ArticleSensors (Basel, Switzerland)2021
Deep and Machine Learning Using SEM, FTIR, and Texture Analysis to Detect Polysaccharide in Raspberry Powders.
Article in Sensors (Basel, Switzerland), 2021. 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.
- Solvent-Free Oil-Based Extraction and Microencapsulation of Lutein from Marigold (Molecules (Basel, Switzerland) · 2026Article
- Phytochemical and Structural Portrayal of Barley and Pearl Millet Through FTIR and SEM.Food science & nutrition · 2025Article
- Evaluation of the Influence of Coating and Coating Composition on the Sorption Properties of Freeze-Dried Carrot Bars.Molecules (Basel, Switzerland) · 2025Article
- The Impact of Drying Methods on the Quality of Blanched Yellow Mealworm (Molecules (Basel, Switzerland) · 2024Article
- The Influence of Micronization on the Properties of Black Cumin Pressing Waste Material.Materials (Basel, Switzerland) · 2024Article
- Explainable AI: Machine Learning Interpretation in Blackcurrant Powders.Sensors (Basel, Switzerland) · 2024Article
- Valorization of Red Beetroot (Molecules (Basel, Switzerland) · 2024Article
- Water Effective Diffusion Coefficient in Dairy Powder Calculated by Digital Image Processing and through Machine Learning Algorithms of CLSM Micrographs.Foods (Basel, Switzerland) · 2023Article
- Effect of the Pulsed Electric Field Treatment on Physical, Chemical and Structural Changes of Vacuum Impregnated Apple Tissue in Aloe Vera Juices.Foods (Basel, Switzerland) · 2023Article
- Classification of Food Additives Using UV Spectroscopy and One-Dimensional Convolutional Neural Network.Sensors (Basel, Switzerland) · 2023Article
- Micronized Powder of Raspberry Pomace as a Source of Bioactive Compounds.Molecules (Basel, Switzerland) · 2023Article
- Texture analysis and artificial neural networks for identification of cereals-case study: wheat, barley and rape seeds.Scientific reports · 2022Article
- Guidelines for a Morphometric Analysis of Prokaryotic and Eukaryotic Cells by Scanning Electron Microscopy.Cells · 2021Review
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In the paper, an attempt was made to use methods of artificial neural networks (ANN) and Fourier transform infrared spectroscopy (FTIR) to identify raspberry powders that are different from each other in terms of the amount and the type of polysaccharide. Spectra in the absorbance function (FTIR) were prepared as well as training sets, taking into account the structure of microparticles acquired from microscopic images with Scanning Electron Microscopy (SEM). In addition to the above, Multi-Layer Perceptron Networks (MLPNs) with a set of texture descriptors (machine learning) and Convolution Neural Network (CNN) with bitmap (deep learning) were devised, which is an innovative attitude to solving this issue. The aim of the paper was to create MLPN and CNN neural models, which are characterized by a high efficiency of classification. It translates into recognizing microparticles (obtaining their homogeneity) of raspberry powders on the basis of the texture of the image pixel.
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