Journal ArticleDOI
How to predict the sugariness and hardness of melons: A near-infrared hyperspectral imaging method.
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Experimental results for the three types of melons show that PLSR produces the most accurate results.About:
This article is published in Food Chemistry.The article was published on 2017-03-01. It has received 61 citations till now. The article focuses on the topics: Hyperspectral imaging & Partial least squares regression.read more
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DeepSpectra: An end-to-end deep learning approach for quantitative spectral analysis
TL;DR: An end-to-end deep learning approach incorporated Inception module, named DeepSpectra, is presented to learn patterns from raw data to improve the model performance and shows improved results than conventional linear and nonlinear calibration approaches in most scenarios.
Journal ArticleDOI
SSC and pH for sweet assessment and maturity classification of harvested cherry fruit based on NIR hyperspectral imaging technology
Xiaoli Li,Wei Yuzhen,Jie Xu,Xuping Feng,Feiyue Wu,Zhou Ruiqing,Juan-Juan Jin,Kaiwen Xu,Xinjie Yu,Yong He +9 more
TL;DR: In this article, the relationship between soluble solids content (SSC) and pH cherry fruit of different maturity stages has been investigated using near-infrared (NIR) hyperspectral imaging technology.
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Innovative nondestructive imaging techniques for ripening and maturity of fruits – A review of recent applications
TL;DR: The contemporary imaging techniques presented in this review portray continuous productiveness as excellent quality assessment, particularly for ripening and maturity analysis tools for fruits, which hold great potentiality to replace conventional procedures.
Journal ArticleDOI
Multispectral Imaging for Plant Food Quality Analysis and Visualization.
Wen-Hao Su,Da-Wen Sun +1 more
TL;DR: A comprehensive review of the use of the multispectral sensor in the quality assessment of plant foods (such as cereals, legumes, tubers, fruits, and vegetables) is presented.
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Potential of Near-Infrared (NIR) Spectroscopy and Hyperspectral Imaging for Quality and Safety Assessment of Fruits: an Overview
Indurani Chandrasekaran,Indurani Chandrasekaran,Shubham Subrot Panigrahi,Lankapalli Ravikanth,Chandra B. Singh +4 more
TL;DR: The literature in this overview portrays the potentials of different chemometric and multivariate image analysis methods used in near-infrared spectroscopy and hyperspectral imaging, respectively, as excellent quality assessment aspects for fruits, however, further improvements are required in handling the voluminous data in industrial applications.
References
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Journal ArticleDOI
Hyperspectral imaging – an emerging process analytical tool for food quality and safety control
TL;DR: HSI equipment, image acquisition and processing are described; current limitations and likely future applications are discussed; and recent advances in the application of HSI to food safety and quality assessment are reviewed.
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Composite kernels for hyperspectral image classification
Gustau Camps-Valls,Luis Gómez-Chova,Jordi Muñoz-Marí,Joan Vila-Francés,Javier Calpe-Maravilla +4 more
TL;DR: This framework of composite kernels demonstrates enhanced classification accuracy as compared to traditional approaches that take into account the spectral information only, flexibility to balance between the spatial and spectral information in the classifier, and computational efficiency.
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Theory and application of near infrared reflectance spectroscopy in determination of food quality
Haiyan Cen,Yong He +1 more
TL;DR: In this article, the authors present an overview of the type of information that can be obtained based on some developed theory and food research of near infrared reflectance spectroscopy (NIRS), and some problems which need to be solved or investigated further are also discussed.
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Recent Advances and Applications of Hyperspectral Imaging for Fruit and Vegetable Quality Assessment
D. Lorente,Nuria Aleixos,Juan Gómez-Sanchis,Sergio Cubero,Oscar Leonardo García-Navarrete,José Blasco +5 more
TL;DR: The different technologies available to acquire the images and their use for the non-destructive inspection of the internal and external features of these products are explained, with details of the statistical techniques most commonly used for this task.
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Nonparametric weighted feature extraction for classification
Bor-Chen Kuo,David A. Landgrebe +1 more
TL;DR: The new method provides greater weight to samples near the expected decision boundary, which tends to provide for increased classification accuracy and to reduce the effect of the singularity problem.