ArticleScientific reports2023
Shape classification technology of pollinated tomato flowers for robotic implementation.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed.
- Olfactory Responses ofInsects · 2026Article
- Antibacterial and Antitumoral Potentials of Phytosynthesized Silver/Silver Oxide Nanoparticles Using Tomato Flower Waste.International journal of molecular sciences · 2024Article
- Deep learning approach for detecting tomato flowers and buds in greenhouses on 3P2R gantry robot.Scientific reports · 2024Article
- Estimation of the amount of pear pollen based on flowering stage detection using deep learning.Scientific reports · 2024Article
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Three pollination methods are commonly used in the greenhouse cultivation of tomato. These are pollination using insects, artificial pollination (by manually vibrating flowers), and plant growth regulators. Insect pollination is the preferred natural technique. We propose a new pollination method, using flower classification technology with Artificial Intelligence (AI) administered by drones or robots. To pollinate tomato flowers, drones or robots must recognize and classify flowers that are ready to be pollinated. Therefore, we created an AI image classification system using a machine learning convolutional neural network (CNN). A challenge is to successfully classify flowers while the drone or robot is constantly moving. For example, when the plant is shaking due to wind or vibration caused by the drones or robots. The AI classifier was based on an image analysis algorithm for pollination flower shape. The experiment was performed in a tomato greenhouse and aimed for an accuracy rate of at least 70% for sufficient pollination. The most suitable flower shape was confirmed by the fruiting rate. Tomato fruit with the best shape were formed by this method. Although we targeted tomatoes, the AI image classification technology is adaptable for cultivating other species for a smart agricultural future.
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