期刊文献+
共找到11篇文章
< 1 >
每页显示 20 50 100
Identification, pathogenicity, and fungicide sensitivity of Eutiarosporella dactylidis associated with leaf blight on maize in China 被引量:1
1
作者 Cheng Guo Xiaojie Zhang +9 位作者 Baobao Wang Zhihuan Yang Jiping Li Shengjun Xu Chunming Wang Zhijie Guo Tianwang Zhou Liu Hong Xiaoming Wang Canxing Duan 《Journal of Integrative Agriculture》 SCIE CAS CSCD 2024年第3期888-900,共13页
Maize(Zea mays L.) is an economically vital grain crop that is cultivated worldwide. In 2011, a maize foliar disease was detected in Lingtai and Lintao counties in Gansu Province, China. The characteristic signs and s... Maize(Zea mays L.) is an economically vital grain crop that is cultivated worldwide. In 2011, a maize foliar disease was detected in Lingtai and Lintao counties in Gansu Province, China. The characteristic signs and symptoms of this disease include irregular chlorotic lesions on the tips and edges of infected leaves and black punctate fruiting bodies in dead leaf tissues. Given favourable environmental conditions, this disease spread to areas surrounding Gansu. In this study, infected leaves were collected from Gansu and Ningxia Hui Autonomous Region between 2018and 2020 to identify the disease-causing pathogen. Based on morphological features, pathogenicity tests, and multilocus phylogenetic analysis involving internal transcribed spacer(ITS), 18S small subunit rDNA(SSU), 28S large subunit rDNA(LSU), translation elongation factor 1-alpha(TEF), and β-tubulin(TUB) sequences, Eutiarosporella dactylidis was identified as the causative pathogen of this newly discovered leaf blight. Furthermore, an in vitro bioassay was conducted on representative strains using six fungicides, and both fludioxonil and carbendazim were found to significantly inhibit the mycelial growth of E. dactylidis. The results of this study provide a reference for the detection and management of Eutiarosporella leaf blight. 展开更多
关键词 maize leaf blight MORPHOLOGY molecular phylogeny Eutiarosporella dactylidis fungicide sensitivity
下载PDF
Detection of maize leaf diseases using improved MobileNet V3-small 被引量:1
2
作者 Ang Gao Aijun Geng +3 位作者 Yuepeng Song Longlong Ren Yue Zhang Xiang Han 《International Journal of Agricultural and Biological Engineering》 SCIE 2023年第3期225-232,共8页
In order to realize the intelligent identification of maize leaf diseases for accurate prevention and control,this study proposed a maize disease detection method based on improved MobileNet V3-small,using a UAV to co... In order to realize the intelligent identification of maize leaf diseases for accurate prevention and control,this study proposed a maize disease detection method based on improved MobileNet V3-small,using a UAV to collect maize disease images and establish a maize disease dataset in a complex context,and explored the effects of data expansion and migration learning on model recognition accuracy,recall rate,and F1-score instructive evaluative indexes,and the results show that the two approaches of data expansion and migration learning effectively improved the accuracy of the model.The structured compression of MobileNet V3-small bneck layer retains only 6 layers,the expansion multiplier of each layer was redesigned,32-fold fast downsampling was used in the first layer,and the location of the SE module was optimized.The improved model had an average accuracy of 79.52%in the test set,a recall of 77.91%,an F1-score of 78.62%,a model size of 2.36 MB,and a single image detection speed of 9.02 ms.The detection accuracy and speed of the model can meet the requirements of mobile or embedded devices.This study provides technical support for realizing the intelligent detection of maize leaf diseases. 展开更多
关键词 maize leaf disease image recognition model compression MobileNetV3-small
原文传递
Detecting maize leaf water status by using digital RGB images 被引量:8
