Endogenous circadian rhythms in polyphenolic composition induce

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Agricultural and Environmental Chemistry

Endogenous circadian rhythms in polyphenolic composition induce changes in antioxidant properties in Brassica cultivars Pilar Soengas, María Elena Cartea, Pablo Velasco, and Marta Francisco J. Agric. Food Chem., Just Accepted Manuscript • DOI: 10.1021/acs.jafc.8b01732 • Publication Date (Web): 31 May 2018 Downloaded from http://pubs.acs.org on May 31, 2018

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Journal of Agricultural and Food Chemistry

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Endogenous circadian rhythms in polyphenolic composition

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induce changes in antioxidant properties in Brassica cultivars

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Pilar Soengas, M. Elena Cartea, Pablo Velasco, Marta Francisco*

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Group of Genetics, Breeding and Biochemistry of Brassicas, Misión Biológica de

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Galicia, Spanish Council for Scientific Research (CSIC), Pontevedra, Spain.

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Running title: Circadian rhythms in polyphenols affect antioxidant properties

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*Corresponding author: Marta Francisco

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Tlf: 0034 986 85 48 00

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Pilar Soengas: [email protected]

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M. Elena Cartea: [email protected]

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Pablo Velasco: [email protected]

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Marta Francisco: [email protected]

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ABSTRACT

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There is increasing evidence that the circadian clock is a significant driver of plant

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phytochemicals. However, little is known about the clock effect on antioxidant

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metabolites in edible crops. Thus, the aim of the present investigation was to study

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whether the antioxidant potential of Brassica cultivars is under circadian regulation and

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its relationship with polyphenol content. To accomplish that we entrain plants of four

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Brassica cultivars to light-dark cycles prior to release into continuous light. The

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antioxidant activity and phenolic content was monitored at four time points of the day

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during four consecutive days: two days under light-dark conditions followed by two

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days under continuous light. Results showed daily oscillation of antioxidant activity. In

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addition, those variations were related with endogenous circadian rhythms in

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polyphenolics and exhibit a species-specific pattern. Considering together, we

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determined that Brassica cultivars have an optimal time during a single day with

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increased levels of health-phytochemicals.

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Keywords:

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polyphenolics, circadian clock.

Brassica

oleracea,

Brassica

rapa,

antioxidants,

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ABTS,

FRAP,

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1. Introduction

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Cruciferous vegetables, in particular those included into the Brassica genus, are

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good sources of a variety of nutrients and health-promoting phytochemicals 1. The

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principal vegetable species of this genus are Brassica oleracea (i.e. broccoli, cabbage,

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cauliflower, kale and Brussels sprouts) and Brassica rapa (i.e. turnip, Chinese cabbage

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and pak choi). Diets rich in those vegetables have been reported to possess many useful

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properties for human health including anti-inflammatory, enzyme inhibition,

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antimicrobial, antiallergic or cytotoxic antitumor activity 1, 2. Part of these properties can

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be related to the high concentration of dietary antioxidants presents in these crops

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including polyphenols, vitamins E and C, and carotenoids which can reduce/scavenge

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reactive oxygene species (ROS). Various ROS, such as singlet oxygen, peroxynitrite

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and hydrogen peroxide, must be continually removed from cells to maintain healthy

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metabolic function. Diminishing the concentrations of ROS can have several benefits

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possibly associated with ion transport systems and so may affect redox signaling 3.

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Antioxidant compounds can be extracted and analyzed separately, but a more general

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approach to know the capacity of vegetable extracts to neutralize ROS is by using

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antioxidant potential assays. The antioxidant potential of Brassica vegetables is high

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compared to other vegetable crops. In fact, broccoli and kale are among the ones having

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the highest potential in the group of vegetable foods, including spinach, carrot, potato,

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purple onion, green pepper, rhubarb or green bean 4.

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The antioxidant properties in food supplies have been the focus of intense

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research. However, during the growth period, plants are frequently subjected to various

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biotic and abiotic factors that can affect the regulation of the biosynthetic pathways

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involved in production of plant phytochemicals, including polyphenols, and therefore,



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change their antioxidant potential. Light is an important environmental factor that

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regulate not only plant growth and development, but also the biosynthesis of both

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primary and secondary metabolites

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absolutely light dependent and its biosynthetic rate is related to light intensity and cycle

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6-8

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consequence in the resulting total flavonoids and total hydroxicinnamates production.

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According to previous studies, a positive and significant relationship has been observed

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between total phenolics, total flavonoids and antioxidant activities in Brassica crops 7, 9.

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It seems that different light conditions would have a direct effect on antioxidant

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activities in plants with changing total polyphenolic content. This may be related with

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the role of those compounds in protecting plants against excess light damages 10.

