Ewa Ropelewska

Professor IO-PIB

The National Institute of Horticultural Research

Poland

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About

Professor Ewa Ropelewska is a faculty member at The National Institute of Horticultural Research in Poland. Her research focuses on the application of imaging technology and machine learning in horticulture, particularly in quality assessment and classification of fruits and vegetables. Recent publications include studies on the storage stability of date fruits and the sensory quality of freeze-dried apples, as well as innovative approaches for earthworm classification and strawberry cultivar discrimination.

Articles (20)

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2023

Collaborators (11)

nicholas watson

Professor of Artificial Intelligence in Food

University of Leeds

UNITED KINGDOM

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Dorota Konopacka

The National Institute of Horticultural Research

POLAND

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Ahmed M. Rady

University of Nottingham

UNITED KINGDOM

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Jan Piecko

Research Institute of Horticulture in Skierniewice

POLAND

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Monika Mieszczakowska

The National Institute of Horticultural Research

POLAND

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Anna Wrzodak

Research Institute of Horticulture

POLAND

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Krzysztof Rutkowski

Head of the Department

The National Institute of Horticultural Research

POLAND

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Andrzej Skwiercz

The National Institute of Horticultural Research

POLAND

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Marcin Pąśko

Research Institute of Horticulture

POLAND

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Mirosław Sobczak

POLAND

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Tadeusz Malewski

Museum and Institute of Zoology

POLAND

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Ewa Ropelewska

Research Interests

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About

Articles (20)

A Novel Tool for Biodiversity Studies: Earthworm Classification via NGS and Neural Networks

Comparison of the Sensory Quality, Image Textures and Color Parameters of Black Chokeberries Dried in a Frozen State by Simultaneous Osmo-Microwave-Vacuum Drying Using Different Osmotic Solutions

Evaluation of Storage Stability of Date Fruit (Phoenix dactylifera L.) at Two Levels of Relative Humidity Based on Selected Functional Compounds and Image Features

Impact of Prolonged Frozen Storage on ‘Mejhoul’ Date Palm Cultivar Based on Selected Qualitative Characteristics

Application of Imaging Technology and Machine Learning to Assess the Behavior of Parthenocarpic and Non-Parthenocarpic Cucumber Cultivars Under Lacto-Fermentation

The Estimation of Phenolic Compounds, Sugars, and Acids of the Cultivar and Clones of Red-Fleshed Apples Based on Image Features

Optimized feature selection using gray wolf and particle swarm algorithms for corn seed image classification

The application of image textures and physicochemical parameters for quality monitoring of freeze-dried cubes and slices of red-fleshed apples

Relationships Between Chemical Properties, Color Parameters, and Image Features of New Clones of Apples (Malus domestica L.) from Ecological Cultivation

Nondestructive discrimination of advanced clones and cultivars of strawberry using an innovative approach involving image analysis and machine learning

The influence of natural preparations on the chemical composition, flesh structure and sensory quality of pepper fruit in organic greenhouse cultivation

Apricot Stone Classification Using Image Analysis and Machine Learning

The innovative approach to the assessment of differences in image textures between windfall apple samples dried using non-thermal and thermal techniques without and with ultrasound pretreatment

The classification of leek seeds based on fluorescence spectroscopic data using machine learning

The application of fluorescence spectroscopy and machine learning as non-destructive approach to distinguish two different varieties of greenhouse tomatoes

Non-destructive discrimination of vacuum-dried banana using image processing operation and machine learning approach

Distinguishing Cyst Nematode Species Using Image Textures and Artificial Neural Networks

Distinguishing Seed Cultivars of Quince (<i>Cydonia oblonga</i> Mill.) Using Models Based on Image Textures Built Using Traditional Machine Learning Algorithms

The Estimation of Chemical Properties of Pepper Treated with Natural Fertilizers Based on Image Texture Parameters

Rapid Detection of Changes in Image Textures of Carrots Caused by Freeze-Drying using Image Processing Techniques and Machine Learning Algorithms

Collaborators (11)

nicholas watson

Dorota Konopacka

Ahmed M. Rady

Jan Piecko

Monika Mieszczakowska

Anna Wrzodak

Krzysztof Rutkowski

Andrzej Skwiercz

Marcin Pąśko

Mirosław Sobczak

Tadeusz Malewski

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