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R. Fernández-Beltran

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Open access Jul 2026

Training noise sensitivity analysis of default and tuned classifiers for NIR spectroscopic detection of pinto bean adulteration

The detection of fraudulent pinto bean adulteration, typically driven by the introduction of low-grade specimens with the Hard-to-Cook (HTC) defect into premium batches, is a persistent challenge in the legume industry. Near-infrared (NIR) spectroscopy combined with machine learning offers a non-destructive route for...

Raziyeh Pourdarbani, S. Sabzi, Dorrin Sotoudeh et al. · 0 citations

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