Plant Phenotyping at crossroads – technologies, demands, networks and future challenges
Wheat phenotyping under field condition
Machine Learning Based Phenotypic Analyses for Predicting Crop Yield and Quality
Identification of regulatory variants in plants to help genome–phenome association studies
Benefits of the spatial and spectral details from ground-based hyperspectral imaging for crop monitoring
Wheat phenotyping in silico
Ulrich Schurr, Forschungszentrum Jülich, Germany
Prof. Uli studied biology at the University of Bayreuth (Germany) and gained his Ph.D in plant sciences form the same university. He then became group leader at the Botanical Institute at University of Heidelberg. He was the founding director of the Institute of Plant Sciences at Forschungszentrum Jülich (Germany) and the Institute for Phytosphere at Heinrich-Heine University Düsseldorf in 2001. Since then he held numerous positions in national and international science institutions and coordinated several major scientific programs including e.g. the Executive Board of the European Technology Platform Plants for the Future (chairman 2015-2017), the Helmholtz Program Key Technologies for the Bioeconomy (speaker) and the Bioeconomy Science Centre (BioSC; Speaker). He has initiated and coordinated important national and international program in plant phenotyping like the German Plant Phenotyping Network (DPPN), the European Plant Phenotyping Network (EPPN) and the International Plant Phenotyping Network (IPPN, Chair). Since 2016 he coordinates the ESFRI project EMPHASIS - European Infrastructure for multi-scale Plant Phenomics and Simulation for food security in a changing climate.
Frederic Baret, INRA, France
Prof. Fred received a PhD in the use of Remote sensing for crop monitoring in 1986. He is currently a research Director at INRA, leading the remote sensing team. He coordinated several National and European projects. He is involved in the development of radiative transfer models at several scales (soil, leaf, canopy) and their use for the retrieval of vegetation biophysical variables. He recently expanded his activity on high throughput phenotyping with the development of measurement systems as well as interpretation methods. He is in charge of the development of phenotyping methods in field conditions within the French Plant Phenotyping Network (PHENOME) project. This includes the application of IoTs, Phenomobiles (fully automatic robot rover) as well as the development of drone observations. He authored more than 220 research papers (h=50 from WoK).
Ji Zhou, Earlham Institute, UK/Nanjing Agricultural University, China
Dr Ji Zhou received his industry-funded PhD in Computer Science in 2011 at the University of East Anglia (UEA, Norwich) UK. Currently, he is a project leader of crop phenomics at the Biotechnology and Biological Sciences Research Council (BBSRC, UK) strategically funded Earlham Institute (EI). He is also a Senior Lecturer of Computer Vision (Hon.) in the school of computing sciences at UEA as well as a Professor of Crop Phenomics at PPRC, NAU China.
Zhou’s laboratory at EI focuses on automatic in-field and indoor phenotyping on important crops such as wheat and rice. His laboratory carries out a range of multi-scale phenotypic analyses using state-of-the-art technologies, including high-throughput image analysis, computer vision, in-field remote sensing, and machine-learning related algorithms.
Yufeng Wu, Nanjing Agricultural University, China
Prof. Wu received a PhD in Genetics in 2008 at Chinese Academy of Sciences in Beijing. His research focuses on the Bioinformatics and Epigenomics in Plants, for example, Characterization of histone modifications in rice centromere using ChIP-chip. He is now the director of Bioinformatics Centre in Nanjing Agricultural University, working on genome informatics and plant phenomics.
Tao Cheng, Nanjing Agricultural University, China
Prof. Cheng is a remote sensing specialist at the National Engineering and Technology Center (NETCIA). His academic training in Canada and the United States was in the field of hyperspectral remote sensing for vegetation dynamics with specialization in spectroscopic estimation of biophysical and biochemical parameters. After joining the NETCIA, his research interests have been focused on growth monitoring and productivity prediction for rice and wheat crops. A major part of his current work lies in: 1) developing ground- and UAV-based platforms for rapid monitoring of agronomic traits (e.g., leaf area index and nitrogen content) and early detection of crop disease; 2) transforming multispectral and hyperspectral imaging techniques in remote sensing of vegetation to field-based plant phenotyping; 3) understanding the spectral responses to crop growth in normal and stress conditions and developing novel algorithms for crop monitoring. These research lines are closely linked to growth diagnosis and regulation for precision crop cultivation purposes. He was appointed Jiangsu Distinguished Professor in 2014 and was elected to IEEE Senior Member in 2016.
Shouyang Liu, INRA, France
Shouyang Liu is a post-doc researcher in INRA, France with Fred Baret in UMT-CAPTE lab and Francois Tardieu and Pierre Martre in LEPSE lab. Now he is part time working with Fred in phenotyping center, NAU.