scholarly journals MVS-Pheno: A Portable and Low-Cost Phenotyping Platform for Maize Shoots Using Multiview Stereo 3D Reconstruction

2020 ◽  
Vol 2020 ◽  
pp. 1-17 ◽  
Author(s):  
Sheng Wu ◽  
Weiliang Wen ◽  
Yongjian Wang ◽  
Jiangchuan Fan ◽  
Chuanyu Wang ◽  
...  
Keyword(s):  
Data Management ◽  
High Throughput ◽  
Management System ◽  
Low Cost ◽  
Point Clouds ◽  
Data Management System ◽  
Plant Phenotyping ◽  
Phenotypic Traits ◽  
High Throughput Phenotyping ◽  
Multiview Stereo

Plant phenotyping technologies play important roles in plant research and agriculture. Detailed phenotypes of individual plants can guide the optimization of shoot architecture for plant breeding and are useful to analyze the morphological differences in response to environments for crop cultivation. Accordingly, high-throughput phenotyping technologies for individual plants grown in field conditions are urgently needed, and MVS-Pheno, a portable and low-cost phenotyping platform for individual plants, was developed. The platform is composed of four major components: a semiautomatic multiview stereo (MVS) image acquisition device, a data acquisition console, data processing and phenotype extraction software for maize shoots, and a data management system. The platform’s device is detachable and adjustable according to the size of the target shoot. Image sequences for each maize shoot can be captured within 60-120 seconds, yielding 3D point clouds of shoots are reconstructed using MVS-based commercial software, and the phenotypic traits at the organ and individual plant levels are then extracted by the software. The correlation coefficient (R2) between the extracted and manually measured plant height, leaf width, and leaf area values are 0.99, 0.87, and 0.93, respectively. A data management system has also been developed to store and manage the acquired raw data, reconstructed point clouds, agronomic information, and resulting phenotypic traits. The platform offers an optional solution for high-throughput phenotyping of field-grown plants, which is especially useful for large populations or experiments across many different ecological regions.

Meter Data Management System with Multi-Channel Power Supply and Matrix Electrical Measurements

2013 ◽  
Vol 303-306 ◽  
pp. 995-1001
Author(s):  
Chin Shun Hsu ◽  
Chao Yang Lee ◽  
Feng Sheng Hsu ◽  
Chu Sing Yang
Keyword(s):  
Data Management ◽  
Power Supply ◽  
Management System ◽  
Power Flow ◽  
Low Cost ◽  
Data Management System ◽  
Electrical Measurements ◽  
Channel Power ◽  
Measurement Control ◽  
Switch Circuit

Today, due to the increase in smart grid and DC appliances implement the use of renewable energy, the power consumption of equipment and appliances can be monitored by smart outlet or smart meter. However, if every devices are installed a meter will be very expensive and lack of flexibility. This work proposes a combination of multi-channel power supply and matrix measurement of electrical meter data management system to increase system built facilitate and promote greater consumption analysis flexibility and benefits. The proposed method includes a programmable logic controller (PLC)based Multi-channel power supply switch circuit (MPSC), measurement control circuit and Zigbee intelligent socket (Smart Outlet) for collecting and controlling the power flow with wireless communication. Three types of wireless metering methods are used to compare cost and metering error rate. The experimental results reveal this work can be an efficient and low-cost metering solution.

MEDIC: An on Site Designed Data Management System for Cardiology

1979 ◽  
Vol 18 (04) ◽  
pp. 199-202 ◽  
Author(s):  
F. Lustman ◽  
P. Lanthier ◽  
D. Charbonneau
Keyword(s):  
Data Management ◽  
Management System ◽  
Selection Process ◽  
Low Cost ◽  
Database Management System ◽  
Data Management System ◽  
Data Quality Control ◽  
Data Definition ◽  
And Performance ◽  
Data Independence

A patient-oriented data management system is described. The environment was cardiology with a heavy emphasis on research and the MEDIC system was designed to meet the day to day program needs. The data are organized in speciality files with dynamic patient records composed of subrecords of different types. The schema is described by a data definition language. Application packages include data quality control, medical reporting and general inquiry.After five years of extensive use in various clinical applications, its utility has been assessed as well as its low cost. The disadvantages, the main being the multifile structure, can now be stated as its advantages, like data independence and performance increase. Although the system is now partially outdated, the experience acquired with its use becomes very helpful in the selection process of the future database management system.

scholarly journals Low-Cost Automated Vectors and Modular Environmental Sensors for Plant Phenotyping

