4results about How to "Improve survival efficiency" patented technology

The invention discloses a microbial preparation for preventing and treating plant root-knot nematode as well as a preparation method and application thereof, and belongs to the technical field of microbial preparations. The microbial preparation for preventing and treating the plant root-knot nematode is of a double-layer coating structure and comprises an inner layer and an outer layer, the inner layer comprises phaffia rhodozyma fermentation liquor, paecilomyces lilacinus fermentation liquor, bacillus subtilis fermentation liquor, bacillus thuringiensis fermentation liquor, beauveria bassiana fermentation liquor and an inner layer carrier material; the outer layer comprises a streptomyces densely-rotating fermentation liquid and an outer layer carrier material; according to the application, the phaffia rhodozyma, the paecilomyces lilacinus, the bacillus subtilis, the bacillus thuringiensis fermentation liquor, the beauveria bassiana fermentation liquor and the streptomyces dense are compounded, and the strains have a synergistic effect, so that functional complementation is realized; a double-layer coating structure is adapted to acid soil, guarantees the initial activity of the strain and improves the survival efficiency of the strain on one hand, and can prolong the shelf life and the function exerting period on the other hand, so that long-acting pest control is realized.

This application relates to a prefabricated smart plant cultivation box and its control method, which includes a planting pot, a water tank, a filter assembly, a soil sensor, an equipment room, and an intelligent control assembly. This application achieves automated monitoring and precise control of the entire plant growth cycle through deep collaboration of multi-sensor fusion and intelligent algorithms. The system can collect environmental parameters such as temperature, humidity, and light, as well as soil nutrients and plant morphological characteristics in real time. Through big data analysis technology, it quickly identifies growth anomalies, such as water shortage, nutrient deficiency, or pest and disease risks, and automatically generates targeted maintenance strategies. This integrated design eliminates the cumbersome process of manual observation and experience-based judgment in traditional plant cultivation, allowing even non-professional users to easily achieve scientific plant management, significantly lowering the maintenance threshold and improving plant survival efficiency.

This utility model relates to the field of plant cultivation technology, and in particular to a self-storing water-retaining tree planting container. It includes a water-storing base, a self-storing water tank fixedly connected inside the water-storing base, a limiting plate fixedly connected inside the water-storing base, six rivet holes arranged in a circular array inside the limiting plate, positioning components fixedly connected to the left and right sides of each of the six rivet holes, an inner cavity inside the water-storing base, first guide components fixedly connected to the left and right sides of the inner cavity, an insertion hole on one side of each first guide component, a tree planting container body disposed inside the inner cavity, movable grooves on the left and right sides of the upper surface of the tree planting container body, guide components disposed inside each of the two movable grooves, and second guide components sleeved on the outside of each of the two guide components. This utility model enhances the clamping and fixing effect on trees, preventing them from bending due to severe weather, while the water-storing structure is flexibly adjustable, improving its practicality.

The invention discloses a method for optimizing a formula of a lactobacillus reuteri composite freeze-drying protective agent based on a neural network model, and belongs to the technical field of optimization of the formula of the composite freeze-drying protective agent. The method comprises the following steps: by taking lactobacillus reuteri as a test strain and the freeze-drying survival rate of the strain as an evaluation index, firstly, carrying out a single-factor test on a candidate lactobacillus reuteri composite freeze-drying protective additive; on the basis, the lactobacillus reuteri composite freeze-drying protective agent which has obvious influence on the freeze-drying survival rate of the strain is screened out through a Plackett-Burman test; finally, a Box-Behnken response surface test and a BP-GA neural network model optimization test are combined, and formula optimization of the lactobacillus reuteri composite freeze-drying protective agent is completed. According to the method, on the basis of a single-factor test, a Plackett-Burman test and a BP-GA neural network model are introduced, the defects of traditional experimental design can be systematically made up, and the globality, nonlinear adaptability and robustness of formula optimization are remarkably improved, so that the direct vat set leavening agent with high survival efficiency is obtained.