About this Research Topic
This Research Topic is part of the High-Throughput Field Phenotyping to Advance Precision Agriculture and Enhance Genetic Gain series.
The discipline of “High Throughput Field Phenotyping” (HTFP) has gained momentum in the last decade. HTFP includes a wide range of disciplines such as plant science, agronomy, remote sensing, and genetics; as well as biochemistry, imaging, computation, agricultural engineering, and robotics.
High throughput technologies have substantially increased our ability to monitor and quantify field experiments and breeding nurseries at multiple scales. HTFP technology can not only rapidly and cost-effectively replace tedious and subjective ratings in the field, but can also unlock the potential of new, latent phenotypes representing underlying biological function. These advances have also provided the ability to follow crop growth and development across seasons at high and previously inaccessible spatial and temporal resolutions. By combining these data with measurements of all environmental factors affecting plant growth and yield (“Envirotyping”), genotypic-specific reaction norms and phenotypic plasticity may be elucidated.
HTFP will continue to gain momentum as a result of closer collaborations among agronomists, plant scientists, breeders, engineers, crop modelers, and the remote sensing community. Combining HTFP with envirotyping, crop modeling, and genetics (particularly genomic selection) will further drive this momentum, ultimately helping to achieve increased genetic gains and crop productivity to address socioeconomic needs sustainably.
In the first edition of the research topic, we brought together 24 articles with contributions from 137 authors. In this second volume, we aim to further unite different disciplines in the contrasting ends of HTFP. Contributions should cover the different aspects of the phenotyping workflow:
i) sensors, carrier systems, and automation;
ii) experimental design, campaign planning, plot extraction;
iii) data management, trait ontologies and common data standards;
iv) modern image analysis, feature detection, photogrammetry, and data fusion;
v) spatiotemporal modeling;
vi) trait calibration using multidimensional data from envirotyping and multi-environment trials.
Contributions should go beyond the current state-of-the-art or critically re-evaluate existing findings. The readiness as well as the potential adoption of HTFP in practice is of paramount interest and should be demonstrated. We welcome innovative Original Research, Review and Perspective articles and novel methods in field-based high-throughput plant phenomics.
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
The discipline of “High Throughput Field Phenotyping” (HTFP) has gained momentum in the last decade. HTFP includes a wide range of disciplines such as plant science, agronomy, remote sensing, and genetics; as well as biochemistry, imaging, computation, agricultural engineering, and robotics.
High throughput technologies have substantially increased our ability to monitor and quantify field experiments and breeding nurseries at multiple scales. HTFP technology can not only rapidly and cost-effectively replace tedious and subjective ratings in the field, but can also unlock the potential of new, latent phenotypes representing underlying biological function. These advances have also provided the ability to follow crop growth and development across seasons at high and previously inaccessible spatial and temporal resolutions. By combining these data with measurements of all environmental factors affecting plant growth and yield (“Envirotyping”), genotypic-specific reaction norms and phenotypic plasticity may be elucidated.
HTFP will continue to gain momentum as a result of closer collaborations among agronomists, plant scientists, breeders, engineers, crop modelers, and the remote sensing community. Combining HTFP with envirotyping, crop modeling, and genetics (particularly genomic selection) will further drive this momentum, ultimately helping to achieve increased genetic gains and crop productivity to address socioeconomic needs sustainably.
In the first edition of the research topic, we brought together 24 articles with contributions from 137 authors. In this second volume, we aim to further unite different disciplines in the contrasting ends of HTFP. Contributions should cover the different aspects of the phenotyping workflow:
i) sensors, carrier systems, and automation;
ii) experimental design, campaign planning, plot extraction;
iii) data management, trait ontologies and common data standards;
iv) modern image analysis, feature detection, photogrammetry, and data fusion;
v) spatiotemporal modeling;
vi) trait calibration using multidimensional data from envirotyping and multi-environment trials.
Contributions should go beyond the current state-of-the-art or critically re-evaluate existing findings. The readiness as well as the potential adoption of HTFP in practice is of paramount interest and should be demonstrated. We welcome innovative Original Research, Review and Perspective articles and novel methods in field-based high-throughput plant phenomics.
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
Keywords: Artificial Intelligence, Machine Learning, Field-Based Phenomics, Precision Phenotyping, Water and Nutrient Use Efficiency, Drought and Heat Tolerance
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
