologies have enabled the detailed characterization of plant genomes, facilitating in-depth dissection of the genetic bases of variation of several crop traits. Concomitantly, high-throughput phenomic (HTP) approaches have aided the comprehensive phenotypic characterization of germplasm under field and controlled environments. In this collection, we aim to highlight recent advancements in converging genomic and phenomic technologies which have shown promise in improving the rate of genetic gains in breeding programs, leading to an increase in crop yield, quality and resilience in the face of a changing climate.
Recent years have witnessed many strides in the development and deployment of high-throughput -omics technologies, particularly genomics and phenomics. Whilst the issue of generating multimillion genotypic data points has been resolved due to the advances made in NGS, HTP is still expensive and challenging, particularly for field environments. The potential use and application of robotics, artificial intelligence, machine learning, sensor technologies and computer science approaches (e.g., 3-dimensional models) are numerous and have been deployed to address many such challenges in HTP. Whilst these phenomic and genomic technologies will greatly support crop improvement, how these multidimensional data sets fit elegantly into the framework of phenotype and genotype relationships and their responses to the environment is important to facilitate informed breeding strategies.
This Research Topic aims to highlight significant advances in crop genetic improvement from studies integrating cutting-edge genomic and phenotyping platforms. Manuscripts from all areas of plant and crop science will be considered that have benefitted from bringing together novel phenomic and genomic tools. Such tools include:
• High-throughput and robotic phenotyping of both controlled and field settings;
• Novel genomics tools;
• Remote sensing technologies;
• Computer science approaches for predicting phenotypes.
We encourage all original research papers, reviews and opinion papers on understanding the convergence between phenotype and genotype dynamics and their relationships using state-of-the-art plant science approaches.
Conventional breeding approaches and technologies have improved many agronomical traits in the past decades, including quality, disease resistance, yield and environmental adaptation traits. Innovations in plant science such as next-generation sequencing (NGS) technologies have enabled the detailed characterization of plant genomes, facilitating in-depth dissection of the genetic bases of variation of several crop traits. Concomitantly, high-throughput phenomic (HTP) approaches have aided the comprehensive phenotypic characterization of germplasm under field and controlled environments. In this collection, we aim to highlight recent advancements in converging genomic and phenomic technologies which have shown promise in improving the rate of genetic gains in breeding programs, leading to an increase in crop yield, quality and resilience in the face of a changing climate.
Recent years have witnessed many strides in the development and deployment of high-throughput -omics technologies, particularly genomics and phenomics. Whilst the issue of generating multimillion genotypic data points has been resolved due to the advances made in NGS, HTP is still expensive and challenging, particularly for field environments. The potential use and application of robotics, artificial intelligence, machine learning, sensor technologies and computer science approaches (e.g., 3-dimensional models) are numerous and have been deployed to address many such challenges in HTP. Whilst these phenomic and genomic technologies will greatly support crop improvement, how these multidimensional data sets fit elegantly into the framework of phenotype and genotype relationships and their responses to the environment is important to facilitate informed breeding strategies.
This Research Topic aims to highlight significant advances in crop genetic improvement from studies integrating cutting-edge genomic and phenotyping platforms. Manuscripts from all areas of plant and crop science will be considered that have benefitted from bringing together novel phenomic and genomic tools. Such tools include:
• High-throughput and robotic phenotyping of both controlled and field settings;
• Novel genomics tools;
• Remote sensing technologies;
• Computer science approaches for predicting phenotypes.
We encourage all original research papers, reviews and opinion papers on understanding the convergence between phenotype and genotype dynamics and their relationships using state-of-the-art plant science approaches.
