6 results about "Colony counting" patented technology

The present application relates to the technical field of analytical detection, and in particular to a detection method of Geobacillus thermophilus in raw milk based on real-time fluorescent quantitative polymerase chain reaction. The detection method of the present application is based on nucleic acid specific detection mechanism, which replaces the phenotype culture mechanism, realizes the rapid and accurate quantification of the target bacteria, and replaces the time-consuming and inaccurate colony counting. Through the design of specific primers and probes, the species level specificity identification is realized, and the problem that the traditional method cannot distinguish the specific contaminated bacteria is solved. Through the optimization of the pretreatment method, the sensitivity of the detection method is greatly improved. The detection method of the present application shortens the detection time, realizes the leap from "days" to "hours", greatly improves the detection efficiency, and has a wide application prospect.

1. Name of the product in this design: Colony Analyzer. 2. Application of this design: This design integrates image acquisition, data processing and statistics, and is widely used in colony counting in the fields of food, pharmaceuticals, cosmetics, environmental monitoring, medical and health care, and scientific research institutions. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: a 3D model. 5. Due to the difficulty in viewing the top view, the top view is omitted.

The invention discloses a microbial colony counting and morphology intelligent analysis method and system, and relates to the technical field of image processing and microbial detection.The method comprises the steps that a multi-modal imaging module collects images of a culture plate in a transmission light and annular lateral light dual mode and fuses the images to generate a multi-modal image; the bacterial colony instance segmentation module performs pixel-level instance segmentation on the fused image by adopting a multi-scale feature fusion network in combination with a channel-space double attention mechanism, and outputs boundary masks of all bacterial colonies; the morphological feature extraction module calculates geometric, texture and optical parameters to construct morphological feature vectors; the strain primary screening module outputs a candidate strain list and confidence through weighted Euclidean distance matching, the problems that manual counting efficiency is low, adhesion bacterial colonies are missed in weighing, and culture medium background interference exists are solved, and the counting accuracy rate reaches 98% or above.

The aim is to provide a colony counting device and method that enable more accurate judgment regarding the validity of counting results and can efficiently count colonies even in samples where spread colonies have occurred. [Solution] A colony counter 10 for counting colonies, which are aggregates of microorganisms, comprises: a camera 13 for capturing a sample image from a petri dish 1 in which microorganisms are cultured; and a control unit 17 that detects spread colony ICs from the sample image based on the number of pixels obtained by binarizing the sample image captured by the camera 13, and determines the validity of the count result from the ratio of the total pixel value of the detected spread colony ICs to the area of ​​the petri dish 1.

This invention relates to the field of image data processing technology, and discloses a multimodal image acquisition and processing method for automated counting of microbial colonies in a production line. The method includes the following steps: imaging a culture dish under test using a multimodal physical imaging module to acquire three-modal fused image data containing at least polarization characteristics, multispectral characteristics, and photometric stereoscopic characteristics; establishing a physical-neural hybrid reflection decoupling network and inputting the three-modal fused image data into the network; based on the diffuse reflection dominant image and the specular reflection dominant image, using a multi-scale colony generation and repair network to perform texture repair on reflective residue areas, wherein the repair network introduces a colony morphology prior constraint layer in the decoder section; outputting the repaired image and performing colony counting based on the repaired image. This invention possesses robustness in suppressing and repairing surface reflective interference and has strong generalization ability.

This invention provides a method for detecting the number of viable bacteria in oil drops, comprising the following steps: (1) adding a diluent and a surfactant to the oil drop to be tested, mixing them evenly to obtain a mixture; (2) sequentially performing colony culture and colony counting on the mixture; wherein the surfactant is selected from one or more of anionic surfactants, cationic surfactants, and amphoteric surfactants. The detection method provided by this invention effectively improves the efficiency and accuracy of viable bacteria detection in oil drops by adding a surfactant and optimizing the type and dosage of the added surfactant, the dilution method, and the water bath conditions. Verification of accuracy, precision, specificity, and reproducibility methods has proven the applicability of the method of this invention for the detection of viable bacteria in oil drops, especially probiotic oil drops.