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Blue light advances bud burst in branches of three deciduous tree species under short-day conditions
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Blue light advances bud burst in branches of three deciduous tree species under short-day conditions
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Journal Article
Blue light advances bud burst in branches of three deciduous tree species under short-day conditions
2018
Overview
Key message
An LED spectrum containing blue light advanced bud burst in branches of
Betula pendula, Alnus glutinosa
and
Quercus robur
compared with a spectrum without blue light in a controlled environment.
During spring, utilising multiple cues allow tree species from temperate and boreal regions to coordinate their bud burst and leaf out, at the right moment to capitalise on favourable conditions for photosynthesis. Whilst the effect of blue light (400–500 nm) has been shown to increase percentage bud burst of axillary shoots of
Rosa
sp., the effects of blue light on spring-time bud burst of deciduous tree species have not previously been reported. We tested the hypotheses that blue light would advance spring bud burst in tree species, and that late-successional species would respond more than early-successional species, whose bud burst is primarily determined by temperature. The bud development of
Alnus glutinosa, Betula pendula
, and
Quercus robur
branches, cut from dormant trees, was monitored under two light treatments of equal photosynthetically active radiation (PAR, 400–700 nm) and temperature, either with or without blue light, under controlled environmental conditions. In the presence of blue light, the mean time required to reach 50% bud burst was reduced by 3.3 days in
Betula pendula
, 6 days in
Alnus glutinosa
, and 6.3 days in
Quercus robur
. This result highlights the potential of the blue region of the solar spectrum to be used as an extra cue that could help plants to regulate their spring phenology, alongside photoperiod and temperature. Understanding how plants combine photoreceptor-mediated cues with other environmental cues such as temperature to control phenology is essential if we are to accurately predict how tree species might respond to climate change.
