Field Scanalyzer - Publications List

    • Sadeghi-Tehran, P., Virlet, N., Ampe, E. M., Reyns, P. and Hawkesford, M. J. 2019. DeepCount: In-Field Automatic Quantification of Wheat Spikes Using Simple Linear Iterative Clustering and Deep Convolutional Neural Networks. Frontiers in Plant Science. 10, p. 1176. https://doi.org/10.3389/fpls.2019.01176

    • Lyra, D. H., Virlet, N., Sadeghi-Tehran, P., Hassall, K. L., Wingen, L. U., Orford, S., Griffiths, S., Hawkesford, M. J. and Slavov, G. 2020. Functional QTL mapping and genomic prediction of canopy height in wheat measured using a robotic field phenotyping platform. Journal of Experimental Botany. p. erz545. https://doi.org/10.1093/jxb/erz545

    • Holman, F. H., Riche, A. B., Castle, M., Wooster, M. J. and Hawkesford, M. J. 2019. Radiometric calibration of ‘Commercial off the shelf’ cameras for UAV-based high-resolution temporal phenotyping of reflectance and NDVI. Remote Sensing. 11 (14), p. 1657. https://doi.org/10.3390/rs11141657

    • Blanchy, G., Virlet, N., Sadeghi-Tehran, P., Watts, C. W., Hawkesford, M. J., Whalley, W. R. and Binley, A. 2020. Time-intensive geoelectrical monitoring under winter wheat . Near Surface Geophysics. https://doi.org/10.1002/nsg.12107

    • Sadeghi-Tehran, P., Virlet, N., Sabermanesh, K. and Hawkesford, M. J. 2017. Multi-feature machine learning model for automatic segmentation of green fractional vegetation cover for high-throughput field phenotyping. Plant Methods. 13 (103), pp. 1-16. https://doi.org/10.1186/s13007-017-0253-8

    • Holman, F. H., Riche, A. B., Michalski, A., Castle, M., Wooster, M. J. and Hawkesford, M. J. 2016. High throughput field phenotyping of wheat plant height and growth rate in field plot trials using UAV based remote sensing. Remote Sensing. 8 (12), p. 1031. https://doi.org/10.3390/rs8121031

    • Sadeghi-Tehran, P., Angelov, P., Virlet, N. and Hawkesford, M. J. 2019. Scalable Database Indexing and Fast Image Retrieval Based on Deep Learning and Hierarchically Nested Structure Applied to Remote Sensing and Plant Biology. Journal of Imaging. 5 (3), p. 33. https://doi.org/10.3390/jimaging5030033

    • Virlet, N., Sabermanesh, K., Sadeghi-Tehran, P., Hawkesford, M. J., Field Scanalyzer: An automated robotic field phenotyping platform for detailed crop monitoring. Functional Plant Biology 44.1 (2017): 143-153. DOI: http://dx.doi.org/10.1071/FP16163

    • Sadeghi-Tehran, P., Sabermanesh, K., Virlet, N. and Hawkesford, M. J. 2017. Automated method to determine two critical growth stages of wheat: heading and flowering. . Frontiers in Plant Science. 8 (252). DOI: https://doi.org/10.3389/fpls.2017.00252

  • Xiuliang Jin ; Pablo Zarco-Tejada ; U Schmidhalter ; Matthew P. Reynolds ; Malcolm J. Hawkesford ; Rajeev K. Varshney ; Tao Yang ; Chengwei Nie ; Zhenhai Li ; Bo Ming ; Yonggui Xiao ; Yongdun Xie ; Shaokun Li (2020) High-throughput estimation of crop traits: A review of ground and aerial phenotyping platforms, in IEEE Geoscience and Remote Sensing Magazine, DOI: https://doi.org/10.1109/MGRS.2020.2998816