Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Brian Krienke"'
Autor:
Jie Jiang, Zeyu Zhang, Qiang Cao, Yan Liang, Brian Krienke, Yongchao Tian, Yan Zhu, Weixing Cao, Xiaojun Liu
Publikováno v:
Remote Sensing, Vol 12, Iss 22, p 3684 (2020)
Using remote sensing to rapidly acquire large-area crop growth information (e.g., shoot biomass, nitrogen status) is an urgent demand for modern crop production; unmanned aerial vehicle (UAV) acts as an effective monitoring platform. In order to impr
Externí odkaz:
https://doaj.org/article/5060fca76ab74d1fb6a4f808caaa2c49
Autor:
Zhaopeng Fu, Jie Jiang, Yang Gao, Brian Krienke, Meng Wang, Kaitai Zhong, Qiang Cao, Yongchao Tian, Yan Zhu, Weixing Cao, Xiaojun Liu
Publikováno v:
Remote Sensing, Vol 12, Iss 3, p 508 (2020)
Leaf area index (LAI) and leaf dry matter (LDM) are important indices of crop growth. Real-time, nondestructive monitoring of crop growth is instructive for the diagnosis of crop growth and prediction of grain yield. Unmanned aerial vehicle (UAV)-bas
Externí odkaz:
https://doaj.org/article/fea8f633451b4cc68c44200fa292ff50
Autor:
Ke Zhang, Xiaojun Liu, Syed Tahir Ata-Ul-Karim, Jingshan Lu, Brian Krienke, Songyang Li, Qiang Cao, Yan Zhu, Weixing Cao, Yongchao Tian
Publikováno v:
Agronomy, Vol 9, Iss 2, p 106 (2019)
Accurate estimation of the nitrogen (N) spatial distribution of rice (Oryza sativa L.) is imperative when it is sought to maintain regional and global carbon balances. We systematically evaluated the normalized differences of the soil and plant analy
Externí odkaz:
https://doaj.org/article/4347a16e588b42629d047d0567a6cde0
Publikováno v:
Precision Agriculture. 23:830-853
Remote sensing data from optical canopy sensors has been successfully used for precision nitrogen (N) management. This study aimed to explore the potential of multispectral camera mounted on fixed-wing unmanned aerial vehicle (UAV) in guiding in-seas
Publikováno v:
Computers and Electronics in Agriculture. 162:154-164
The interpretation of optical canopy sensor readings for determining optimal rates of late-season site-specific nitrogen application to corn (Zea mays L.) can be complicated by spatially variable water sufficiency, which can also affect canopy size a
Autor:
Meng Wang, Yang Gao, Kaitai Zhong, Brian Krienke, Xiaojun Liu, Qiang Cao, Weixing Cao, Jie Jiang, Yongchao Tian, Zhaopeng Fu, Yan Zhu
Publikováno v:
Remote Sensing, Vol 12, Iss 3, p 508 (2020)
Remote Sensing; Volume 12; Issue 3; Pages: 508
Remote Sensing; Volume 12; Issue 3; Pages: 508
Leaf area index (LAI) and leaf dry matter (LDM) are important indices of crop growth. Real-time, nondestructive monitoring of crop growth is instructive for the diagnosis of crop growth and prediction of grain yield. Unmanned aerial vehicle (UAV)-bas
Autor:
Randy Saner, Eric Henning, Amy M. Schmidt, Sarah Sivits, Todd Whitney, Agustin Jose Olivo, Gary Lesoing, Richard K. Koelsch, Aaron Nygren, Larry Howard, Troy Ingram, Brian Krienke, Amy D. Timmerman
Publikováno v:
2020 ASABE Annual International Virtual Meeting, July 13-15, 2020.
In nearly every production environment, there are opportunities to capture profits if waste streams can be further processed or enhanced to create “value added” products. This study investigated the impacts on soil characteristics and crop produc
Autor:
Richard B. Ferguson, Brian Krienke, Kyle H. Holland, Michael Schlemmer, David B. Marx, Kent M. Eskridge
Publikováno v:
Precision Agriculture. 18:900-915
Ground-based active sensors have been used in the past with success in detecting nitrogen (N) variability within maize production systems. The use of unmanned aerial vehicles (UAVs) presents an opportunity to evaluate N variability with unique advant
Autor:
Xiaojun Liu, Ke Zhang, Weixing Cao, Qiang Cao, Syed Tahir Ata-Ul-Karim, Yongchao Tian, Yan Zhu, Jingshan Lu, Songyang Li, Brian Krienke
Publikováno v:
Agronomy, Vol 9, Iss 2, p 106 (2019)
Agronomy
Volume 9
Issue 2
Agronomy
Volume 9
Issue 2
Accurate estimation of the nitrogen (N) spatial distribution of rice (Oryza sativa L.) is imperative when it is sought to maintain regional and global carbon balances. We systematically evaluated the normalized differences of the soil and plant analy
Autor:
Brian Krienke, Zeyu Zhang, Weixing Cao, Yan Liang, Qiang Cao, Yongchao Tian, Xiaojun Liu, Jie Jiang, Yan Zhu
Publikováno v:
Remote Sensing, Vol 12, Iss 3684, p 3684 (2020)
Remote Sensing
Volume 12
Issue 22
Pages: 3684
Remote Sensing
Volume 12
Issue 22
Pages: 3684
Using remote sensing to rapidly acquire large-area crop growth information (e.g., shoot biomass, nitrogen status) is an urgent demand for modern crop production; unmanned aerial vehicle (UAV) acts as an effective monitoring platform. In order to impr