aceResearch on the optimal modeling path for inversion of Pb content in rice leaves based on hyperspectral data of ground objects and machine learning and cross-scale remote sensing monitoring
Real-time and accurate monitoring of heavy metal concentrations in rice is essential for ensuring food safety and supporting the safe utilization of contaminated agricultural land. Hyperspectral technology offers advantages such as rapid, nondestructive, cost-effective, and environmentally friendly monitoring. This study developed multiple models for estimating Pb content in rice leaves, compared their performance, and identified stable modeling pathways for continuous regional monitoring using hyperspectral rem…
In contrast, the combination of Whale Optimization Algorithm (WOA) and PLS achieved the highest validation estimation accuracy (R 2 = 0.7452).
Evidence
- Peer-reviewedEnvironmental Monitoring and Assessment2026-09-23
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Truvace Impact Record TRV-2026-1188, v1: “Research on the optimal modeling path for inversion of Pb content in rice leaves based on hyperspectral data of ground objects and machine learning and cross-scale remote sensing monitoring.” Truvace, 2026-09-26. /record/TRV-2026-1188 (accessed at citation time). sha256 0a9e434cf1a2297a…
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