Plant growth-promoting rhizobacteria （PGPR） are considered to be the most promising agents for cash crop production via increasing crop yields and decreasing disease occurrence. The Bacillus amyloliquefaciens strain...Plant growth-promoting rhizobacteria （PGPR） are considered to be the most promising agents for cash crop production via increasing crop yields and decreasing disease occurrence. The Bacillus amyloliquefaciens strain W19 can produce secondary metabolites （iturin and bacillomycin D） effectively against Fusarium oxysporum f. sp. cubense （FOC）. In this study, the ability of a bio-organic fertilizer （BIO） containing strain W19 to promote plant growth and suppress the Fusarium wilt of banana was evaluated in both pot and field experiments. The results showed that application of BIO significantly promoted the growth and fruit yield of banana while suppressing the banana Fusariurn wilt disease. To further determine the beneficial mechanisms of the strain, the colonization of green fluorescent protein-tagged strain W19 on banana roots was observed using confocal laser scanning microscopy and scanning electron microscopy. The effect of banana root exudates on the formation of biofilm of strain W19 indicated that the banana root exudates may enhance colonization. In addition, the strain W19 was able to produce indole-3-acetic acid （IAA）, a plant growth-promoting hormone. The results of these experiments revealed that the application of strain W19-enriched BIO improved the banana root colonization of strain W19 and growth of banana and suppressed the Fusarium wilt. The PGPR strain W19 can be a useful biocontrol agent for the production of banana under field conditions.展开更多
Remote sensing technology has long been used to detect and map crop diseases.Airborne and satellite imagery acquired during growing seasons can be used not only for early detection and within-season management of some...Remote sensing technology has long been used to detect and map crop diseases.Airborne and satellite imagery acquired during growing seasons can be used not only for early detection and within-season management of some crop diseases,but also for the control of recurring diseases in future seasons.With variable rate technology in precision agriculture,site-specific fungicide application can be made to infested areas if the disease is stable,although traditional uniform application is more appropriate for diseases that can spread rapidly across the field.This article provides a brief overview of remote sensing and precision agriculture technologies that have been used for crop disease detection and management.Specifically,the article illustrates how airborne and satellite imagery and variable rate technology have been used for detecting and mapping cotton root rot,a destructive soilborne fungal disease,in cotton fields and how site-specific fungicide application has been implemented using prescription maps derived from the imagery for effective control of the disease.The overview and methodologies presented in this article should provide researchers,extension personnel,growers,crop consultants,and farm equipment and chemical dealers with practical guidelines for remote sensing detection and effective management of some crop diseases.展开更多
现有基于深度学习的农作物病害识别方法对网络浅层、中层、深层特征中包含的判别信息挖掘不够,且提取的农作物病害图像显著性特征大多不足,为了更加有效地提取农作物病害图像中的判别特征,提高农作物病害识别精度,提出一种基于多层信息...现有基于深度学习的农作物病害识别方法对网络浅层、中层、深层特征中包含的判别信息挖掘不够,且提取的农作物病害图像显著性特征大多不足,为了更加有效地提取农作物病害图像中的判别特征,提高农作物病害识别精度,提出一种基于多层信息融合和显著性特征增强的农作物病害识别网络(Crop disease recognition network based on multi-layer information fusion and saliency feature enhancement,MISF-Net)。MISF-Net主要由ConvNext主干网络、多层信息融合模块、显著性特征增强模块组成。其中,ConvNext主干网络主要用于提取农作物病害图像的特征;多层信息融合模块主要用于提取和融合主干网络浅层、中层、深层特征中的判别信息;显著性特征增强模块主要用于增强农作物病害图像中的显著性判别特征。在农作物病害数据集AI challenger 2018及自制数据集RCP-Crops上的实验结果表明,MISF-Net的农作物病害识别准确率分别达到87.84%、95.41%,F1值分别达到87.72%、95.31%。展开更多
基金supported by the National Natural Science Foundation of China (Nos. 31572212 and 31372142)the National Key Basic Research Program of China (No. 2015CB150503)+5 种基金the Chinese Ministry of Science and Technology (No. 2013AA102802)the Natural Science Foundation of Jiangsu Province, China (No. BK20150059)the Priority Academic Program Development (PAPD) of Jiangsu Higher Education Institutions of Chinathe 111 Project of China (No. B12009)the National Training Program of Innovation and Entrepreneurship for Undergraduates of China (No. 201410307089)the "Qing Lan" Project of China
文摘Plant growth-promoting rhizobacteria （PGPR） are considered to be the most promising agents for cash crop production via increasing crop yields and decreasing disease occurrence. The Bacillus amyloliquefaciens strain W19 can produce secondary metabolites （iturin and bacillomycin D） effectively against Fusarium oxysporum f. sp. cubense （FOC）. In this study, the ability of a bio-organic fertilizer （BIO） containing strain W19 to promote plant growth and suppress the Fusarium wilt of banana was evaluated in both pot and field experiments. The results showed that application of BIO significantly promoted the growth and fruit yield of banana while suppressing the banana Fusariurn wilt disease. To further determine the beneficial mechanisms of the strain, the colonization of green fluorescent protein-tagged strain W19 on banana roots was observed using confocal laser scanning microscopy and scanning electron microscopy. The effect of banana root exudates on the formation of biofilm of strain W19 indicated that the banana root exudates may enhance colonization. In addition, the strain W19 was able to produce indole-3-acetic acid （IAA）, a plant growth-promoting hormone. The results of these experiments revealed that the application of strain W19-enriched BIO improved the banana root colonization of strain W19 and growth of banana and suppressed the Fusarium wilt. The PGPR strain W19 can be a useful biocontrol agent for the production of banana under field conditions.
文摘Remote sensing technology has long been used to detect and map crop diseases.Airborne and satellite imagery acquired during growing seasons can be used not only for early detection and within-season management of some crop diseases,but also for the control of recurring diseases in future seasons.With variable rate technology in precision agriculture,site-specific fungicide application can be made to infested areas if the disease is stable,although traditional uniform application is more appropriate for diseases that can spread rapidly across the field.This article provides a brief overview of remote sensing and precision agriculture technologies that have been used for crop disease detection and management.Specifically,the article illustrates how airborne and satellite imagery and variable rate technology have been used for detecting and mapping cotton root rot,a destructive soilborne fungal disease,in cotton fields and how site-specific fungicide application has been implemented using prescription maps derived from the imagery for effective control of the disease.The overview and methodologies presented in this article should provide researchers,extension personnel,growers,crop consultants,and farm equipment and chemical dealers with practical guidelines for remote sensing detection and effective management of some crop diseases.
文摘现有基于深度学习的农作物病害识别方法对网络浅层、中层、深层特征中包含的判别信息挖掘不够,且提取的农作物病害图像显著性特征大多不足,为了更加有效地提取农作物病害图像中的判别特征,提高农作物病害识别精度,提出一种基于多层信息融合和显著性特征增强的农作物病害识别网络(Crop disease recognition network based on multi-layer information fusion and saliency feature enhancement,MISF-Net)。MISF-Net主要由ConvNext主干网络、多层信息融合模块、显著性特征增强模块组成。其中,ConvNext主干网络主要用于提取农作物病害图像的特征;多层信息融合模块主要用于提取和融合主干网络浅层、中层、深层特征中的判别信息;显著性特征增强模块主要用于增强农作物病害图像中的显著性判别特征。在农作物病害数据集AI challenger 2018及自制数据集RCP-Crops上的实验结果表明,MISF-Net的农作物病害识别准确率分别达到87.84%、95.41%,F1值分别达到87.72%、95.31%。
