Cell to whole-plant phenotyping: the best is yet to come

S Dhondt, N Wuyts, D Inzé - Trends in plant science, 2013 - cell.com
Imaging and image processing have revolutionized plant phenotyping and are now a major
tool for phenotypic trait measurement. Here we review plant phenotyping systems by …

Leaf counting with deep convolutional and deconvolutional networks

S Aich, I Stavness - … of the IEEE international conference on …, 2017 - openaccess.thecvf.com
In this paper, we investigate the problem of counting rosette leaves from an RGB image, an
important task in plant phenotyping. We propose a data-driven approach for this task …

[HTML][HTML] Genomic selection for forest tree improvement: Methods, achievements and perspectives

VG Lebedev, TN Lebedeva, AI Chernodubov… - Forests, 2020 - mdpi.com
The breeding of forest trees is only a few decades old, and is a much more complicated,
longer, and expensive endeavor than the breeding of agricultural crops. One breeding cycle …

Plant phenomics and the need for physiological phenotyping across scales to narrow the genotype-to-phenotype knowledge gap

DK Großkinsky, J Svensgaard… - Journal of …, 2015 - academic.oup.com
Plants are affected by complex genome× environment× management interactions which
determine phenotypic plasticity as a result of the variability of genetic components. Whereas …

[HTML][HTML] Close-range hyperspectral imaging of whole plants for digital phenotyping: Recent applications and illumination correction approaches

P Mishra, S Lohumi, HA Khan, A Nordon - Computers and Electronics in …, 2020 - Elsevier
Digital plant phenotyping is emerging as a key research domain at the interface of
information technology and plant science. Digital phenotyping aims to deploy high-end non …

[HTML][HTML] High-throughput analysis of leaf physiological and chemical traits with VIS–NIR–SWIR spectroscopy: a case study with a maize diversity panel

Y Ge, A Atefi, H Zhang, C Miao, RK Ramamurthy… - Plant methods, 2019 - Springer
Background Hyperspectral reflectance data in the visible, near infrared and shortwave
infrared range (VIS–NIR–SWIR, 400–2500 nm) are commonly used to nondestructively …

Exploiting the centimeter resolution of UAV multispectral imagery to improve remote-sensing estimates of canopy structure and biochemistry in sugar beet crops

S Jay, F Baret, D Dutartre, G Malatesta, S Héno… - Remote Sensing of …, 2019 - Elsevier
The recent emergence of unmanned aerial vehicles (UAV) has opened a new horizon in
vegetation remote sensing, especially for agricultural applications. However, the benefits of …

[HTML][HTML] PlantCV v2: Image analysis software for high-throughput plant phenotyping

MA Gehan, N Fahlgren, A Abbasi, JC Berry, ST Callen… - PeerJ, 2017 - peerj.com
Systems for collecting image data in conjunction with computer vision techniques are a
powerful tool for increasing the temporal resolution at which plant phenotypes can be …

[HTML][HTML] Adaptation strategies to improve the resistance of oilseed crops to heat stress under a changing climate: An overview

M Ahmad, EA Waraich, M Skalicky, S Hussain… - Frontiers in plant …, 2021 - frontiersin.org
Temperature is one of the decisive environmental factors that is projected to increase by 1.
5° C over the next two decades due to climate change that may affect various agronomic …

[HTML][HTML] Automated phenotyping of plant shoots using imaging methods for analysis of plant stress responses–a review

JF Humplík, D Lazár, A Husičková, L Spíchal - Plant methods, 2015 - Springer
Current methods of in-house plant phenotyping are providing a powerful new tool for plant
biology studies. The self-constructed and commercial platforms established in the last few …