Follow
David Deery
David Deery
Verified email at csiro.au
Title
Cited by
Cited by
Year
Proximal remote sensing buggies and potential applications for field-based phenotyping
D Deery, J Jimenez-Berni, H Jones, X Sirault, R Furbank
Agronomy 4 (3), 349-379, 2014
3782014
High throughput determination of plant height, ground cover, and above-ground biomass in wheat with LiDAR
JA Jimenez-Berni, DM Deery, P Rozas-Larraondo, ATG Condon, ...
Frontiers in plant science 9, 237, 2018
2182018
Methodology for high-throughput field phenotyping of canopy temperature using airborne thermography
DM Deery, GJ Rebetzke, JA Jimenez-Berni, RA James, AG Condon, ...
Frontiers in plant science 7, 1808, 2016
1312016
Field crop phenomics: enabling breeding for radiation use efficiency and biomass in cereal crops
RT Furbank, JA Jimenez‐Berni, B George‐Jaeggli, AB Potgieter, ...
New Phytologist 223 (4), 1714-1727, 2019
1262019
A multisite managed environment facility for targeted trait and germplasm phenotyping
EGBLJEM Greg J. Rebetzke, Karine Chenu, Ben Biddulph, Carina Moeller, Dave M ...
Functional Plant Biology 40 (1), 1-13, 2013
115*2013
High-throughput phenotyping technologies allow accurate selection of stay-green
GJ Rebetzke, JA Jimenez-Berni, WD Bovill, DM Deery, RA James
Journal of experimental botany 67 (17), 4919-4924, 2016
852016
High-throughput phenotyping to enhance the use of crop genetic resources
GJ Rebetzke, J Jimenez-Berni, RA Fischer, DM Deery, DJ Smith
Plant Science 282, 40-48, 2019
792019
A practical method using a network of fixed infrared sensors for estimating crop canopy conductance and evaporation rate
HG Jones, PA Hutchinson, T May, H Jamali, DM Deery
biosystems engineering 165, 59-69, 2018
452018
Genetic variation for photosynthetic capacity and efficiency in spring wheat
V Silva-Pérez, J De Faveri, G Molero, DM Deery, AG Condon, ...
Journal of Experimental Botany 71 (7), 2299-2311, 2020
432020
Evaluation of the phenotypic repeatability of canopy temperature in wheat using continuous-terrestrial and airborne measurements
DM Deery, GJ Rebetzke, JA Jimenez-Berni, WD Bovill, RA James, ...
Frontiers in Plant Science 10, 875, 2019
382019
SensorDB: a virtual laboratory for the integration, visualization and analysis of varied biological sensor data
A Salehi, J Jimenez-Berni, DM Deery, D Palmer, E Holland, ...
Plant methods 11 (1), 1-14, 2015
342015
Influence of soil structure on the shrinkage behaviour of a soil irrigated with saline–sodic water
JB X. Peng, R. Horn, D. Deery, M. B. Kirkham
Soil Research 43 (4), 555–563, 2005
302005
Ground-based LiDAR improves phenotypic repeatability of above-ground biomass and crop growth rate in wheat
DM Deery, GJ Rebetzke, JA Jimenez-Berni, AG Condon, DJ Smith, ...
Plant Phenomics 2020, 2020
162020
Uptake of water from a Kandosol subsoil. II. Control of water uptake by roots
DM Deery, JB Passioura, JR Condon, A Katupitiya
Plant and soil 368, 649-667, 2013
142013
Field phenomics: will it enable crop improvement?
DM Deery, HG Jones
Plant Phenomics 2021, 2021
112021
Uptake of water from a Kandosol subsoil: I. Determination of soil water diffusivity
DM Deery, JB Passioura, JR Condon, A Katupitiya
Plant and soil 368, 483-492, 2013
92013
Modelling temporal genetic and spatio‐temporal residual effects for high‐throughput phenotyping data
AP Verbyla, J De Faveri, DM Deery, GJ Rebetzke
Australian & New Zealand Journal of Statistics 63 (2), 284-308, 2021
82021
Phenonet: A distributed sensor network for field crop phenotyping
B Furbank, X Sirault, D Deery
Proc. 1st International Plant Phenomics Symposium: from Gene to Form and …, 2009
62009
Water uptake by a single plant: Analysis using experimentation and modeling
D Deery
Charles Sturt University, 2008
52008
Impact of varying light and dew on ground cover estimates from active NDVI, RGB, and LiDAR
DM Deery, DJ Smith, R Davy, JA Jimenez-Berni, GJ Rebetzke, RA James
Plant Phenomics 2021, 2021
32021
The system can't perform the operation now. Try again later.
Articles 1–20