ArticleFoods (Basel, Switzerland)2025
Development and Prediction of a Non-Destructive Quality Index (Qi) for Stored Date Fruits Using VIS-NIR Spectroscopy and Artificial Neural Networks.
Article in Foods (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed.
- Comparative Study of Effects of Different Organic Acid Treatments on Preservation Quality of Two Bamboo Shoot Species Using PCA Comprehensive Evaluation and Quality Index Models.Foods (Basel, Switzerland) · 2026Article
- Rapid Monitoring of Storage Deterioration in Processed Coix Seeds Using Near-Infrared Spectroscopy Guided by GC-IMS.Foods (Basel, Switzerland) · 2026Article
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Authors and funding
2 authors.
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Abstract
This study proposes a novel non-destructive approach to assessing and predicting the quality of stored date fruits using a composite quality index (Qi) modeled via visible-near-infrared (VIS-NIR) spectroscopy and artificial neural networks (ANNs). Two leading cultivars, Sukkary and Khlass, were stored for 12 months using three temperature regimes (25 °C, 5 °C, and -18 °C) and five types of packaging. The samples were grouped into six moisture content categories (4.36-36.70% d.b.), and key physicochemical traits, namely moisture, pH, hardness, total soluble solids (TSSs), density, color, and microbial load, were used to construct a normalized, dimensionless Qi. Spectral data (410-990 nm) were preprocessed using second-derivative transformation and modeled using partial least squares regression (PLSR) and the ANNs. The ANNs outperformed PLSR, achieving the correlation coefficient (R
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