TillerPET: An AI model for high-throughput phenotyping of rice tiller traits 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.

🌾🤖 AI ‘TillerPET’ sees rice secrets! 🌱 Counts & maps growth from photos, across years & fields. Unlocking yield potential! ✨ #RiceRevolution

Source: phys.org/news/2025-12-tillerpet-a...

BasisPointInsight.com - Genome Editing: A Quiet Revolution in Indian Rice Fields by G. Chandrashekhar Indian scientists are quietly rewriting the genetic code of rice. Early field trials of genome-edited varieties promise higher yields, lower input use, and greater resilience to climate stress. by G. ...

3/3 And is India ready to lead in agri-innovation through science that edits — not imports — the future?

Read G. Chandrashekhar’s analysis for BasisPoint 👇

#GenomeEditing #CRISPR #RiceRevolution #AgriInnovation #ClimateSmartFarming #AgTech #IndiaAgriculture