High-throughput imaging and phenotyping dataset of C4 grain crops

The images collected here could potentially help the development of new crop growth models for proso, pearl, foxtail and Japanese millet and teff. Therefore these images can be used to match the predictions from the growth models for plant height and leaf count and area. The plant height obtained for all three maize genotypes were within the same range for the same time period found in a previous study. Also, with the availability of crop models described for maize, these images could be analyzed using maize crop models to test how translatable is such model to the other grasses imaged here. This test allows us to assess how broad or specific the crop growth models for maize are, and if they could be used to predict the growth models of other related grasses in this study. The data obtained for both maize and sorghum can be used to test how well previous growth models of these plants predict what was collected in this study, helping validate such models. Obtaining image data for crops for a long period of time can be challenging, which could limit the amount of information available to test new methods. For this reason, the present dataset can be used in the development of new methods to estimate different plant traits.

Data and Resources

Additional Info

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Author James C. Schnable, Daniel S. Carvalho
Last Updated June 23, 2024, 17:04 (UTC)
Created June 23, 2024, 17:04 (UTC)
Citation James C. Schnable, Daniel S. Carvalho 2019. High-throughput imaging and phenotyping dataset of C4 grain crops. CyVerse Data Commons. DOI 10.25739/7n5e-9w17
Date created in discovery environment 2019-07-10 14:42:54
Date last modified in discovery environment 2020-02-20 22:05:33
identifierType DOI
publisher CyVerse Data Commons
resourceType Image data, Phenotyping, C4 Grasses