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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

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…

By the Truvace desk1 min read1 sourcePeer-reviewedTRV-2026-1188· cite & verify
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
COAMPS modeled surface layer refractivity in the Roughness and Evaporation Duct experiment 2001 by Newton, D. Adam. Public domain

In brief

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.

The results indicated that the combination of feature band selection algorithms and modeling methods substantially affected model performance. In contrast, the combination of Whale Optimization Algorithm (WOA) and PLS achieved the highest validation estimation accuracy (R 2 = 0.7452).

Main points

  1. 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.
  2. Hyperspectral technology offers advantages such as rapid, nondestructive, cost-effective, and environmentally friendly monitoring.
  3. 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 remote sensing data.

The gain

In contrast, the combination of Whale Optimization Algorithm (WOA) and PLS achieved the highest validation estimation accuracy (R 2 = 0.7452).

The rundown

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 remote sensing data. A meta-analysis was conducted to assess how different spectral preprocessing methods and modeling strategies affect model performance.

Sources

  1. Peer-reviewedEnvironmental Monitoring and Assessment2026-09-23

The debate