New Mexico State University

Awards Issued Prior to January 20, 2025, Were Funded Under Previous Administrations and May Not Reflect the Priorities and Policies of the Current Administration. the Long-term Goal of the Project Is to Achieve Advanced Technologies for Establishing Robot-enabled Smart, Sustainable, and Eco-friendly Farming Using a Team of Cooperative Robots With a High Level of Autonomy. the Envisioned Multi-robot Team Will Carry Out Various Agricultural Tasks During the Planting, Cultivating, and Harvesting Phases to Sustainably Enhance Productivity. Water Scarcity Is a Major Problem for Crop Production Worldwide, Including in the Southwestern United States, and Growers Are Increasingly Using Groundwater for Agriculture in Southern New Mexico. Particularly, Chile Pepper, as the Signature Crop of New Mexico State, Has Significantly Suffered From Climatic Change, Long-term Drought, Labor Shortage, and the International Competitive Market That Has Led to a Huge Reduction in Production and Negative Economic Impact on the Local Farmers. Robot-enabled Precision Farming and Gene Editing Can Offer Important Tools and Approaches for Addressing These Issues by Breeding Disease Resistance, Drought Tolerance, and Mechanized Harvesting Efficient Crops With More Water-use Efficiency and Productivity While Managing Irrigation and Soil Quality to Sustain Agricultural Productivity. However, These Data-driven Approaches Require a Continuous and Significantly Large Amount of Data to Be Effective. These Requirements Create Manual Data Collection Challenges Due to Its Labor-intensive, Error-prone, and Costly Nature. Robots and Autonomous Systems Have Been Steadily Integrated Into Farming Systems for Other Crops, Enabling Automated and Intelligent Means to Address Challenges and Problems Such as the Increasing Need for Huge Data-collection and Monitoring Crop Health for Higher Yield Production, Which Can Save the Man-hour, Reduce Errors, and Be Cost-effective. Data-driven Precision Farming Can Be Efficiently and Effectively Carried Out Using a Team of Robots With Multi-modal Sensing to Address These Issues. This Approach Provides Irrigation and Soil Quality Management Based on Soil Moisture, Nutrition Level, and Crop Water Use, Which Will Help Find the Optimal Irrigation Time and Amount, Resulting in Higher Productivity and Quality.