5

. Polyphenolic biosynthesis in Brassica is

. However, different cultivars had a different response to light conditions and in

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Plants, like other living organisms, have evolved circadian clocks, an

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endogenous timing system, that allow them to anticipate and prepare for cyclical

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changes in their environment, such as those associated with the transitions from night to

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day and between seasons 11. In this way, the plant can coordinate accurately the timing

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at which each metabolite is required to synchronize multiple physiological and

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developmental responses. Many genes encoding enzymes of polyphenol biosynthesis in

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the model plant Arabidopsis thaliana increase their transcripts before dawn 11. Thus, it

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can be hypothesized that daily oscillations in the light-dark cycle could influence

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polyphenolic composition in plants during a single day. To our knowledge, there are

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currently no reported studies under controlled conditions on the influence of the

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circadian clock on the contents of those bioactive compounds in Brassica cultivars.

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New agriculture requires developing new ecologically based approaches for

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increase plant phytochemicals with a role in plant protection and in human health. Thus, 4 ACS Paragon Plus Environment

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identifying specific growing conditions and determining the optimal harvest times in

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order to obtain cultivars with increased concentrations of bioactive phytochemicals

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could offer value-added commercial opportunities to the food industry. The aim of the

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present investigation was to study whether the antioxidant potential of Brassica

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cultivars is under circadian regulation and its relationship with polyphenol content. To

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investigate for species-specific patterns we studied four different phenolic-containing

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cultivars belonging to B. oleracea (broccoli and cabbage) and B. rapa (Chinese cabbage

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and turnip greens).

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2. Material and methods

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2.1. Plant material and growing conditions

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We studied different phenolic-containing cultivars from two Brassica species: cabbage

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(B. oleracea var. capitata), broccoli (B. oleracea var. botrytis), Chinese cabbage (B.

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rapa spp. pekinensis) and turnip greens (B. rapa ssp. rapa). Seeds of commercial

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hybrids of each cultivar were purchased from vegetable seed market (Batlle Seeds,

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Spain). All the genotypes were evaluated at the same time within a single plant growth

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chamber. If hybridization is accompanied by consistent genomic changes, then we

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expect synthetic commercial hybrids to exhibit consistent changes in phenotypic

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characteristics when they grow under controlled environmental conditions. All seeds

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were planted in potting soil, stratified at 4°C in the dark for three days to optimize

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germination. Plants were sown in a randomized block design experiment consisting in

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192 pots (4 x 4 cm), each containing one plant, distributed in three blocks. Within each 5 ACS Paragon Plus Environment


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block, the complete set of genotypes was randomly organized (16 plants × 4 genotypes).

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The plants were entrained to cycles of 16 h of light and 8 h of dark at 22°C and 60% of

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humidity for one month. At the stage of five leaves per plant, they were release into

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continuous light and temperature (22°C). The soil was regularly watered once per week

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until the day before of the beginning of the experiment.

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Leave samples for metabolite analysis and antioxidant evaluation were collected

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at two different light cycles during four consecutive days. Two days during the light-

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dark conditions (16 h of light/8 h of dark) and other two days during continuous light.

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Three replicate samples (each containing all the leaves from one plant) per cultivar were

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harvested at four distinct daily time points defined by the light-dark conditions: -1 h

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before and after the lights turned off (end of the day light period and beginning of the

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night period, respectively) and 1h before and after the lights turned on (end of the night

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period and beginning of the day light period, respectively).

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All samples were transferred to the laboratory and conserved at –80°C prior to

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lyophilization (BETA 2–8 LD plus, Christ) during 72 h. The dried material was

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powdered by using an IKA-A10 (IKA-Werke GmbH & Co.KG) mill, and the fine

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powder was used for further analysis.

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2.2. Evaluation of antioxidant activity

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Freeze-dried and ground samples (10mg) were extracted with 1 mL of 80% aqueous

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methanol in dark maceration for 24h. After centrifugation (3700 rpm, 5 min),

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methanolic extracts were employed in order to determine the antioxidant activity by

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[2,2'-azino-bis(3-ethylbenzothiazoline-6-sulphonic acid)] cation assay (ABTS) and by 6 ACS Paragon Plus Environment

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ferric reducing antioxidant activity (FRAP). Three technical replications were analysed

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for each sample Standard prepared with different concentrations of Trolox® (0, 0.008,

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0.016, 0.024, 0.032, 0.040 mM) was also measured. Antioxidant activity was

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normalized to Trolox® equivalents per gram (g) of dry weight (DW).

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2.2.1. ABTS assay

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The method of decolorization of free radicals ABTS employed was a modified version

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of that used by Samarth et al

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generated by oxidation of ABTS 7 mM potassium persulphate 2.45 mM in water, at

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room temperature for 16 h. For each analysis, the ABTS solution was freshly diluted

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with water in order to obtain an initial absorbance around 0.8 at 734 nm. An aliquot of

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10 µL methanolic extract for sample was added to 250 µL of ABTS solution.

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Absorbances were measured at 734 nm after 30 min of incubation in the dark at room

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temperature.