Sensors ◽  
2020 ◽  
Vol 20 (11) ◽  
pp. 3319
Author(s):  
Stuart A. Bagley ◽  
Jonathan A. Atkinson ◽  
Henry Hunt ◽  
Michael H. Wilson ◽  
Tony P. Pridmore ◽  
...  
Keyword(s):  
High Throughput ◽  
Low Cost ◽  
Time Lapse ◽  
Plant Phenotyping ◽  
Environmental Sensors ◽  
Controlled Conditions ◽  
Sensor Platform ◽  
High Throughput Phenotyping ◽  
Controlled Environments ◽  
Time Lapse Imaging

High-throughput plant phenotyping in controlled environments (growth chambers and glasshouses) is often delivered via large, expensive installations, leading to limited access and the increased relevance of “affordable phenotyping” solutions. We present two robot vectors for automated plant phenotyping under controlled conditions. Using 3D-printed components and readily-available hardware and electronic components, these designs are inexpensive, flexible and easily modified to multiple tasks. We present a design for a thermal imaging robot for high-precision time-lapse imaging of canopies and a Plate Imager for high-throughput phenotyping of roots and shoots of plants grown on media plates. Phenotyping in controlled conditions requires multi-position spatial and temporal monitoring of environmental conditions. We also present a low-cost sensor platform for environmental monitoring based on inexpensive sensors, microcontrollers and internet-of-things (IoT) protocols.

scholarly journals Novel 3D Imaging Systems for High-Throughput Phenotyping of Plants

2021 ◽  
Vol 13 (11) ◽  
pp. 2113
Author(s):  
Tian Gao ◽  
Feiyu Zhu ◽  
Puneet Paul ◽  
Jaspreet Sandhu ◽  
Henry Akrofi Doku ◽  
...  
Keyword(s):  
3D Reconstruction ◽  
High Throughput ◽  
Imaging System ◽  
Point Clouds ◽  
Imaging Systems ◽  
Phenotypic Traits ◽  
Reconstruction Algorithms ◽  
High Quality ◽  
3D Point Clouds ◽  
High Throughput Phenotyping

The use of 3D plant models for high-throughput phenotyping is increasingly becoming a preferred method for many plant science researchers. Numerous camera-based imaging systems and reconstruction algorithms have been developed for the 3D reconstruction of plants. However, it is still challenging to build an imaging system with high-quality results at a low cost. Useful comparative information for existing imaging systems and their improvements is also limited, making it challenging for researchers to make data-based selections. The objective of this study is to explore the possible solutions to address these issues. We introduce two novel systems for plants of various sizes, as well as a pipeline to generate high-quality 3D point clouds and meshes. The higher accuracy and efficiency of the proposed systems make it a potentially valuable tool for enhancing high-throughput phenotyping by integrating 3D traits for increased resolution and measuring traits that are not amenable to 2D imaging approaches. The study shows that the phenotype traits derived from the 3D models are highly correlated with manually measured phenotypic traits (R2 > 0.91). Moreover, we present a systematic analysis of different settings of the imaging systems and a comparison with the traditional system, which provide recommendations for plant scientists to improve the accuracy of 3D construction. In summary, our proposed imaging systems are suggested for 3D reconstruction of plants. Moreover, the analysis results of the different settings in this paper can be used for designing new customized imaging systems and improving their accuracy.

PRISM: A data management system for high-throughput proteomics

PROTEOMICS ◽  
2006 ◽  
Vol 6 (6) ◽  
pp. 1783-1790 ◽  
Author(s):  
Gary R. Kiebel ◽  
Ken J. Auberry ◽  
Navdeep Jaitly ◽  
David A. Clark ◽  
Matthew E. Monroe ◽  
...  
Keyword(s):  
Data Management ◽  
High Throughput ◽  
Management System ◽  
Data Management System

Design of Smart Healthcare Data Management System Based on Hadoop

2014 ◽  
Vol 998-999 ◽  
pp. 1121-1124 ◽  
Author(s):  
Min Zhang ◽  
Ren Zhang ◽  
Cheng Sheng Liu
Keyword(s):  
Data Management ◽  
Data Storage ◽  
Management System ◽  
Cloud Storage ◽  
Low Cost ◽  
Structural Data ◽  
Data Management System ◽  
Traditional Management ◽  
Healthcare Data ◽  
Smart Healthcare

This paper describes a smart healthcare data management system based on hadoop. Aiming at the disadvantage of Traditional management of medical data such as the increasing cost of consumption and the limited availability of the data, the smart healthcare data management system in this paper introduces a hybrid storage architecture including designs of Structured data storage which supported by RDBMS and Non-structural data storage which supported by Hadoop. This smart healthcare data management system has the advantages of low-cost, high fault tolerance, and scalability, and builds a cloud storage platform applied in the system of smart healthcare.

Sign in / Sign up

Export Citation Format

Share Document