AIMC Topic: Spinacia oleracea

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Integrating transformer-based machine learning with SERS technology for the analysis of hazardous pesticides in spinach.

Journal of hazardous materials Apr 3, 2024
This study introduces an innovative strategy for the rapid and accurate identification of pesticide residues in agricultural products by combining surface-enhanced Raman spectroscopy (SERS) with a state-of-the-art transformer model, termed SERSFormer...
Gold Metal Nanoparticles Spectrum Analysis, Raman Food Contamination Pesticide Residues Spinacia oleracea Silver Pesticides Machine Learning
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Development of prediction software to describe total mesophilic bacteria in spinach using a machine learning-based regression approach.

Food science and technology international = Ciencia y tecnologia de los alimentos internacional Apr 18, 2023
The purpose of this study was to create a tool for predicting the growth of total mesophilic bacteria in spinach using machine learning-based regression models such as support vector regression, decision tree regression, and Gaussian process regressi...
Machine Learning Decision Trees Food Microbiology Support Vector Machine Software Spinacia oleracea Regression Analysis Bacteria
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Spectroscopy and imaging technologies coupled with machine learning for the assessment of the microbiological spoilage associated to ready-to-eat leafy vegetables.

International journal of food microbiology Oct 29, 2021
Based on both new and previously utilized experimental data, the present study provides a comparative assessment of sensors and machine learning approaches for evaluating the microbiological spoilage of ready-to-eat leafy vegetables (baby spinach and...
Machine Learning Spectroscopy, Fourier Transform Infrared Spinacia oleracea Least-Squares Analysis Vegetables
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Predicting sensory evaluation of spinach freshness using machine learning model and digital images.

PloS one Mar 19, 2021
The visual perception of freshness is an important factor considered by consumers in the purchase of fruits and vegetables. However, panel testing when evaluating food products is time consuming and expensive. Herein, the ability of an image processi...
Sensation Spinacia oleracea Algorithms Image Processing, Computer-Assisted Models, Theoretical Support Vector Machine Neural Networks, Computer Machine Learning
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Anticancer activity of biologically synthesized silver and gold nanoparticles on mouse myoblast cancer cells and their toxicity against embryonic zebrafish.

Materials science & engineering. C, Materials for biological applications Dec 23, 2016
The aim of this study was to evaluate the anticancer activity of bioinspired silver nanoparticles (AgNPs) and gold nanoparticles (AuNPs) against mouse myoblast cancer cells (CC). Both AgNPs and AuNPs were biologically synthesized using Spinacia olera...
Cell Shape Gold Ethidium Caspases Mice Metal Nanoparticles Antineoplastic Agents Myoblasts Photoacoustic Techniques Cell Survival Cell Line, Tumor Staining and Labeling Plant Extracts Silver Spinacia oleracea Plant Leaves Animals Apoptosis Embryo, Nonmammalian Toxicity Tests Zebrafish Acridine Orange X-Ray Diffraction
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Modified Activated Carbon Prepared from Acorn Shells as a New Solid-Phase Extraction Sorbent for the Preconcentration and Determination of Trace Amounts of Nickel in Food Samples Prior to Flame Atomic Absorption Spectrometry.

Journal of AOAC International Nov 17, 2016
A new solid-phase extraction (SPE) sorbent was introduced based on acidic-modified (AM) activated carbon (AC) prepared from acorn shells of native oak trees in Kurdistan. Hydrochloric acid (15%, w/w) and nitric acid (32.5%, w/w) were used to conditio...
Spinacia oleracea Quercus Solid Phase Extraction Mentha Nickel Brassica Temperature Hydrogen-Ion Concentration Spectrophotometry, Atomic Charcoal
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