Latifa Greche

Name	Latifa Greche
Job title	Phenotyping Computer Vision Scientist
Email address	latifa.greche@rothamsted.ac.uk
Department	Sustainable Soils and Crops
Office	Harpenden

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Research outputs

Hyperspectral imaging for phenotyping plant drought stress and nitrogen interactions using multivariate modeling and machine learning techniques in wheat

Okyere, F., Cudjoe, D., Virlet, N., Castle, M., Riche, A. B., Greche, L., Mohareb, F., Simms, D., Mhada, M. and Hawkesford, M. J. 2024. Hyperspectral imaging for phenotyping plant drought stress and nitrogen interactions using multivariate modeling and machine learning techniques in wheat. Remote Sensing. 16 (18), p. 3446. https://doi.org/10.3390/rs16183446

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