High-Throughput Technologies for Alfalfa Germplasm Evaluation in the Field.

Challenges to provide food, feed and fiber to an increasing global population include limited availability of water and nutrients. Key aspects towards developing new cultivars capable of being productive under these shifting conditions include field-based phenotyping of large populations to identify high-yielding individuals. These individuals can be used as parents to develop new populations as part of the cultivar development pipeline as well as increase our understanding of their underlying stress tolerance mechanisms. Field-based phenotyping with manual data collection is often time-consuming, thus limiting the number of data-points collected throughout the growing season. For alfalfa, a perennial species, opportunities for integrating high-throughput phenotyping platforms including the use of sensors mounted on both phenomobiles and unmanned aerial vehicles (UAV) represent viable alternatives to manual data collection and increase the frequency and resolution of field-based phenotyping data. The objective of this study was to assess the value of two different phenotyping approaches to screen a diverse set of alfalfa accessions for their ability to establish and produce biomass in a low pH, P-limited field site. We identified opportunities and limitations of each of these systems (manual data collection, sensors mounted on a phenomobile and UAV) in terms of capabilities, time, cost and precision in regards to their ability to identify the best alfalfa individuals to be used for practical plant breeding applications. Advances in high-throughput phenotyping enable field-based screening of a large number of accessions that can be used to capture genetic diversity and lead to the development of enhanced cultivars that are productive with lower inputs.