3
作者 Han Wenting Sun Yu +2 位作者 Xu Tengfei Chen Xiangwei Su Ki Ooi 《International Journal of Agricultural and Biological Engineering》 SCIE EI CAS 2014年第1期45-53,共9页
To explore the correlation between crop leaf digital RGB(Red,Green and Blue)image features and the corresponding moisture content of the leaf,a Canon digital camera was used to collect image information from detached ... To explore the correlation between crop leaf digital RGB(Red,Green and Blue)image features and the corresponding moisture content of the leaf,a Canon digital camera was used to collect image information from detached leaves of heading-stage maize.A drying method was adopted to measure the moisture content of the leaf samples,and image processing technologies,including gray level co-occurrence matrices and grayscale histograms,was used to extract the maize leaf texture feature parameters and color feature parameters.The correlations of these feature parameters with moisture content were analyzed.It is found that the texture parameters of maize leaf RGB images,including contrast,correlation,entropy and energy,were not significantly correlated with moisture content.Thus,it was difficult to use these features to predict moisture content.Of the six groups of eigenvalues for the leaf color feature parameters,including mean,variance,energy,entropy,kurtosis and skewness,mean and kurtosis were found to be correlated with moisture content.Thus,these features could be used to predict the leaf moisture content.The correlation coefficient(R2)of the mean-moisture content relationship model was 0.7017,and the error of the moisture content prediction was within±2%.The R2 of the kurtosis-moisture content relationship model was 0.7175,and the error of the moisture content prediction was within±1.5%.The study results proved that RGB images of crop leaves could be used to measure moisture content. 展开更多
关键词 maize leaf moisture content image processing color feature extraction texture feature extraction
原文传递
Anti-adhesive Property of Maize Leaf Surface Related with Temperature and Humidity 被引量:6
4
作者 Zhiwu Han Jia Fu +3 位作者 Yuqiang Fang Junqiu Zhang Shichao Niu Luquan Ren 《Journal of Bionic Engineering》 SCIE EI CSCD 2017年第3期540-548,共9页
The anti-adhesive surfaces have always aroused great interest of worldwide scientists and engineers. But in practical ap- plications, it often faces the threat and impact of temperature and humidity. In this work, the... The anti-adhesive surfaces have always aroused great interest of worldwide scientists and engineers. But in practical ap- plications, it often faces the threat and impact of temperature and humidity. In this work, the excellent anti-adhesive perform- ance of maize leaf under high temperature and humidity were investigated in detail. Firstly, the adhesion forces of the maize leaf surface under different temperature and humidity were measured by using Atomic Force Microscopy (AFM). The temperature of the substrate was varied between 23 ~C to 100 ~C, and the ambient relative humidity is from 18% to 100%. It was found that the adhesion force of maize leaf decreased with the increase of temperature and humidity. The mechanism of its excellent anti-adhesive performance of maize leaf under high temperature and relative humidity was revealed. The transverse and lon- gitudinal ridges on maize leaf surface interlace with each other, forming small air pockets, which reduces the actual contact area between the object and the maize leaf. With the increase of humidity, the liquid film will be formed in the air pockets gradually and so much water vapor is produced with increase of tempera^tre. Then the air flow rate increases though the wavy top of transverse ridges, inducing the dramatic decrease of adhesion force. Inspired by this mechanism, four samples with this bionic structure were made. This functional "biomimetic structure" would have potential value in the wide medical equipments such as high frequency electric knife with anti-adhesion surface under high temperature and high humidity. 展开更多
