3D Point Cloud and Machine Learning Help Pear Growers Thin Fruit Smarter, Not Harder
· newswise.com · popularity 21/100 · 0 similar stories today · AI & Data Science (Artificial Intelligence)
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Summary
<img src="https://www.newswise.com/legacy/image.php?image=https://media.newswise.com/pio/articles/857409/6ae0b28396717_1_857409.jpg&width=100&height=150" alt="Newswise image" />Maintaining an appropriate fruit load is essential for balancing yield and quality in pear production, yet growers still rely largely on experience when deciding how much fruit to thin. Now, researchers have developed a data-driven framework that estimates whole-tree leaf number from three-dimensional (3D) point cloud-derived canopy traits and machine learning, then converts that estimate into a reasonable fruit load (FL) recommendation. Field trials showed the approach improved fruit weight and size without reducing yield, offering a practical tool for precision orchard management.
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