WeChat Mini Program
Old Version Features

三种虫生菌协同毒性及与有机肥耦合效应研究

South China Agriculture(2022)

Cited 0|Views20
Abstract
为揭示白僵菌、绿僵菌、淡紫紫孢菌对蚜虫、地蚕、根结线虫的毒性大小,并探索生防菌与有机肥耦合效应,采用PDA对白僵菌、绿僵菌、淡紫紫孢菌对其进行活化培养,并稀释不同浓度菌剂作用于蚜虫,观察单独菌种下毒性大小,然后利用对峙法研究菌种间拮抗性,寻求最优协同杀虫组合,最后利用响应面法设计不同有机肥与菌剂配比,分析混合配方对防效的影响.结果表明:三种虫生真菌对蚜虫的毒力大小为白僵菌>淡紫紫孢菌>绿僵菌,50%致死浓度分别为5.048×106、6.962×106、1.155×107 cfu·mL-1,三种虫生菌间没有拮抗性,白僵菌与淡紫紫孢菌对蚜虫和根结线虫的协同效果最优,协同毒力指数分别为3.66、4.77,有机肥与虫生菌耦合效果影响因子大小为有机肥比例>菌剂浓度>油饼比例,并得到"有机肥80.5%+油饼14.3%+白僵菌-淡紫紫孢菌组合菌剂8.4%"配比对线虫的防效最高.
More
求助PDF
上传PDF
Bibtex
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
  • Pretraining has recently greatly promoted the development of natural language processing (NLP)
  • We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
  • We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
  • The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
  • Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
Summary is being generated by the instructions you defined