Data synthesis for crop variety evaluation. A review
Crop varieties should fulfill multiple requirements, including agronomic performance and product quality. Variety evaluations depend on data generated from field trials and sensory analyses, performed with different levels of participation from farmers and consumers. Such multi-faceted variety evalu...
| Autores principales: | , , , , |
|---|---|
| Formato: | Journal Article |
| Lenguaje: | Inglés |
| Publicado: |
Springer
2020
|
| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/108761 |
| _version_ | 1855515770993246208 |
|---|---|
| author | Brown, David Bergh, Inge van den Bruin, Sytze de Machida, Lewis Etten, Jacob van |
| author_browse | Bergh, Inge van den Brown, David Bruin, Sytze de Etten, Jacob van Machida, Lewis |
| author_facet | Brown, David Bergh, Inge van den Bruin, Sytze de Machida, Lewis Etten, Jacob van |
| author_sort | Brown, David |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Crop varieties should fulfill multiple requirements, including agronomic performance and product quality. Variety evaluations depend on data generated from field trials and sensory analyses, performed with different levels of participation from farmers and consumers. Such multi-faceted variety evaluation is expensive and time-consuming; hence, any use of these data should be optimized. Data synthesis can help to take advantage of existing and new data, combining data from different sources and combining it with expert knowledge to produce new information and understanding that supports decision-making. Data synthesis for crop variety evaluation can partly build on extant experiences and methods, but it also requires methodological innovation. We review the elements required to achieve data synthesis for crop variety evaluation, including (1) data types required for crop variety evaluation, (2) main challenges in data management and integration, (3) main global initiatives aiming to solve those challenges, (4) current statistical approaches to combine data for crop variety evaluation and (5) existing data synthesis methods used in evaluation of varieties to combine different datasets from multiple data sources. We conclude that currently available methods have the potential to overcome existing barriers to data synthesis and could set in motion a virtuous cycle that will encourage researchers to share data and collaborate on data-driven research. |
| format | Journal Article |
| id | CGSpace108761 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2020 |
| publishDateRange | 2020 |
| publishDateSort | 2020 |
| publisher | Springer |
| publisherStr | Springer |
| record_format | dspace |
| spelling | CGSpace1087612025-11-12T05:38:03Z Data synthesis for crop variety evaluation. A review Brown, David Bergh, Inge van den Bruin, Sytze de Machida, Lewis Etten, Jacob van data environmental engineering Crop varieties should fulfill multiple requirements, including agronomic performance and product quality. Variety evaluations depend on data generated from field trials and sensory analyses, performed with different levels of participation from farmers and consumers. Such multi-faceted variety evaluation is expensive and time-consuming; hence, any use of these data should be optimized. Data synthesis can help to take advantage of existing and new data, combining data from different sources and combining it with expert knowledge to produce new information and understanding that supports decision-making. Data synthesis for crop variety evaluation can partly build on extant experiences and methods, but it also requires methodological innovation. We review the elements required to achieve data synthesis for crop variety evaluation, including (1) data types required for crop variety evaluation, (2) main challenges in data management and integration, (3) main global initiatives aiming to solve those challenges, (4) current statistical approaches to combine data for crop variety evaluation and (5) existing data synthesis methods used in evaluation of varieties to combine different datasets from multiple data sources. We conclude that currently available methods have the potential to overcome existing barriers to data synthesis and could set in motion a virtuous cycle that will encourage researchers to share data and collaborate on data-driven research. 2020-08 2020-07-14T11:39:06Z 2020-07-14T11:39:06Z Journal Article https://hdl.handle.net/10568/108761 en Open Access application/pdf Springer Brown, D.; Van den Bergh, I.; de Bruin, S.; Machida, L.; van Etten, J. (2020) Data synthesis for crop variety evaluation. A review. Agronomy for Sustainable Development 40: 25. ISSN: 1774-0746 |
| spellingShingle | data environmental engineering Brown, David Bergh, Inge van den Bruin, Sytze de Machida, Lewis Etten, Jacob van Data synthesis for crop variety evaluation. A review |
| title | Data synthesis for crop variety evaluation. A review |
| title_full | Data synthesis for crop variety evaluation. A review |
| title_fullStr | Data synthesis for crop variety evaluation. A review |
| title_full_unstemmed | Data synthesis for crop variety evaluation. A review |
| title_short | Data synthesis for crop variety evaluation. A review |
| title_sort | data synthesis for crop variety evaluation a review |
| topic | data environmental engineering |
| url | https://hdl.handle.net/10568/108761 |
| work_keys_str_mv | AT browndavid datasynthesisforcropvarietyevaluationareview AT berghingevanden datasynthesisforcropvarietyevaluationareview AT bruinsytzede datasynthesisforcropvarietyevaluationareview AT machidalewis datasynthesisforcropvarietyevaluationareview AT ettenjacobvan datasynthesisforcropvarietyevaluationareview |