![]() ![]() To be useful to breeding programs, HTP methods must be amenable to plot sizes, experimental designs and field conditions in these programs. In this context, HTP is an assessment of plant phenotypes on a scale and with a level of speed and precision not attainable with traditional methods, many of which include visual scoring and manual measurements. Plant phenotyping involves a wide range of plant measurements such as growth development, canopy architecture, physiology, disease and pest response and yield. The phenotype results from the interactions between a plant’s genes and environmental (abiotic and biotic) factors. To contribute to this piece of the challenge, we describe here a semi-automated HTP analysis pipeline using a low cost unmanned aerial system (UAS) platform, which will increase the capacity of breeders to assess large numbers of lines in field trials.Ī plant phenotype is a set of structural, morphological, physiological, and performance-related traits of a given genotype in a defined environment. To get to the point of predicting the real-world performance of plants, HTP platforms must innovate and advance to the level of quantitatively assessing millions of plant phenotypes. High throughput phenotyping (HTP) platforms could provide the keys to connecting the genotype to phenotype by both increasing the capacity and precision and reducing the time to evaluate huge plant populations. Extraordinary advances over the last 5–10 years in sequencing and genotyping technology have driven down the cost and are providing an abundance of genomic data, but this only comprise half of the equation to understand the function of plant genomes and predicting plant phenotypes. The grand challenge remains in connecting genetic variants to observed phenotypes followed by predicting phenotypes in new genetic combinations. The rates of genetic improvement are below what is needed to meet projected demand for staple crops such as wheat. In a world of finite resources, climate variability, and increasing populations, food security has become a critical challenge. In the scope of tools development, the pipeline developed in this study can be effectively employed for other UAS and also other crops planted in breeding nurseries. Low-cost UAS platforms have great potential for use as a selection tool in plant breeding programs. The approaches described here for UAS imaging and extraction of proximal sensing data enable collection of HTP measurements on the scale and with the precision needed for powerful selection tools in plant breeding. Their correlation to spectroradiometer readings was as high as or higher than repeated measurements with the spectroradiometer per se. We observed VIs extracted from calibrated images of Canon S100 had a significantly higher correlation to the spectroradiometer (r = 0.76) than VIs from the MultiSpec 4C camera (r = 0.64). We determined radiometric calibration methods developed for satellite imagery significantly improved the precision of VIs from the UAS. We found good correlation between the VIs obtained from UAS platforms and ground-truth measurements and observed high broad-sense heritability for VIs. We also examined the relationships between vegetation indices (VIs) extracted from high spatial resolution multispectral imagery collected with two different UAS systems (eBee Ag carrying MultiSpec 4C camera, and IRIS+ quadcopter carrying modified NIR Canon S100) and ground truth spectral data from hand-held spectroradiometer. The image dataset was processed using a photogrammetric pipeline based on image orientation and radiometric calibration to produce orthomosaic images. We developed a semi-automated image-processing pipeline to extract plot level data from UAS imagery. The objective of this study was to complete a baseline assessment of the utility of UAS in assessment field trials as commonly implemented in wheat breeding programs. For field-based high-throughput phenotyping (HTP), UAS platforms can provide high-resolution measurements for small plot research, while enabling the rapid assessment of tens-of-thousands of field plots. In the context of plant breeding and genetics, current approaches for phenotyping a large number of breeding lines under field conditions require substantial investments in time, cost, and labor. Low cost unmanned aerial systems (UAS) have great potential for rapid proximal measurements of plants in agriculture. ![]()
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