Sakai Shibusawa

Tokyo University of Agriculture and Technology

Papers

Total Citations

H-Index

About

Sakai Shibusawa is a pioneering figure in agricultural robotics and precision farming, with a focus on machine vision systems for automated fruit grading. His most cited work, "Extracting External Features of Sweet Peppers Using Machine Vision System on Mobile Fruits Grading Robot" (2012), introduces algorithms to sort color, estimate size, classify shape, detect bruises, and predict mass of sweet peppers—tested on 372 samples of the variety "California Wonder." This research, though garnering 3 citations, laid foundational groundwork for integrating robotics into post-harvest processing, emphasizing efficiency and accuracy in quality assessment. Shibusawa's contributions extend to developing mobile grading robots that enhance agricultural productivity, reducing labor dependency. His work is notable for bridging computer vision and agronomy, inspiring further studies in automated crop handling. While citation counts are modest, the practical implications of his algorithms for real-time fruit inspection underscore his impact on sustainable farming technologies. Shibusawa remains a key reference for researchers exploring machine learning applications in agriculture, particularly for small-scale farmers seeking affordable automation solutions.