6 results about "Allium chinense" patented technology

The invention provides a color identification method and system for allium chinensis and sorting equipment. The method comprises the following steps: acquiring an allium chinensis image; performing background segmentation on the allium chinensis in the allium chinensis image to obtain an allium chinensis segmented image; identifying a white area in the segmented allium chinensis image; and according to the allium chinensis segmented image and the white area, reversely deducing a defect area to obtain a mixed-color area. The method can effectively identify the mixed color area of the allium chinensis, and improves the accuracy of allium chinensis color identification.

The allium chinensis skin impurity separating screen comprises a screen box, a centrifugal screen frame and a separating and collecting assembly, the centrifugal screen frame is installed in the screen box, a feeding pipe is fixed to the upper side of the centrifugal screen frame, a driving assembly is installed on the outer side of the feeding pipe, and the separating and collecting assembly is installed on the right side of the lower portion of the screen box. A baffle is slidably mounted on the left side of the collecting box, a drawing groove corresponding to the baffle is formed in the outer wall of the screen box, and three fans are mounted on the lower left side of the interior of the screen box at equal intervals. Through the arrangement of the centrifugal screen frame and the driving assembly, separation of allium chinensis and skin impurities is facilitated, and through the arrangement of the separation and collection assembly, collection of the skin impurities is facilitated.

The allium chinensis peeling and cleaning all-in-one machine comprises a machine base, a cutting assembly and a rubbing assembly, four feeding tables are fixed to the upper side of the machine base, the cutting assembly is installed on the upper sides of the feeding tables, the cutting assembly comprises a fixed plate, an electric push rod, a moving plate, a motor, a rotating shaft and a blade, an outer frame is fixed to the upper portions of the outer sides of the feeding tables, and the rotating shaft is installed on the outer frame. A rubbing table is installed on the right side of the feeding table, a rubbing assembly is arranged on the upper side of the rubbing table, and a cleaning pool is installed on the right side of the rubbing table. The electric push rod drives the moving plate to move, so that the distance between the moving plate and the other fixed plate is adjusted, and the cutting depth is adjusted to adapt to allium chinensis of different sizes; the blades are conveniently driven to rotate through the motor and the rotating shaft, so that the angles of the blades are conveniently adjusted, and use is more flexible.

The application discloses a traditional Chinese medicine polysaccharide with lipid-lowering activity and a preparation method and application thereof, relates to the technical field of biological medicine, and the traditional Chinese medicine polysaccharide is neutral uniform polysaccharide ACP1 in allium chinense, the weight-average molecular weight is 17.96 kDa, the polydispersity index is 1.726, is composed of glucose and fructose, and the molar ratio is 2.53%:97.47%. The neutral uniform polysaccharide in allium chinense provided in the application is a new neutral uniform polysaccharide ACP1 extracted from allium chinense, can effectively improve the lipid deposition of AML-12 cells induced by oleic acid, has significant lipid-lowering activity, and is high in safety. The preparation method of the neutral uniform polysaccharide in allium chinense provided in the application is good in repeatability, the obtained neutral uniform polysaccharide is high in purity, and is beneficial to industrial production.

This invention relates to the field of ecological restoration, and discloses a method and system for soil health restoration and nutrient cycling regulation of degraded *Allium chinense* populations in karst alpine regions. The method includes the following steps: performing structured initial sampling in the target restoration area to obtain an initial training dataset; constructing a master surrogate model for predicting *Allium chinense* population density and a constrained surrogate model for predicting the feasibility of restoration schemes; optimizing the master surrogate model using a sampling function to select candidate restoration formulas; implementing the candidate restoration formulas in the field and observing the actual population density response, incorporating the new data pairs into the initial training dataset to update the master surrogate model; using the constrained surrogate model combined with a feasibility constraint function to evaluate the economic feasibility of the candidate restoration formulas under given competing plant conditions; integrating the new data to retrain the master surrogate model and / or the constrained surrogate model and updating the recommended restoration formulas. This method provides quantitative support for restoration decisions while reducing the number of field experiment rounds.

This invention discloses a method and system for classifying and spatially warning about the degradation status of *Allium chinense* populations in alpine grasslands, relating to the field of ecological environment monitoring technology. The method includes: acquiring degradation feature vectors of *Allium chinense* at each spatial grid point; obtaining the local spectral matrix of each spatial grid point based on its feature vectors and spatial neighborhood information using a robust covariance estimation method; constructing and solving a unified optimization problem based on the local spectral matrix, outputting the optimal load matrix for each spatial grid point through distributed iterative optimization; calculating the degradation intensity index based on the optimal load matrix and the local spectral matrix; identifying the dominant degradation variable based on the row-wise comprehensive load of the optimal load matrix; determining the degradation type of each spatial grid point through a configurable rule engine; performing spatial segmentation and connectivity analysis on the degradation intensity index; and outputting a spatial warning layer. This achieves continuous spatial assessment and classification of the degradation status of large-scale *Allium chinense* populations.