Changes in Light Spectra Modify Secondary Compound Concentrations and BVOC Emissions of Norway Spruce Seedlings

Canadian Journal of Forest Research

Changes in light spectra modify secondary compound concentrations and BVOC emissions of Norway spruce seedlings

Journal: Canadian Journal of Forest Research

Manuscript ID cjfr-2020-0120.R1

Manuscript Type: Article

Date Submitted by the 11-Nov-2020 Author:

Complete List of Authors: Kivimäenpää, Minna; University of Eastern Finland, Department of Environmental and Biological Science Virjamo, Virpi; University of Eastern Finland, Department of EnvironmentalDraft and Biological Sciences; University of Eastern Finland, School of Forest Sciences Ghimire, Rajendra; University of Eastern Finland, Environmental and Biological Sciences Holopainen, Jarmo; University of Eastern Finland, Department of Environmental and Biological sciences Julkunen-Tiitto, Riitta; University of Eastern Finland, Department of Environmental and Biological sciences Martz, Françoise; Natural Resources Institute Finland Nissinen, Katri; University of Eastern Finland, Department of Environmental and Biological Sciences; University of Eastern Finland, School of Forest Sciences Riikonen, J.; Natural Resources Institute Finland

Norway spruce, Biogenic volatile organic compounds, phenolic Keyword: compounds, alkaloids, blue light

Is the invited manuscript for consideration in a Special Not applicable (regular submission) Issue? :

Title: Changes in light spectra modify secondary compound concentrations and BVOC emissions

of Norway spruce seedlings

Authors: Minna Kivimäenpää*1, Virpi Virjamo2, 3, Rajendra P. Ghimire1, Jarmo K. Holopainen1, Riitta

Julkunen-Tiitto2, Françoise Martz4, Katri Nissinen2, 3, Johanna Riikonen5

Affiliations: 1University of Eastern Finland, Department of Environmental and Biological Sciences,

P.O.Box 1627, FI-70211 Kuopio, Finland, 2University of Eastern Finland, Department of

Environmental and Biological Sciences, Joensuu, Finland, 3University of Eastern Finland, School of

Forest Sciences, Joensuu, Finland, 4Natural Resources Institute Finland, Rovaniemi, Finland, 5Natural Resources Institute Finland, Kuopio, FinlandDraft *Corresponding author. email: [email protected], telephone: +358 40 355 3185

1 © The Author(s) or their Institution(s) Canadian Journal of Forest Research Page 2 of 37

Abstract

Our objective was to study how changes in the light spectra affects growth, carbohydrate, chlorophyll, carotenoid, terpene, alkaloid and phenolic concentrations, and BVOC (biogenic volatile organic compound) emissions of Norway spruce (Picea abies) seedlings. This study was conducted during the growth of the third needle generation in plant growth chambers. Two light spectra with the main difference in proportion of blue light (400-500 nm) and equal photon flux densities were provided by

LED (light-emitting diode) lamps: 1) control (white light + 12 % blue light) and 2) increased blue light

(+B) (white light + 45% blue light). The +B treatment increased needle concentrations of total flavonoids and acetophenones. The major changes in the phenolic profile were an accumulation of astragalin derivatives and the aglycone of picein. +B decreased concentrations of the main alkaloid compound, epidihydropinidine, and it’s precursor, 2-methyl-6-propyl-1,6-piperideine, emission rates of limonene, myrcene and total monoterpenes,Draft and concentrations of a few terpenoid compounds, mainly in stems. Growth, needle carbohydrates and pigments were not affected. The results suggest that supplemental blue light shifts carbon allocation between secondary metabolism routes, from alkaloid and terpenoid synthesis to flavonoid and acetophenone synthesis. The changes may affect herbivory and abiotic stress tolerance of Norway spruce.

Keywords: blue light, Norway spruce, biogenic volatile organic compounds, phenolic compounds, alkaloids

2 © The Author(s) or their Institution(s) Page 3 of 37 Canadian Journal of Forest Research

1 Introduction

3 Quality and quantity of light are primary factors affecting plant germination, morphogenesis, growth,

4 reproduction and defence. Several photoreceptors participate in perceiving different wavelengths of

5 light, such as phototropins and cryptochromes for blue light (400-500 nm) and phytochromes for red

6 (600-700 nm) and far-red (700-800 nm) light (Huché-Thélier et al. 2016). Pigments absorbing blue and

7 red light for photosynthesis are chlorophyll a and b and carotenoids in blue region (Huché-Thélier et al.

8 2016). Carotenoids (Lichtenthaler and Buschmann 2001) and anthocyanins in blue region (Close and

9 Beadle 2003) additionally protect chloroplasts from oxidative stress, such as that caused by excess

10 light. Proportions or ratios of wavelengths also affect plant performance, e.g., increased proportion of

11 blue wavelengths increase chlorophyll concentrations (Huché-Thélier et al. 2016). 12 Use of LED (light emitting diode) lightingDraft has increased in greenhouse-based plant production due 13 to the LEDs’ high energy efficiency and low radiant heat load. LEDs are also used in photobiological

14 studies, because adjustable, narrow-band wavelengths of light of LEDs allow lighting with desired

15 wavelengths. There is an increasing number of studies about LED provided light quality on growth,

16 morphology and chemical quality of horticultural species (e.g. Olle and Viršile 2013), but tree species

17 have been less studied. Among the boreal conifer species, responses to light quality of shade-intolerant

18 Scots pine (Pinus sylvestris) are better known than those of shade-tolerant Norway spruce (Picea

19 abies), and the effects of R:FR (red:far-red wavelengths) ratio are better known than the effects of blue

20 wavelengths (Riikonen et al. 2016). An LED-based technique has been utilized in the pre-cultivation of

21 transplant seedlings of forest tree species under controlled conditions: seedlings are grown in mini-

22 containers under optimal conditions for a few weeks, and then transplanted to larger containers and

23 thereafter grown under sunlight (Mattsson et al. 2010). Riikonen (2016) reported reduced stem biomass

24 and increased root-to-shoot ratio in Norway spruce transplant seedlings under blue light increment.

25 Less information is available on the effects of blue light on older seedlings of Norway spruce. A gene

26 expression study by OuYang et al. (2015) suggests that both primary (starch, sucrose, carotenoids) and

27 secondary metabolites (flavonoids) of Norway spruce needles increase in response to blue wavelengths 3 © The Author(s) or their Institution(s) Canadian Journal of Forest Research Page 4 of 37

28 of light, but the effects of blue light increment on concentrations of biochemical compounds in Norway

29 spruce tissues are not well known.

30 Many secondary compounds provide protection against biotic and abiotic stress in plants. For

31 Norway spruce, the most important secondary compound groups are volatile (isoprene, monoterpenes,

32 sesquiterpenes) and non-volatile (diterpenes) terpenoids (Trapp and Croteau 2001) and phenolics

33 (acetophenones, phenolic acids, flavonoids, stilbenes, lignans, tannins) (Metsämuuronen and Sirén

34 2019). The effects of environmental factors on alkaloids, which are also found in Norway spruce, have

35 been less studied (Holopainen et al. 2018). Increments of blue and other high-energy wavelengths of

36 light could be used to modify stress resistance of spruce seedlings by increasing concentrations of

37 secondary compounds. Namely, high-energy UV-A and B have been shown to increase concentrations

38 of flavonoid compounds in Scots pine (Turunen et al. 1999) and Norway spruce (Virjamo et al. 2014) 39 and several reports have indicated increasedDraft concentrations of flavonoids and other phenolics as a 40 response to blue light increments in horticultural plants (e.g., Taulavuori et al. 2013). Much less is

41 known about blue light effects on terpenoid emissions of trees. Pallozzi et al. (2013) exposed leaves of

42 Populus x canadensis, Quercus ilex and Citrus reticulata to white or blue light at different light

43 intensities and reported blue light to decrease isoprene and monoterpene emissions at modest or high

44 light intensities. The decreases in emissions could be explained by negative effects of blue light on

45 photosynthesis. The results of OuYang et al. (2015) indicated that blue light increased gene expression

46 for secondary metabolism pathways, such as those of phenylpropanoids, including flavonoids, and

47 jasmonic acid, which is involved in defence signalling (references in OuYang et al. 2015) and regulates

48 monoterpene biosynthesis (Martin et al. 2003). They also suggested that Norway spruce seedlings

49 exposed to blue light allocated fixed carbon to defence instead of growth.

