During the last decade, plant phenomics has grown enormously as a research field in agriculture. With incredible technological advancements in computer vision tools, plant phenomics has found many applications, including, for instance, plant species recognition, plant stress quantification, and crop yield prediction. These various applications of plant phenomics have evolved into multiple specialized niches involving national, international, and multi-disciplinary experts (e.g., plant physiologist, breeders, engineers, informatics, etc.). In the meantime, plant phenomics is increasingly accessible to a larger number of researchers worldwide thanks to the introduction of new, cost-effective setups, adaptable phenotyping platforms, and the emergence of open-source image processing software.
With the growing interest in plant phenomics, a unique platform where experts and novices can easily connect and exchange knowledge and resources are a priority. Fostering communication and cooperation among different stakeholders as well as promoting the interdisciplinary training required for effective plant phenotyping research are among the main purposes of our group.
This group is a platform imagined as an interactive “ metabolic network ”, where the nodes represent the different areas of plant phenomics applications, along with their sub-communities of experts. The main purpose is to provide all the knowledge essential to plan and start your own project of plant phenomics, making phenomics easy for everybody.
This platform will contribute to the goals of Digital Agriculture:
Bringing together a broad network of experts to share information on data and data science-related projects, collaborations, tools, practices, and discoveries.
Building partnerships and resources that address emerging issues and discuss challenges and opportunities in agriculture using novel approaches from diverse disciplines.
An online and free workshops where invited specialists will introduce the different applications and approaches in plant phenomics. The main focus of the proposed series of workshops, called “Fridays Hands-On Workshop Series,” will be data management and analysis - often the most challenging part of digital phenotyping. Each workshop will include a short theoretical introduction followed by practical data analysis, where the instructors will guide the audience through available and open-source data, tools, and codes.
|Filipe Matias||18/Sep||FIELDimageR pipeline: Image analyses applied to plant breeding|
|Mitchell Feldmann||25/Sep||Quantizing and Quantifying Fruit and Leaf Shape in the Latent Space Using R|
|Chenyong Miao||02/Oct||Conducting semantic segmentation on plant hyperspectral images using Python scikit-learn machine learning library|
|Ana Maria Heilman, Salvador Gezan, Johan Aparicio, Didier Murillo||09/Oct||Mr.Bean: An R-Shiny Web Application for the Analysis of Plant Breeding Experiments|
|India Johnson||16/Oct||Getting Started with WebODM: An Open-Source Solution to Your Mapping Problems|
|Malia Gehan, Haley Schuhl, Noah Fahlgren||23/Oct||An introduction to image analysis workflows with PlantCV|
|Henri Chung||30/Oct||Introduction to Tidymodels|
|Yufeng Ge||06/Nov||Leaf-level hyperspectral reflectance to rapidly estimate plant chemical traits|
|Kelly Robbins & Nicolas Morales||13/Nov||Getting started with ImageBreed: Managing and storing drone imagery|
Preparing for the next workshop:
6) An introduction to image analysis workflows with PlantCV
PhenomeForce Slack Channel is a single place for our community to share messages, tools, pipelines, and files. All main areas of plant phenotyping are being covered by specialists enthusiastic to share their knowledge. If you are interested to be part of this group, please send a message to email@example.com.