AIMC Topic: Fruit

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Foodomics approaches: New insights in phenolic compounds analysis.

Food research international (Ottawa, Ont.) Mar 13, 2025
Fruits, vegetables, and plant-based foods contain several bioactive substances such as phenolic compounds (PCs), that are plant secondary metabolites with attributed health properties. The study of the metabolic pathways of PCs, including those relat...
Fruit Vegetables Metabolomics Phenols Proteomics Food Analysis
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Online assessment of soluble solids content in strawberries using a developed Vis/NIR spectroscopy system with a hanging grasper.

Food chemistry Mar 7, 2025
Online detection of internal quality of strawberries presents challenges particularly concerning fruit damage, detection accuracy, and processing efficiency. This study explores the feasibility of using Vis/NIRS for online detection of SSC in strawbe...
Spectroscopy, Near-Infrared Fragaria Fruit
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Optimization of enzyme-ultrasound assisted extraction from mulberries anthocyanins based on response surface methodology and deep neural networks and analysis of in vitro antioxidant activities.

Food chemistry Mar 5, 2025
This study used Xinjiang native "medicinal and food dual-use" resource mulberries as raw material, and optimized the extraction process of mulberries anthocyanins by enzyme-ultrasound-assistance through the establishment of a response surface model (...
Anthocyanins Fruit Antioxidants Plant Extracts Ultrasonic Waves Neural Networks, Computer Ultrasonics Morus Chemical Fractionation Polygalacturonase
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GPC-YOLO: An Improved Lightweight YOLOv8n Network for the Detection of Tomato Maturity in Unstructured Natural Environments.

Sensors (Basel, Switzerland) Feb 28, 2025
Effective fruit identification and maturity detection are important for harvesting and managing tomatoes. Current deep learning detection algorithms typically demand significant computational resources and memory. Detecting severely stacked and obscu...
Fruit Deep Learning Neural Networks, Computer Solanum lycopersicum Algorithms
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Modelling of pome fruit pollen performance using machine learning.

Scientific reports Feb 26, 2025
Agriculture, particularly fruit production, is considered a crucial industry with a significant economic impact in many countries. Extreme fluctuations in air temperature can negatively affect the flowering periods of fruit species. Therefore, it is ...
Neural Networks, Computer Machine Learning Germination Fruit Temperature Pollen Tube Citrus Pollen
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Multilayered visual metabolomics analysis framework for enhanced exploration of functional components in wolfberry.

Food chemistry Feb 25, 2025
Wolfberry, regarded as a nutritious fruit, has garnered significant attention in the food industry due to potential health benefits. However, the tissue-specific distribution and dynamic accumulation patterns of nutritional metabolites such as flavon...
Lycium Metabolomics Metabolic Networks and Pathways Flavonoids Fruit
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Deep learning combined Monte Carlo simulation reveal the fundamental light propagation in apple puree: Monitoring the quality changes from different cultivar, storage period and heating duration.

Food research international (Ottawa, Ont.) Feb 21, 2025
This work explored the light propagation of purees from a large variability of apple cultivar, storage period and heating duration based on their optical absorption (μ) and reduced scattering (μ') properties at 900-1650 nm, in order to better monitor...
Malus Food Storage Hot Temperature Monte Carlo Method Neural Networks, Computer Fruit Deep Learning Rheology Light Viscosity
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Application of deep learning for fruit defect recognition in Psidium guajava L.

Scientific reports Feb 20, 2025
Psidium guajava L. is an important tropical and subtropical fruit. Due to its geographical location and suitable climate, Taiwan produces Psidium guajava L. all year round. Quality standardization is therefore a crucial issue. The primary objective w...
Plant Diseases Psidium Fruit Image Processing, Computer-Assisted Taiwan Deep Learning
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Rapid detection and quantitative analysis of thiram in fruits using a shape-adaptable flexible SERS substrate combined with deep learning.

Analytical methods : advancing methods and applications Feb 20, 2025
Ensuring food safety necessitates rapid identification of pesticide residues on fruits. Herein, we developed a shape-adaptable flexible surface-enhanced Raman scattering (SERS) substrate, combined with a deep learning algorithm, to quickly detect and...
Silver Solanum lycopersicum Spectrum Analysis, Raman Metal Nanoparticles Pesticide Residues Blueberry Plants Thiram Fruit Dimethylpolysiloxanes Neural Networks, Computer Reproducibility of Results Deep Learning
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Exploring a universal model for predicting blueberry soluble solids content based on hyperspectral imaging and transfer learning to address spatial heterogeneity challenge.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Feb 18, 2025
Accurate assessment of soluble solid content (SSC) in blueberries is crucial for quality evaluation. However, in real production lines, blueberries are usually in random placement and the biological heterogeneity of blueberry parts can lead to spectr...
Fruit Machine Learning Blueberry Plants Hyperspectral Imaging Solubility
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