Design and validation of a real-time cassava planter seed quality monitoring system based on optical fiber sensors and rotary encoders

Targeting the issues of seed leakage and cutting segment adhesion due to poor seed feeding and cutting in real-time seed-cutting cassava planters, this study developed a seeding quality monitoring system. Based on the structure and working principle of the seed cutting and discharging device, the installation methods of the matrix fiber optic sensor and rotary encoder were determined. By combining the operational characteristics of the planter's ground wheel drive with seed cutting and seed dropping, a monitoring model correlating the sowing parameters with seed dropping time was established; a monitoring window was created by extracting and processing the rotary encoder pulse signal, and the number of seeds sown after each opposing cutter's operation was calculated based on the pulse width information within the monitoring window. The monitoring system's statistics were compared and analyzed with the manual statistics, and the bench test showed that the monitoring system designed in this study offers high accuracy. When the simulated rotational speed of the opposing cutter ranges from 10 to 30 rpm, the average monitoring error between the monitored and actual seeding quantities for the left and right rows is less than 1.4%. The monitoring system can promptly and accurately activate sound and light alarms for faults, achieving a 100% success rate in alarms and an average fault response time of less than 0.4 seconds. Field tests demonstrate that the average error in seeding volume is 0.91%, and the monitoring system can timely alert to faults occurring in the planter. The system fulfills the requirements for real-time monitoring of cassava seeding volume at various operating speeds in field conditions, and can serve as a reference for monitoring operational parameters in subsequent cassava combine harvesters.

Authors

Institutions

Publication Details

Journal
Frontiers in Plant Science
Published
2024-12-03
DOI
https://doi.org/10.3389/fpls.2024.1481909
Citations
3
Primary Topic
Smart Agriculture and AI
Type
article
Field-Weighted Citation Impact
1.80
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Design and validation of a real-time cassava planter seed quality monitoring system based on optical fiber sensors and rotary encoders

Zhende Cui, Xilin Wang, Fengguang He, Shuang Zheng et al.
3 citations
Frontiers in Plant Science
Smart Agriculture and AI
1.80
article

Design and validation of a real-time cassava planter seed quality monitoring system based on optical fiber sensors and rotary encoders

Zhende Cui, Xilin Wang, Fengguang He, Shuang Zheng, Ganran Deng, Pinlan Chen, Ye Dai, Bin Yan, Ling Li, Guojie Li, Shuangmei Qin, Sili Zhou, Zehua Liu
article en
3 citations

Abstract

Targeting the issues of seed leakage and cutting segment adhesion due to poor seed feeding and cutting in real-time seed-cutting cassava planters, this study developed a seeding quality monitoring system. Based on the structure and working principle of the seed cutting and discharging device, the installation methods of the matrix fiber optic sensor and rotary encoder were determined. By combining the operational characteristics of the planter's ground wheel drive with seed cutting and seed dropping, a monitoring model correlating the sowing parameters with seed dropping time was established; a monitoring window was created by extracting and processing the rotary encoder pulse signal, and the number of seeds sown after each opposing cutter's operation was calculated based on the pulse width information within the monitoring window. The monitoring system's statistics were compared and analyzed with the manual statistics, and the bench test showed that the monitoring system designed in this study offers high accuracy. When the simulated rotational speed of the opposing cutter ranges from 10 to 30 rpm, the average monitoring error between the monitored and actual seeding quantities for the left and right rows is less than 1.4%. The monitoring system can promptly and accurately activate sound and light alarms for faults, achieving a 100% success rate in alarms and an average fault response time of less than 0.4 seconds. Field tests demonstrate that the average error in seeding volume is 0.91%, and the monitoring system can timely alert to faults occurring in the planter. The system fulfills the requirements for real-time monitoring of cassava seeding volume at various operating speeds in field conditions, and can serve as a reference for monitoring operational parameters in subsequent cassava combine harvesters.

Frontiers in Plant ScienceVol. 15
Chinese Academy of Tropical Agricultural Sciences (CN), Ministry of Agriculture and Rural Affairs (CN)
Openalex Percentile: Top 12%
Smart Agriculture and AI
1.80
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.