scholarly journals CoverageTool: A semi-automated graphic software: applications for plant phenotyping

Plant Methods ◽  
2019 ◽  
Vol 15 (1) ◽  
Author(s):  
Lianne Merchuk-Ovnat ◽  
Zev Ovnat ◽  
Orit Amir-Segev ◽  
Yaarit Kutsher ◽  
Yehoshua Saranga ◽  
...  
Keyword(s):  
Plant Phenotyping ◽  
Software Applications ◽  
Graphic Software

scholarly journals Parametric integration of design features selection with recording of construction of working machines

2021 ◽  
Vol 338 ◽  
pp. 01008
Author(s):  
Piotr Gendarz
Keyword(s):  
Market Economy ◽  
Specific Class ◽  
Features Selection ◽  
Design Features ◽  
Software Applications ◽  
Graphic Program ◽  
Graphic Software ◽  
Parametric Integration ◽  
Design And Construction

Adaptation of the graphic program for constructing of a specific class of technical means, being the specialty of the design and construction office, is the basic challenge of the market economy. This office that prepares the offer and then the competitive construction of the technical means in the shortest possible time as a result obtains the order. This effect is enabled by graphic software applications.

Determining institutional discrepancies for ERM software applications

2115 ◽  
Author(s):  
Özlem (Gökkurt) Bayram ◽  
Fahrettin Özdemirci ◽  
M. Taylan Güvercin
Keyword(s):  
Software Applications

Web Services Architecture Model to Support Distributed Systems

2019 ◽  
Vol 54 (6) ◽  
Author(s):  
Sawsan Ali Hamid ◽  
Rana Alauldeen Abdalrahman ◽  
Inam Abdullah Lafta ◽  
Israa Al Barazanchi
Keyword(s):  
Web Services ◽  
Web Service ◽  
Distributed System ◽  
Modern Technology ◽  
Service Description ◽  
Architecture Model ◽  
Software Applications ◽  
Evolving Model ◽  
The Web

Recently, web services have presented a new and evolving model for constructing the distributed system. The meteoric growth of the Web over the last few years proves the efficacy of using simple protocols over the Internet as the basis for a large number of web services and applications. Web service is a modern technology of web, which can be defined as software applications with a programmatic interface based on Internet protocol. Web services became common in the applications of the web by the help of Universal, Description, Discovery and Integration; Web Service Description Language and Simple Object Access Protocol. The architecture of web services refers to a collection of conceptual components in which common sets of standard can be defined among interoperating components. Nevertheless, the existing Web service's architecture is not impervious to some challenges, such as security problems, and the quality of services. Against this backdrop, the present study will provide an overview of these issues. Therefore, it aims to propose web services architecture model to support distributed system in terms of application and issues.

scholarly journals The Performances of Hyperspectral Sensors for Proximal Sensing of Nitrogen Levels in Wheat

Sensors ◽  
2020 ◽  
Vol 20 (16) ◽  
pp. 4550
Author(s):  
Huajian Liu ◽  
Brooke Bruning ◽  
Trevor Garnett ◽  
Bettina Berger
Keyword(s):  
Hyperspectral Imaging ◽  
High Throughput ◽  
Management Practices ◽  
Leaf Tissue ◽  
Plant Phenotyping ◽  
Proximal Sensing ◽  
N Content ◽  
Hyperspectral Sensors ◽  
Wheat Leaves ◽  
Non Destructive

The accurate and high throughput quantification of nitrogen (N) content in wheat using non-destructive methods is an important step towards identifying wheat lines with high nitrogen use efficiency and informing agronomic management practices. Among various plant phenotyping methods, hyperspectral sensing has shown promise in providing accurate measurements in a fast and non-destructive manner. Past applications have utilised non-imaging instruments, such as spectrometers, while more recent approaches have expanded to hyperspectral cameras operating in different wavelength ranges and at various spectral resolutions. However, despite the success of previous hyperspectral applications, some important research questions regarding hyperspectral sensors with different wavelength centres and bandwidths remain unanswered, limiting wide application of this technology. This study evaluated the capability of hyperspectral imaging and non-imaging sensors to estimate N content in wheat leaves by comparing three hyperspectral cameras and a non-imaging spectrometer. This study answered the following questions: (1) How do hyperspectral sensors with different system setups perform when conducting proximal sensing of N in wheat leaves and what aspects have to be considered for optimal results? (2) What types of photonic detectors are most sensitive to N in wheat leaves? (3) How do the spectral resolutions of different instruments affect N measurement in wheat leaves? (4) What are the key-wavelengths with the highest correlation to N in wheat? Our study demonstrated that hyperspectral imaging systems with satisfactory system setups can be used to conduct proximal sensing of N content in wheat with sufficient accuracy. The proposed approach could reduce the need for chemical analysis of leaf tissue and lead to high-throughput estimation of N in wheat. The methodologies here could also be validated on other plants with different characteristics. The results can provide a reference for users wishing to measure N content at either plant- or leaf-scales using hyperspectral sensors.

