ArticleData in brief2023
Strawberry-DS: Dataset of annotated strawberry fruits images with various developmental stages.
Article in Data in brief, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed, 20 citations in OpenAlex.
- SLFCNet: an ultra-lightweight and efficient strawberry feature classification network.PeerJ. Computer science · 2025Article
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Authors and funding
3 authors at 3 institutions in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
Strawberry (Fragaria X ananassa) is one of the most popular fruits cultivated around the world. That is owing to its unique flavor and nutritious properties in addition to the wide usage utility in fresh or processed condition. Strawberry fruits also have a significant economic importance around the world with strong potential as an export commodity. As a matter of fact, investigation and assessment of various strawberry fruit characteristics at different developmental stages is crucial for candidate cultivars selection in fruit plantation as well as fruit yield prediction. Strawberry fruits developmental stage is conventionally applied visually based on expert knowledge, which is a time and labor exhaustive process. Thus, this paper presents a dataset, namely Strawberry-DS (Strawberry-Developmental Stages) dataset, consisting of strawberry fruits (Festival CV type) expert-annotated images at various developmental stages. Data collection was performed on site during the period between January and March from a greenhouse located in the Central Laboratory for Agricultural Climate (CLAC) at the Agricultural Research Center of the Ministry of Agriculture and Land Reclamation in Giza, Egypt. The dataset comprises 247 high-resolution RGB (.jpg) images annotated manually, using Roboflow Annotate annotation tool with reference to ground truth Region of Interest (RoI), and presented in YOLO (.txt files) format. The presented Strawberry-DS dataset can be generally used for developing various automated models of strawberry fruits detection, fruits maturity stage classification, as well as visual counting, through taking into account the visual features such as shape, color, size, and texture of strawberry fruits. Strawberry-DS is freely available at: https://data.mendeley.com/datasets/z6dtfdpzz8/1.
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