Login
Toggle navigation
Home
ICPA
Conference
Abstract Management
Abstract Topic Groups
Author Instructions
Registration
Registration Information
16th ICPA - Conference Registration
Registrants Map
Hotel and Travel Information
Tour
Workshops
Exhibit Hall Map
Sponsors
Conference Program
General Outline
Oral Program
Poster Program
Student Poster Awards
Keynote
Plenary Session
Awards
Photos
Conference Survey
Proceedings
Leadership
ISPA Leadership
Officers
Past Presidents
Officer Responsibilities
Country Representatives
Communities
Community Guidance
On-Farm Experimentation
Nitrogen
Latin America
Economics
African Association for Precision Agriculture
Membership
ISPA Member Benefits
Membership Form
Events
ISPA Events
ACPA
ACPA Proceedings
AfCPA
AfCPA Proceedings
CLAP
CLAP Proceedings
ECPA
ECPA Proceedings
ICPA
ISPA Webinars
OFE
AAPA
Latin American
Robotics and Automation Symposium
Event Overview
Registration
Program
Venue
Speakers
About ISPA
Newsletters
History
Jobs
Precision Ag Definition
Agriculture Course Database Submission
Publications
ICPA Proceedings
ECPA Proceedings
Contact Us
Members
Suggestion Form
Conference
Abstract Management
Abstract Topic Groups
Author Instructions
Registration
Registration Information
16th ICPA - Conference Registration
Registrants Map
Hotel and Travel Information
Tour
Workshops
Exhibit Hall Map
Sponsors
Conference Program
General Outline
Oral Program
Poster Program
Student Poster Awards
Keynote
Plenary Session
Awards
Photos
Conference Survey
Proceedings
Proceedings
Search
Authors
Topics
Years
Types
Find matching any:
Reset
» Add more topics
Add filter to result:
In-Field Corn Stalk Location Using Rapid Line-Scan Technique
Y. Shi, N. Wang
Ms.
Corn plant spacing and population information is important in assessing planter performance and making decisions on field operations. The objective in this study was to investigate the potential of using laser line-scan sensing technique to locate corn plant stalks on-the-go. A mobile test platform equipped with a commercial laser line scanner, an encoder, a DAQ card, a PC and a RGB camera was constructed. Data was collected for two 10m corn rows at their middle growth stages - V8 and V10 - in Lake Carl Blackwell Agronomy Farm of Oklahoma State University, and was processed later in lab with algorithms developed to recognize and locate stalks. A 4% of mean false negative error and a 29% of mean false positive error at growth stage V8, a 6.7% of mean false positive error and a 12.7% mean false positive error at growth stage V10 were achieved. The system setup and data processing algorithms in this study can be integrated into the variable-rate-spray system to help improving real-time, high spatial resolution variable rate application and increasing the nitrogen use efficiency.
Keyword
: Corn, plant population, plant spacing, laser line scanner
Y. Shi
N. Wang
Sensor Application in Managing In-season Crop Variability
Poster
2012
Download paper