Page 282 - PC2019 Program & Proceedings

PLANT CANADA 2019

P137. Indoleamine plant growth regulators perceive and initiate plant responses to specific light
spectra in Scutellaria species
*1
2
Forsyth, J. ; L. Erland ; S. Murch 2
1 University of British Columbia
2
UBC
As sessile organisms, plants use light as an indicator of their environment as well as to mediate plant
growth through signalling networks involving plant growth regulators (PGRs). We hypothesized that a
novel class of PGRs, the indoleamines, are plant signaling molecules that perceive changes in light
composition and initiate a cascade of metabolic responses. To examine this, we grew three Scutellaria
species (skullcap): S. lateriflora, S. galericulata and S. racemosa in vitro. Axenic cultures were exposed
to red, blue, green or white light spectra provided by light emitting diode (LED) lighting systems. The
PGRs melatonin, serotonin, abscisic acid (ABA), auxin, and jasmonic acid (JA), were quantified by ultra
performance liquid chromatography-tandem mass spectrometry. Serotonin was detected in plants grown
under red and blue light. Melatonin was detected in plants grown under all of the different LED spectra
and at highest levels in plants grown under blue and red light. Auxin was found at significant levels in
plants grown under blue lights. In S. galericulata plants, the concentration of ABA was the highest under
white light with decreasing amounts produced by plants grown under green, blue and red light. We
propose that the indoleamines are an important signal which allow plants perceive and respond to
changing light conditions and that Scutellaria is an excellent in vitro system for the investigation of these
signaling events.

Jillian Forsyth (jill.forsyth@hotmail.com)

TOPIC 16: Horticultural Field Production (Posters P138-P139)

P138. Remote assessment of phenological and phenotypic variability in wild blueberry fields
Anku, K.; D. Percival
Dalhousie University

Research and development activities using a PrecisionHawk Lancaster M4 and M5, and DJI Matrice 600
Pro unmanned aerial vehicles (UAV) equipped with 18.4 megapixel camera was conducted during the
2016 to 2018 field seasons to determine if the UAV system could accurately assess wild blueberry
coverage, phenotypic population structure, and vegetative and floral bud growth stage. This was
complimented with field level validation of blueberry coverage, vegetative and floral bud growth stage,
and phenotypes identification. In addition, hyperspectral VIS/NIR scans of selected blueberry phenotypes
◦
were obtained using a radiometer equipped with a 10 foreoptic. Results indicated that it was possible to
provide precise and accurate assessment of: (i) blueberry coverage and topographic features, (ii) the
distribution of Vaccinium angustifolium Ait. and V. myrtilloides Michx. phenotypes, (iii) canopy growth
and development stage, and (iv) several weed species including goldenrod, sheep sorrel and fescue
grasses that were present within the fields. However, use of the high resolution digital camera did not
consistently provide an accurate estimate of bloom intensity or yield potential. Therefore, results from the
study have indicated that these technologies have the potential to significantly improve field assessment
for blueberry plant coverage and pest related factors. This can be integrated with emerging agrochemical
application technologies to significantly reduce agrochemical usage, decrease the cost of production and
improve the overall sustainability of the production system.

Kenneth Anku (kenneth.anku@dal.ca)

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