In a new study published in The Crop Journal on November 7, researchers developed an AI model named TillerPET that enables simultaneous in-situ high-throughput phenotyping of tiller number and compactness from post-harvest rice RGB images. It demonstrates stable performance across multi-year, multi-location rice RGB datasets.