Non Technical Summary
The project titled "Building AI/ML Capacity for Digital Agriculture and Plant Phenotyping Technologies Research, Education, and Extension at FAMU" has primary objectives that encompass groundbreaking research, technology dissemination, educational enrichment, and community engagement. In collaboration with Purdue and the UNL, the project aligns with the CBG's program's major goals.Objective 1 focuses on adapting cutting-edge plant phenotyping technology into an affordable tool for muscadine vineyards. This innovation will expedite grape leaf diseases identification, subsequently deploying AI-driven models for disease detection, led by renowned experts from Purdue and FAMU. Objective 2 revolves around establishing a digital agriculture IoT pilot, integrating advanced irrigation scheduling and disease sensing in muscadine vineyards. Spearheaded by UNL and FAMU, this project will demonstrate precision water management and disease monitoring. Objective 3 entails curriculum enhancement and experiential learning for minority African American students in AI/ML applications. By fostering expertise in precision agriculture, the project aims to attract, train, and retain diverse talent in the Agricultural Engineering field. Objective 4 is dedicated to promoting AI/ML technologies among underserved farmers and stakeholders through innovative Extension programs. A long-term showcase facility will serve as a hub for engaging outreach activities, linking research with events like the FAMU Grape Harvest Festival.This project aligns seamlessly with the CBG program's goals: diversifying the agricultural sciences workforce, fostering collaborations among institutions, and elevating the quality of FAMU research, education, and extension. By combining AI/ML advancements with agriculture, the project transcends disciplines, fostering an inclusive environment of learning, innovation, and outreach for sustainable agriculture.

Classification

Knowledge Area (KA)	Subject of Investigation (SOI)	Field of Science (FOS)	Percent
402	1139	2020	60%
111	0210	3020	40%

Knowledge Area
111 - Conservation and Efficient Use of Water; 402 - Engineering Systems and Equipment;

Subject Of Investigation
0210 - Water resources; 1139 - Grapes, general/other;

Field Of Science
2020 - Engineering; 3020 - Education;

Goals / Objectives
To build AI/ML capacity for digital agriculture and plant phenotyping technologies research, education, and extension at FAMU.

Project Methods
Procedures for accomplishing objective 1:(1) Determine the diseases-specific signature bands (VIP spectral bands) for disease signals by analyzing high-resolution hyperspectral images of single grape leaves. (2)Develop a "Smartphone-Plus" low-cost and easy-to-deploy handheld multispectral scanner for Muscadine grape leaves. (3)Deploy and test the vineyard-ready disease detection multispectral tool.Procedures for accomplishing objective 2: (1)Deploy Internet of Things (IoT) sensors with network communications; (2)Build an advanced drip irrigation scheduling system for Muscadine vineyards.Procedures for Accomplishing Objective 3: (1) Curriculum Assessment and Enhancement; (2) Continuation of Experiential Learning Programs and Research Internships; (3) Student Recruitment and Engagement; (4) Monitoring, Support, Feedback, and Continuous Improvement.Procedures for Accomplishing Objective 4: (1) Establish FAMU Viticulture Center as a long-term pilot showcase facility that serves as a physical space to demonstrate AI/ML technologies and practices. (2) Collaboration with Extension Partners; (3) Continuous Assessment and Feedback.