50 The aim of this study was to reveal how light spectra with blue light increment affects

51 concentrations of secondary compounds (terpenoids, phenolics, alkaloids) and volatile terpenoid

52 emissions of Norway spruce seedlings during the growth period. In addition, we assessed impacts on

53 primary metabolism, including concentrations of light-harvesting pigments for photosynthesis, and

54 soluble sugars and starch, which are transported and stored forms of photosynthetically fixed carbon. 4 © The Author(s) or their Institution(s) Page 5 of 37 Canadian Journal of Forest Research

55 We also studied the effects of blue light increment on height and stem growth and above-ground

56 biomass. Our hypothesis was that blue light increment increases concentrations of secondary

57 compounds at the expense of growth.

59 Material and methods

61 Seedling material

62 On 15 June 2015, Norway spruce seeds (registered seed orchard no. 177, 61°34́́ N, 26°05ʹE, 100 m

63 above sea level) were sown in hard-walled plastic containers (Plantek PL81, BCC, Iso-Vimma,

64 Finland; 81 seedlings per tray, cell volume 85 cm3, 549 seedlings m-2), which were filled with pre-

65 fertilized and pre-limed medium-coarse sphagnum peat (Kekkilä white 420 F6W, Kekkilä Oy, Tuusula, 66 Finland) and covered with a layer of sand (1–2Draft mm). The seedlings were grown in a nursery in Central 67 Finland (Suonenjoki, Finland) according to Finnish nursery practice for one-year-old seedlings using

68 standard fertilization and irrigation procedures (Juntunen and Rikala 2001). The seedlings were

69 overwintered under snow cover and grown in the nursery for one more growing season, during which

70 the seedlings were exposed to short-day-treatment between 11 July and 1 August 2016. On 27

71 November 2016, the seedlings were packed into cardboard boxes that were frozen stored (-4°C) until

72 14 July 2017. The boxes were thawed in a cold storage room (+4°C) for one week, after which the

73 seedlings were kept in a greenhouse under natural light conditions until 9 August 2017, when they were

74 distributed between two experimental treatments organized in six growth chambers (Conviron Adaptis

75 A1000, Conviron, Winnipeg, Canada). For each growth chamber, one container (Plantek PL81),

76 including 23 seedlings surrounded by extra seedlings to avoid the edge effect were prepared. On 29

77 August, the seedlings were relocated within each container in such a way that an empty row of cells

78 were left between the rows that contained the seedlings to improve the light conditions. From the

79 beginning of August, the seedlings were fertilized weekly with 0.2% Taimi-Superex (19% nitrogen

80 [N], 5% phosphorus, 20% potassium + micronutrients; Kekkilä, Inc., Eurajoki, Finland), resulting in a

81 total of 14.8 g N m-2 during the experiment. 5 © The Author(s) or their Institution(s) Canadian Journal of Forest Research Page 6 of 37

83 Treatments

84 The two treatments included in the experiment were: 1) control = white light + 12% blue light (400-500

85 nm) of the total photon flux density from 400 nm to 800 nm, and 2) +B = white light + 45% blue light

86 (Fig. 1, Table 1). Both treatments were replicated in 3 growth chambers (n=3). The light treatments

87 were provided by programmable LED lamps (Heliospectra L4A Series 10, Heliospectra AB,

88 Gothenburg, Sweden), with adjustable light spectrum and intensity. The spectral composition (200-800

89 nm) was measured using a spectroradiometer (AvaSpec-ULS2048 Starline, Avantes BV, Apeldoorn,

90 The Netherlands) at the beginning of the experiment. In both treatments, the maximum

91 photosynthetically active radiation (PAR) was 500 µmol m-2 s-1 directly under the central point of the

92 LEDs, and 430 µmol PAR m-2 s-1 in the outer sides of the trays. To obtain the same PAR in the 93 treatments, in +B treatment, intensity of Draft other wavelengths were lowered which resulted in higher 94 blue:red and blue:green, but the other wavelength ratios were adjusted to be similar in the treatments

95 (Table 1). The daily variation in light intensity and air temperature was programmed to resemble those

96 prevailing in Finland in July (Fig. 2), and the daily photoperiod was 20 h. The trays were rotated twice

97 weekly to minimize the variation in light conditions between the seedlings located in different spots

98 within the tray. RH fluctuated between 60 and 70 %. The seedlings were 1.5 years old at the beginning

99 of the experiment, which lasted for 36 days. Shoots with the third needle age class grew in these

100 experimental conditions. At the end of the experiment, the seedlings had ended their height growth, but

101 visible buds had not yet formed.

102

103 Growth measurements and sampling for chemical analyses

104 The experimental seedlings (23 per chamber and 69 per treatment) were examined for height and stem

105 diameter at the beginning and at the end of the light treatments. The sampling for chemical analyses

106 was done at the end of the experiment. Fifteen seedlings from both treatments (5 per chamber) were

107 randomly assigned for analyses of biogenic volatile organic compound emissions and above-ground

108 biomass analyses (needle, stem and total dry weight, DW). From the remaining seedlings, 21 from both 6 © The Author(s) or their Institution(s) Page 7 of 37 Canadian Journal of Forest Research

109 treatments (7 per chamber) were randomly selected for pigment, carbohydrate and terpene

110 concentration analyses. The seedlings were transported to another laboratory and (ca. 1.5 hours after

111 removal from the chambers) the current year main shoot was cut, immediately frozen in liquid nitrogen

112 and stored at -80 °C for chlorophyll, carotenoid and terpenoid concentration analyses. The needle

113 samples of the same individuals were freeze-dried (Freeze dryer Alpha 1-2, Christ, Osterode am Harz,

114 Germany) and stored at -20 °C for anthocyanin and carbohydrate analyses. An additional 15 seedlings

115 from both treatments (5 per chamber) were randomly selected for phenolics and alkaloid analyses.

116 Pieces of 20 cm were cut from the top of the seedlings and put immediately on ice and frozen to -20 C.

117 The frozen needles were separated from the stems in a cold room (+4 C) immediately prior to

118 analyses. Separate needle samples from the same seedlings were dried at 105 °C for 24 h for needle

119 DW quantification, which is needed for phenolic and alkaloid concentration calculations. Chlorophyll, 120 carotenoids, anthocyanins, carbohydrates, phenolicsDraft and alkaloids were analysed from the current year 121 needles. Terpenes were analysed from the current year stems and needles separately.

122

123 Chlorophylls, carotenoids and anthocyanins

124 Needles for chlorophyll and carotenoid analyses were ground to powder in liquid nitrogen using a mortar

125 and pestle. Samples of 50 mg were extracted in 7 ml DMSO at 65 °C for 80 min and concentrations of

126 chlorophyll a and b and total carotenoids (xanthophylls and carotenes) were determined by

127 spectrophotometry (Utriainen and Holopainen 2000). Anthocyanins were extracted from 10 mg of

128 freeze-dried sample with 4 mL of acidified (1 % HCl) methanol at 4 °C for 48 hours and total

129 anthocyanin concentration was determined spectrophotometrically as done by Männistö et al. (2017).

130

131 Carbohydrates

132 Extraction and analysis of carbohydrates was performed as described by Domisch et al. (2018). In

133 brief, 15 mg dry needle powder were extracted three times with water at +80 °C and analyzed by HPLC

134 (NexeraX2, Shimadzu, Kyoto, Japan) using a ligand-exchange column (Hi-Plex Ca, 300 x 7.7 mm,

7 © The Author(s) or their Institution(s) Canadian Journal of Forest Research Page 8 of 37

135 Agilent) and a guard column (Hi-Plex Ca 50 x7.7mm, Agilent, Santa Clara, CA, USA). Elution was

136 done with milliQ water at +80°C (0.6 ml min-1) and detection was done using an evaporative light

137 scattering detector (Sedex 90LT, Sedere, Olivet, France). Carbohydrates purchased from Supelco

138 (glucose, sucrose), Fluka (fructose, raffinose), Aldrich (-pinitol) and Alfa Aesar (meso-erythritol)

139 were used for quantification. Starch was enzymatically degraded to glucose from the pellet after

140 extraction of soluble sugars using -amylase (E-BLAAM, Megazyme) followed by amyloglucosidase

141 (E-AMGDF, Megazyme, Bray, Ireland). Glucose was quantified using the glucose oxidase/peroxidase

142 method GOPOD kit (K-GLUC, Megazyme, Bray, Ireland) adapted to a microplate.

