Wan Shen AlgaeAC Enhanced Algae Automatic Classification and Counting Instrument

Automatic identification and classification counter for Algae, Model AlgaeAC plus

2、 Purpose:

The dominant species and quantity of phytoplankton in water bodies, as well as their particle size distribution, are important basis for studying water environment. However, manual judgment has always been used, which is quite time-consuming and laborious. The AlgaeAC algae automatic classification and counting instrument can effectively solve the pain point problem for users. It is mainly used in ecological surveys, fisheries, aquaculture, and education to automatically classify and count phytoplankton (algae) samples in water bodies, measure their size, and determine their biomass. The AlgaeAC enhanced model also comes with intelligent identification modules for algae and planktonic animals, helping to reduce the heavy identification workload of the past, and is an essential tool for ecological investigation and monitoring.

3、 Core parameters:

1. ★ Full time autofocus with over 24 million pixels and high-resolution large field of view optical imaging, which can automatically stitch 625 automatic camera fields into nearly 5 billion pixel super field of view images, effectively avoiding algae from being automatically chopped up by the edges of each field of view. Optimized focusing algorithm for microalgae, ensuring clear scanning images and supporting magnification factors such as 20X and 40X objectives.

2. After pre-treatment, the water sample is placed in the algae counting box, and the entire process of algae recognition and classification counting is automatically completed (automatic moving field of view focusing scanning and photography, automatic classification recognition counting, and automatic generation of statistical reports). The detection is based on the "SL733-2016 Technical Regulations for Monitoring phytoplankton in Inland Waters", "Methods for Monitoring and Analyzing Water and Wastewater" (Fourth Edition), Part 5 "Biological Monitoring Methods for Water and Wastewater", as well as the calculation requirements for algae corresponding to GB17378-2007 "Marine Monitoring Specification" and GB/T12763-2007 "Marine Survey Specification".

3. The system contains common phyla of cyanobacteria, diatoms, green algae, naked algae, hidden algae, golden algae, dinoflagellates, and yellow algaeClassification and recognition library of 85 genera and above algae speciesIt can be expanded to more than 100 genera and species according to local conditions.

4. ★ It can analyze and obtain morphological parameters such as area, perimeter, volume, length, width, main axis, secondary axis, and equivalent diameter of each algal body. Can analyze and count the quantity, area, volume, and proportion of various algae (by phylum or genus); Sort and display the proportion of each category in a bar chart. Further statistical analysis of data can be conducted in Excel software. Algae names can be directly marked on the collected images, and images of each algae can be extracted and segmented, automatically classified and saved. Historical data can be viewed retrospectively. Automatically provide a classification and counting statistical report, indicating dominant species and dominance, and sorting by dominant species. Automatically calculate Shannon Wiener index, evenness index, richness index, algal individual density, algal cell density, biomass, etc.

5. ★ Can automatically classify and analyze algae ranging from 3 to 1000 μ m, with automatic scanning imaging and analysis time of about 20 minutes for 100 fields of view (optional for 25-400 fields of view); The detection range is 10⁵-10¹⁰Per liter (try to avoid mixing sediment and impurities as much as possible); The automatic recognition rate of dominant species in the local classification recognition library is ≥ 90%, the comprehensive automatic recognition rate is ≥ 80%, and the final recognition rate after interactive correction can reach over 98%; At a concentration of 10⁷-10⁸When per liter, the repeatability error of automatic analysis is less than 5%.

6. ★ Intelligent identification module for algae and planktonic animals

1) It can quickly and effectively search for images to intelligently identify up to 24584 species of algae and plankton in seawater and freshwater (Chinese and Latin bilingual plankton expert database: algae have 15 phyla, 1666 genera, and 15087 species; plankton have 24 major categories, 1941 genera, and 9497 species). There are currently over 270300 valid image libraries, and each library's species and content can be expanded independently. It is also possible to search and identify copepods by P5 chest foot.

2) It can automatically index algae and planktonic animals in the user's established count table to generate a small database of the watershed of interest, making it faster and more accurate to search for images and identify resources.

3) The Microcystis analysis module can automatically learn and analyze the cell count of clustered Microcystis populations, and automatically count planktonic animals such as granular or single-cell microalgae, chain microalgae cells, nematodes, etc.

4) Capable of counting and measuring the morphology of algae and planktonic animals, and compiling and reporting the sequences of dominant species. Built in 34 geometric models, the volume and biomass of planktonic organisms can be calculated by measuring a small number of parameters.

7. ★ Imitating the process of detecting algae with an artificial microscope, imaging counting can be performed using five counting methods: whole slide counting, diagonal counting, grid counting, and random field counting.

8. It can be located and annotated on the map based on the geographic coordinates of the collection location, supporting various map sources such as Amap, Amap, Google Maps, and Google Satellite Maps.

9. The manufacturer provides assistance in establishing a local classification initial identification database service, remote assistance guidance, and a 3-year free remote upgrade service.

4、 Configuration List:

1) Wan Shen AlgaeAC Enhanced Algae Automatic Classification and Counting Software (including Plankton Intelligent Identification System) 1 set

2) High precision electronic control X-Y automatic scanning platform+1 set of controller

3) One set of high-resolution optical imaging system with full-time autofocus

4) 1 set of Olympus BX53 three eye biological microscope

5) One branded computer (i5 9th generation or above CPU/16GB memory/GTX1060 GPU/256GB solid-state drive with CUDA support+1T hard drive/23 "color display, 1 USB 3.0 port+3 USB 2.0 ports, running on Windows 10 operating system)

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