ArticleFoods (Basel, Switzerland)2022
Nondestructive Testing of Pear Based on Fourier Near-Infrared Spectroscopy.
Article in Foods (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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10 citing papers in PubMed, 35 citations in OpenAlex.
- Development of a Liquid Microbial Enzyme Synergistic Fermentation Process for Strong-Aroma and Soy-Sauce-Aroma Fresh Distiller's Grains and the Evaluation of Their Nutritional Value in Pigs.Animals : an open access journal from MDPI · 2026Article
- Genetic diversity and comprehensive evaluation of physicochemical traits in Phyllanthus emblica L. for breeding and resource utilization.BMC plant biology · 2025Article
- Relationship between optical properties and internal quality of Orah Mandarins during storage.Scientific reports · 2025Article
- Quantitative Classification and Prediction of Starkrimson Pear Maturity by Near-Infrared Spectroscopy.Foods (Basel, Switzerland) · 2024Article
- A holistic visualization for quality of Chinese materia medica: Structural and metabolic visualization by magnetic resonance imaging.Journal of pharmaceutical analysis · 2024Review
- Rapid Determination of Crude Protein Content in Alfalfa Based on Fourier Transform Infrared Spectroscopy.Foods (Basel, Switzerland) · 2024Article
- Predictive Analysis of Linoleic Acid in Red Meat Employing Advanced Ensemble Models of Bayesian and CNN-Bi-LSTM Decision Layer Fusion Based Hyperspectral Imaging.Foods (Basel, Switzerland) · 2024Article
- CNN-LSTM Neural Network for Identification of Pre-Cooked Pasta Products in Different Physical States Using Infrared Spectroscopy.Sensors (Basel, Switzerland) · 2023Article
- Towards sweetness classification of orange cultivars using short-wave NIR spectroscopy.Scientific reports · 2023Article
- Prediction Models for the Content of Calcium, Boron and Potassium in the Fruit of 'Huangguan' Pears Established by Using Near-Infrared Spectroscopy.Foods (Basel, Switzerland) · 2022Article
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Authors and funding
10 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Fourier transform near-infrared (FT-NIR) spectroscopy is a nondestructive, rapid, real-time analysis of technical detection methods with an important reference value for producers and consumers. In this study, the feasibility of using FT-NIR spectroscopy for the rapid quantitative analysis and qualitative analysis of 'Zaosu' and 'Dangshansuli' pears is explored. The quantitative model was established by partial least squares (PLS) regression combined with cross-validation based on the spectral data of 340 pear fresh fruits and synchronized with the reference values determined by conventional assays. Furthermore, NIR spectroscopy combined with cluster analysis was used to identify varieties of 'Zaosu' and 'Dangshansuli'. As a result, the model developed using FT-NIR spectroscopy gave the best results for the prediction models of soluble solid content (SSC) and titratable acidity (TA) of 'Dangshansuli' (residual prediction deviation, RPD: 3.272 and 2.239), which were better than those developed for 'Zaosu' SSC and TA modeling (RPD: 1.407 and 1.471). The results also showed that the variety identification of 'Zaosu' and 'Dangshansuli' could be carried out based on FT-NIR spectroscopy, and the discrimination accuracy was 100%. Overall, FT-NIR spectroscopy is a good tool for rapid and nondestructive analysis of the internal quality and variety identification of fresh pears.
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