143

144 Terpenes

145 Terpenoid concentrations were determined from needles and stems using a modification of a method 146 described by Kainulainen et al. (1992). NeedlesDraft stored at -80 °C were ground to a fine powder and 147 stems to small pieces in liquid nitrogen and 200 mg of samples were extracted in 2 mL of n-hexane at

148 room temperature for 2 hours, and washed with 2 x 2 mL n-hexane. 1-chloro octane was used as an

149 internal standard. The extracts were analyzed using a gas chromatograph (Agilent Technologies 6890N,

150 China) equipped with a mass selective detector (type 5973 inert, Agilent Technologies, USA).

151 Separations were carried out on a 30-m HP-5MS 19091S-433 (i.d. 0.25 mm; film thickness 0.25 µm,

152 Agilent J&W Scientific, USA) column. Helium was used as a carrier gas, and linear velocity was about

153 40 cm s-1. The split sampling technique (split ratio 1:5) was used and 1 µL was injected. The initial

154 column temperature was 50 °C, with a hold for 1 min, and then programmed from 50 to 115 °C with a

155 temperature rise of 5 °C min-1 and then to 280 °C with a temperatures rise of 15 °C min-1, and held for

156 10 min. Mass numbers from m/z 33 to 350 were recorded. Compound identification and quantification

157 was based on their mass spectra, retention time and authentic standard compounds as described by

158 Kainulainen et al. (1992).

159

160 Phenolics

8 © The Author(s) or their Institution(s) Page 9 of 37 Canadian Journal of Forest Research

161 Low-molecular-weight phenolic compounds were extracted from needles according to the method

162 described by Nybakken et al. (2012). Needles were cut in to small pieces and 25–27 mg of cut material

163 was homogenized for 30 s in 600 µL of ice-cold methanol (MeOH) at rpm 5500 using a Precellys-

164 homogenizer (Bertin Technologies, Montigny-le-Bretonneux, France). Homogenized samples were

165 incubated on ice for 15 min and centrifuged at +4 C at 16700 g for 3 min (Eppendorf Centrifuge

166 5415R, Hamburg, Germany). Supernatants were collected, and sample residues were re-extracted three

167 times. Pooled supernatants were evaporated to dryness in a vacuum centrifuge at +45 C (Eppendorf

168 270 Concentrator, Hamburg, Germany) and samples were stored in a freezer (-20 C) until analysis. For

169 analyses of needle phenolics, the dried needle samples were dissolved in 1.2 mL MeOH:MilliQ water

170 (1:1) and run on an HPLC-DAD system (Nissinen et al. 2018). The HPLC (Series 1100, Agilent, USA)

171 was equipped with a binary pump (G1312A), an ALS autosampler (G1329A), a vacuum degasser 172 (G1322A), a column compartment (G1316A)Draft with a reverse-phase column (Zorbax SB-C18, 4.6 × 75 173 mm, particle size 3.5 μm, Agilent) and a diode array detector (G1315B). Eluent A was 1.5 %

174 tetrahydrofuran + 0.25 % orthophosphoric acid in Milli-Q water and eluent B was 100 % MeOH. The

175 gradient for eluent A was 0–5 min 100%, 5–10 min 100–85%, 10–20 min 85–70%, 20–40 min 70–

176 50%, 40–50 min 50%. We identified different compounds based on retention times and UV-spectra and

177 referring them to literature and commercial standards. The concentrations of different compounds were

178 quantified according to commercial standards (Virjamo et al. 2013). Flavonoids were quantified at 320

179 nm, phenolic acids, acetophenones, stilbenes and lignans were quantified at 220 nm.

180 Condensed tannins (proanthocyanidins) were quantified using the acid butanol assay (Hagerman

181 2011). MeOH-soluble condensed tannins were determined from the HPLC-MeOH extracts and MeOH-

182 insoluble condensed tannins from approximately 0.8 mg of the dried sample pellet residues obtained

183 after MeOH extractions. Condensed tannins extracted from mature Norway spruce needles were used

184 as standards for quantification (Virjamo et al. 2013).

185

186 Alkaloids

9 © The Author(s) or their Institution(s) Canadian Journal of Forest Research Page 10 of 37

187 Alkaloids were extracted from Norway spruce needles by solid phase-partitioning (Virjamo et al.

188 2013). Frozen needles were ground in liquid nitrogen and approximately 1 g of needle powder was

189 incubated in 0.5 M aq. HCl for 1 hour in an orbital shaker. Samples were filtered (WhatmanTH, Ashless

190 90mm, GE Healthcare Life Sciences, UK) and their pH was adjusted ≥ 11 with 6 M aq. NaOH.

191 Samples were loaded into an Extrelut® NT 20 PE column (refillable, 20 mL capacity, Merck,

192 Germany). The column was eluted three times with 18 ml of CH2Cl2 (SupraSolv®, Merck, Germany).

193 Combined eluates were concentrated with a rotary evaporator to 1–2 mL and adjusted to 2 mL with

194 CH2Cl2 in a volumetric flask. The identification and quantification of alkaloid compounds was done

195 according to Virjamo et al. (2013) with an Agilent 6890 gas chromatograph (GC) with an HP5973 mass

196 selective detector (MS), HP-1MS column (30 m x 0.25 mm ID, 25-µm film thickness, Agilent) and

197 G1701DA ChemStation D.00.00.38 (Agilent). GC conditions were as follows: injector and transfer line 198 240ºC; initial oven temperature 70ºC programmedDraft to increase by 20ºC/min to 280ºC. A 2 µl injection 199 volume (split ratio 91.1:1). The carrier gas was helium. Different compounds were identified using

200 literature (Virjamo and Julkunen-Tiitto 2014 and references therein). Synthetic (±)-epidihydropinidine

201 (Virjamo et al. 2013) was used for alkaloid quantification.

202

203 Biogenic volatile organic compound emissions

204 BVOC samples were collected from the headspace of seedlings using polyethylene terephthalate (PET)

205 bags as enclosures. PET bags (25 × 55 cm, Look) were pre-cleaned at 120° C for 1h. To make

206 enclosures long enough for the seedlings, two bags were joined at their open edges with duct tape (the

207 bag sleeves overlapping by 10 cm) and the other edge of the large bags were opened with scissors. To

208 minimize BVOC emissions due to mechanical damage, seedlings were carefully removed from the

209 containers. Extra care was taken to ensure roots were not broken or separated from the surrounding soil.

210 The root system and soil were wrapped in aluminium foil to exclude rhizosphere emissions. The whole

211 seedling was enclosed in the PET bag and the open end of the bag was fastened with a shutter. The

212 enclosure was held in an upright position by placing it in the jar. The volume of the bag was ca. 10 L,

213 and ca. 30 % of the bag volume was occupied by a seedling. A hole was cut in the upper side of the 10 © The Author(s) or their Institution(s) Page 11 of 37 Canadian Journal of Forest Research

214 bag, and charcoal filtered and MnO2 scrubbed air was channelled into the bag via Teflon tubing at a

215 flow rate of 0.6 L min-1. The tubing was fastened with a shutter to make it airtight. After the bags were

216 flushed with filtered air for 20 min, BVOC samples were pulled into purified stainless-steel tubes

217 (ﬁlled with 200 mg Tenax TA and Carbopack B adsorbents 1:1, Markes International, Llantrisant, UK)

218 – which were secured through a hole cut in the other upper corner of the bag – at a rate of 0.2 L min-1

219 for 10 min using a battery-operated collection system designed for ﬁeldwork (see details in

220 Kivimäenpää et al. 2018). The tubes were sealed with Teﬂon-coated brass caps and samples were

221 stored at +4°C until analysis. The sampling was conducted in a greenhouse next to the growth

222 chambers. Seedlings were illuminated with greenhouse lamps during collection. The average PAR was

223 300 µmol m-2 s-1 and it was monitored with a quantum sensor (Li-cor, Lincoln, NE, USA). Air

224 temperatures inside the collection bags were recorded with wireless data loggers (Hygrochron DS1923- 225 f5 iButton, Maxim Integrated products, SanDraft Jose, CA, USA). The average temperature was +23 °C. 226 Blank samples were collected from plant growth media (of the same volume used for growing plants)

227 wrapped in aluminium foil, as well as from empty collection bags, to examine the purity of the

228 background air entering the bag enclosures. After BVOC collection, the seedlings were cut at the base

229 of their stems, enclosed in paper bags and oven-dried at +60 °C for a week. DW of needles, stem and

230 total above-ground DW was determined and the total above-ground DW was used in emission rate

231 calculations.

