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Outputs (13)

Integrating phenotyping and modelling approaches StomaGAN: improving image-based analysis of stomata through generative adversarial networks (2025)
Journal Article
Gibbs, J. A., & Gibbs, A. J. (2025). Integrating phenotyping and modelling approaches StomaGAN: improving image-based analysis of stomata through generative adversarial networks. in silico Plants, 7(1), Article diaf002. https://doi.org/10.1093/insilicoplants/diaf002

Stomata regulate gas exchange between plants and the atmosphere, but analysing their morphology is challenging due to anatomical variability and artifacts during image acquisition. Deep learning (DL) can address these challenges but often requires la... Read More about Integrating phenotyping and modelling approaches StomaGAN: improving image-based analysis of stomata through generative adversarial networks.

Application of deep learning for the analysis of stomata: a review of current methods and future directions (2024)
Journal Article
Gibbs, J. A., & Burgess, A. J. (2024). Application of deep learning for the analysis of stomata: a review of current methods and future directions. Journal of Experimental Botany, 75(21), 6704-6718. https://doi.org/10.1093/jxb/erae207

Plant physiology and metabolism relies on the function of stomata, structures on the surface of above ground organs, which facilitate the exchange of gases with the atmosphere. The morphology of the guard cells and corresponding pore which make up th... Read More about Application of deep learning for the analysis of stomata: a review of current methods and future directions.

A Deep Learning Method for Fully Automatic Stomatal Morphometry and Maximal Conductance Estimation (2021)
Journal Article
Gibbs, J. A., Mcausland, L., Robles-Zazueta, C. A., Murchie, E. H., & Burgess, A. J. (2021). A Deep Learning Method for Fully Automatic Stomatal Morphometry and Maximal Conductance Estimation. Frontiers in Plant Science, 12, Article 780180. https://doi.org/10.3389/fpls.2021.780180

Stomata are integral to plant performance, enabling the exchange of gases between the atmosphere and the plant. The anatomy of stomata influences conductance properties with the maximal conductance rate, gsmax, calculated from density and size. Howev... Read More about A Deep Learning Method for Fully Automatic Stomatal Morphometry and Maximal Conductance Estimation.

A canopy conundrum: can wind-induced movement help to increase crop productivity by relieving photosynthetic limitations? (2019)
Journal Article
Burgess, A. J., Gibbs, J. A., & Murchie, E. H. (2019). A canopy conundrum: can wind-induced movement help to increase crop productivity by relieving photosynthetic limitations?. Journal of Experimental Botany, 70(9), 2371-2380. https://doi.org/10.1093/jxb/ery424

Wind-induced movement is a ubiquitous occurrence for all plants grown in natural or agricultural settings and in the context of high, damaging wind speeds it has been well studied. However, the impact of lower wind speeds (that do not cause any damag... Read More about A canopy conundrum: can wind-induced movement help to increase crop productivity by relieving photosynthetic limitations?.

Image-based 3D canopy reconstruction to determine potential productivity in complex multi-species crop systems (2017)
Journal Article
Burgess, A. J., Retkute, R., Pound, M. P., Mayes, S., & Murchie, E. H. (2017). Image-based 3D canopy reconstruction to determine potential productivity in complex multi-species crop systems. Annals of Botany, 119(4), 517-532. https://doi.org/10.1093/aob/mcw242

Background and Aims: Intercropping systems contain two or more species simultaneously in close proximity. Due to contrasting features of the component crops, quantification of the light environment and photosynthetic productivity is extremely difficu... Read More about Image-based 3D canopy reconstruction to determine potential productivity in complex multi-species crop systems.