A Multi-Stage, Pixel-Level Annotated Apple Dataset for Precision Agriculture Research

Published: 24 July 2025| Version 2 | DOI: 10.17632/gfcmdbvw65.2
Contributors:
Dandan Wang, Bo Wang

Description

The dataset of apples was collected from September 2017 to October 2019 in an experimental orchard at the College of Horticulture, Northwest A&F University (Yangling, Shaanxi, China). The dataset consists of 1,128 apple images captured under varying natural lighting and weather conditions, covering multiple growth stages—from immature green apples to mature red targets—including transitional color variations. The dataset is classified into three distinct categories: immature (green), semi-mature (transitional), and mature (red). Table 1 gives a detailed description and visualization for each categories. The dataset contains 1,128 annotated images capturing apples across three developmental stages: 534 images with immature (green) apples, 316 with semi-mature (color-transitioning) apples, and 387 with mature (red) apples. The non-additive total reflects natural orchard conditions where individual images frequently contain multiple maturity stages—either three stages simultaneously or two transitional stages coexisting. This indicates that asynchronous fruit development occurs within orchards. Across all images, we annotated 2,117 distinct apple instances: 926 immature (green), 453 semi-mature (patchy coloration), and 738 mature (red) apples.

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Institutions

  • Xi'an University of Science and Technology

Categories

Precision Agriculture, Apple

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