PMID- 30513952
OWN - NLM
STAT- PubMed-not-MEDLINE
DCOM- 20181217
LR  - 20200225
IS  - 1424-8220 (Electronic)
IS  - 1424-8220 (Linking)
VI  - 18
IP  - 12
DP  - 2018 Dec 3
TI  - A Real-Time Weed Mapping and Precision Herbicide Spraying System for Row Crops.
LID - 10.3390/s18124245 [doi]
LID - 4245
AB  - This study developed and field tested an automated weed mapping and variable-rate 
      herbicide spraying (VRHS) system for row crops. Weed detection was performed 
      through a machine vision sub-system that used a custom threshold segmentation 
      method, an improved particle swarm optimum (IPSO) algorithm, capable of 
      segmenting the field images. The VRHS system also used a lateral histogram-based 
      algorithm for fast extraction of weed maps. This was the basis for determining 
      real-time herbicide application rates. The central processor of the VRHS system 
      had high logic operation capacity, compared to the conventional controller-based 
      systems. Custom developed monitoring system allowed real-time visualization of 
      the spraying system functionalities. Integrated system performance was then 
      evaluated through field experiments. The IPSO successfully segmented weeds within 
      corn crop at seedling growth stage and reduced segmentation error rates to 0.1% 
      from 7.1% of traditional particle swarm optimization algorithm. IPSO processing 
      speed was 0.026 s/frame. The weed detection to chemical actuation response time 
      of integrated system was 1.562 s. Overall, VRHS system met the real-time data 
      processing and actuation requirements for its use in practical weed management 
      applications.
FAU - Xu, Yanlei
AU  - Xu Y
AUID- ORCID: 0000-0002-9447-7242
AD  - College of Information and Technology, JiLin Agricultural University, Changchun 
      130118, China. yanleixu@163.com.
AD  - Department of Biological Systems Engineering, Centre for Precision and Automated 
      Agricultural Systems, Washington State University, Prosser, WA 99350, USA. 
      yanleixu@163.com.
FAU - Gao, Zongmei
AU  - Gao Z
AD  - Department of Biological Systems Engineering, Centre for Precision and Automated 
      Agricultural Systems, Washington State University, Prosser, WA 99350, USA. 
      zongmei.gao@wsu.edu.
FAU - Khot, Lav
AU  - Khot L
AD  - Department of Biological Systems Engineering, Centre for Precision and Automated 
      Agricultural Systems, Washington State University, Prosser, WA 99350, USA. 
      lav.khot@wsu.edu.
FAU - Meng, Xiaotian
AU  - Meng X
AD  - College of Information and Technology, JiLin Agricultural University, Changchun 
      130118, China. mengxiaotian11@163.com.
FAU - Zhang, Qin
AU  - Zhang Q
AD  - Department of Biological Systems Engineering, Centre for Precision and Automated 
      Agricultural Systems, Washington State University, Prosser, WA 99350, USA. 
      qinzhang@wsu.edu.
LA  - eng
GR  - 31801753/National Natural Science Foundation of China/
PT  - Journal Article
DEP - 20181203
PL  - Switzerland
TA  - Sensors (Basel)
JT  - Sensors (Basel, Switzerland)
JID - 101204366
PMC - PMC6308525
OTO - NOTNLM
OT  - particle swarm optimum algorithm
OT  - smart controller
OT  - variable-rate herbicide spraying
OT  - weed map
COIS- The authors declare no conflict of interest.
EDAT- 2018/12/06 06:00
MHDA- 2018/12/06 06:01
PMCR- 2018/12/01
CRDT- 2018/12/06 06:00
PHST- 2018/10/26 00:00 [received]
PHST- 2018/11/22 00:00 [revised]
PHST- 2018/11/29 00:00 [accepted]
PHST- 2018/12/06 06:00 [entrez]
PHST- 2018/12/06 06:00 [pubmed]
PHST- 2018/12/06 06:01 [medline]
PHST- 2018/12/01 00:00 [pmc-release]
AID - s18124245 [pii]
AID - sensors-18-04245 [pii]
AID - 10.3390/s18124245 [doi]
PST - epublish
SO  - Sensors (Basel). 2018 Dec 3;18(12):4245. doi: 10.3390/s18124245.