Non-polluted antibacterial peptide biopesticide

Abstract

The invention discloses a non-polluted antibacterial peptide biopesticide, which comprises the following materials in parts by weight: 40-50 parts of earthworm antibacterial peptide, 15-20 parts of houttuynia cordata, 5-17 parts of bean starch, 15-19 parts of phenethyl phenol polyoxyethylene ether, 5-23 parts of corn straw powder, 3-9 parts of paenibacillus polymyxa, 22-31 parts of oil-tea cakes, 5-8 parts of anise, 10-14 parts of cloves, 20-31 parts of anise oil, 13-20 parts of paraquat and 90-150 parts of water. The pesticide disclosed by the invention is simple in production process and free from pollution in the production process; the pesticide is natural and non-toxic, belonging to non-polluted green and environment-friendly products. The pesticide is especially suitable for producing non-polluted organic agricultural products.

Description

technical field [0001] The invention relates to a pollution-free antimicrobial peptide biological pesticide. Background technique [0002] The annual planting area of ​​rice, the main food crop in my country, exceeds 28 million hectares, and the planting area of ​​vegetables and fruits exceeds 1800 hectares. Among them, the area of ​​disease and insect pest control is about 6.7 billion mu. Every year, the occurrence of pests and diseases will lead to a large area of ​​production reduction and quality reduction of these commercial crops. [0003] The current main control technology still relies on chemical pesticides. Extensive use of chemical pesticides has made my country one of the countries with the most severe chemical pesticide sludge in the world, which has caused the detection of toxic pesticide residues in agricultural products and food in my country to generally exceed the standard. And then endanger people's food safety and health. In international trade, the an...

AI Technical Summary

Problems solved by technology

So far, there is no report on earthworm antimicrobial peptide pesticides and its use in spraying rice, vegetable, melon and fruit stems and leaves to control pests and diseases in data retrieval.