Deployment and Analysis of Instance Segmentation Algorithm for In-field Grade Estimation of Sweetpotatoes

Shape estimation of sweetpotato (SP) storage roots is inherently challenging due to their varied size and shape characteristics. Even measuring "simple" metrics, such as length and width, requires significant time investments either directly in-field or afterward using automated graders. In this paper, we present the results of a model that can perform grading and provide yield estimates directly in the field quicker than manual measurements. Detectron2, a library consisting of deep-learning object detection algorithms, was used to implement Mask R-CNN, an instance segmentation model. This model was deployed for in-field grade estimation of SPs and evaluated against an optical sorter. Storage roots from various clones imaged with a cellphone during trials between 2019 and 2020, were used in the model's training and validation to fine-tune a model to detect SPs. Our results showed that the model could distinguish individual SPs in various environmental conditions including variations in lighting and soil characteristics. RMSE for length, width, and weight, from the model compared to a commercial optical sorter, were 0.66 cm, 1.22 cm, and 74.73 g, respectively, while the RMSE of root counts per plot was 5.27 roots, with r^2 = 0.8. This phenotyping strategy has the potential enable rapid yield estimates in the field without the need for sophisticated and costly optical sorters and may be more readily deployed in environments with limited access to these kinds of resources or facilities.Comment: 21 pages, 11 figure

Three-dimensional and molecular analysis of the arterial pole of the developing human heart

Labeling experiments in chicken and mouse embryos have revealed important roles for different cell lineages in the development of the cardiac arterial pole. These data can only fully be exploited when integrated into the continuously changing morphological context and compared with the patterns of gene expression. As yet, studies on the formation of separate ventricular outlets and arterial trunks in the human heart are exclusively based on histologically stained sections. So as to expand these studies, we performed immunohistochemical analyses of serially sectioned human embryos, along with three-dimensional reconstructions. The development of the cardiac arterial pole involves several parallel and independent processes of formation and fusion of outflow tract cushions, remodeling of the aortic sac and closure of an initial aortopulmonary foramen through formation of a transient aortopulmonary septum. Expression patterns of the transcription factors ISL1, SOX9 and AP2α show that, in addition to fusion of the SOX9-positive endocardial cushions, intrapericardial protrusion of pharyngeal mesenchyme derived from the neural crest contributes to the separation of the developing ascending aorta from the pulmonary trunk. The non-adjacent walls of the intrapericardial arterial trunks are formed through addition of ISL1-positive cells to the distal outflow tract, while the facing parts of the walls form from the protruding mesenchyme. The morphogenetic steps, along with the gene expression patterns reported in this study, are comparable to those observed in the mouse. They confirm the involvement of mesenchymal tissues derived from endocardium, mesoderm and migrating neural crest cells in the process of initial septation of the distal part of the outflow tract, and its subsequent separation into discrete intrapericardial arterial trunks