232 BVOC samples were analyzed by gas chromatography – mass spectrometry (GC−MS, Hewlett

233 Packard type 6890, Waldbronn, Germany; MSD 5973, Beaconsﬁeld, UK). Compounds were desorbed

234 (Perkin Elmer ATD400 Automatic Thermal Desorption System, Wellesley, MA, USA) at 250 °C for

235 10 min, cryofocused in a cold trap at −30 °C, and subsequently injected onto an HP-5 capillary column

236 (50 m × 0.2 mm inner diameter × 0.33 µm ﬁlm thickness, J&W Scientiﬁc, Folsom, CA, USA). The

237 oven temperature was 40 °C for 1 min, and then raised to 210 °C at a rate of 5 °C min-1 and finally

238 increased to 250 °C at a rate of 20 °C min-1. The carrier gas was helium.

239 Different VOCs were identiﬁed by comparing their mass spectra with those in the Wiley library and

240 commercial standards. The compounds for which commercial standards were not available, were 11 © The Author(s) or their Institution(s) Canadian Journal of Forest Research Page 12 of 37

241 quantiﬁed using α-pinene (for non-oxygenated monoterpenes), 1,8-cineole (for oxygenated

242 monoterpenes) and longifolene (for sesquiterpenes) as reference compounds. The detection limit set for

243 the chromatograms was 1 ng. BVOC emission rates were calculated using the equation below:

244

245

246 where E = VOC emission rate (ng g-1 seedling DW h-1), F = flow rate of input air (L h-1), C2 =

247 concentration of compound per liter volume of output air (ng L-1), C1 = concentration of compound in

248 input air (considered as 0 ng L-1, since input air was filtered and blank emissions were reduced from

249 plant emissions) and M = seedling DW (g).

250

251 Statistics

252 Data were analysed by Mixed Models ANOVADraft using treatment (two light spectra) as a fixed factor,

253 and chamber identity was set as a random factor in order to take into account data dependencies, i.e.,

254 certain seedlings grew in the same chamber. In case the residuals of the model were not normally

255 distributed, the data was logarithm or square root transformed. If the transformations did not make

256 residuals normally distributed, data was tested by Mann-Whitney test. Untransformed data is shown in

257 the results. IBM SPSS Statistics for Windows (version 25.0, IBM Corp., Armonk, N.Y., USA) was

258 used for all statistical tests. P-values < 0.05 were considered significant and <0.1 marginally significant

259 trends.

260

261 Results

262

263 Growth, chlorophylls, total anthocyanins and carbohydrates

264 Increased blue light treatment did not affect seedling growth, needle chlorophyll, total anthocyanin or

265 carbohydrate concentrations (Table 2). Sucrose, glucose, fructose and pinitol were all detected in

266 spruce needles, but sucrose represented at least 75% of those soluble carbohydrates (Table 2).

12 © The Author(s) or their Institution(s) Page 13 of 37 Canadian Journal of Forest Research

267

268 Terpene concentrations

269 Terpene extracts from stems contained 11 monoterpenes, 5 sesquiterpenes and 7 diterpenes (Table 3).

270 Respective compound numbers for needle extracts were 30, 15 and 5 (Table 4). β-pinene (24 % of total

271 concentration), α-pinene (16 %), limonene and β-phellandrene (together 21 %) and Δ-3-carene (11 %)

272 were the major compounds in stems (Table 3). In needles, major monoterpenes were bornyl acetate (17

273 %), camphene (11 %), limonene (7 %) and α-pinene (6 %) (Table 4). The major stem monoterpenes β-

274 phellandrene and Δ-3-carene were absent or present as trace compounds in needles. Conversely, many

275 oxygenated monoterpenes, such as bornyl acetate, camphor, borneol and α-terpineol were found only in

276 the needle extracts. Many diterpenes remained unidentified. Comparison of their retention time and

277 mass spectra showed that different diterpenes were detected in stems and needles. Blue light treatment 278 significantly decreased concentrations of α-terpinoleneDraft and longifolene, and marginally significantly 279 decreased that of Δ-3-carene, in stems (Table 3). A few minor monoterpenes, ocimene, linalool and

280 piperitone, were present in the needles of the control treatment, but were not detected in the blue light

281 treatment (Table 4).

282

283 BVOC emissions

284 BVOC emissions consisted of isoprene, 20 monoterpenes, 8 sesquiterpenes and 2 GLV (green leaf

285 volatile) compounds (Table 5). The compounds with the highest emissions rates were the monoterpenes

286 α-pinene (32 % of total emission rates), β-pinene (17 %), limonene (10 %), camphene (7 %) and

287 myrcene (6 %). Blue light increment significantly decreased emission rates of limonene and myrcene

288 (Table 5). Total monoterpene emissions were 57 % lower in the blue light treatment, and the effect was

289 marginally significant. Isoprene and sesquiterpene emission rates were not significantly affected. GLVs

290 were emitted only by a few plant individuals.

291

292 Phenolic concentrations

13 © The Author(s) or their Institution(s) Canadian Journal of Forest Research Page 14 of 37

293 Needle phenolic profile consisted of 2 acetophenone, 2 phenolic acid, 2 stilbene, 18 flavonoid, 3 lignan

294 compounds and MeOH-soluble and MeOH-insoluble condensed tannins (Table 6). Blue light increment

295 caused statistically significant changes with a 56 % increase in concentrations of total acetophenones

296 and a 53 % increase in total flavonoids (Table 6). Among the individual compounds, the aglycone of

297 picein, a quercetin derivative and two dicoumaroyl-astragalins were significantly and kaempherol 3-

298 glucoside (astragalin) marginally significantly increased (Table 6). Blue light increment also increased

299 a protocatechuic acid derivative (phenolic acid). Other phenolics, i.e. stilbenes, lignans and condensed

300 tannins, were not significantly affected (Table 6).

301

302 Alkaloid concentrations

303 Six different alkaloid compounds were found in needles (Table 7). Blue light increment significantly 304 decreased the concentration of the main Draft alkaloid compound, epidihydropinidine, by 34 % and the 305 concentration of its precursor, 2-methyl-6-propyl-1,6-piperideine, by 16.5 % (Table 7). Total alkaloid

306 concentrations were not affected (Table 7).

307

308 Discussion

309

310 Blue light increment shifted secondary metabolism, but not at the expense of growth

311 The results of this study showed that changes the light spectrum affect the secondary chemistry of

312 Norway spruce seedlings during the growth phase, and in particular, alkaloids, flavonoids,

313 acetophenones, and volatile terpenoids. The changes may be due to increased blue wavelengths,

314 reduced red or other wavelengths, or altered ratios of blue to other wavelengths. Unaltered levels of

315 chlorophylls and carbohydrates, above-ground biomass, height and stem diameter increment suggest

316 that blue light increment did not affect the primary metabolites or growth parameters studied. The

317 results may indicate that the production of secondary metabolites induced by the increased proportion

318 of blue light were not done at the expense of primary metabolism or growth, but instead carbon was

319 allocated to the accumulation of flavonoid and acetophenone compounds at the expense of 14 © The Author(s) or their Institution(s) Page 15 of 37 Canadian Journal of Forest Research

320 metabolically more costly alkaloid and terpenoid compounds (Gershenzon 1994). The potential

321 significance of carbon assimilation should be verified e.g., with leaf CO2 measurements which were not

322 done in this study. Riikonen et al. (2016), however, have previously shown that net photosynthesis of

323 Norway spruce seedlings was not affected by decreased or increased proportions of blue or red

324 wavelengths. The lack of growth responses in this study supports previous studies that found that

