Shaochun Ma

China Agricultural University, Henan University of Science and Technology

Papers

Total Citations

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About

Shaochun Ma is a researcher working at the intersection of agricultural engineering, robotics, and computer vision, with a focus on automating the harvesting of crops such as apples and sugarcane. His work addresses some of the most persistent challenges in agricultural automation, including the mechanical damage caused during harvesting and the accurate detection of crop features in complex field environments. In his 2016 study on apple bruising responses during impact, Ma investigated the physical vulnerabilities of fresh market apples during mechanized handling — a critical barrier to the commercial adoption of bulk harvesting systems. This research, which has garnered 12 citations, contributed foundational insights into improving the gentleness and efficiency of automated apple harvesting machinery. More recently, his 2025 work on sugarcane stalk node detection leverages an improved YOLOv8 deep learning model deployed on edge devices, tackling real-world challenges such as occlusion and variable lighting in field conditions. Already accumulating 3 citations shortly after publication, this work signals Ma's growing contributions to precision agriculture and intelligent harvesting systems. Together, his research reflects a sustained commitment to bridging the gap between agricultural robotics and practical, field-ready solutions.