Material state sensing and prediction for low-damage sugarcane base cutting: Mechanisms, challenges and perspectives

Sugarcane harvesting is a key link in the sugarcane production chain, and base-cutting quality is an important factor affecting mechanized harvesting performance. Stubble damage can affect bud germination and the sustainable productivity of ratoon sugarcane. High stubble breakage, uprooting, and large fluctuations in base-cutting quality are still common during mechanized harvesting. Traditional studies have mainly focused on basecutter structural improvement, blade geometry optimization, and operating parameter matching. These studies have improved cutting quality under specific conditions, but they still cannot fully explain the internal causes of unstable stubble damage under complex field conditions. This review focuses on stubble damage during sugarcane basecutting. It reviews the definitions, assessment methods, and agronomic consequences of stubble damage, the mechanical mechanisms of base-cutting failure, the material-state basis of stalk response, and nondestructive sensing and pre-cut damage prediction. Some studies indicates that stubble breakage and uprooting result from the interaction among external mechanical loading, stalk material state, and root-soil boundary constraints. Cutter-stalk interaction, blade geometry, operating parameters, dynamic disturbance, and blade wear determined the external mechanical demand. Moisture content, biochemical composition, tissue structure, spatial heterogeneity, and mechanical properties determine the state-dependent resistance of the stalk. Root-soil constraints further affect load transfer and the transition between local fracture and global uprooting. NIRS, hyperspectral imaging, and machine vision have shown potential for sensing compositional, mechanical, and geometric traits. X-ray/micro-CT can provide high-resolution structural information for mechanism analysis and model calibration. However, most current sensing studies remain at the laboratory, offline, or post-cut stage. A validated field model for direct pre-cut prediction of stubble breakage or uprooting is still lacking. Based on these findings, this review proposes a composition, structure, mechanics, failure framework and a technical route of pre-cut sensing, state estimation, damage-risk prediction, adaptive control. These concepts provide a basis for developing low-damage, stable, and state-driven sugarcane harvesting systems.