Dr. Sindhuja Sankaran Phenomics Lab
FACT: Research Experience for Undergraduates on Phenomics Big Data Management
Some of the skills developed in this research experience (image processing, data processing, genomics/phenomics, machine learning, etc.) are relevant to the medical field as well.
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 is 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 toward crop improvement. The strong motivation for this project comes from the need to develop a 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 the development of automated sensing/image processing tools, phenomics data-based visualization, 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 about 9 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 products 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 fewer 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 utilize 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.
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 deadline: OPEN UNTIL FILLED
- Application review begins: 15 March 2023
- Selection notification: 20 March-15 April 2023
- Tentative general program period: 1 June -4 August 2022 (start date will be adapted to accommodate students from the semester, quarter, and trimester systems)
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 2024.
- Freshman or higher class standing with a decent 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.
USDA-NIFA REEU Project
- Integration of Phenomics and Genomics Data
- Intelligent Sensing for Precise and Scalable Phenomics
- Phenomics in Wheat Breeding Programs
- Phenomics in Pome Fruit (Apple, Pear) Breeding Program
- Phenomics in Small Fruit (Berries) Research
- Sensors in Phenomics
- Phenomics using Robotic Systems in Legume Breeding Program