ArticleFoods (Basel, Switzerland)2025
Vis/NIR Spectroscopy and Vis/NIR Hyperspectral Imaging for Non-Destructive Monitoring of Apricot Fruit Internal Quality with Machine Learning.
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 13 papers.
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Who cites it
13 citing papers in PubMed.
- Postharvest Fruit Grading Technologies and Equipment: A Review.Foods (Basel, Switzerland) · 2026Review
- Tri-Band Vis-NIR Spectroscopy with Color Residual-Variance Gated Attention Fusion for Rapid Assessment of Hongmeiren (Foods (Basel, Switzerland) · 2026Article
- Interpretable Spectral Evidence Learning from Vis/NIR Imaging for Non-Destructive Authentication of Herbal Medicines.Molecules (Basel, Switzerland) · 2026Article
- Next-Generation Harvester Technologies: Synergizing Smart Grading and Biomechanical Damage Control in Mechanized Tomato Production.Sensors (Basel, Switzerland) · 2026Review
- Effect of Glycine Betaine on Chilling Injury in Eggplant Peel Revealed by FTIR Spectroscopy.Foods (Basel, Switzerland) · 2026Article
- Effect of Temperature on the Drying Kinetics of Caturra Coffee: Correlation with Hyperspectral Imaging and Sensory Quality.Foods (Basel, Switzerland) · 2026Article
- Advanced Spectroscopic, Imaging, and Nanotechnology Tools for Diagnosing Fungal Diseases in Fruits.Food science & nutrition · 2026Review
- Study on the effect of moisture content on the spectral detection of soluble solids in apricot.Scientific reports · 2026Article
- Multivariate Quantitative Prediction of Soluble Solids Content, Moisture Content, and Fruit Firmness in 'Dinosaur Egg' Apricot Plum via Near-Infrared Spectroscopy with Cross-Parameter Feature Fusion and SHapley Additive exPlanations-Based Optimization.Foods (Basel, Switzerland) · 2025Article
- Insights of freshness phenotype detection for postharvest fruit and vegetables.Plant phenomics (Washington, D.C.) · 2025Review
- Prediction of Key Quality Parameters in Hot Air-Dried Jujubes Based on Hyperspectral Imaging.Foods (Basel, Switzerland) · 2025Article
- Prediction of Total Soluble Solids in Apricot Using Adaptive Boosting Ensemble Model Combined with NIR and High-Frequency UVE-Selected Variables.Molecules (Basel, Switzerland) · 2025Article
- From data to decisions: a paradigm shift in fruit agriculture through the integration of multi-omics, modern phenotyping, and cutting-edge bioinformatic tools.Frontiers in plant science · 2025Review
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The fruit supply chain requires simple, non-destructive, and fast tools for quality evaluation both in the field and during the post-harvest phase. In this study, a portable visible and near-infrared (Vis/NIR) spectrophotometer and a portable Vis/NIR hyperspectral imaging (HSI) device were tested to highlight genetic differences among apricot cultivars, and to develop multi-cultivar and multi-year models for the most important marketable attributes (total soluble solids, TSS; titratable acidity, TA; dry matter, DM). To do this, the fruits of seventeen cultivars from a single experimental orchard harvested at the commercial maturity stage were considered. Spectral data emphasized genetic similarities and differences among the cultivars, capturing changes in the pigment content and macro components of the apricot samples. In recent years, machine learning techniques, such as artificial neural networks (ANNs), have been successfully applied to more efficiently extract valuable information from spectral data and to accurately predict quality traits. In this study, prediction models were developed based on a multilayer perceptron artificial neural network (ANN-MLP) combined with the Levenberg-Marquardt learning algorithm. Regarding the Vis/NIR spectrophotometer dataset, good predictive performances were achieved for TSS (R
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