325 growth of Norway spruce, as a shade-tolerant species, is not very sensitive to altered light quality (e.g.,

326 Riikonen et al. 2016). Shifts in secondary metabolism, such as opposite changes in terpenoid and

327 phenolic concentrations in needles, as a response to other abiotic factors such as nitrogen availability

328 (Björkman et al. 1998) or elevated atmospheric CO2 (Sallas et al. 2003), have earlier been reported for

329 Scots pine, and as a response to UV-B radiation in leaves of grey poplar (Populus x canescens) (Kaling

330 et al. 2015). 331 Draft 332 Induction of phenolic compounds

333 Increment of blue light did not change the concentration of total low molecular weight phenolics, but

334 induced accumulation of individual phenolic compounds. The major changes in the phenolic profile

335 were accumulation of dicoumaroyl astragalins (including their precursor kaempherol 3-glucoside) and

336 the aglycone of picein. Increase in astragalin derivative concentrations is similar to that detected earlier

337 in Norway spruce needles under elevated UV-B radiation (Virjamo et al. 2014). This increase in their

338 concentrations is thus likely to be related to the role of flavonoids as antioxidant compounds or as

339 screens of high-energy UV-B, UV-A and blue range wavelengths (Hoque and Remus 1999). Our

340 results are in line with the study by OuYang et al. (2015) where (night-time) increment of blue

341 wavelengths increased gene expression for flavonoid synthesis in Norway spruce seedlings. As far as

342 we know, the induction of dicoumaroyl astragalins by increased proportion of blue light observed here

343 is a novel finding. The strong induction of astragalins by blue light increment could be applied to

344 growing seedlings in nurseries. Growing seedlings under blue light increment before out-planting may

345 make them more tolerant to UV-radiation when seedlings are exposed to sunlight radiation outdoors.

15 © The Author(s) or their Institution(s) Canadian Journal of Forest Research Page 16 of 37

346 Increment of blue light increased the concentration of the aglycone of picein by more than tenfold.

347 A similar response has not been reported in earlier UV-B experiment with Norway spruce (Virjamo et

348 al. 2014). The aglycone of picein is both a precursor of picein and its degradation product catalysed by

349 a glucosylhydrolase PgβGLU-1 (Parent et al. 2018). Here, picein concentrations remained stable

350 between the two light treatments suggesting that the increase in concentrations of the aglycone of

351 picein might be related to changes in biosynthesis rather than in the activity of endogenous

352 glucosidases. Increase in the picein aglycone concentration in the blue light treatment is interesting

353 from the perspective of insect herbivory resistance as high acetophenone aglycon concentrations have

354 been shown to be a good predictor of spruce budworm (Choristoneura fumiferana) resistance in Picea

355 glauca (Parent et al. 2017). Phenolics, such as acetophenones and stilbenes, are known to accumulate in

356 Norway spruce needles during cold acclimation (Rummukainen et al. 2007). It might be worth 357 investigating if the increase in acetophenoneDraft concentration in the needles by blue light increments 358 during shoot growth could improve the tolerance of seedlings to cold temperatures, for example, after

359 autumn planting followed by colder temperatures (Luoranen et al. 2018).

360

361 Reduction of alkaloids

362 Changes in the concentration of coniferous 2,6-desubstituted alkaloids have previously been linked to

363 nitrogen availability (Gerson and Kelsey 1999) and temperature (Virjamo et al. 2014). While

364 temperature (Virjamo et al. 2014) and nitrogen availability (Gerson and Kelsey 1999) have been shown

365 to increase alkaloid concentration in conifers here we reported that increment of blue light decreased

366 the concentrations of two main alkaloid components of needles. The effect of blue light on conifer

367 alkaloids has not been studied earlier, but it has been shown to induce biosynthesis of indole alkaloids

368 in Camptotheca acuminate seedlings (Liu et al. 2015), which is opposite to the findings reported here.

369 However, similar to coniine, biosynthesis of 2,6-desubstituted coniferous piperidines begin untypically

370 from the polyketidine pathway resulting in different key enzymes compared to many other types of

371 alkaloid (Leete et al. 1975).

16 © The Author(s) or their Institution(s) Page 17 of 37 Canadian Journal of Forest Research

372 2,6-desubstituted coniferous piperidine alkaloids can be cis- and trans-oriented and both forms were

373 detected in Norway spruce (Virjamo et al. 2013). Their biosynthesis is likely separated in the early

374 phase of the biosynthesis pathway (Virjamo and Julkunen-Tiitto 2014) and accumulation of cis-

375 oriented compounds increased at elevated temperature while concentrations of trans-oriented

376 compounds remained stable (Virjamo et al. 2014). Interestingly, here blue light increment changed only

377 concentrations of trans-oriented compounds, epidihydropinidine and 2-methyl-6-propyl-1,6-piperidine.

378 These results suggest that biosynthesis of cis- and trans-oriented alkaloids are induced by different

379 environmental conditions. Moreover, decrease of trans-oriented compounds in blue light increment

380 seems to be highly light spectrum specific, as earlier studies with additional UV-B light have not

381 shown changes in the concentration of these compounds (Virjamo et al. 2014). Virjamo et al. (2013)

382 linked high concentrations of piperidine alkaloids and low concentrations of stilbenes to increased vole- 383 feeding of Norway spruce seedlings. TheyDraft also showed that concentrations of 2-methyl-6-propyl-1,6- 384 piperidine in bark and needles responded similarly when naturally regenerated and spring-planted and

385 autumn-planted seedlings were compared (Virjamo et al. 2013). Thus, reduced 2-methyl-6-propyl-1,6-

386 piperidine in needles by increased blue light can indicate potential effects on vole-feeding preference if

387 the seedlings grown under increased blue light would be outplanted.

388

389 Reductions in terpene emission rates from shoots and concentrations in stem

390 Terpene emissions of Norway spruce comprise de novo synthesised compounds from the needles

391 (Ghirardo et al. 2010) and compounds stored in oleoresin in resin ducts in needles and in the inner bark

392 and wood (Šimpraga et al. 2019). Monoterpenes are also present in spruce cuticular waxes (Despland et

393 al. 2016). Terpenoid emissions from plants are temperature-dependent and volatility also depends on

394 compounds’ chemical and physical properties (Mofikoya et al. 2019). Temperatures were similar

395 between the treatments during growth and constant during BVOC measurements and thus, could not

396 explain decreases in limonene, myrcene and total monoterpene emissions under the treatment increased

397 blue light. Supporting our study, blue light decreased isoprene and total monoterpene emissions of a

398 few broad-leaved tree species (Pallozzi et al. 2013). Significant decreases only in limonene and 17 © The Author(s) or their Institution(s) Canadian Journal of Forest Research Page 18 of 37

399 myrcene here may indicate that light regulation of terpene synthesis takes place at the level of terpene

400 synthases. (On the other hand, high variation in BVOC profile of the seedlings of seed origin may have

401 masked responses of other monoterpenes to the treatments.) Results of Pallozzi et al. (2013) showed

402 that blue light decreased CO2 assimilation that could affect substrate availability for terpene synthesis

403 and explain reduced isoprenoid emission. Blue light is known to reduce CO2 assimilation rate in other

404 conifers (Scots pine and Sitka spruce (Picea sitchensis)) (Morison and Jarvis, 1983), but higher or

405 lower proportion or red or blue wavelength did not affect net photosynthesis of Norway spruce

406 seedlings (Riikonen et al. 2016). Moreover, Huang et al. (2018) could not establish influence of

407 photosynthesis of monoterpene emissions in Norway spruce. Thus, blue light increment may affect

408 terpene synthesis in Norway spruce by regulating enzymes or gene expression which should be studied

409 in more detail. In addition, the significance of other wavelengths on terpene biosynthesis and BVOC 410 emission mechanisms deserves attention.Draft In this study, spectra of control treatment had higher 411 proportion of green, yellow, red or far-red wavelengths in the control treatment, which all have been

412 shown to increase BVOC emissions from herbaceous plants (Carvalho et al. 2016). In Arabidopsis,

413 Phytochrome B that absorbs red and far-red wavelengths of light control MEP pathway genes

414 responsible for the synthesis of monoterpenes (Rodríguez-Concepción et al. 2004).

