5 results about "Tracheid" patented technology

This invention discloses a method, apparatus, medium, and equipment for detecting tracheid cavities in transverse sections of coniferous wood, belonging to the field of wood identification technology. Based on an active learning approach, this invention combines generative adversarial networks (GANs) for sparse data sampling and uses the output of a target detection model as a SAM (Self-Assisted Analysis) prompting strategy to achieve automatic segmentation of tracheid cavities in coniferous wood transverse sections and obtain quantitative anatomical data. By optimizing the data sampling process and enhancing the model's adaptability, this method effectively improves the accuracy and efficiency of cavity segmentation and can be adapted to any coniferous wood transverse section microscopic image. It achieves low-cost construction of a coniferous wood microscopic image database and the development of a model for the detection, segmentation, and measurement of coniferous wood tracheid cavities. This solves the problems of difficult manual detection and high collection and annotation costs caused by the complex structure and sampling difficulty of tracheid cavities in coniferous wood transverse sections, enabling automatic and rapid detection, segmentation, and measurement of coniferous wood tracheid cavities.

The invention discloses a coniferous wood cross section tracheid cell cavity detection method, device, medium and equipment, and belongs to the technical field of wood identification. Based on the technical scheme of the active learning method, sparse data sampling is carried out in combination with the generative adversarial network, the output of the target detection model is adopted as an SAM prompt strategy, automatic segmentation of the cross section cell cavity of the coniferous wood is achieved, and quantitative anatomical data is obtained. According to the method, by optimizing the data sampling process and enhancing the adaptability of the model, the precision and efficiency of cell cavity segmentation can be effectively improved, and the method can be suitable for any coniferous material cross section microscopic images. The construction of a low-cost coniferous material microscopic image database and the development of a coniferous material tracheid cell cavity detection, segmentation and measurement model are realized, and the problems of difficulty in manual detection, high acquisition and labeling cost and the like caused by complex structure and sampling difficulty of the tracheid cell cavity of the cross section of the coniferous material are solved; and automatic and rapid detection, segmentation and measurement of the coniferous wood tracheid cell cavity are realized.

This invention discloses a method for accurately measuring tracheid wall thickness in *Pinus sylvestris* based on micro-CT images, a method for selecting high carbon-fixing varieties of *Pinus sylvestris*, and a system, belonging to the field of forest tree genetics and breeding technology. Addressing the systematic underestimation of tracheid wall thickness due to partial volume effect in micro-CT measurements, this invention employs the gray-scale centroid method to calculate the sub-pixel position of the wall-cavity boundary, reducing the measurement error from ±1.5 μm to ±0.3 μm. Based on accurate wall thickness data, screening criteria are established: "average wall thickness ≥ 75th percentile of the population, coefficient of variation ≤ 15%, and proportion of thick-walled tracheids ≥ 60%". Combined with carbon storage index verification, this enables precise selection of high carbon-fixing varieties. This method is non-destructive, efficient, and reproducible, and is applicable to the genetic improvement of *Pinus sylvestris* and similar coniferous trees.

The present invention discloses a preparation method of a hydrophilic porous noise-reducing organic ground cover, which is specifically implemented according to the following steps: Step 1, obtain branches and cut the branches to obtain cut pieces or cut grains; Step 2, naturally dry the cut pieces or cut grains obtained in Step 1 to form a common organic ground cover; Step 3, prepare an infiltration modifier solution, and then perform surface modification on the common organic ground cover formed in Step 2 by spraying or infiltration, and finally obtain a cut material substrate after pre-drying; Step 4, prepare a pore-forming agent; Step 5, enable the cut material substrate obtained in Step 3 to fully absorb the pore-forming agent prepared in Step 4, and then undergo track-type microwave drying to obtain a hydrophilic porous noise-reducing organic ground cover. The present invention utilizes tracheids to absorb the pore-forming agent to form gas-induced pores, forming a surface porous structure, which can effectively reduce noise.

The present invention discloses a method for preparing a porous, noise-reducing organic ground cover. The method is specifically implemented in the following steps: Step 1: Obtain branches and cut them to obtain cuttings or pellets; Step 2: Naturally air-dry the cuttings or pellets obtained in Step 1 to form a common organic ground cover; Step 3: Prepare a porogen; Step 4: Allow the cuttings obtained in Step 2 to fully absorb the porogen prepared in Step 3, and then subject the substrate to crawler-type microwave drying to obtain the porous, noise-reducing organic ground cover. The method utilizes tracheids to absorb the porogen to form gas-induced pores, forming a porous surface structure that effectively reduces noise.