The convergence of digital twin technology and sixth-generation (6G) wireless networks presents transformative opportunities for precision agriculture through real-time remote farm operations. This research develops an integrated framework combining digital twin simulation, 6G ultra-reliable low-latency communication, and autonomous agricultural systems to enable remote farm management with minimal human intervention. The proposed architecture incorporates Internet of Things sensors, edge computing nodes, artificial intelligence algorithms, and haptic feedback mechanisms achieving latency below 1 millisecond and reliability exceeding 99.9999%. Through simulation modeling and experimental validation across three agricultural scenarios—autonomous harvesting, precision irrigation, and livestock monitoring—results demonstrate system performance improvements including 94% prediction accuracy for crop health assessment, 87% reduction in water consumption, and 76% decrease in operational costs compared to conventional farming methods. The framework addresses bandwidth requirements of 1-10 Tbps, computation processing demands, and cybersecurity vulnerabilities inherent in hyper-connected agricultural systems. Findings indicate that 6G-enabled digital twins can revolutionize agricultural productivity, sustainability, and food security while reducing environmental impacts. This research contributes novel insights bridging telecommunications engineering, agricultural science, and cyber-physical systems.