415 Decreased limonene, myrcene and total monoterpene emissions may indicate that blue light

416 increment can affect susceptibility to herbivory. Plant volatiles are used in host recognition by insects,

417 and they affect oviposition and feeding (Bruce and Pickett 2011). Monoterpenes in cuticular waxes,

418 including myrcene and limonene, were shown to stimulate oviposition and feeding of spruce budworm

419 Choristoneura fumiferana in Picea glauca (Ennis et al. 2017). Limonene has been shown to inhibit the

420 attractiveness of α-pinene to the pine weevil (Hylobius abietis) and also to have repellent properties

421 that reduce stem feeding on spruce seedlings (Pettersson et al. 2008 and references therein). Thus,

422 seedlings grown under increased blue light and having lower limonene emission rates may be more

423 susceptible to pine weevil damage when transferred outdoors. Reduction of terpinolene and (marginally

424 significantly) 3-carene concentration in stems in response to blue light increment may also affect the

425 resistance of spruce seedlings to biotic stresses. Methyl jasmonate, a compound used to induce 18 © The Author(s) or their Institution(s) Page 19 of 37 Canadian Journal of Forest Research

426 terpenoid biosynthesis similar to stem-boring insects or fungal pathogens, induced 3-carene and

427 terpinolene synthesis in spruce stems (Fäldt et al. 2003, and references therein about the defensive role

428 of 3-carene in conifer defence against biotic stresses). Close linkage in biosynthesis of terpinolene and

429 3-carene (Fäldt et al. 2003) may explain why blue light affected these two compounds in this study.

430

431 Contribution of stem and needles to the BVOC emission profile

432 Concurrent analysis of the whole shoot BVOC emissions and terpene concentrations from both stems

433 and needles separately, increases our knowledge on the contribution of needle and stem terpene stores

434 to BVOC emissions of Norway spruce. Separate BVOC measurements from stems and needles of the

435 spruce shoots are difficult, because needles cover the shoots densely and mechanical damage, such as

436 needle bending or removal for adjusting the collection bag or chamber, would affect emissions rates. 437 Results of Ghimire et al. (2013) suggest thatDraft the influence of needle removal on BVOC-emissions, at 438 least by herbivory, can be long-lasting. Terpene concentration measurements both in stems and needles

439 in this study suggest that terpene storage in the stem was the major emission source of 3-carene and β-

440 phellandrene, because 3-carene was one of the main compounds in stem extracts, but trace compound

441 in needles, and β-phellandrene was not found in needle extracts. Conversely, needle storage contributed

442 to the emissions of oxidized monoterpenes, such as camphor, borneol, α-terpineol and bornyl acetate,

443 but stem storage did not. The higher number of compounds in the extract samples (especially from

444 needles) than in the shoot BVOC emission samples is due to the low volatility of certain compounds,

445 such as several oxidized MTs and diterpenes. In addition, the detection limit was slightly better (lower

446 baseline in chromatograms) in the terpene extraction method than in the BVOC emission method.

447 Šimpraga et al. (2019) showed that the BVOC emission rates from the bark of intact tree trunks are of

448 the same level as those from mature shoots (including needles and stem) in Norway spruce. Our results

449 support the view that the substantial terpene storage in spruce stem (Sallas et al. 2003) can be a

450 significant source of BVOC emissions. We suggest that calculating area- or biomass-based emission

451 rates of conifer BVOCs should include contributions of both needles and stems, not only needles, as is

453

454 Conclusions

455 Increases in flavonoid and acetophenone concentrations, and decreases in alkaloids concentration,

456 terpene emissions and concentration in the stem, caused by increment of blue light (or reduction of red

457 light or higher ratio of blue to other wavelengths) during shoot growth, may affect biotic (herbivory,

458 fungal pathogen) and abiotic (UV-B, low temperatures) stress tolerance of Norway spruce needles. This

459 modification of the light spectrum did not cause a trade-off between seedling growth investment and

460 chemical defence. Increasing blue wavelengths of LED lighting in nursery seedling production could

461 provide improved protection against abiotic and biotic stress for seedlings when transferred to natural

462 light and when out-planted, but reduced terpene concentrations and lower emission rates of pine-weevil

463 repellent limonene may also increase the risk of herbivory. How long-lasting the changes in the defence 464 chemistry are, and what their potential influenceDraft on seedling tolerance might be, needs to be tested in 465 field conditions.

466

467 Acknowledgements: Chief laboratory technician Jaana Rissanen is thanked for help in chlorophyll and

468 terpene extraction, laboratory engineer Pasi Yli-Pirilä in running GC-MS for terpene samples, chief

469 laboratory technician Sinikka Sorsa for help in HPLC-analyses of phenolics. Associate professor James

470 Blande is thanked for revising the language. This study was supported by the University of Eastern

471 Finland top research area BORFOR and by funding from the Academy of Finland (project no. 278424).

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Table 1. The proportion of different wavelength ranges in the light treatments.

wavelength range, nm Control +B 400-500 blue 12 45 500-600 green/yellow 52 36 600-700 red 31 16 700-800 far-red 5 3 red/far-reda 1.54 1.66 blue/green 0.26 1.24 blue/red 0.45 3.24 Pfr/Ptot 0.79 0.70 Note: The values represent the percentage of each wavelength range of the total photon flux density from 400 nm to 800 nm. There was no UV (< 400 nm) in the spectra.

a650–670 nm/720–740 nm. Draft

Table 2. Seedling height and stem diameter increment (mm), needle, stem and total above-ground dry weight (DW, g) and concentrations (mg g-1 DW) of chlorophylls, carotenoids and carbohydrates in current year needles of Norway spruce seedlings grown under white light (Control) or white light + increased blue light (+B).

Control +B F P-value Growth Height 88.3 (3.7) 88.8 (2.6) 0.016 0.905 Stem diameter 0.76 (0.03) 0.85 (0.09) 1.085 0.355 Needle DW 3.32 (0.29) 3.34 (0.19) 0.002 0.964 Stem DW 2.13 (0.17) 2.08 (0.10) 0.059 0.810 Total DW 5.56 (0.45) 5.43 (0.28) 0.004 0.952

Pigments Chlorophyll a 1.01 (0.05) 0.89 (0.07) 2.677 0.110 Chlorophyll b 0.09 (0.05) 0.09 (0.05) 0.001 0.975 Total carotenoids 0.23 (0.01) 0.22 (0.02) 1.964 0.169 Total anthocyanins 0.39 (0.01) 0.42 (0.02) 1.824 0.185 Carbohydrates Starch 15.6 (0.5) 16.1 (1.0) 0.170 0.682 Sucrose 5.9 (0.3) Draft5.4 (0.4) 1.014 0.374 aGlucose 0.30 (0.03) 0.30 (0.04) 0.008 0.934 Pinitol 0.89 (0.05) 0.95 (0.04) 0.813 0.419 aFructose 0.53 (0.04) 0.59 (0.09) 0.447 0.648 Sum of soluble sugars 7.6 (0.2) 7.3 (0.3) 0.488 0.524 NSC 23.2 (0.3) 23.4 (1.3) 0.059 0.809 Note. Values are averages (SE) of 69 seedlings for height and stem diameter, 15 for biomasses and of

21 seedlings for pigments and carbohydrates. F and P-values from Mixed Models ANOVA. NSC = non-structural carbohydrates is sum of soluble sugars and starch. a Logarithm transformation for Mixed

Models ANOVA.

Table 3. Concentrations of terpenes (mg g-1 FW) in the current year stem of Norway spruce seedlings

grown under white light (Control) or white light + increased blue light (+B).

