检索结果-南通市图书馆

Study on Dormancy Mechanism and Dormancy-breaking Method of velvetleaf(Abutilon theophrasti)Seeds

Agricultural Biotechnology 2020年第5期9卷 29-31,36页

作者： Kuojie XIAO Chenzhong JIN Yunyun ZHOU Jun PAN Shunli XIAO Kaifa GUO Xinnan QING Xiu LIU Key Laboratory of Pesticide Harmless Application of Hunan Higher Education Hunan University of HumanitiesScience and TechnologyLoudi 417000China Collaborative Innovation Center for Farmland Weeds Control Techniques and Application of Human Province Loudi 417000China

[Objectives]This study was conducted to explore how can we better break the dormancy of velvetleaf seeds and the best method to promote seed germination.[Methods]With the seeds of velvetleaf(Abutilon theophrasti)as experimental materials,the dormancy of velvetleaf seeds was revealed through seed vigor determination,water absorption rate determination and germination tests,and the seeds of velvetleaf were treated by physical and chemical methods to explore the best method for breaking dormancy of velvetleaf seeds.[Results]Poor water permeability of seed coat and endogenous inhibitory substances present in the seeds were the main reasons leading to the dormancy of velvetleaf *** shell-breaking treatment,98%concentrated sulfuric acid treatment and 40%NaOH strong alkali treatment all could break the dormancy obstacle of velvetleaf seed *** the above measures with 200 mg/ml gibberellin solution could further improve the germination ability of *** them,compositing the mechanical shell-breaking treatment with gibberellin had the best effect,followed by the composite of 10 and 15 min of 98%concentrated sulfuric acid treatment with gibberellin.[Conclusions]This study lays a foundation for the utilization and development and the comprehensive prevention and control research of velvetleaf seeds.

关键词： velvetleaf Dormancy breaking Seed germination Treatment

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Variations in Growth, Photosynthesis and Defense System Among Four Weed Species Under Increased UV-B Radiation

引用

Journal of Integrative Plant Biology 2007年第5期49卷 621-627页

作者： Shiwen Wang Liusheng Duan Anthony Egrinya Eneji Zhaohu Li State Key Laboratory of Plant Physiology and Biochemistry Centre of Crop Chemical Control Department of Agronomy China Agricultural University Beijing 100094 China

Weed tolerance of UV-B radiation varies with species, and the radiation could affect weed ecology and management. Variations In growth, photosynthesis and defense system among four important agronomic weeds, Abutllon theophrastl Medlk, Amaranthus retroflexus L., Digitaria sanguinalis （L.） Scop and Chloris virgata Swartz, under Increased UV-B radiation （ambient and increased radiation at 2.7, 5.4 and 10.8 kJ.m^-2.d-1） were studied In the greenhouse experiment. After 2 weeks of radiation, the shoots＇ dry mass decreased with increasing UV-B radiation except for D. sanguinalis. The reduction in biomass was the result of changes in morphology and physiology. Higher levels of UV-B treatment decreased the leaf area, plant height, net photosynthetic rate and chlorophyll contents, while it increased the contents of wax and UV-B absorbing compound in all species, except for A. retroflexus, which did not increase significantly. The activity of superoxide dismutase, catalase, ascorbate peroxide and the content of ascorblc acid changed differently among the weed species as UV-B radiation increased. D. sangulnalls was the most tolerant and A. retroflexus the most sensitive to increased UV-B radiation. The results also show that the two grass species （D. sanguinalis and C. virgata） were more tolerant to UV-B radiation than the two broadleafed species （A. theophrasti and A. retroflexus）. The UV-B absorbing compound and leaf wax played Important roles against UV-B damages in the two grass weeds. The overall results suggest that weed community, competition and management will be altered by continuous ozone depletion.

关键词： crabgrass fingergrass leaf wax redroot UV-B absorbing compounds UV-B radiation velvetleaf

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Using Vegetation Indices as Input into Random Forest for Soybean and Weed Classification

引用

American Journal of Plant Sciences 2016年第15期7卷 2186-2198页

作者： Reginald S. Fletcher Crop Production Systems Research Unit Agricultural Research Service United States Department of Agriculture Stoneville USA

Weed management is a major component of a soybean (Glycine max L.) production system;thus, managers need tools to help them distinguish soybean from weeds. Vegetation indices derived from light reflectance properties of plants have shown promise as tools to enhance differences among plants. The objective of this study was to evaluate normalized difference vegetation indices derived from multispectral leaf reflectance data as input into random forest machine learner to differentiate soybean and three broad leaf weeds: Palmer amaranth (Amaranthus palmeri L.), redroot pigweed (A. retroflexus L.), and velvetleaf (Abutilon theophrasti Medik). Leaf reflectance measurements were acquired from plants grown in two separate greenhouse experiments conducted in 2014. Twelve normalized difference vegetation indices were derived from the reflectance measurements, including advanced, green, greenred, green-blue, and normalized difference vegetation indices, shortwave infrared water stress indices, normalized difference pigment and red edge indices, and structure insensitive pigment index. Using the twelve vegetation indices as input variables, the conditional inference version of random forest (cforest) readily distinguished soybean and velvetleaf from the two pigweeds (Palmer amaranth and redroot pigweed) and from each other with classification accuracies ranging from 93.3% to 100%. The greatest errors were observed between the two pigweed classes, with classification accuracies ranging from 70% to 93.3%. Results suggest combining them into one class to increase classification accuracy. Vegetation indices results were equivalent to or slightly better than results obtained with sixteen multispectral bands used as input data into cforest. This research further supports using vegetation indices and machine learning algorithms such as cforest as decision support tools for weed identification.

关键词： Normalized Difference Vegetation Index Palmer Amaranth Redroot Pigweed velvetleaf Remote Sensing

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

欢迎您,

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：