Crop phenomics is a new transdisciplinary field of research that is a critical interface between plant biology, engineering, and data sciences. Phenomics data refers to sensory data acquired from high-throughput sensing/automation equipment that are associated with crop phenotypes/traits. Crop phenotyping is a complex process as the plant phenotype results from interactions between the genetic framework, dynamically changing environment, and complex plant physiology. In recent years, phenomics technologies have challenged traditional crop phenotyping approaches, especially for efforts towards crop improvement. The strong motivation for this project comes from the need to develop unique interdisciplinary skillset and promote genuine interest among undergraduate students in this field of research for phenomics data-driven discoveries for impact on global food security. In this project, our diverse team of eight faculty mentors, actively pursuing research in topics associated with phenomics big data management research such as development of automated sensing/image processing tools, phenomics data-based visualization and hypothesis extraction tools, and phenomics data-based variety development will provide educational and outreach benefits to traditional and underrepresented undergraduate students by providing an immersive research experience for 9-10 weeks. The six major objectives defined in this project are to: (1) create a cohort-wide program offering transdisciplinary educational opportunities, (2) develop technical and research expertise, (3) develop professional and communication skills, and encourage graduate education, (4) promote networking and socialization, (5) promote diversity and broaden participation, and (6) proactively engage in project evaluation.
Background on Phenomics:
Plant breeders and scientists are working towards developing new crop varieties for various reasons such as: 1) produce crops that have better yields to address global food security; 2) have high quality produce for better health (both for human and livestock; e.g. potato varieties with vitamins and higher protein content) and consumer choice (e.g. tastier apple varieties); and 3) can be produced sustainably (with less chemical inputs and lower water consumption, for instance). Phenotyping is a key adjunct to these crop improvement processes, that allows thorough evaluation of desirable crop traits (pre- and post-harvest) such as growth rate, drought tolerance, disease resistance, etc. Sensor applications for high-throughput phenotyping or phenomics utilizes sensing, automation, and data mining tools for evaluating these phenotypes/plant traits resulting from genotype-environment interactions, which is the major subject of this research experience theme.
- Sensors in Phenomics
- Phenomics in Wheat Breeding Programs
- Intelligent Sensing for Precise and Scalable Phenomics
- Visual Exploration and Hypotheses Extraction of Phenomics Data
- Integration of Phenomics and Genomics Data
- Phenomics in Small Fruit (Berries) Research
- Phenomics in Pome Fruit (Apple, Pear) Breeding Program
In addition to research experience, activities include:
- Phenomics Data Boot Camp participation
- Field trips
- Field day participation
- WSU Summer Research Symposium participation
- Brown bag seminars
- Graduate education seminar
- Application review begins: 1 March, 2020.
- Application deadline: 15 March, 2020.
- Research experience: 28 May-1 August, 2020.
- Selection notification: 20 March-1 April, 2020.
Student support includes:
- Stipend = $4,500.
- Support for travel and housing.
- U.S. citizen or permanent resident.
- Must be enrolled in an undergraduate institution (2 or 4-year) and graduate after September 2020.
- Sophomore or higher class standing with 3.25 or higher cumulative GPA.
- Agricultural engineering, electrical engineering, agriculture, plant sciences, horticulture, biology, engineering, programming and software development, computer science, mechatronics, computer information systems, mathematics, statistics, or other related majors.
- Underrepresented students in science and engineering, and students from community colleges that do not offer research opportunities for undergraduates are strongly encouraged to apply.