Control +B F/Ua P-value Tricyclene 0.002 (0.001) 0.002 (0.001) 178.5a 0.602 bα-Pinene 0.337 (0.031) 0.379 (0.033) 0.622 0.402 cCamphene 0.041 (0.004) 0.039 (0.004) 0.201 0.656 Sabinene 0.038 (0.007) 0.023 (0.006) 139.0a 0.102 bβ-Pinene 0.481 (0.061) 0.580 (0.070) 1.188 0.283 Myrcene 0.065 (0.004) 0.076 (0.005) 2.750 0.105 α-Phellandrene 0.001 (0.001) 0 (0) 170.0a 0.429 Δ-3-Carene 0.294 (0.053) 0.173 (0.044) 134.0a 0.076↓ b,dLimonene+β-Phellandrene 0.433 (0.036) 0.477 (0.053) 0.341 0.563 α-Terpinolene 0.049 (0.008) 0.027 (0.007) 120.0a 0.030↓ Bornyl acetate 0 (0) 0.001 (0.001) 210.0a 0.799 Total monoterpenes 1.741 (0.068) 1.776 (0.103) 0.076 0.798 Longipinene 0.004 (0.001) 0.003 (0.001) 190.0a 0.799 Longifolene 0.015 (0.002) 0.008 (0.002) 5.458 0.025↓ β-Caryophyllene 0.004 (0.002) 0.007 (0.003) 222.0a 0.565 α-Humulene 0.001 (0.001) <0.001 (<0.001) 190.0a 0.799 Germacrene-D 0.001 (0.001) 0.002 (0.001) 220.0a 0.602 bTotal sesquiterpenes 0.025 (0.004) 0.020 (0.004) 0.334 0.593 Cembrene 0.049 (0.008)Draft0.042 (0.007) 164.5a 0.341 Unknown DT1 0.021 (0.007) 0.021 (0.006) 202.0a 0.968 Unknown DT2 0.002 (0.002) 0.004 (0.002) 212.0a 0.758 Unknown oxidized DT3 0 (0) 0.003 (0.003) 210.0a 0.799 Unknown DT4 0.013 (0.005) 0.010 (0.005) 178.5a 0.565 Thunbergol 0.377 (0.061) 0.316 (0.062) 0.489 0.489 cUnknown DT5 0.276 (0.045) 0.228 (0.051) 1.076 0.306 Total diterpenes (DT) 0.738 (0.099) 0.623 (0.103) 0.755 0.390 Note. Values are averages (SE) of 20 seedlings. F from Mixed Models ANOVA or aU from Mann- Whitney test with P-values are shown, significant P-values emboldened. The arrows indicate the direction of changes due to increased blue-light treatment. bLogarithm transformed, csquare-root transformed for Mixed Models ANOVA, dco-eluted.

Table 4. Concentrations of terpenes (mg g-1 FW) in the current year needles of Norway spruce seedlings grown under white light (Control) or white light + increased blue light (+B). Control +B F/Ua P-value bTricyclene 0.149 (0.007) 0.156 (0.008) 0.286 0.623 α-Pinene 0.814 (0.040) 0.952 (0.056) 2.895 0.165 bCamphene 1.583 (0.066) 1.613 (0.078) 0.078 0.795 Sabinene 0.118 (0.013) 0.102 (0.008) 1.049 0.362 β-Pinene 0.123 (0.011) 0.135 (0.012) 0.334 0.595 Myrcene 0.330 (0.036) 0.308 (0.023) 0.259 0.637 bα-Phellandrene 0.016 (0.002) 0.018 (0.002) 0.107 0.758 Δ-3-Carene 0.001 (0.001) 0.001 (0.001) 212.0a 0.919 Limonene 1.131 (0.130) 1.009 (0.106) 180.0a 0.434 b1,8-Cineole 0.643 (0.073) 0.556 (0.045) 0.655 0.463 Ocimene 0.004 (0.003) 0 (0) 180.0a 0.083↓ c(E)-β-Ocimene 0.114 (0.021) 0.094 (0.021) 1.058 0.310 (E)-β-Sabinenehydrate 0.022 (0.004) 0.024 (0.002) 231.5a 0.574 α-Terpinolene 0.055 (0.004) 0.049 (0.003) 0.722 0.441 Unknown oxidized MT 1 0.003 (0.002) 0.002 (0.002) 192.0a 0.362 Linalool 0.016 (0.009) 0 (0) 180.0a 0.083↓ bCamphor 0.158 (0.031) 0.090 (0.015) 2.190 0.215 Exo-methyl-camphenilol 0.146 (0.019) 0.153 (0.016) 0.110 0.742 Iso-borneol 0.002 (0.001) 0.003 (0.002) 222.5a 0.566 Endo-borneol 0.132 (0.035) 0.092 (0.013) 185.0a 0.514 α-Terpineol 0.166 (0.023) 0.126 (0.013) 2.251 0.142 Unknown oxidized MT 2 0.001 (0.001) 0.003 (0.002) 222.0a 0.488 Fenchyl acetate 0.002 (0.001) 0.006 (0.002) 254.0a 0.128 dUnknown oxidized MT 3 0.007 (0.004) 0.001 (0.001) 189.0a 0.287 Piperitone 0.009 (0.005) 0 (0) 170.0a 0.043↓ Bornyl acetate 2.441 (0.133)Draft2.592 (0.184) 0.303 0.611 Unknown oxidized MT 4 0.001 (0.001) 0.001 (0.001) 210.0a 1.000 Unknown oxidized MT 5 0.010 (0.005) 0.009 (0.005) 208.0a 0.940 Unknown oxidized MT 6 0.026 (0.007) 0.041 (0.011) 252.0a 0.266 Unknown oxidized MT 7 0 (0) 0.003 (0.003) 220.5a 0.306 Total monoterpenes (MT) 8.224 (0.450) 8.138 (0.441) 0.019 0.892 Longipinene 0.003 (0.001) 0.003 (0.001) 206.0a 0.885 Unknown ST 1 0.002 (0.001) 0.001 (0.001) 195.0a 0.572 bLongifolene 0.017 (0.002) 0.012 (0.002) 2.955 0.094 β-Caryophyllene 0.039 (0.007) 0.041 (0.010) 201.0a 0.814 Unknown ST 2 <0.001 (<0.001) 0 (0) 200.0a 0.329 bα-Humulene 0.028 (0.005) 0.028 (0.007) <0.001 0.985 β-Cubebene 0.006 (0.002) 0.004 (0.001) 187.0a 0.495 Germacrene-D 0.030 (0.005) 0.029 (0.005) 0.020 0.890 eUnknown ST 3 0.002 (0.001) 0.002 (0.001) 193.0 0.522 Bicyclogermacrene 0.043 (0.003) 0.035 (0.003) 1.994 0.230 γ-Cadinene 0.033 (0.004) 0.029 (0.003) 0.453 0.539 δ-Cadinene 0.013 (0.002) 0.010 (0.002) 1.534 0.223 Unknown ST 4 0.002 (0.001) 0.002 (0.001) 194.0a 0.497 fUnknown oxidized ST 5 1.443 (0.148) 1.267 (0.116) 0.603 0.481 Unknown ST 6 0.005 (0.002) 0.003 (0.001) 183.0a 0.381 Total sesquiterpenes (ST) 1.668 (0.162) 1.466 (0.137) 0.547 0.501 Unknown oxidized DT 1 0 (0) 0.005 (0.005) 220.5 0.306 Unknown DT 2 0.008 (0.008) 0.007 (0.007) 210.0a 1.000 gUnknown oxidized DT 3 1.820 (0.261) 1.979 (0.175) 0.225 0.659 Unknown DT 4 0.824 (0.151) 0.843 (0.091) 244.5a 0.368 Unknown oxidized DT 5 2.362 (0.366) 2.541 (0.214) 239.0a 0.449 Total diterpenes (DT) 5.014 (0.736) 5.375 (0.421) 0.177 0.677 Note. Values are averages (SE) of 20 seedlings. F from Mixed Models ANOVA or aU from Mann-Whitney test with P- values are shown, significant P-values emboldened. The arrows indicate the direction of changes due to blue-light treatment. bLogarithm transformed, csquare-root transformed for Mixed Models ANOVA, d potentially citronellol, epotentially cadina- 1,4-diene, f1,6-germacradien-5-ol or endo-1-bourbonanol, gpotentially manool

Table 5. Emission rates of volatile organic compounds (ng g-1 seedling DW h-1) from Norway spruce

seedlings grown under white light (Control) or white light + increased blue light (+B).

