番茄枯萎病拮抗菌KCKB1的分离、鉴定及生防效果
Jiangsu Agricultural Sciences（2023）
Abstract
为筛选获得针对番茄枯萎病的生防菌,从山东寿光设施大棚内番茄根际筛选获得1株细菌菌株KCKB1,通过菌落形态特征观察以及16S rRNA基因序列分析,菌株KCKB1确认为枯草芽孢杆菌(Bacillus subtilis),并对其开展对峙培养、种属鉴定、生长特性研究、抑菌谱检测以及盆栽防效验证.结果表明,菌株KCKB1能有效抑制番茄枯萎病,盆栽防治效果达到61.46％;菌株KCKB1可以提高番茄植株叶片内抗氧化酶(SOD、CAT)以及抑菌物质合成酶(PAL、PPO)的活性,进而提高植株抗病性.同时,菌株KCKB1还具有溶磷、固氮、产铁载体、产ACC脱氨酶、产IAA等促生功能,能明显促进番茄植株的生长.此外,菌株KCKB1对链格孢菌、甘薯长喙壳菌、灰葡萄孢、烟草疫霉菌、尖孢镰刀菌甘薯专化型5种病原菌均具有良好的的抑菌效果.综上,枯草芽孢杆菌菌株KCKB1具有良好的生防潜力与广阔的应用前景,为对番茄枯萎病进行生物防治提供了菌种资源.
More求助PDF
上传PDF
View via Publisher
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