关键词 maize leaf ANTI-ADHESION TEMPERATURE relative humidity bionic surface
原文传递
Maize leaf disease identification using deep transfer convolutional neural networks 被引量:2
5
作者 Zheng Ma Yue Wang +4 位作者 Tengsheng Zhang Hongguang Wang Yingjiang Jia Rui Gao Zhongbin Su 《International Journal of Agricultural and Biological Engineering》 SCIE CAS 2022年第5期187-195,F0004,共10页
Gray leaf spot,common rust,and northern leaf blight are three common maize leaf diseases that cause great economic losses to the worldwide maize industry.Timely and accurate disease identification can reduce economic ... Gray leaf spot,common rust,and northern leaf blight are three common maize leaf diseases that cause great economic losses to the worldwide maize industry.Timely and accurate disease identification can reduce economic losses,pesticide usage,and ensure maize yield and food security.Deep learning methods,represented by convolutional neural networks(CNNs),provide accurate,effective,and automatic diagnosis on server platforms when enormous training data is available.Restricted by dataset scale and application scenarios,CNNs are difficult to identify small-scale data sets on mobile terminals,while the lightweight networks,designed for the mobile terminal,achieve a better balance between efficiency and accuracy.This paper proposes a two-staged deep-transfer learning method to identify maize leaf diseases in the field.During the deep learning period,8 deep and 4 lightweight CNN models were trained and compared on the Plant Village dataset,and ResNet and MobileNet achieved test accuracy of 99.48%and 98.69%respectively,which were then migrated onto the field maize leave disease dataset collected on mobile phones.By using layer-freezing and fine-tuning strategies on ResNet and MobileNet,fine-tuned MobileNet achieved the best accuracy of 99.11%.Results confirmed that disease identification performance from lightweight CNNs was not inferior to that of deep CNNs and transfer learning training efficiency was higher when lacking training samples.Besides,the smaller gaps between source and target domains,the better the identification performance for transfer learning.This study provides an application example for maize disease identification in the field using deep-transfer learning and provides a theoretical basis for intelligent maize leaf disease identification from images captured with mobile devices. 展开更多
关键词 maize leaf disease deep learning transfer learning convolutional neural networks
原文传递
Characterization of maize leaf pyruvate orthophosphate dikinase using high throughput sequencing 被引量:2
6
作者 Yuling Zhang Rita Giuliani +10 位作者 Youjun Zhang Yang Zhang Wagner Luiz Araujo Baichen Wang Peng Liu Qi Sun Asaph Cousins Gerald Edwards Alisdair Fernie Thomas P. Brutnell Pinghua Li 《Journal of Integrative Plant Biology》 SCIE CAS CSCD 2018年第8期670-690,共21页
In C4 photosynthesis, pyruvate orthophosphate dikinase (PPDK) catalyzes the regeneration of phospho- enolpyruvate in the carbon shuttle pathway. Although the biochemical function of PPDK in maize is well characteriz... In C4 photosynthesis, pyruvate orthophosphate dikinase (PPDK) catalyzes the regeneration of phospho- enolpyruvate in the carbon shuttle pathway. Although the biochemical function of PPDK in maize is well characterized, a genetic analysis of PPDK has not been reported. In this study, we use the maize transposable elements Nlutator and Ds to generate multiple mutant alleles of PPDK. Loss-of- function mutants are seedling lethal, even when plants were grown under 2% CO2, and they show very low capacity for CO2 assimilation, indicating C4 photosynthesis is essential in