Trends in quality assessment and drying methods used for fruits and vegetables

Reis, Felipe Richter; Marques, Caroline; Moraes, Ana Carolina Sales de; Masson, Maria Lúcia

doi:10.1016/j.foodcont.2022.109254

Cited by 26 publications

(12 citation statements)

References 47 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Machine learning using algorithms has provided an innovative approach to effectively analyze multidimensional data. Considering the analysis of raw materials and food products, machine learning algorithms can effectively identify important attributes (parameters) of food that can affect its quality [ 19 , 20 , 21 , 22 , 23 ]. An interesting tool is ensembles of classifiers due to their optimal estimation of data as a result of product classification [ 24 , 25 , 26 ].…”

Section: Introductionmentioning

confidence: 99%

Efficiency of Identification of Blackcurrant Powders Using Classifier Ensembles

Przybył,

Walkowiak,

Kowalczewski

2024

Foods

View full text Add to dashboard Cite

In the modern times of technological development, it is important to select adequate methods to support various food and industrial problems, including innovative techniques with the help of artificial intelligence (AI). Effective analysis and the speed of algorithm implementation are key points in assessing the quality of food products. Non-invasive solutions are being sought to achieve high accuracy in the classification and evaluation of various food products. This paper presents various machine learning algorithm architectures to evaluate the efficiency of identifying blackcurrant powders (i.e., blackcurrant concentrate with a density of 67 °Brix and a color coefficient of 2.352 (E520/E420) in combination with the selected carrier) based on information encoded in microscopic images acquired via scanning electron microscopy (SEM). Recognition of blackcurrant powders was performed using texture feature extraction from images aided by the gray-level co-occurrence matrix (GLCM). It was evaluated for quality using individual single classifiers and a metaclassifier based on metrics such as accuracy, precision, recall, and F1-score. The research showed that the metaclassifier, as well as a single random forest (RF) classifier most effectively identified blackcurrant powders based on image texture features. This indicates that ensembles of classifiers in machine learning is an alternative approach to demonstrate better performance than the existing traditional solutions with single neural models. In the future, such solutions could be an important tool to support the assessment of the quality of food products in real time. Moreover, ensembles of classifiers can be used for faster analysis to determine the selection of an adequate machine learning algorithm for a given problem.

show abstract

Section: Introductionmentioning

confidence: 99%

Efficiency of Identification of Blackcurrant Powders Using Classifier Ensembles

Przybył,

Walkowiak,

Kowalczewski

2024

Foods

View full text Add to dashboard Cite

show abstract

“…These methods contribute to improve the dehydration process, reducing drying time, increasing energy efficiency, and/or improving the quality of the final product ( Radojčin et al, 2021 ). On the other hand, these methods are not necessarily cost-effective, so the food industry often combines different dehydration methods to maximize the benefits of each dehydration technology ( Richter Reis, Marques, Moraes, & Masson, 2022 ). For instance, vacuum dehydration technology is often used in combination with freeze-drying and microwave drying to reduce drying time and enhance drying efficiency.…”

Section: Dehydration Methodsmentioning

confidence: 99%

The role of emerging technologies in the dehydration of berries: Quality, bioactive compounds, and shelf life

et al. 2022

View full text Add to dashboard Cite

“…Dried foodstuffs gain widespread popularity as a food product globally. Assessing their quality is a crucial step in preparing them for commercial markets (Richter Reis et al, 2022). Over the recent years, numerous scientific reports have conducted various quality analyses in this regard.…”

Section: Osmotic Dryingmentioning

confidence: 99%

Preservation of fruits through drying—A comprehensive review of experiments and modeling approaches

Kilic,

Sahin,

Hassan

et al. 2024

J Food Process Engineering

View full text Add to dashboard Cite

A significant part of the world's population still has problems in accessing food. The growing world population will exacerbate this issue in the future. Innovative studies conducted in this field play a crucial role in addressing the issue of drying and storage of foods. Atmospheric drying methods, such as rotary, tunnel, conveyor, cabinet, tower, and kiln dryers, offer advantages in relation to high production capacities, cost‐effective initial setup, and economical operating conditions. However, concurrently, the weaknesses of these methods arise from factors such as drying duration, uneven moisture content, and space requirements. The solar dryer method is especially effective in dehydrating agricultural products, offering an energy‐saving advantage compared to other methods. However, it is important to note that this approach, which involves exposing crops to direct sunlight, comes with several drawbacks affecting both food quality and health. In cases where the quality of highly valued foodstuffs is crucial, subatmospheric drying methods like vacuum, freeze, and microwave freeze are typically preferred. However, the primary drawback of this approach lies in its high operating costs, particularly in terms of energy consumption. Artificial neural networks (ANNs) can be used for predictive modeling, helping to forecast drying behavior and optimize process parameters in food drying applications especially nonlinear connections among variables. ANNs are adept at managing nonlinearities, offering a more precise depiction of the intricate interactions within food drying systems. This review examines articles from the last 5 years in the literature, synthesizing research conducted in food drying. The findings indicate a predominant interest among researchers in methodologies with lower environmental impact, prompting increased attention to studies addressing this aspect. There is a notable emphasis on the frequent exploration of energy‐efficient systems. The ongoing research focuses on the development of methods utilizing ultrasonic, infrared radiation, and electrohydrodynamic techniques to achieve more effective, shorter‐duration, energy‐efficient drying processes with enhanced control over the final product.

show abstract

Trends in quality assessment and drying methods used for fruits and vegetables

Cited by 26 publications

References 47 publications

Efficiency of Identification of Blackcurrant Powders Using Classifier Ensembles

Efficiency of Identification of Blackcurrant Powders Using Classifier Ensembles

The role of emerging technologies in the dehydration of berries: Quality, bioactive compounds, and shelf life

Preservation of fruits through drying—A comprehensive review of experiments and modeling approaches

Contact Info

Product

Resources

About