North American Plant Phenotyping Network
The North American Plant Phenotyping Network (NAPPN): is an association of scientists and researchers in the rapidly evolving area of plant phenomics, formed as a regional partner of the International Plant Phenotyping Network (IPPN).
Vision: The field of phenomics will become so advanced that the tools that would enable researchers to analyze and quantify phenotypic data become turn-key, thus enabling plant biologists to treat phenotypic prediction as a routine component of plant biological investigation and development.
Mission: NAPPN seeks to achieve this vision by:
Accelerating the visibility and impact of advanced plant phenotyping research
Maximizing existing synergies, identify and reduce potential bottlenecks, and facilitate collaboration spanning disciplines, locations and facilities across the region and beyond
Incentivizing mutually beneficial research between public and private sectors
Promoting a framework for data standards that facilitate data access and sharing
Increasing the visibility and impact of plant phenotyping as a tool to enable plant sciences research beyond its own current research community
Facilitating the interdisciplinary training needed for effective basic and translational plant phenotyping research
Values: The NAPPN involves diverse stakeholders including, but not limited to, researchers, developers, and consumers of phenotyping technologies across all organizational dimensions. To do so, NAPPN relies on and encourages open communication and welcomes participation by individuals from diverse backgrounds, areas of study, and organization types. Members share involvement and interest in plant phenomics and are welcome from all ranks and levels of training, stature, and expertise.
NAPPN Annual Conference: Our annual conference highlights exciting scientific content, hosts the NAPPN General Assembly meeting, as well as hands-on workshops, virtual tours, and more! Scientific sessions at our conference cover topics such as Computational Plant Sciences, Artificial Intelligence and Machine Learning in Plant Phenotyping, Sensor & Systems, Engineering, Phenomics Enabled Biology, and open-source platforms and will be geared for an interdisciplinary audience of scientists. To learn more about our annual conference, visit the conference home page.