High-Throughput Phenotyping in Soybean

Soybean [Glycine max (L.) Merr.] breeders and geneticists routinely evaluate thousands of plots per year in order to characterize various accessions and breedingBreeding populations for a multitude of traits, for example, morphological, physiological, abiotic and biotic stressAbiotic and biotic stresses, plant organs, and seed composition. Most of these trait evaluations require experienced raters to spend countless hours, recording phenotypes for each genotype in different filial generations. Plant breeders strive to work with increased population sizes, and improved accuracy of selection to increase the response to selection. These requirements have motivated the development of high-throughput phenotypingHigh-Throughput Phenotyping (HTP) (HTP) methods and associated tools (i.e., hardware) and software solutions. This chapter consists of several topics related to HTP, including sensorsSensors, unmanned aerial systemsUnmanned Aerial Systems (UAS), and ground robotsGround robots, as these are important components of plant phenotyping in the new technological era. The advances in image-based analysisImage-based analysis and machine learningMachine learning methods have accompanied the improvements in phenotyping capabilities, both aerial and ground. This chapter includes the current state of the artState of the art in types of sensors, aerial, and ground-based HTP, in conjunction with machine learningMachine learning-based analytics, particularly for physiological and morphological traits, abiotic and biotic stressesAbiotic and biotic stresses, and root-related traits. Advances in the integrationIntegration of HTPHigh-Throughput Phenotyping (HTP) with crop modeling are provided. Finally, the complementary relationship between HTP and genomic studies is explained with pertinent examples.