Skip to main content

Research Article

A High-Throughput Phenotyping System Using Machine Vision to Quantify Severity of Grapevine Powdery Mildew

Andrew Bierman1, Tim LaPlumm1, Lance Cadle-Davidson2,3, David Gadoury3, Dani Martinez3, Surya Sapkota3, and Mark Rea1

1Lighting Research Center, Rensselaer Polytechnic Institute, Troy, NY 12180, USA
2United States Department of Agriculture-Agricultural Research Service, Grape Genetics Research Unit, Geneva, NY 14456, USA
3Plant Pathology and Plant-Microbe Biology Section, School of Integrative Plant Science, Cornell University, Geneva, NY 14456, USA
Correspondence should be addressed to Lance Cadle-Davidson; lance.cadledavidson@ars.usda.gov

How to Cite this Article

Andrew Bierman, Tim LaPlumm, Lance Cadle-Davidson, et al., “A High-Throughput Phenotyping System Using Machine Vision to Quantify Severity of Grapevine Powdery Mildew,” Plant Phenomics, vol. 2019, Article ID 9209727, 13 pages, 2019. https://doi.org/10.34133/2019/9209727.

  • Views 325
  • Citations 0
Altmetric Attention Score
Find out more