Open Access. Powered by Scholars. Published by Universities.®

Engineering Commons

Open Access. Powered by Scholars. Published by Universities.®

University of Nebraska - Lincoln

Biological Systems Engineering: Papers and Publications

Civil and Environmental Engineering

UAV

Publication Year

Articles 1 - 4 of 4

Full-Text Articles in Engineering

Estimation Of Cotton Canopy Parameters Based On Unmanned Aerial Vehicle (Uav) Oblique Photography, Jinyong Wu, Sheng Wen, Yubin Lan, Xuanchun Yin, Jiantao Zhang, Yufeng Ge Dec 2022

Estimation Of Cotton Canopy Parameters Based On Unmanned Aerial Vehicle (Uav) Oblique Photography, Jinyong Wu, Sheng Wen, Yubin Lan, Xuanchun Yin, Jiantao Zhang, Yufeng Ge

Biological Systems Engineering: Papers and Publications

Background: The technology of cotton defoliation is essential for mechanical cotton harvesting. Agricultural unmanned aerial vehicle (UAV) spraying has the advantages of low cost, high efficiency and no mechanical damage to cotton and has been favored and widely used by cotton planters in China. However, there are also some problems of low cotton defoliation rates and high impurity rates caused by unclear spraying amounts of cotton defoliants. The chemical rate recommendation and application should be based upon crop canopy volume rather than on land area. Plant height and leaf area index (LAI) is directly connected to plant canopy structure. …


Design Of Plant Protection Uav Variable Spray System Based On Neural Networks, Sheng Wen, Quanyong Zhang, Xuanchun Yin, Yubin Lan, Jiantao Zhang, Yufeng Ge Jan 2019

Design Of Plant Protection Uav Variable Spray System Based On Neural Networks, Sheng Wen, Quanyong Zhang, Xuanchun Yin, Yubin Lan, Jiantao Zhang, Yufeng Ge

Biological Systems Engineering: Papers and Publications

Recently, unmanned aerial vehicles (UAVs) have rapidly emerged as a new technology in the fields of plant protection and pest control in China. Based on existing variable spray research, a plant protection UAV variable spray system integrating neural network based decision making is designed. Using the existing data on plant protection UAV operations, combined with artificial neural network (ANN) technology, an error back propagation (BP) neural network model between the factors affecting droplet deposition is trained. The factors affecting droplet deposition include ambient temperature, ambient humidity, wind speed, flight speed, flight altitude, propeller pitch, nozzles pitch and prescription value. Subsequently, …


Rapeseed Seedling Stand Counting And Seeding Performance Evaluation At Two Early Growth Stages Based On Unmanned Aerial Vehicle Imagery, Biquan Zhao, Jian Zhang, Chenghai Yang, Guangsheng Zhou, Youchun Ding, Yeyin Shi, Dongyan Zhang, Jing Xie, Qingxi Liao Jan 2019

Rapeseed Seedling Stand Counting And Seeding Performance Evaluation At Two Early Growth Stages Based On Unmanned Aerial Vehicle Imagery, Biquan Zhao, Jian Zhang, Chenghai Yang, Guangsheng Zhou, Youchun Ding, Yeyin Shi, Dongyan Zhang, Jing Xie, Qingxi Liao

Biological Systems Engineering: Papers and Publications

The development of unmanned aerial vehicles (UAVs) and image processing algorithms for field-based phenotyping offers a non-invasive and effective technology to obtain plant growth traits such as canopy cover and plant height in fields. Crop seedling stand count in early growth stages is important not only for determining plant emergence, but also for planning other related agronomic practices. The main objective of this research was to develop practical and rapid remote sensing methods for early growth stage stand counting to evaluate mechanically seeded rapeseed (Brassica napus L.) seedlings. Rapeseed was seeded in a field by three different seeding devices. A …


Rapeseed Seedling Stand Counting And Seeding Performance Evaluation At Two Early Growth Stages Based On Unmanned Aerial Vehicle Imagery, Biquan Zhao, Jian Zhang, Chenghai Yang, Guangsheng Zhou, Youchun Ding, Yeyin Shi, Dongyan Zhang, Jing Xie, Qingxi Liao Jan 2018

Rapeseed Seedling Stand Counting And Seeding Performance Evaluation At Two Early Growth Stages Based On Unmanned Aerial Vehicle Imagery, Biquan Zhao, Jian Zhang, Chenghai Yang, Guangsheng Zhou, Youchun Ding, Yeyin Shi, Dongyan Zhang, Jing Xie, Qingxi Liao

Biological Systems Engineering: Papers and Publications

The development of unmanned aerial vehicles (UAVs) and image processing algorithms for field-based phenotyping offers a non-invasive and effective technology to obtain plant growth traits such as canopy cover and plant height in fields. Crop seedling stand count in early growth stages is important not only for determining plant emergence, but also for planning other related agronomic practices. The main objective of this research was to develop practical and rapid remote sensing methods for early growth stage stand counting to evaluate mechanically seeded rapeseed (Brassica napus L.) seedlings. Rapeseed was seeded in a field by three different seeding devices. A …