High throughput phenotyping to accelerate crop breeding and monitoring of diseases in the field

• Published in: Current opinion in plant biology Vol. 38; pp. 184 - 192
• Main Authors: Shakoor, Nadia, Lee, Scott, Mockler, Todd C
• Format: Journal Article
• Language: English
• Published: England Elsevier Ltd 01.08.2017; Elsevier
• Subjects: 09 BIOMASS FUELS; artificial intelligence; Breeding; computer vision; crop yield; Crops, Agricultural - physiology; cultivars; data collection; disease resistance; geographic information systems; image analysis; information management; infrastructure; Machine Learning; monitoring; phenotype; plant breeding; quantitative traits; screening
• ISSN: 1369-5266; 1879-0356; 1879-0356
• DOI: 10.1016/j.pbi.2017.05.006

•Phenotyping technology can increase the throughput of plant screening in the field.•Early season detection of plant diseases is key to reducing crop yield losses.•Disease diagnosis relies on symptom recognition through observations and ratings.•Remote sensing methods can identify, quantify and monitor plant diseases.•Sensor-based phenotyping will accelerate the rate of genetic gain in crops. Effective implementation of technology that facilitates accurate and high-throughput screening of thousands of field-grown lines is critical for accelerating crop improvement and breeding strategies for higher yield and disease tolerance. Progress in the development of field-based high throughput phenotyping methods has advanced considerably in the last 10 years through technological progress in sensor development and high-performance computing. Here, we review recent advances in high throughput field phenotyping technologies designed to inform the genetics of quantitative traits, including crop yield and disease tolerance. Successful application of phenotyping platforms to advance crop breeding and identify and monitor disease requires: (1) high resolution of imaging and environmental sensors; (2) quality data products that facilitate computer vision, machine learning and GIS; (3) capacity infrastructure for data management and analysis; and (4) automated environmental data collection. Accelerated breeding for agriculturally relevant crop traits is key to the development of improved varieties and is critically dependent on high-resolution, high-throughput field-scale phenotyping technologies that can efficiently discriminate better performing lines within a larger population and across multiple environments.