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High-Throughput Phenotyping in Soybean

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High-Throughput Crop Phenotyping

Part of the book series: Concepts and Strategies in Plant Sciences ((CSPS))

Abstract

Soybean [Glycine max (L.) Merr.] breeders and geneticists routinely evaluate thousands of plots per year in order to characterize various accessions and breeding populations for a multitude of traits, for example, morphological, physiological, abiotic and biotic stress, 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 phenotyping (HTP) methods and associated tools (i.e., hardware) and software solutions. This chapter consists of several topics related to HTP, including sensors, unmanned aerial systems, and ground robots, as these are important components of plant phenotyping in the new technological era. The advances in image-based analysis and machine learning methods have accompanied the improvements in phenotyping capabilities, both aerial and ground. This chapter includes the current state of the art in types of sensors, aerial, and ground-based HTP, in conjunction with machine learning-based analytics, particularly for physiological and morphological traits, abiotic and biotic stresses, and root-related traits. Advances in the integration of HTP with crop modeling are provided. Finally, the complementary relationship between HTP and genomic studies is explained with pertinent examples.

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Acknowledgements

The support of USDA CRIS project IOW04714 (to A.K.S., A.S.), USDA National Institute of Food and Agriculture (NIFA) Food and Agriculture Cyberinformatics Tools (FACT) award 2019-67021-29938 (to A.S., A.K.S., B.G., S.S.), NSF S&CC award 1952045 (to A.K.S., S.S.), NSF CPS Frontier award CNS-1954556 (to S.S., B.G., A.K.S., A.S.), Iowa Soybean Association (to A.K.S.); Plant Sciences Institute (to A.K.S., B.G., S.S., F.E.M.); Bayer Chair in Soybean Breeding (to A.K.S.); and R F Baker Center for Plant Breeding (to A.K.S.) is sincerely appreciated.

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  1. Department of Agronomy, Iowa State University, Ames, IA, USA

    Asheesh K. Singh, Arti Singh, Fernando E. Miguez, Clayton N. Carley, Matthew E. Carroll, Mariana V. Chiozza, Kevin O. Chiteri, Kevin G. Falk, Sarah E. Jones, Talukder Z. Jubery, Kyle A. Parmley, Ashlyn M. Rairdin, Johnathon M. Shook, Liza Van der Laan & Jiaoping Zhang

  2. Department of Mechanical Engineering, Iowa State University, Ames, IA, USA

    Soumik Sarkar, Baskar Ganapathysubramanian, Seyed V. Mirnezami & Therin J. Young

  3. Department of Agronomy, Kansas State University, Manhattan, KS, USA

    William Schapaugh

  4. Department of Electrical Engineering, Iowa State University, Ames, IA, USA

    Koushik Nagasubramanian

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Correspondence to Asheesh K. Singh .

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  1. University of Missouri, Columbia, MO, USA

    Jianfeng Zhou

  2. University of Missouri, Columbia, MO, USA

    Henry T. Nguyen

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Singh, A.K. et al. (2021). High-Throughput Phenotyping in Soybean. In: Zhou, J., Nguyen, H.T. (eds) High-Throughput Crop Phenotyping. Concepts and Strategies in Plant Sciences. Springer, Cham. https://doi.org/10.1007/978-3-030-73734-4_7

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