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Loganathan Girija, D
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Authors
Loganathan Girija, D
Usama Bin Sabir, S
Rathore, D
Khot, L.R
Mattupalli, C
Karkee, M
Loganathan Girija, D
Gorthi, S
Bhalekar, D
Khot, L.R
Keller, M
Topics
Agricultural Robotics, Automation, and Mechanization
Precision Horticulture and Specialty Crop Management
Type
Poster
Year
2026
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1. A Dual-Arm Machine-Vision-Guided Robotic System for High-Throughput Tissue Sampling in Potato Tubers

High-throughput molecular pathogen detection in potato tubers requires tissue sampling methods that are both sensitive and specific. A critical step in this workflow is the manual extraction of tissue cores, which is labor-intensive and time-consuming, limiting scalability for large-scale diagnostics. To address this challenge, this study developed a machine-vision-guided, dual-arm coordinated inline robotic system that integrates tuber picking, rotation, and tissue sampling mechanisms. In this... D. Loganathan Girija, S. Usama Bin Sabir, D. Rathore, L.R. Khot, C. Mattupalli, M. Karkee

2. Enhanced Deep Learning Framework Driven Grape Berry Temperature Estimation and 72-h Forecasting for Precision Heat Stress Management

The increasing frequency of extreme summer heat events poses a significant threat to grape production in the Pacific Northwest (PNW), U.S., and globally. Elevated temperatures can induce sunburn, accelerate organic acid degradation, and cause anthocyanin loss, ultimately reducing berry quality. Berry surface temperature (BST), which can exceed ambient air temperature by up to 15 °C, is a primary indicator of heat stress severity. However, BST dynamics are governed by complex, nonlinear thermodynamic...