Leaf-GP: an open and automated software application for measuring growth phenotypes for arabidopsis and wheat

Background

Plants demonstrate dynamic growth phenotypes that are determined by genetic and environmental factors. Phenotypic analysis of growth features over time is a key approach to understand how plants interact with environmental change as well as respond to different treatments. Although the importance of measuring dynamic growth traits is widely recognised, available open software tools are limited in terms of batch image processing, multiple traits analyses, software usability and cross-referencing results between experiments, making automated phenotypic analysis problematic.

Results

Here, we present Leaf-GP (Growth Phenotypes), an easy-to-use and open software application that can be executed on different computing platforms. To facilitate diverse scientific communities, we provide three software versions, including a graphic user interface (GUI) for personal computer (PC) users, a command-line interface for high-performance computer (HPC) users, and a well-commented interactive Jupyter Notebook (also known as the iPython Notebook) for computational biologists and computer scientists. The software is capable of extracting multiple growth traits automatically from large image datasets. We have utilised it in Arabidopsis thaliana and wheat (Triticum aestivum) growth studies at the Norwich Research Park (NRP, UK). By quantifying a number of growth phenotypes over time, we have identified diverse plant growth patterns between different genotypes under several experimental conditions. As Leaf-GP has been evaluated with noisy image series acquired by different imaging devices (e.g. smartphones and digital cameras) and still produced reliable biological outputs, we therefore believe that our automated analysis workflow and customised computer vision based feature extraction software implementation can facilitate a broader plant research community for their growth and development studies. Furthermore, because we implemented Leaf-GP based on open Python-based computer vision, image analysis and machine learning libraries, we believe that our software not only can contribute to biological research, but also demonstrates how to utilise existing open numeric and scientific libraries (e.g. Scikit-image, OpenCV, SciPy and Scikit-learn) to build sound plant phenomics analytic solutions, in a efficient and effective way.

Conclusions

Leaf-GP is a sophisticated software application that provides three approaches to quantify growth phenotypes from large image series. We demonstrate its usefulness and high accuracy based on two biological applications: (1) the quantification of growth traits for Arabidopsis genotypes under two temperature conditions; and (2) measuring wheat growth in the glasshouse over time. The software is easy-to-use and cross-platform, which can be executed on Mac OS, Windows and HPC, with open Python-based scientific libraries preinstalled. Our work presents the advancement of how to integrate computer vision, image analysis, machine learning and software engineering in plant phenomics software implementation. To serve the plant research community, our modulated source code, detailed comments, executables (.exe for Windows; .app for Mac), and experimental results are freely available at https://github.com/Crop-Phenomics-Group/Leaf-GP/releases.

     

Canine angiostrongylosis: an emerging disease in Europe

Objective – The aim of this article is to review Angiostrongylus vasorum infection in dogs, including the life cycle, signalment, clinical signs, diagnosis, and treatment. Apparent changes in the epidemiology of this unique parasite are considered, alongside information available regarding its recent geographic spread.
Etiology – A. vasorum is a metastrongyloid parasite capable of causing an array of clinical problems in dogs, including cardiorespiratory, coagulopathic, and neurologic signs. Currently, the parasite has a worldwide distribution; however, it usually arises in small pockets of enzootic foci. Recent reports suggest a changing distribution of this parasite, which has renewed interest in its epidemiology and in the risk of expansion to new areas including mainland North America.
Diagnosis – A definitive diagnosis of angiostrongylosis is usually made using the modified Baermann technique either using feces or tracheobronchial secretions; however, this review also discusses novel methods such as serologic and molecular techniques.
Therapy – Once a diagnosis of angiostrongylosis is made, prompt treatment should follow with anthelmintic drugs (such as moxidectin/imidacloprid, milbemycin oxime, or fenbendazole) and supportive care dependent upon the patient's clinical signs. Currently, there is no proven prophylactic regime.
Prognosis – The prognosis appears to be very dependent upon the severity of clinical signs at presentation. A. vasorum can be fatal and death may be sudden. However, if a prompt diagnosis is made and appropriate treatment is administered complete clinical resolution is possible.     