Control +B U P-value Isoprene 73.0 (10.9) 167.4 (117.6) 98.0 0.567 Tricyclene 31.5 (3.9) 27.4 (2.9) 110.0 0.935 α-Pinene 1995.3 (1223.5) 564.4 (244.5) 87.0 0.305 Camphene 277.5 (40.2) 241.6 (36.3) 85.0 0.116 Sabinene 39.1 (10.1) 22.1 (7.1) 75.5 0.561 β-Pinene 961.9 (430.3) 372.0 (163.4) 114.0 0.967 Myrcene 343.4 (129.8) 113.1 (48.9) 56.0 0.019↓ α-Phellandrene 17.6 (6.3) 7.4 (3.2) 88.0 0.325 Δ-3-Carene 219.2 (139.7) 145.9 (83.4) 100.0 0.624 α-Terpinene 6.9 (1.9) 3.9 (0.9) 90.0 0.367 p-Cymene 20.5 (3.8) 15.1 (2.9) 86.5 0.285 Limonene 518.9 (109.5) 248.5 (36.6) 56.0 0.019↓ β-Phellandrene 206.9 (87.1) 144.5 (87.2) 113.0 1.000 1,8-Cineole 148.0 (61.1) 82.1 (15.9) 102.0 0.683 (E)-β-Ocimene 6.2 (2.6) 2.8 (0.9) 103.0 0.713 γ-Terpinene 8.2 (2.5) 5.1 (1.6) 87.5 0.305 α-Terpinolene 37.8 (17.4) 18.6 (8.7) 76.0 0.137 Camphor 23.1 (11.4) 14.9 (3.3) 114.0 0.967 Borneol 6.3 (1.3) Draft6.2 (1.7) 106.5 0.802 α-Terpineol 2.5 (1.9) 2.7 (1.7) 119.0 0.806 Bornyl acetate 140.0 (24.2) 103.2 (18.9) 82.0 0.217 Total monoterpenes 5047.1 (1696.8) 2159.2 (568.2) 66.0 0.056↓ Longipinene 6.4 (2.9) 3.0 (0.7) 105.0 0.775 α-Copaene 1.3 (0.9) 0.5 (0.4) 105.0 0.775 Longifolene 14.7 (7.6) 7.5 (2.1) 101.0 0.653 β-Caryophyllene 1.8 (0.8) 9.4 (5.7) 109.0 0.902 α-Humulene 2.4 (1.1) 2.1 (0.9) 112.0 1.000 Germacrene-D 2.2 (1.5) 0.6 (0.5) 110.5 0.935 γ-Cadinene 0.6 (0.5) 0.3 (0.2) 110.5 0.935 δ-Cadinene 2.5 (1.0) 1.4 (0.4) 100.0 0.624 Total sesquiterpenes 34.8 (14.7) 23.6 (6.8) 115.5 0.902 Cis-3-hexen-ol 0 (0) 2.4 (2.4) 120.0 0.775 Cis-3-hexenyl-acetat 14.6 (14.6) 7.6 (7.6) 112.0 1.000 Total GLVs 14.6 (14.6) 10.0 (7.8) 96.0 0.512 Note. Values are averages (SE) of 15 seedlings. U from Mann-Whitney test with P-values are shown, significant P-values emboldened. The arrows indicate the direction of changes due to blue-light treatment.

Table 6. Phenolic compound concentrations (mg g-1 DW) in the current year needles of Norway spruce seedlings grown under white light (Control) or white light + increased blue light (+B).

Control +B F/Ua P picein 15.0 (2.6) 15.7 (0.81) 0.045 0.834 baglycone of picein 0.79 (0.47) 9.02 (1.58) 12.518 0.020↑ Total acetophenones 15.83 (2.80) 24.76 (2.00) 6.125 0.020↑ cprotocatechuic acid der. 0.03 (0.013) 0.06 (0.004) 5.150 0.031↑ bp-OH-cinnamic acid der. 1.42 (0.29) 1.19 (0.27) 0.005 0.946 bTotal phenolic acids 1.44 (0.30) 1.25 (0.27) 0.116 0.736 piceatannol glucoside 0.90 (0.09) 0.71 (0.14) 0.977 0.331 methyl-piceatannol glucoside 0.44 (0.07) 0.41 (0.04) 0.171 0.683 Total stilbenes 1.35 (0.20) 1.11 (0.13) 0.963 0.335 ampelopsin der. 0.03 (0.002) 0 97.5a 0.539 catechin 1.48 (0.10) 1.79 (0.19) 1.411 0.245 naringenin der. 0.21 (0.17) 0.07 (0.07) 111.5a 0.967 bepicatechin 0.53 (0.05) 0.55 (0.03) 0.091 0.765 bampelopsin 0.11 (0.02) 0.13 (0.03) <0.0001 0.991 eriodictyol 7-glucoside <0.01 (<0.01) 0.01 (0.01) 106.0a 0.806 myricetin 3-galactoside 0.12 (0.04) 0.15 (0.02) 0.610 0.479 kaempherol diglucoside 0.04 (0.004) 0.06 (0.008) 0.990 0.328 naringenin 7-glucoside 0.51 (0.38) 0.18 (0.18) 98.0a 0.567 bhyperin 0.08 (0.08)Draft0.32 (0.03) 0.584 0.455 apigenin der. 0.14 (0.07) 0.07 (0.01) 83.0a 0.233 bkaempherol 3-glucoside 0.34 (0.16) 1.02 (0.08) 5.863 0.073↑ bquercetin der. 1 0.26 (0.07) 0.70 (0.07) 12.218 0.025↑ bquercetin der. 2 0.02 (0.02) 0.14 (0.03) 0.505 0.494 eriodictyol der. 0 0.01 (0.01) 112.5a 0.539 monomethyl astragalin 0.47 (0.26) 0.21 (0.01) 138.0 0.305 dicoumaroyl astragalin der. 1 3.10 (0.53) 5.15 (0.15) 11.439 0.002↑ dicoumaroyl astragalin der. 2 0.35 (0.09) 1.35 (0.10) 29.696 0.001↑ Total flavonoids 7.79 (1.31) 11.89 (0.47) 7.541 0.010↑ neolignan 2 0.70 (0.04) 0.64 (0.05) 0.587 0.486 neolignan 3 0.94 (0.06) 0.97 (0.10) 0.047 0.830 lignan 6 0.10 (0.07) 0.15 (0.02) 2.692 0.112 Total lignans 1.75 (0.08) 1.76 (0.09) 0.005 0.947 bMeOH soluble CT 23.31 (3.04) 28.94 (2.68) 1.833 0.187 MeOH insoluble CT 53.52 (2.80) 59.15 (2.14) 2.545 0.122 Total CT 76.83 (6.21) 88.08 (4.02) 2.312 0.140 Note. Values are averages (SE) of 15 seedlings. F from Mixed Models ANOVA or aU from Mann- Whitney test with P-values are shown, significant P-values emboldened. Der. stands for derivative, CT for condensed tannins. The arrows indicate the direction of changes due to blue-light treatment. bLogarithm transformed, csquare-root transformed for Mixed Models ANOVA

Table 7. Alkaloid concentrations (mg g-1 DW) in the current year needles of Norway spruce seedlings

Control +B F/Ua P b2-methyl-6-propyl-1,6- 0.121 (0.010) 0.101 (0.016) 4.414 0.045↓ piperideine epidihydropinidine 0.145 (0.022) 0.096 (0.009) 52.0a 0.011↓ tentative 1,6-dehydropinidine 0.792 (0.024) 0.790 (0.084) <0.001 0.986 euphococcinine 0.097 (0.001) 0.090 (0.005) 78.0a 0.161 tentative 1,6- 0.094 (0.002) 0.088 (0.003) 74.0a 0.116 dehydropinidinone btentative isomer of 1,6- 0.082 (0.005) 0.082 (0.005) 0.724 0.443 dehydropinidine Total alkaloids 1.330 (0.065) 1.265 (0.577) 1.260 0.271 grown under white light (Control) or white light + increased blue light (+B).

Note. Values are averages (SE) of 15 seedlings. F from Mixed Models ANOVA or aU from Mann- Whitney test with P-values are shown, significant P-values emboldened.

bLogarithm transformed for Mixed Models ANOVA Draft

Figures:

Draft

Fig. 1. Spectral distribution of light (400–800 nm) under the two light treatments.

Fig. 2. Temperature (grey columns) and photosynthetically active radiation (PAR, line) in the growth

chambers during the experiment. Draft