Aerial Imagery Analysis - Quantifying Appearance and Number of Sorghum Heads for Applications in Breeding and Agronomy.

Sorghum (Sorghum bicolor L. Moench) is a C4 tropical grass that plays an essential role in providing nutrition to humans and livestock, particularly in marginal rainfall environments. The timing of head development and the number of heads per unit area are key adaptation traits to consider in agronomy and breeding but are time consuming and labor intensive to measure. We propose a two-step machine-based image processing method to detect and count the number of heads from high-resolution images captured by unmanned aerial vehicles (UAVs) in a breeding trial. To demonstrate the performance of the proposed method, 52 images were manually labeled; the precision and recall of head detection were 0.87 and 0.98, respectively, and the coefficient of determination (R 2) between the manual and new methods of counting was 0.84. To verify the utility of the method in breeding programs, a geolocation-based plot segmentation method was applied to pre-processed ortho-mosaic images to extract >1000 plots from original RGB images. Forty of these plots were randomly selected and labeled manually; the precision and recall of detection were 0.82 and 0.98, respectively, and the coefficient of determination between manual and algorithm counting was 0.56, with the major source of error being related to the morphology of plants resulting in heads being displayed both within and outside the plot in which the plants were sown, i.e., being allocated to a neighboring plot. Finally, the potential applications in yield estimation from UAV-based imagery from agronomy experiments and scouting of production fields are also discussed.

High-Throughput Phenotyping of Sorghum Plant Height Using an Unmanned Aerial Vehicle and Its Application to Genomic Prediction Modeling.

Genomics-assisted breeding methods have been rapidly developed with novel technologies such as next-generation sequencing, genomic selection and genome-wide association study. However, phenotyping is still time consuming and is a serious bottleneck in genomics-assisted breeding. In this study, we established a high-throughput phenotyping system for sorghum plant height and its response to nitrogen availability; this system relies on the use of unmanned aerial vehicle (UAV) remote sensing with either an RGB or near-infrared, green and blue (NIR-GB) camera. We evaluated the potential of remote sensing to provide phenotype training data in a genomic prediction model. UAV remote sensing with the NIR-GB camera and the 50th percentile of digital surface model, which is an indicator of height, performed well. The correlation coefficient between plant height measured by UAV remote sensing (PHUAV) and plant height measured with a ruler (PHR) was 0.523. Because PHUAV was overestimated (probably because of the presence of taller plants on adjacent plots), the correlation coefficient between PHUAV and PHR was increased to 0.678 by using one of the two replications (that with the lower PHUAV value). Genomic prediction modeling performed well under the low-fertilization condition, probably because PHUAV overestimation was smaller under this condition due to a lower plant height. The predicted values of PHUAV and PHR were highly correlated with each other (r = 0.842). This result suggests that the genomic prediction models generated with PHUAV were almost identical and that the performance of UAV remote sensing was similar to that of traditional measurements in genomic prediction modeling. UAV remote sensing has a high potential to increase the throughput of phenotyping and decrease its cost. UAV remote sensing will be an important and indispensable tool for high-throughput genomics-assisted plant breeding.

Functions of Runx in IgA class switch recombination.

Runt-related (Runx) transcriptional regulators play essential roles in various cell fate determination processes, and dysfunction of these regulators causes many human diseases. Considerable insight into the functions of Runx proteins was provided mainly by studies of hematopoietic and skeletal disorders. Recently, extensive investigations have revealed new functions of these transcription factors in immune cell differentiation and functioning. In the present review, we discuss the mechanisms of selective IgA production in the intestine and report the involvement of Runx proteins in this process.

Requirement for Runx proteins in IgA class switching acting downstream of TGF-beta 1 and retinoic acid signaling.

IgA is a specific isotype required for mucosal immunity and is the most abundant Ab produced in vivo. Recently, several inductive signals for IgA class switch recombination have been identified; however, the molecular details of the action of these signals and the specific factors acting in B cells remain elusive. In this study, we show that combination of retinoic acid (RA) and TGF-beta1 with other factors induced a much higher frequency of IgA-switched cells than reported previously. In addition, IgA production is severely impaired in Runx2-Runx3 double-deficient mice. In Runx2-Runx3-deficient B cells, both RA- and TGF-beta1-dependent inductions of alpha germline transcription are completely blocked. These data suggest that Runx proteins play an essential role in IgA class switching acting downstream of RA and TGF-beta1 signaling.