LEADER 02206nam  2200397z- 450 
001 9910346752203321
005 20210211
035   $a(CKB)4920000000094192
035   $a(oapen)https://directory.doabooks.org/handle/20.500.12854/56153
035   $a(oapen)doab56153
035   $a(EXLCZ)994920000000094192
100   $a20202102d2018      |y         0
101 0 $aeng
135   $aurmn|---annan
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 00$aPhenomics
210   $cFrontiers Media SA$d2018
215   $a1 online resource (222 p.)
225 1 $aFrontiers Research Topics
311 08$a2-88945-607-2 
330   $a"Phenomics" is an emerging area of research whose aspiration is the systematic measurement of the physical, physiological and biochemical traits (the phenome) belonging to a given individual or collection of individuals. Non-destructive or minimally invasive techniques allow repeated measurements across time to follow phenotypes as a function of developmental time. These longitudinal traits promise new insights into the ways in which crops respond to their environment including how they are managed. To maximize the benefit, these approaches should ideally be scalable so that large populations in multiple environments can be sampled repeatedly at reasonable cost. Thus, the development and validation of non-contact sensing technologies remains an area of intensive activity that ranges from Remote Sensing of crops within the landscape to high resolution at the subcellular level. Integration of this potentially highly dimensional data and linking it with variation at the genetic level is an ongoing challenge that promises to release the potential of both established and under-exploited crops.
606   $aBotany & plant sciences$2bicssc
610   $aartificial vision
610   $aMultispectral imaging
610   $aPhenomics
610   $aRGB data
610   $aRGB image analysis
615  7$aBotany & plant sciences
700   $aMarcos Egea-Cortines$4auth$01329317
702   $aJohn Doonan$4auth
906   $aBOOK
912   $a9910346752203321
996   $aPhenomics$93039418
997   $aUNINA