Matthieu Bogard
Papers
1
Total Citations
21
H-Index
1
About
Matthieu Bogard is a leading researcher at the intersection of plant phenomics, quantitative genetics, and climate-resilient agriculture. His work centers on developing high-throughput phenotyping methods—particularly robotized indoor systems—to bridge the gap between controlled environments and field performance. His most cited paper (2023, 21 citations) demonstrates that indoor robotized phenotyping can enable genomic prediction of adaptive traits like plant architecture and stomatal conductance, which are critical for breeding crops resilient to climate change. This contribution challenges the traditional focus on yield alone, showing that traits measured at high throughput indoors can reliably predict field outcomes. Bogard’s research has significant implications for speed breeding programs, offering a scalable solution to accelerate genetic gains in changing environments. His work is notable for integrating robotics, computer vision, and statistical genomics, making him a key figure in the push toward data-driven, climate-adaptive crop improvement.
Research Focus
Key Achievements
Top Papers
- 1