Optimizing wetland restoration and management for avian communities using a mixed integer programming approach

Conservation planning and management decisions often present trade-offs among habitats and species, generating uncertainty about the composition and configuration of habitat that will best meet management goals. The public acquisition of 5471 ha of salt ponds in San Francisco Bay for tidal-marsh restoration presents just such a challenge. Because the existing ponds support large numbers of waterbirds, restoring the entire area to tidal marsh could cause undesirable local declines for many species. To identify management strategies that simultaneously maximize abundances of marsh- and pond-associated species, we applied an integer programming approach to maximize avian abundance, comparing across two objectives, two models, and five species weightings (20 runs total). For each pond, we asked: should it be restored to a tidal marsh or kept as a managed pond, and with what salinity and depth? We used habitat relationship models as inputs to non-linear integer programs to find optimal or near-optimal solutions. We found that a simple linear objective, based on maximizing a weighted sum of standardized species’ abundance, led to homogeneous solutions (all-pond or all-marsh). Maximizing a log-linear objective yielded more heterogeneous configurations that benefit more species. Including landscape terms in the models resulted in slightly greater habitat aggregation, but generally favored pond-associated species. It also led to the placement of certain habitats near the bay’s edge. Using the log-linear objective, optimal restoration configurations ranged from 9% to 60% tidal marsh, depending on the species weighting, highlighting the importance of thoughtful a priori consideration of priority species.     

Prediction of kiwifruit orchard characteristics from satellite images

Precision Agriculture - The dry matter content of New Zealand kiwifruit is currently measured using destructive testing of a 90-fruit sample. Dry matter content varies from 14 to 20% with a...     

Performance Evaluation of Integrated Constructed Wetlands Treating Domestic Wastewater

The performances of a new and a mature integrated constructed wetland (ICW) system treating domestic wastewater were evaluated for the first time. The new ICW in Glaslough (near Monaghan, Ireland) comprises five wetland cells, and the mature system in Dunhill (near Waterford, Ireland) comprises four cells. The performance assessment for these systems is based on physical and chemical parameters collected for 1 year in Glaslough and 5 years in Dunhill. The removal efficiencies for the former system were relatively good if compared to the international literature: biochemical oxygen demand (BOD, 99.4%), chemical oxygen demand (COD, 97.0%), suspended solids (SS, 99.5%), ammonia nitrogen (99.0%), nitrate nitrogen (93.5%), and molybdate-reactive phosphorus (MRP, 99.2%). However, the mature ICW had removal efficiencies that decreased over time as the Dunhill village expanded rapidly. The mean removal efficiencies were as follows: BOD (95.2%), COD (89.1%), SS (97.2%), ammonia nitrogen (58.2%), nitrate nitrogen (?11.8%), and MRP (34.0%). The findings indicate that ICW are efficient in removing BOD, COD, SS, and ammonia nitrogen from domestic wastewater. Moreover, both ICW systems did not pollute the receiving surface waters and the groundwater.     

Cutaneous infiltrates and peripheral blood immune responses in dogs with immunomodulatory‐responsive lymphocytic–plasmacytic pododermatitis

This study characterizes T‐ and B‐lymphocyte responses in the peripheral blood and lesional skin of dogs with immunomodulatory‐responsive lymphocytic–plasmacytic pododermatitis (ImR‐LPP), a term previously proposed to denote a subpopulation of dogs with idiopathic pododermatitis. T‐cell (CD3⁺, CD4⁺ and CD8⁺) and B‐cell (CD21⁺) counts were significantly increased in both the epidermis and dermis of lesional ImR‐LPP skin compared with that in pedal skin from healthy controls. CD3⁺, CD4⁺, CD8⁺ and CD21⁺ cells were commonly observed in perivascular sites in the superficial dermis, periadnexally, beneath the dermal–epidermal (DE) junction and in the epidermis of lesional ImR‐LPP skin. The CD8⁺/CD3⁺ T‐cell ratio in peripheral blood was significantly increased in the ImR‐LPP group (0.42 versus 0.35 in controls). Serum IgA, IgG and IgM concentrations were all significantly elevated in affected dogs. Lymphocyte stimulation indices in ImR‐LPP dogs were comparable with control levels except for a lower response to ionomycin (6.0 versus 11.1). Dogs with ImR‐LPP had a higher incidence and mean (semi‐quantitative) score for IgA, IgG and IgM deposits in the epidermis, and a significantly increased incidence of dermal IgA⁺, IgG⁺ and IgM⁺ mononuclear inflammatory cells. The results indicate that upregulated T‐ and B‐lymphocyte responses may contribute to the pathogenesis of the skin lesions observed in dogs with ImR‐LPP.