maize. Using RNA-seq and GC-MS technologies, we exam- ined the transcriptional and metabolic responses to a deficiency in PPDK activity. These results indicate loss of PPDK results in downregulation of gene expression ofenzymes of the C4 cycle, the Calvin cycle, and components of photochemistry. Furthermore, the loss of PPDK did not change Kranz anatomy, indicating that this metabolic defect in the C4 cycle did not impinge on the morphological differentiation of C4 characters. However, sugar metabolism and nitrogen utilization were altered in the mutants. An interaction between light intensity and genotype was also detected from transcriptome profiling, suggesting altered transcriptional and metabolic responses to environmental and endogenous signals in the PPDK mutants. 展开更多
关键词 Characterization of maize leaf pyruvate orthophosphate dikinase using high throughput sequencing
原文传递
Occurrence and Damage of Maize Gray Leaf Spot and Its GPS Monitoring
7
作者 郑宇鸣 李勃 +2 位作者 张锡顺 林郁 刘振环 《Plant Diseases and Pests》 CAS 2010年第6期1-3,11,共4页
Maize gray leaf spot is a kind of leaf disease seriously threatened the production of maize,which occurs all around the world.The occurrence and damage conditions of maize gray leaf spot at home and abroad and in Yunn... Maize gray leaf spot is a kind of leaf disease seriously threatened the production of maize,which occurs all around the world.The occurrence and damage conditions of maize gray leaf spot at home and abroad and in Yunnan Province are described,the latest research process of maize gray leaf spot are summarized,and the integrated control methods of maize gray leaf spot and its GPS monitoring are further introduced. 展开更多
关键词 maize gray leaf spot Occurrence and damage GPS monitoring
下载PDF
Study on the Bacterial Carrying Seeds as the Primary Infection Sources of Curvularia Leaf Spot in Maize
8
作者 刁毅 叶华智 《Plant Diseases and Pests》 CAS 2011年第1期11-13,共3页
[Objective] The aim was to study the bacterial carrying seeds as the primary infection sourcs of Cunularia leaf spot of maize, and to provide the theo-retical basis for the control of the disease in production. [ Meth... [Objective] The aim was to study the bacterial carrying seeds as the primary infection sourcs of Cunularia leaf spot of maize, and to provide the theo-retical basis for the control of the disease in production. [ Method] Through slide germination and seed tissue isolation method, the viabilities of seeds with internaland external bacterial carrying were detected ; the infection of bacterial carrying of seeds on the young seedling was detected indoors by sand culture method ; and the infection of bacterial carrying seeds on maize was detected using field cultivation method. [Result] The conidia of Gunularia and mycelia carried by maize seeds could survive through the winter. Intemal bacterial carrying of seed affected the germination of seeds, but external bacterial carrying did not affect the germination; internal and external bacterial carrying seeds could infect the radicle and gemmule of maize seedling. [Condusion] The conidia of Curvularia and mycelia carried by maize'seeds could survive through the winter and infect the seedling, which would make the seedlings have weak growth. 展开更多
关键词 Cunularia leaf spot of maize Primary infection source Bacterial carrying seeds
下载PDF
QTL mapping for leaf area in maize (Zea mays L.) under multienvironments 被引量:3
9
作者 CUI Ting-ting HE Kun-hui +3 位作者 CHANG Li-guo ZHANG Xing-hua XUE Ji-quan LIU Jian-chao 《Journal of Integrative Agriculture》 SCIE CAS CSCD 2017年第4期800-808,共9页
