ASHS 2024 Conference

Introduction and Overview

Speaker: Kathryn Orvis
Professor
Department of Horticulture and Landscape Architecture
Purdue University
625 Ag Mall Drive
West Lafayette, IN 47907-2010

Title: Digital Agriculture and AI on Specialty Crops Production

Description: Digital agriculture is the 4th agricultural revolution and Artificial Intelligence (AI) is part of it. Currently, in the "connected agriculture"; era, many technologies have been released on the marked regarding the use of multispectral
sensors for many purposes in agriculture. This talk is going to cover information on how to use Digital Agriculture online platforms to process multispectral imagery, and how AI can be used to collect individual in-field plant data.

Speaker: Luan Pereira de Oliveira
Assistant Professor and Precision Agriculture Extension Specialist
Department of Horticulture
University of Georgia
139 Engineering Building
2329 Rainwater Road
Tifton, GA 31793

Title: Bringing the Future of AI to the Farm.
Description: In this talk, we will cover the multitude of use cases where AI can be applied in farming – from weed detection and robotics to Generative AI-based farm assistants and Virtual Reality. We go through the industry trends of applied Artificial Intelligence and think big about farm automation for the future.

Speaker: Justin Hoffman
Chief Technology Officer of AgTechLogic


Title: From Concept to Impact: The Evolution of Moss Robotics through Industry-
University Collaboration

Description: Moss Robotics' journey began with a project focused on autonomous driving technology for tree nurseries, born out of a collaboration between Carnegie Mellon University, Robotics Institute and Hale; Hine Nursery in Tennessee. In this talk, we share the story of how we discovered the real value our solution could offer to growers, and how we refined our ideas through continuous iteration. This process transformed moss robotics from a simple concept into the company it is today. We will cover the steps of our evolution, emphasizing the practical benefits of combining academic research with industry needs to innovate effectively. Additionally, we look ahead to how emerging technologies might further influence our growth and the agricultural industry as a whole, aiming for advancements in farming practices that are both technologically sophisticated and grounded in real-world applications.

Speaker: Di Hu
Founder and CEO
Moss Robotics

Title: AI-Enhanced Computer Vision for Crop Monitoring in Controlled Environment
Agriculture

Description: Controlled environment agriculture (CEA) production remains expensive due to high operation costs. Growers can reduce production costs by nurturing crops with data, however, the data is highly diverse, and growers lack the expertise to analyze this data to derive actionable insights for informed decision-making. In addition, traditional crop monitoring is carried out manually, which makes it unfeasible to collect data daily to get actionable insights for high yields. Recent advancements in sensing and computing technologies, such as AI, computer vision, edge computing, and edge-
cloud integration, have opened opportunities to develop data-driven technologies to enhance decision-making capabilities. Integrating AI and computer vision technologies has emerged as a transformative toolset that can collect real-time plant data at high spatial and temporal resolutions, pivotal in optimizing resource management and maximizing production. The CE Engineering lab delves into cutting-edge computer vision applications within CEA, focusing on various applications, including phenotyping leafy greens, yield estimation, disease monitoring, and plant spacing optimization. This presentation will explore the details of lettuce phenotyping, disease classification, strawberry fruit classification, and yield estimation. We will delve into the technical aspects of these algorithms, including image processing techniques, machine learning models, and data integration strategies. This presentation will showcase state-of-the-art deep learning approaches, including segmentation algorithms, model training, and deep classifiers. Overall, this presentation aims to provide insights into the transformative potential of computer vision in CEA, offering a glimpse into the future of data-driven and sustainable CE production.

Speaker: Azlan Zahid
Assistant Professor,
Department of Biological and Agricultural Engineering
Texas A&M AgriLife Research
Texas A&M University System
Dallas, TX 75252, USA


Panel: 30-minute panel with the above speakers, to allow time for Q&A and discussion.