A data workflow to support plant breeding decisions from a terrestrial field-based high-throughput plant phenotyping system
Abstract Field-based high-throughput plant phenotyping (FB-HTPP) has been a primary focus for crop improvement to meet the demands of a growing population in a changing environment. Over the years, breeders, geneticists, physiologists, and agronomists have been able to improve the understanding betw...
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMC
2020-07-01
|
| Series: | Plant Methods |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1186/s13007-020-00639-9 |
| _version_ | 1819093434438254592 |
|---|---|
| author | Alison L. Thompson Kelly R. Thorp Matthew M. Conley Michael Roybal David Moller Jacob C. Long |
| author_facet | Alison L. Thompson Kelly R. Thorp Matthew M. Conley Michael Roybal David Moller Jacob C. Long |
| author_sort | Alison L. Thompson |
| collection | DOAJ |
| description | Abstract Field-based high-throughput plant phenotyping (FB-HTPP) has been a primary focus for crop improvement to meet the demands of a growing population in a changing environment. Over the years, breeders, geneticists, physiologists, and agronomists have been able to improve the understanding between complex dynamic traits and plant response to changing environmental conditions using FB-HTPP. However, the volume, velocity, and variety of data captured by FB-HTPP can be problematic, requiring large data stores, databases, and computationally intensive data processing pipelines. To be fully effective, FB-HTTP data workflows including applications for database implementation, data processing, and data interpretation must be developed and optimized. At the US Arid Land Agricultural Center in Maricopa Arizona, USA a data workflow was developed for a terrestrial FB-HTPP platform that utilized a custom Python application and a PostgreSQL database. The workflow developed for the HTPP platform enables users to capture and organize data and verify data quality before statistical analysis. The data from this platform and workflow were used to identify plant lodging and heat tolerance, enhancing genetic gain by improving selection accuracy in an upland cotton breeding program. An advantage of this platform and workflow was the increased amount of data collected throughout the season, while a main limitation was the start-up cost. |
| first_indexed | 2024-12-21T23:11:27Z |
| format | Article |
| id | doaj.art-4946e9f0d4034ffbbaea09df96bcff89 |
| institution | Directory Open Access Journal |
| issn | 1746-4811 |
| language | English |
| last_indexed | 2024-12-21T23:11:27Z |
| publishDate | 2020-07-01 |
| publisher | BMC |
| record_format | Article |
| series | Plant Methods |
| spelling | doaj.art-4946e9f0d4034ffbbaea09df96bcff892022-12-21T18:47:01ZengBMCPlant Methods1746-48112020-07-0116111310.1186/s13007-020-00639-9A data workflow to support plant breeding decisions from a terrestrial field-based high-throughput plant phenotyping systemAlison L. Thompson0Kelly R. Thorp1Matthew M. Conley2Michael Roybal3David Moller4Jacob C. Long5USDA-ARS Arid Land Agricultural Research CenterUSDA-ARS Arid Land Agricultural Research CenterUSDA-ARS Arid Land Agricultural Research CenterUSDA-ARS Arid Land Agricultural Research CenterUSDA-ARS Arid Land Agricultural Research CenterUSDA-ARS Arid Land Agricultural Research CenterAbstract Field-based high-throughput plant phenotyping (FB-HTPP) has been a primary focus for crop improvement to meet the demands of a growing population in a changing environment. Over the years, breeders, geneticists, physiologists, and agronomists have been able to improve the understanding between complex dynamic traits and plant response to changing environmental conditions using FB-HTPP. However, the volume, velocity, and variety of data captured by FB-HTPP can be problematic, requiring large data stores, databases, and computationally intensive data processing pipelines. To be fully effective, FB-HTTP data workflows including applications for database implementation, data processing, and data interpretation must be developed and optimized. At the US Arid Land Agricultural Center in Maricopa Arizona, USA a data workflow was developed for a terrestrial FB-HTPP platform that utilized a custom Python application and a PostgreSQL database. The workflow developed for the HTPP platform enables users to capture and organize data and verify data quality before statistical analysis. The data from this platform and workflow were used to identify plant lodging and heat tolerance, enhancing genetic gain by improving selection accuracy in an upland cotton breeding program. An advantage of this platform and workflow was the increased amount of data collected throughout the season, while a main limitation was the start-up cost.http://link.springer.com/article/10.1186/s13007-020-00639-9Field-based high-throughput plant phenotypingDatabaseData processingPlant breeding |
| spellingShingle | Alison L. Thompson Kelly R. Thorp Matthew M. Conley Michael Roybal David Moller Jacob C. Long A data workflow to support plant breeding decisions from a terrestrial field-based high-throughput plant phenotyping system Plant Methods Field-based high-throughput plant phenotyping Database Data processing Plant breeding |
| title | A data workflow to support plant breeding decisions from a terrestrial field-based high-throughput plant phenotyping system |
| title_full | A data workflow to support plant breeding decisions from a terrestrial field-based high-throughput plant phenotyping system |
| title_fullStr | A data workflow to support plant breeding decisions from a terrestrial field-based high-throughput plant phenotyping system |
| title_full_unstemmed | A data workflow to support plant breeding decisions from a terrestrial field-based high-throughput plant phenotyping system |
| title_short | A data workflow to support plant breeding decisions from a terrestrial field-based high-throughput plant phenotyping system |
| title_sort | data workflow to support plant breeding decisions from a terrestrial field based high throughput plant phenotyping system |
| topic | Field-based high-throughput plant phenotyping Database Data processing Plant breeding |
| url | http://link.springer.com/article/10.1186/s13007-020-00639-9 |
| work_keys_str_mv | AT alisonlthompson adataworkflowtosupportplantbreedingdecisionsfromaterrestrialfieldbasedhighthroughputplantphenotypingsystem AT kellyrthorp adataworkflowtosupportplantbreedingdecisionsfromaterrestrialfieldbasedhighthroughputplantphenotypingsystem AT matthewmconley adataworkflowtosupportplantbreedingdecisionsfromaterrestrialfieldbasedhighthroughputplantphenotypingsystem AT michaelroybal adataworkflowtosupportplantbreedingdecisionsfromaterrestrialfieldbasedhighthroughputplantphenotypingsystem AT davidmoller adataworkflowtosupportplantbreedingdecisionsfromaterrestrialfieldbasedhighthroughputplantphenotypingsystem AT jacobclong adataworkflowtosupportplantbreedingdecisionsfromaterrestrialfieldbasedhighthroughputplantphenotypingsystem AT alisonlthompson dataworkflowtosupportplantbreedingdecisionsfromaterrestrialfieldbasedhighthroughputplantphenotypingsystem AT kellyrthorp dataworkflowtosupportplantbreedingdecisionsfromaterrestrialfieldbasedhighthroughputplantphenotypingsystem AT matthewmconley dataworkflowtosupportplantbreedingdecisionsfromaterrestrialfieldbasedhighthroughputplantphenotypingsystem AT michaelroybal dataworkflowtosupportplantbreedingdecisionsfromaterrestrialfieldbasedhighthroughputplantphenotypingsystem AT davidmoller dataworkflowtosupportplantbreedingdecisionsfromaterrestrialfieldbasedhighthroughputplantphenotypingsystem AT jacobclong dataworkflowtosupportplantbreedingdecisionsfromaterrestrialfieldbasedhighthroughputplantphenotypingsystem |