Leaves are the main organs of photosynthesis in green plants. Leaf area plays a vital role in dry matter accumulation and grain yield in maize (Zea mays L.). Thus, investigating the genetic basis of leaf area will a... Leaves are the main organs of photosynthesis in green plants. Leaf area plays a vital role in dry matter accumulation and grain yield in maize (Zea mays L.). Thus, investigating the genetic basis of leaf area will aid efforts to breed maize with high yield. In this study, a total of 150 F7 recombinant inbred lines (RILs) derived from a cross between the maize lines Xu 178 and K12 were used to evaluate three ear-leaves area (TELA) under multi-environments. Inclusive composite interval map- ping (ICIM) was used to identify quantitative trait loci (QTLs) for TELA under a single environment and estimated breeding value (EBV). A total of eight QTLs were detected under a single environmental condition, and four QTLs were identified for EBV which also can be detected in single environment. This indicated that the EBV-detected QTLs have high genetic stability. A major QTL (qTELA_2-9) located in chromosome bin 2.04/2.05 could be detected in four environments and has a high phenotypic contribution rate (ranging from 10.79 to 16.51%) that making it a good target for molecular breeding. In addition, joint analysis was used to reveal the genetic basis of leaf area in six environments. In total, six QTLxenvironment interactions and nine epistatic interactions were identified. Our results reveal that the genetic basis of the leaf area is not only mainly determined by additive effects, but also affected by epistatic effects environmental interaction effects. 展开更多
关键词 maize leaf area multi-environments QTL environment interaction epistatic effect
下载PDF
Field Control Efficacy of Several Reagents against Northern Leaf Blight of Maize(Exserohilum turcicum) 被引量:1
10
作者 Sha Honglin Chi Chang Ma Wei 《Plant Diseases and Pests》 CAS 2018年第2期14-15,共2页
[Objective] The paper was to screen suitable agents for controlling northern leaf blight of maize in field. [Method] Field efficacy test was conducted using the agents of propiconazole, azoxystrobin, propiconazole... [Objective] The paper was to screen suitable agents for controlling northern leaf blight of maize in field. [Method] Field efficacy test was conducted using the agents of propiconazole, azoxystrobin, propiconazole·azoxystrobin, coumoxystrobin·tebuconazole, coumoxystrobin·tebuconazole and azoxystrobin. [Result] At 14 d post secondary spraying, the control effects of 25% propionazole EC 168.8 g/hm^2, 25% azoxystrobin SC 300 g/hm^2, 18.7% propiconazole·azoxystrobin SC 196.4 g/hm^2, 40% coumoxystrobin·tebuconazole SC 180 m L/hm^2, 40% coumoxystrobin·tebuconazole SC 180 m L/hm^2+ 25% azoxystrobin SC 300 g/hm^2 against northern leaf blight of maize were 77.35%, 77.11%, 78.13%, 74.60% and 80.94%, re-spectively. The agents were safe and harmless to maize. [Conclusion] Considering the production factors, 18.7% propiconazole·azoxystrobin SC196.4 g/hm^2 or 40% coumoxystrobin·tebuconazole SC 180 m L/hm^2+ 25% azoxystrobin SC 300 g/hm^2 can be sprayed in production before the incidence or in the initial incidence of northern leaf blight of maize. 展开更多
关键词 Propieonazole AZOXYSTROBIN Propieonazole-azoxystrobin Coumoxystrobin- tebueonazole Northern leaf blight of maize Control
下载PDF
Crop Diversity for Ecological Disease Control in Potato and Maize 被引量:17
11
作者 何霞红 朱书生 +12 位作者 王海宁 谢勇 孙雁 高东 杨静 刘林 李启信 张绍波 赵高慧 胡明成 姜开梅 李成云 朱有勇 《Journal of Resources and Ecology》 CSCD 2010年第1期45-50,共6页
本文针对中国西南山区作物病害发病高峰与降雨高峰重叠难以防治的难点,进行了生态调控马铃薯与玉米种植结构避雨避病的试验。试验结果表明,时间上提前和推后马铃薯种植避开了降雨高峰,平均降低晚疫病病情指数44.3%。空间上行距拉宽株距... 本文针对中国西南山区作物病害发病高峰与降雨高峰重叠难以防治的难点,进行了生态调控马铃薯与玉米种植结构避雨避病的试验。试验结果表明,时间上提前和推后马铃薯种植避开了降雨高峰,平均降低晚疫病病情指数44.3%。空间上行距拉宽株距缩小,通风透光减轻病害,套种玉米的大斑病平均降低病情指数为14.8%,小斑病平均降低22.5%。本试验的另一重要结果表明,通过调整马铃薯种植结构可以大幅度提高耕地产出率,马铃薯与玉米套种,提前和推后种植马铃薯分别提高土地利用率1.738-1.766。本文研究结果对作物病害的生态防治和增加粮食产量有重要现实意义。通过时空优化作物与环境的配置,合理利用农业生态结构,适应最佳生态环境,实现优质高产高效。 展开更多
关键词 crop diversity AGROECOLOGY INTERCROPPING potato late blight disease maize northern leaf blight maize southern leaf blight
原文传递
上一页 1 下一页 到第
使用帮助 返回顶部