AI Drones Find Early‑Maturing Wheat for Resilience
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- University of Barcelona and Agrotecnio used drones and AI to evaluate 64 durum wheat varieties under irrigated and rain‑fed Mediterranean conditions.
- Plant Phenomics published the study, which found that early vigorous growth and early maturation, not prolonged greenness, predict stable yields under variable climate.
- Drones equipped with RGB, multispectral, and thermal cameras, together with ground sensors, monitored wheat development throughout the growing cycle, eliminating the need for harvest‑based analysis.
- Artificial intelligence models trained on the multi‑sensor data accurately predicted both yield and yield stability for each genotype.
- The study identified that high‑yield genotypes show high initial vigor and sustained greenness, while stable genotypes have lower initial vigor and shorter cycles, and proposed a selection method balancing both traits.
- Plant breeding programs could use this technology to develop wheat varieties better adapted to drought and high temperatures, addressing climate change challenges.
Why it matters: Plant breeders and wheat growers gain a rapid, low‑cost phenotyping tool that predicts yield stability, allowing them to select lines that maintain harvests despite drought or heat, while traditional field trials remain costly and slower. It reduces the need for extensive harvest‑based testing and shortens breeding cycles, helping develop climate‑resilient wheat varieties.
