Field-based crop phenotyping: Multispectral aerial imaging for evaluation of winter wheat emergence and spring stand

被引:96
作者
Sankaran, Sindhuja [1 ]
Khot, Lav R. [1 ,2 ]
Carter, Arron H. [3 ]
机构
[1] Washington State Univ, Dept Biol Syst Engn, Pullman, WA 99164 USA
[2] Washington State Univ, Irrigated Agr Res & Extens Ctr, Ctr Precis & Automated Agr Syst, Prosser, WA 99350 USA
[3] Washington State Univ, Dept Crop & Soil Sci, Pullman, WA 99164 USA
基金
美国食品与农业研究所;
关键词
Plant breeding; Unmanned aerial vehicles; Remote sensing; Crop growth; CONVENTIONAL TILLAGE SYSTEMS; NO-TILL; BLOCK-DESIGNS; TEMPERATURE; VEGETATION; TRIALS; INDEX; SOIL;
D O I
10.1016/j.compag.2015.09.001
中图分类号
S [农业科学];
学科分类号
09 ;
摘要
The physical growing environment of winter wheat can critically be affected by micro-climatic and seasonal changes in a given agroclimatic zone. Therefore, winter wheat breeding efforts across the globe focus heavily on emergence and winter survival, as these traits must first be accomplished before yield potential can be evaluated. In this study, multispectral imaging using unmanned aerial vehicle was investigated for evaluation of seedling emergence and spring stand (an estimate of winter survival) of three winter wheat market classes in Washington State. The studied market classes were soft white club, hard red, and soft white winter wheat varieties. Strong correlation between the ground-truth and aerial image-based emergence (Pearson correlation coefficient, r = 0.87) and spring stand (r = 0.86) estimates was established. Overall, aerial sensing technique can be a useful tool to evaluate emergence and spring stand phenotypic traits. Also, the image database can serve as a virtual record during winter wheat variety development and may be used to evaluate the variety performance over the study years. (C) 2015 Elsevier B.V. All rights reserved.
引用
收藏
页码:372 / 379
页数:8
相关论文
共 33 条
[1]  
Carver BF, 2009, Wheat science and trade
[2]   Proximal Remote Sensing Buggies and Potential Applications for Field-Based Phenotyping [J].
Deery, David ;
Jimenez-Berni, Jose ;
Jones, Hamlyn ;
Sirault, Xavier ;
Furbank, Robert .
AGRONOMY-BASEL, 2014, 4 (03) :349-379
[3]   Imaging plants dynamics in heterogenic environments [J].
Fiorani, Fabio ;
Rascher, Uwe ;
Jahnke, Siegfried ;
Schurr, Ulrich .
CURRENT OPINION IN BIOTECHNOLOGY, 2012, 23 (02) :227-235
[4]  
Girl G.S., 2003, CROP SCI, V43, P2135
[5]   Wide dynamic range vegetation index for remote quantification of biophysical characteristics of vegetation [J].
Gitelson, AA .
JOURNAL OF PLANT PHYSIOLOGY, 2004, 161 (02) :165-173
[6]   Small-Scale Remotely Piloted Vehicles in Environmental Research [J].
Hardin, Perry J. ;
Hardin, Thomas J. .
GEOGRAPHY COMPASS, 2010, 4 (09) :1297-1311
[7]  
Hasslen D.A., 1995, WASHINGTON AGR STAT
[8]   Wheat Cultivar Performance and Stability between No-Till and Conventional Tillage Systems in the Pacific Northwest of the United States [J].
Higginbotham, Ryan W. ;
Jones, Stephen S. ;
Carter, Arron H. .
SUSTAINABILITY, 2013, 5 (03) :882-895
[9]   Adaptability of Wheat Cultivars to a Late-Planted No-Till Fallow Production System [J].
Higginbotham, Ryan W. ;
Jones, Stephen S. ;
Carter, Arron H. .
SUSTAINABILITY, 2011, 3 (08) :1224-1233
[10]   A visible band index for remote sensing leaf chlorophyll content at the canopy scale [J].
Hunt, E. Raymond, Jr. ;
Doraiswamy, Paul C. ;
McMurtrey, James E. ;
Daughtry, Craig S. T. ;
Perry, Eileen M. ;
Akhmedov, Bakhyt .
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION, 2013, 21 :103-112