Inseop Jang, a Ph.D. candidate in the Department of Agricultural Machinery Engineering at Jeonbuk National University (JBNU) (supervisor: Yongjin Jo), presented research showing that the spectroscopic characteristics of visible light can be used to predict paddy soil composition, and won the "Best Poster Presentation Award" in the poster presentation category at the 2026 Spring Conference of the Korean Society of Agricultural Machinery held recently.

At the conference, Jang presented research results in the field of precision agricultural machinery systems under the title "Vis–NIR Spectroscopy-Based Prediction of Paddy Soil Composition and Evaluation of Decision Support for Fertilizer Prescription."

This study designed a model to predict the chemical properties of paddy soil using the visible–near infrared (Vis–NIR) spectroscopic characteristics of soil and evaluated the potential for decision-support in fertilizer prescription based on the predicted soil chemical component values.

In particular, the study confirmed meaningful model performance in predicting soil organic matter and available silica, which are major variables in fertilizer prescription formulas for paddy rice. The fertilizer prescription decision-support system based on these predictions demonstrated a certain degree of consistency, suggesting its potential use as a field-based precision agriculture decision-support technology.

Jang said, "This award was made possible by my supervisor's generous guidance and the help of the laboratory members who conducted the research with me. I am deeply grateful to everyone who assisted." He added, "Going forward, I plan to develop this into an on-site decision-support technology that takes into account the driving and working environments of agricultural machinery to contribute to the realization of precision agriculture."