ArticleScientific reports2024
Enhancing citrus fruit yield investigations through flight height optimization with UAV imaging.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 7 papers, 1 of them a synthesis that pooled it.
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Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Research progress on precision orchard yield estimation based on multi-source information perception sensors.Frontiers in plant science · 2026Pooled it
- RGB-UAV-based phenotyping reveals the influence of planting density on physiological traits, biomass, and yield in buckwheat.BMC plant biology · 2026Article
- Dataset for orange fruit detection from UAV in citrus orchards.Data in brief · 2026Article
- Estimation of Nitrogen Status inPlants (Basel, Switzerland) · 2026Article
- EABI-DETR: An Efficient Aerial Small Object Detection Network.Biomimetics (Basel, Switzerland) · 2025Article
- LRDS-YOLO enhances small object detection in UAV aerial images with a lightweight and efficient design.Scientific reports · 2025Article
- Comparative analysis of adaptive and general labeling methods for soybean leaf detection.Frontiers in plant science · 2025Article
Corrections and comments
- Erratum issued
Authors and funding
9 authors.
Funding
Abstract
Citrus fruit yield is essential for market stability, as it allows businesses to plan for production and distribution. However, yield estimation is a complex and time-consuming process that often requires a large number of field samples to ensure representativeness. To address this challenge, we investigated the optimal altitude for unmanned aerial vehicle (UAV) imaging to estimate the yield of Citrus unshiu fruit. We captured images from five different altitudes (30 m, 50 m, 70 m, 90 m, and 110 m), and determined that a resolution of approximately 5 pixels/cm is necessary for reliable estimation of fruit size based on the average diameter of C. unshiu fruit (46.7 mm). Additionally, we found that histogram equalization of the images improved fruit count estimation compared to using untreated images. At the images from 30 m height, the normal image estimates fruit numbers as 73, 55, and 88. However, the histogram equalized image estimates 88, 71, 105. The actual number of fruits is 124, 88, and 141. Using a Vegetation Index such as I
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