Purpose -The purpose of this paper is to develop a robotic system to feed aquatic organisms and measure water physicochemical parameters in experimental aquaculture ponds. Design/methodology/approach -A dispatcher unit dispenses a precise amount of food and control panel software schedules the tasks and operates the robot. In the control panel, the feeding and measuring schedule is defined and sent to the mobile robot and the amount of food is requested by the robot to the dispatcher for each pond. The robot travels automatically on a monorail to dispense the food and measure the water parameters. The data are transmitted to the control panel. The system can be remotely operated over the internet through a client-server software framework. Findings -The robotic system is a tool for delegating feeding and measuring tasks. This allows researchers and technicians time to focus on more substantive aquacultural research tasks. Research limitations/implications -Future improvement will include an automatic unit for cleaning sensors between ponds to minimize the risk of cross-contamination. Practical implications -The system systematized feeding and measuring tasks, minimized human error, and optimized the use of resources for aquacultural experimentation. The robotic system can be programmed for a variety of experimental conditions, such as the delivery of different diets at diverse schedules. Originality/value -The proposed robot was tested for feeding freshwater redclaw crayfish (Cherax quadricarinatus) and monitored the water parameters in real time. Based on the field results, the robotic system provided a reliable and robust device for aquacultural research applications.
An on-water remote monitoring robotic system was developed for indirectly estimating the relative density of marine cyanobacteria blooms at the subtidal sandy-rocky beach in Balandra Cove, Baja California Sur, Mexico. The system is based on an unmanned surface vehicle to gather underwater videos of the seafloor for avoiding physical damage on Anabaena sp. cyanobacteria colonies, which grow in tufts of filaments weakly attached to rocks, seagrass, and macroalgae. An on-axis image stabilization mechanism was developed to support a camcorder and minimize wave perturbation while recording underwater digital images of the seafloor. Color image processing algorithms were applied to estimate the patch coverage area and density, since Anabaena sp. filaments exhibit a characteristic green tone. Results of field tests showed the feasibility of the robotic system to estimate the relative density, distribution, and coverage area of cyanobacteria blooms, preventing the possible impact of direct observation. The robotic system could also be used in surveys of other benthos in the sublittoral zone.
RNA-Sequencing and de novo assembly have enabled the analysis of species with non-available reference transcriptomes, although intrinsic features (biological and technical) induce errors in the reconstruction. A strategy to resolve these errors consists of varying assembling process parameters to generate multiple reconstructions. However, the best assembly selection remains a challenge. Quantitative metrics for quality assessment have been inconsistent when compared with pertinent references. In this paper, a criterion for supporting assembly selection based on mapping DNA microarray hybridized probes to assembly sets is proposed. Mouse and fruit fly RNA-Seq datasets were assembled with standard de novo procedures. Quality assessment was estimated using quantitative metrics and the proposed criterion. The assembly that best mapped to the available reference transcriptomes of these model species provided the highest quality assembly. The hybridized probes identified the best assemblies, whereas quantitative metrics remained inconsistent. For example, subtle probe mapping difference of 0.25 %, but statistically significant (ANOVA, p ), enabled the assembly selection that led to identify 3,719 more contigs and led to 1,049 further mapped contigs to the mouse reference transcriptome. The microarray data availability for non-model species makes the proposed criterion suitable for quality assessment of multiple de novo assembly strategies.
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