scholarly journals Maize-IAS: a maize image analysis software using deep learning for high-throughput plant phenotyping

Plant Methods ◽  
2021 ◽  
Vol 17 (1) ◽  
Author(s):  
Shuo Zhou ◽  
Xiujuan Chai ◽  
Zixuan Yang ◽  
Hongwu Wang ◽  
Chenxue Yang ◽  
...  
Keyword(s):  
Computer Vision ◽  
Image Analysis ◽  
Deep Learning ◽  
High Throughput ◽  
Batch Processing ◽  
Plant Phenotyping ◽  
Plant Science ◽  
Analysis Software ◽  
Image Analysis Software ◽  
Maize Growth

Abstract Background Maize (Zea mays L.) is one of the most important food sources in the world and has been one of the main targets of plant genetics and phenotypic research for centuries. Observation and analysis of various morphological phenotypic traits during maize growth are essential for genetic and breeding study. The generally huge number of samples produce an enormous amount of high-resolution image data. While high throughput plant phenotyping platforms are increasingly used in maize breeding trials, there is a reasonable need for software tools that can automatically identify visual phenotypic features of maize plants and implement batch processing on image datasets. Results On the boundary between computer vision and plant science, we utilize advanced deep learning methods based on convolutional neural networks to empower the workflow of maize phenotyping analysis. This paper presents Maize-IAS (Maize Image Analysis Software), an integrated application supporting one-click analysis of maize phenotype, embedding multiple functions: (I) Projection, (II) Color Analysis, (III) Internode length, (IV) Height, (V) Stem Diameter and (VI) Leaves Counting. Taking the RGB image of maize as input, the software provides a user-friendly graphical interaction interface and rapid calculation of multiple important phenotypic characteristics, including leaf sheath points detection and leaves segmentation. In function Leaves Counting, the mean and standard deviation of difference between prediction and ground truth are 1.60 and 1.625. Conclusion The Maize-IAS is easy-to-use and demands neither professional knowledge of computer vision nor deep learning. All functions for batch processing are incorporated, enabling automated and labor-reduced tasks of recording, measurement and quantitative analysis of maize growth traits on a large dataset. We prove the efficiency and potential capability of our techniques and software to image-based plant research, which also demonstrates the feasibility and capability of AI technology implemented in agriculture and plant science.

scholarly journals Enabling Knowledge Sharing within e-Government Back-Office through Ontological Engineering

2007 ◽  
Vol 2 (1) ◽  
pp. 33-48
Author(s):  
Graciela Brusa ◽  
María Laura Caliusco ◽  
Omar Chiotti
Keyword(s):  
Organizational Innovation ◽  
Santa Fe ◽  
Ontological Engineering ◽  
The Public ◽  
Software Applications ◽  
Process Characteristics ◽  
Main Requirement ◽  
The Government ◽  
Back Office

Nowadays, organizational innovation constitutes the government challenges for providing better and more efficient services to citizens, enterprises or other public offices. E–government seems to be an excellent opportunity to work on this way. The applications that support front-end services delivered to users have to access information systems of multiple government areas. This is a significant problem for e-government back-office since multiple platforms and technologies coexist. Moreover, in the back-office there is a great volume of data that is implicit in the software applications that support administration activities. In this context, the main requirement is to make available the data managed in the back-office for the e-government users in a fast and precise way, without misunderstanding. To this aim, it is necessary to provide an infrastructure that make explicit the knowledge stored in different government areas and deliver this knowledge to the users. This paper presents an approach on how ontological engineering techniques can be applied to solving the problems of content discovery, aggregation, and sharing in the e-government back-office. This approach is constituted by a specific process to develop an ontology in the public sector and an ontology-based architecture. In order to present the process characteristics, a case study applied to a local government domain is analyzed. This domain is the budget and financial information of Santa Fe Province (Argentine).

State-of-the-art of graphic software packages

1977 ◽  
Vol 11 (3) ◽  
pp. 1-117 ◽  
Author(s):  
Compuater Graphics staff
Keyword(s):  
State Of The Art ◽  
Software Packages ◽  
Graphic Software
Sign in / Sign up

Export Citation Format

Share Document