Near-infrared spectroscopy for moisture content prediction in soil-mixed woody biomass
2026 · Scientific Reports
저자
Bat-Uchral BATJARGAL, Minjee Kang, Youngmin Cho, Sangwoo Park, Sung‐Wook Hwang, 곽효원 (Hyo Won Kwak), I. G. Choi, Hwanmyeong Yeo
연구주제
Spectroscopy and Chemometric Analyses
NTIS 과학기술표준분류
에너지/자원만에너지·환경·원자력 확장
지원 과제·AI 키워드로 잡을 근거가 없어 분류하지 않았다.
AI 연구 키워드·방법
biomass moisture content logging residue soil contamination woody biomass
키워드 (OpenAlex)
near-infrared spectroscopy moisture content prediction woody biomass logging residues soil contamination non-destructive measurement partial least squares regression
초록
Accurate measurement of moisture content (MC) in woody biomass is essential for preventing biological degradation during storage and transport, particularly because mineral soil contamination commonly occurs during harvesting. This study evaluated the feasibility of Near-Infrared (NIR) spectroscopy (870 to 2500 nm) as a rapid, non-destructive alternative to oven-drying for quantifying the MC of soil-mixed woody biomass. To reflect field variability, 24 oven-dried samples were reconditioned to obtain a broad MC range (3 to 16%, dry basis). Two preprocessing techniques, Standard Normal Variate (SNV) transformation and Savitzky-Golay (SG) second-derivative filtering, were applied to improve spectral quality and model robustness. The combined SNV + SG preprocessing, integrated with Partial Least Squares Regression (PLSR), yielded the highest accuracy. For logging residues, the optimized mode…
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교수 1
연구주제 1
Spectroscopy and Chemometric Analyses