A Direct Comparison of Remote Sensing Approaches for High-Throughput Phenotyping in Plant Breeding

Abstract

Remote sensing (RS) of plant canopies permits non-intrusive, high-throughput monitoring of plant physiological characteristics. This study compared three RS approaches using a low flying UAV (unmanned aerial vehicle), with that of proximal sensing, and satellite-based imagery. Two physiological traits were considered, canopy temperature (CT) and a vegetation index (NDVI), to determine the most viable approaches for large scale crop genetic improvement. The UAV-based platform achieves plot-level resolution while measuring several hundred plots in one mission via high-resolution thermal and multispectral imagery measured at altitudes of 30–100 m. The satellite measures multispectral imagery from an altitude of 770 km. Information was compared with proximal measurements using IR thermometers and an NDVI sensor at a distance of 0.5–1 m above plots. For robust comparisons, CT and NDVI were assessed on panels of elite cultivars under irrigated and drought conditions, in different thermal regimes, and on un-adapted genetic resources under water deficit. Correlations between airborne data and yield/biomass at maturity were generally higher than equivalent proximal correlations. NDVI was derived from high-resolution satellite imagery for only larger sized plots (8.5 × 2.4 m) due to restricted pixel density. Results support use of UAV-based RS techniques for high-throughput phenotyping for both precision and efficiency.

Strategic crossing of biomass and harvest index—source and sink—achieves genetic gains in wheat

“…Rutkoski 2016), especially with the advent of high throughput phenotyping which can help overcome problems associated with low heritability/repeatability of complex traits related to yield (Tattaris et al 2016). However, this study shows that trait-based approaches have at least as much value in the selection of parents for strategic crossing (Richards 2006;Reynolds and Langridge 2016).…”

High‐Throughput Approaches for Phenotyping Alfalfa Germplasm under Abiotic Stress in the Field

“…The development and use of high‐throughput phenotyping technologies such as drones and sensors mounted on ground‐based vehicles can be useful in multiple screening and breeding applications. These include evaluating diverse accessions from germplasm collections for allele mining and quantification of smaller differences in productivity among elite breeding lines (Furbank and Tester, 2011; Tattaris et al, 2016), monitoring insect pressure in crop species (Lamp, 2018), or predicting biomass yield. Zeng and Chen (2018) used near‐infrared vegetation canopy reflectance measured in the field to estimate forage biomass yield and nutrient contents of a legume–grass mixture with an accuracy of prediction between 0.67 and 0.80.…”

Optimizing the Processing of UAV-Based Thermal Imagery

“…In agriculture, UAV-based thermal remote sensing has been successfully applied for disease detection [20], high-throughput phenotyping in plant breeding [21], or for mapping drought stressed areas e.g., [22][23][24]. New developments also include the estimation of transpiration [25][26][27] or stomatal conductance [28].…”