Next Article in Journal
Alleviate Similar Object in Visual Tracking via Online Learning Interference-Target Spatial Structure
Previous Article in Journal
Modified Gray-Level Coding Method for Absolute Phase Retrieval
Previous Article in Special Issue
Validation of a CFD Model by Using 3D Sonic Anemometers to Analyse the Air Velocity Generated by an Air-Assisted Sprayer Equipped with Two Axial Fans
Article Menu
Issue 10 (October) cover image

Export Article

Open AccessArticle
Sensors 2017, 17(10), 2381; doi:10.3390/s17102381

Optical Sensing of Weed Infestations at Harvest

1
Columbia Basin Agricultural Research Center, Oregon State University, Adams, OR 97810, USA
2
Soil and Water Conservation Research Unit, Agricultural Research Service (USDA-ARS), Adams, OR 97810, USA
*
Author to whom correspondence should be addressed.
Received: 24 August 2017 / Revised: 23 September 2017 / Accepted: 10 October 2017 / Published: 19 October 2017
(This article belongs to the Special Issue Sensors in Agriculture and Forestry)
View Full-Text   |   Download PDF [1650 KB, uploaded 19 October 2017]   |  

Abstract

Kochia (Kochia scoparia L.), Russian thistle (Salsola tragus L.), and prickly lettuce (Lactuca serriola L.) are economically important weeds infesting dryland wheat (Triticum aestivum L.) production systems in the western United States. Those weeds produce most of their seeds post-harvest. The objectives of this study were to determine the ability of an optical sensor, installed for on-the-go measurement of grain protein concentration, to detect the presence of green plant matter in flowing grain and assess the potential usefulness of this information for mapping weeds at harvest. Spectra of the grain stream were recorded continuously at a rate of 0.33 Hz during harvest of two spring wheat fields of 1.9 and 5.4 ha. All readings were georeferenced using a Global Positioning System (GPS) receiver with 1 m positional accuracy. Chlorophyll of green plant matter was detectable in the red (638–710 nm) waveband. Maps of the chlorophyll signal from both fields showed an overall agreement of 78.1% with reference maps, one constructed prior to harvest and the other at harvest time, both based on visual evaluations of the three green weed species conducted by experts. Information on weed distributions at harvest may be useful for controlling post-harvest using variable rate technology for herbicide applications. View Full-Text
Keywords: weed mapping; on-line optical sensing; site-specific weed management weed mapping; on-line optical sensing; site-specific weed management
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Barroso, J.; McCallum, J.; Long, D. Optical Sensing of Weed Infestations at Harvest. Sensors 2017, 17, 2381.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top