Phenomics 2015
DOI: 10.1007/978-3-319-13677-6_7
|View full text |Cite
|
Sign up to set email alerts
|

Disease Phenomics

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1

Citation Types

0
5
0
1

Year Published

2017
2017
2022
2022

Publication Types

Select...
3
2

Relationship

0
5

Authors

Journals

citations
Cited by 5 publications
(6 citation statements)
references
References 23 publications
0
5
0
1
Order By: Relevance
“…This responsibility will fall to research teams, where a large cohort of deep knowledge needs to be shared in order to deploy phenomics tools into breeding programs. Particularly, plant breeders will need to be open and proactive at realizing the potential that phenomics tools could have to advance their breeding programs ( Giglioti et al, 2015 ; Cobb et al, 2019 ). However, it is important to remember that phenomics will not always shorten the timeline for cultivar development; rather, it will facilitate an upscale and increase in accuracy of phenotyping capability.…”
Section: Future Directionsmentioning
confidence: 99%
“…This responsibility will fall to research teams, where a large cohort of deep knowledge needs to be shared in order to deploy phenomics tools into breeding programs. Particularly, plant breeders will need to be open and proactive at realizing the potential that phenomics tools could have to advance their breeding programs ( Giglioti et al, 2015 ; Cobb et al, 2019 ). However, it is important to remember that phenomics will not always shorten the timeline for cultivar development; rather, it will facilitate an upscale and increase in accuracy of phenotyping capability.…”
Section: Future Directionsmentioning
confidence: 99%
“…For the quantification of diseases, images-based methods that rely on the reflectance of waves have been developed, such as analyzing the images in the visible spectrum, hyperspectral images, thermographic images, and chlorophyll fluorescence images [84]. Likewise, several automated and versatile disease phenomics platforms based on imaging techniques have been developed.…”
Section: Phenomics-assisted Breedingmentioning
confidence: 99%
“…For instance, the multi-sensor platforms Scanalyser 3DHT and Scanalyser FIELD are developed by the company LemnaTec (http://www.lemnatec.com) for the high-throughput phenotyping in the greenhouse and field, respectively. The American company Qubit Systems (http://qubitsystems.com/portal/) developed PlantScreen™ Conveyor Systems and PlantScreen™ Field Systems for greenhouse and field studies, respectively [84]. The image-based methods have been implemented to examine the diseases caused by the genus Xanthomonas in citrus [85] and bean [86].…”
Section: Phenomics-assisted Breedingmentioning
confidence: 99%
“…(Würschum, 2012). The individuals in the segregating population are genotyped and phenotyped in order to screen for the trait(s) of interest accurately and rapidly, enabling the discovery of links and the association between plant genes and their expression in the form of traits (Giglioti et al, 2015). However, the small size of early generations in segregating populations usually hinders the power of QTL detection and heritability is low in these populations.…”
Section: Molecular Toolsmentioning
confidence: 99%
“…However, in recent years great advances in technology have started to pave the way for high throughput field screening platforms. The development of such platforms coincided with an increasing interest in its use by plant phenomic centres, universities and multinational breeding and seed companies around the world(Giglioti et al, 2015). High throughput phenotyping platforms have greatly assisted in the development of field screening of complex traits such as yield, drought adaptation, pathogen virulence or aggressiveness and plant resistance traits, rendering data collection more efficient and consistent across the field.Some of the important traits that have been correlated with high yield potential and adaptation to heat and drought stress include staygreen (or rate of senescence) and canopy temperature.…”
mentioning
confidence: 99%