Frank Okyere

NameFrank Okyere
Job titlePhD Student
Email addressfrank.okyere@rothamsted.ac.uk
DepartmentSustainable Soils and Crops
OfficeHarpenden

Research outputs

Modeling the spatial-spectral characteristics of plants for nutrient status identification using hyperspectral data and deep learning methods

Okyere, F., Cudjoe, D., Sadeghi-Tehran, P., Virlet, N., Riche, A. B., Castle, M., Greche, L., Simms, D., Mhada, M., Mohareb, F. and Hawkesford, M. J. 2023. Modeling the spatial-spectral characteristics of plants for nutrient status identification using hyperspectral data and deep learning methods. Frontiers in Plant Science. 14, p. 1209500. https://doi.org/10.3389/fpls.2023.1209500

Machine Learning Methods for Automatic Segmentation of Images of Field and Glasshouse Based Plants for High Throughput Phenotyping

Okyere, F., Cudjoe, D., Sadeghi-Tehran, P., Virlet, N., Riche, A. B., Castle, M., Greche, L., Mohareb, F., Simms, D. M., Mhada, M. and Hawkesford, M. J. 2023. Machine Learning Methods for Automatic Segmentation of Images of Field and Glasshouse Based Plants for High Throughput Phenotyping. Plants - Basel. 12 (10), p. 2035. https://doi.org/10.3390/plants12102035

Using proximal sensing parameters linked to the photosynthetic capacity to assess the nutritional status and yield potential in quinoa

Cudjoe, D., Okyere, F., Virlet, N., Castle, M., Buchner, P. H., Parmar, S., Sadeghi-Tehran, P., Riche, A. B., Sohail, Q., Mhada, M., Ghanem, M., Waine, T. W., Mohareb, F. and Hawkesford, M. J. 2023. Using proximal sensing parameters linked to the photosynthetic capacity to assess the nutritional status and yield potential in quinoa. Acta Horticulturae. 1360, pp. 373-379. https://doi.org/10.17660/ActaHortic.2023.1360.45

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