ArticleFoods (Basel, Switzerland)2019
Identifying Freshness of Spinach Leaves Stored at Different Temperatures Using Hyperspectral Imaging.
Article in Foods (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- A hybrid CNN model for multi-class freshness and disease detection in local spinach varieties.BMC plant biology · 2026Article
- Article
- Hyperspectral reflectance imaging for visualizing reducing sugar content, moisture, and hollow rate in red ginseng.Heliyon · 2024Article
- Research Progress of Machine Learning in Extending and Regulating the Shelf Life of Fruits and Vegetables.Foods (Basel, Switzerland) · 2024Review
- Simultaneous determination of pigments of spinach (Food chemistry: X · 2024Article
- Quality Assessment and Ripeness Prediction of Table Grapes Using Visible-Near-Infrared Spectroscopy.Foods (Basel, Switzerland) · 2023Article
- Online Machine Vision-Based Modeling during Cantaloupe Microwave Drying Utilizing Extreme Learning Machine and Artificial Neural Network.Foods (Basel, Switzerland) · 2023Article
- Identification of Moldy Peanuts under Different Varieties and Moisture Content Using Hyperspectral Imaging and Data Augmentation Technologies.Foods (Basel, Switzerland) · 2022Article
- Advances in Machine Learning and Hyperspectral Imaging in the Food Supply Chain.Food engineering reviews · 2022Review
- Estimation of amino acid contents in maize leaves based on hyperspectral imaging.Frontiers in plant science · 2022Article
- Fast Identification of Soybean Seed Varieties Using Laser-Induced Breakdown Spectroscopy Combined With Convolutional Neural Network.Frontiers in plant science · 2021Article
- Assessment of the vigor of rice seeds by near-infrared hyperspectral imaging combined with transfer learning.RSC advances · 2020Article
- Integration of Partial Least Squares Regression and Hyperspectral Data Processing for the Nondestructive Detection of the Scaling Rate of Carp (Foods (Basel, Switzerland) · 2020Article
- Discrimination of Grape Seeds Using Laser-Induced Breakdown Spectroscopy in Combination with Region Selection and Supervised Classification Methods.Foods (Basel, Switzerland) · 2020Article
- Investigation on Data Fusion of Multisource Spectral Data for Rice Leaf Diseases Identification Using Machine Learning Methods.Frontiers in plant science · 2020Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Spinach is prone to spoilage in the course of preservation. Spinach leaves stored at different temperatures for different durations will have varying degrees of freshness. In order to monitor the freshness of spinach leaves during storage, a rapid and non-destructive method-hyperspectral imaging technology-was applied in this study. Visible near-infrared reflectance (Vis-NIR) (380-1030 nm) and near-infrared reflectance (NIR) (874-1734 nm) hyperspectral imaging systems were used. Spinach leaves preserved at different temperatures with different durations (0, 3, 6, 9 days at 4 °C and 0, 1, 2 days at 20 °C) were studied. Principal component analysis (PCA) was adopted as a qualitative analysis method. The second-order derivative spectra were utilized to select effective wavelengths. Partial least squares discriminant analysis (PLS-DA), support vector machine (SVM), and extreme learning machine (ELM) were used to build models based on full spectra and effective wavelengths. All three models achieved good results, with accuracies above 92% for both Vis-NIR spectra and NIR spectra. ELM obtained the best results, with all accuracies reaching 100%. The overall results indicate the possibility of the freshness identification of spinach preserved at different temperatures for different durations using two kinds of hyperspectral imaging systems.
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