New Approaches to Assessing the Quality of Cherry Fruit

Sour Cherry is among the most consumed fruits which is highly appreciated by consumers, it is studied by the world community due to its pleasant taste, appearance, nutritional and biochemical properties. Therefore, new approaches to assessing the quality of cherry fruit aimed at reducing post-harvest losses and further extending the shelf life of the fruit remain relevant. The aim of the study was to substantiate commercial and sensory indicators for a comprehensive assessment of the quality of cherry fruit to select the best varieties and ensure sustainable fruit production for the improvement of diets. In the course of the experiment, we used the descriptive-profile and scoring methods of sensory analysis. To determine sensory and commercial properties, 10 model cherry varieties were selected. The cherry fruits of the model varieties were divided into two commercial classes according to technological parameters and the presence of defects. For each cultivar of fruits a sensory profile was compiled and a score was assigned to the following descriptors: colour intensity, taste, firmness and juiciness of flesh, skin density. Each expert of the group conducted rating tests on ten fruit samples and evaluated them in order of advantage in appearance, aroma, taste and texture. Then, the comparative total score was calculated. The description of commercial and organoleptic parameters for fresh sour cherries has been improved on a 9-point scale, which increases the objectivity of the analysis for stakeholders. According to the indicators of fruit size and presence of defects, the fruits were distributed into 1st and 2nd commercial classes. The cherry cultivar Solidarnist, which provided the maximum number of 1st class fruits, was selected as the most valuable. The cherry cultivar Hriot Melitopolskyi produced the largest number of 2nd class fruits. According to the comprehensive assessment, the highest sensory indicators have been found in Hriot Melitopolskyi and Modnytsia cultivars. The complex interpretation of the main commercial and sensory indicators of sour cherries makes it possible to further integrate them into a criterion-based express method for determining the fruit quality of different varieties by visual indicators. This can then be used to optimize the quality of raw materials and select the method of fruit processing.

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-12-31
DOI
https://doi.org/10.5281/zenodo.15278059
Primary Topic
Advanced Scientific Research Methods
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

New Approaches to Assessing the Quality of Cherry Fruit

Zenodo (CERN European Organization for Nuclear Research)
Advanced Scientific Research Methods
article

New Approaches to Assessing the Quality of Cherry Fruit

article en

Abstract

Sour Cherry is among the most consumed fruits which is highly appreciated by consumers, it is studied by the world community due to its pleasant taste, appearance, nutritional and biochemical properties. Therefore, new approaches to assessing the quality of cherry fruit aimed at reducing post-harvest losses and further extending the shelf life of the fruit remain relevant. The aim of the study was to substantiate commercial and sensory indicators for a comprehensive assessment of the quality of cherry fruit to select the best varieties and ensure sustainable fruit production for the improvement of diets. In the course of the experiment, we used the descriptive-profile and scoring methods of sensory analysis. To determine sensory and commercial properties, 10 model cherry varieties were selected. The cherry fruits of the model varieties were divided into two commercial classes according to technological parameters and the presence of defects. For each cultivar of fruits a sensory profile was compiled and a score was assigned to the following descriptors: colour intensity, taste, firmness and juiciness of flesh, skin density. Each expert of the group conducted rating tests on ten fruit samples and evaluated them in order of advantage in appearance, aroma, taste and texture. Then, the comparative total score was calculated. The description of commercial and organoleptic parameters for fresh sour cherries has been improved on a 9-point scale, which increases the objectivity of the analysis for stakeholders. According to the indicators of fruit size and presence of defects, the fruits were distributed into 1st and 2nd commercial classes. The cherry cultivar Solidarnist, which provided the maximum number of 1st class fruits, was selected as the most valuable. The cherry cultivar Hriot Melitopolskyi produced the largest number of 2nd class fruits. According to the comprehensive assessment, the highest sensory indicators have been found in Hriot Melitopolskyi and Modnytsia cultivars. The complex interpretation of the main commercial and sensory indicators of sour cherries makes it possible to further integrate them into a criterion-based express method for determining the fruit quality of different varieties by visual indicators. This can then be used to optimize the quality of raw materials and select the method of fruit processing.

Zenodo (CERN European Organization for Nuclear Research)
National University of Life and Environmental Sciences of Ukraine (UA), Polissia National University (UA), Bogdan Khmelnitsky Melitopol State Pedagogical University (UA), Dmytro Motornyi Tavria State Agrotechnological University (UA), Mykolayiv National Agrarian University (UA)
Openalex Percentile: Top 48%
Advanced Scientific Research Methods
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.