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2.2.2. FRAP assay

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For FRAP assay, the procedure followed the method of Benzie and Strain14. The FRAP

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reagent was prepared by mixing 10 volumes of 300 mM acetate buffer (pH 3.6), one

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volume of 10 mM TPTZ (2,4,6-tripyridyl-s-triazine, Sigma-Aldrich, Germany) in 40

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mM hydrochloric acid and one volume of 20 mM ferric chloride and then incubating at

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37 °C for 5 min. Fifty microliters of extract were added to 250 µl of freshly prepared

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FRAP reagent and mixed thoroughly. Readings were taken at 593 nm after 20 min in a

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microplate spectrophotometer (Spectra MR).

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and initially reported by Re et al


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. ABTS was


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2.3. Phenolic determination and quantification

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The same leaf samples that were used for antioxidant activity were also used for the

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determination of phenolic compounds. Fifty milligrams of each sample were extracted

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in 500 µL 70% methanol and sonicated during 1 h (model: 3510E-MTH, Bransonic®,

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Mexico) to facilitate the extraction. The suspensions were allowed to stand overnight at

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4 ºC and afterwards they were sonicated again for 1h. Then, samples were centrifuged at

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3700 rpm for 15 min. Supernatants were recovered and were filtered through 0.22 µm

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PTFE filters (Multi Screen®, Ireland). For phenolics identification, three samples from

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each cultivar were analyzed by HPLC-DAD-ESI/MSn in an Agilent HPLC 1100 series

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equipped with a diode array detector and mass detector in series (Agilent Technologies,

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Waldbronn, Germany) at the same conditions described by Francisco et al.

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spectrometry data were acquired in the negative ionization mode. Individual phenolic

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compounds were identified based on the data obtained from the standard substances or

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published literature based on the mass spectra together with the ([M–H]−) 15-17. Table S1

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sumarizes the identification data for the identified phenolic compounds. Quantification

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of phenolic compounds was carried out in an Ultra-High-Performance Liquid-

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Chromatograph (UHPLC Nexera LC-30AD; Shimadzu) equipped with a Nexera SIL-

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30AC injector and one SPD-M20A UV/VIS photodiode array detector was used for the

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quantification. The UHPLC column was a Kinetex™ 2.6 µm C18 82-102 Å, LC

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Column 100 × 4.6 mm, protected with a C18 guard cartridge. The flow rate was 0.4 mL

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/min-1 and the oven temperature was set at 30 ºC. The mobile phase consisted of two

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solvents: water-acetic acid (1%) (A) and methanol (B), starting with 10% B and using a

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gradient to obtain 40% B at 15 min and 60 % B at 24 min. The injection volume was 3

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µL. Chromatograms were recorded at 330 nm and data was processed on a computer

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with the LabSolutions software (Shimadzu). Quinic acids derivatives were quantified as 8 ACS Paragon Plus Environment

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. Mass

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chlorogenic acid (Sigma–Aldrich Chemie GmbH, Steinheim, Germany), flavonoids of

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kamepferol as kaempferol-3-O-glucoside, flavonoids of quercetin as quercetin-3-O-

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glucoside, flavonoids of isorhmanetin as isorhamnetin-3-O-glucoside (Merck,

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Darmstadt, Germany) and sinapic acid and derivatives as sinapic acid (Sigma–Aldrich

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Chemie GmbH, Steinheim, Germany). The calibration curves were made, at least with

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six data points, from 0.01 to 1 mM. The polyphenols were reported as µmol g-1 DW. In

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total, twenty seven compounds were identified (Table S1): Sums of each kind of

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compound were expressed as: total caffeoyl quinic acids, total flavonoids, total sinapoyl

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derivatives and total phenolics.

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2.4. Statistical analysis

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We examined temporal patterns of 33 variables, including individual phenolic

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compounds, sums of compounds by category (total quinic acids, total sinapoyl

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derivatives, total flavonoids and total phenolics) as well as the antioxidant variables

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(ABTS and FRAP). To test how a daily light cycle affect antioxidant properties and

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changes in polyphenolic composition under light-dark conditions, we conducted a

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mixed model ANOVA where the main effects of plant cultivars, time point (beginning

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of the night period, end of the night period, beginning of the light period and end of the

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light period) and their interactions were considered as fixed factors. Block and their

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interactions with plant cultivars and time point were considered as random factors. As

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we found a significant interaction between plant cultivar and time point, we also

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performed these analyses individually for each plant cultivar considering the time point

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as a fixed effect and block and the interaction between block and time point as random

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factors. Means comparisons were done with Fisher’s protected least signiﬁcant

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difference (LSD) at the 0.05 level of probability. 9 ACS Paragon Plus Environment


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The Pearson correlation analysis were performed between antioxidant activity

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methods (FRAP and ABTS) and total quinic acids, total sinapics, total flavonoids and

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total phenolics with data from all samples collected at different times of the day in the

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plants grown under light-dark cycles. To test the contribution of each individual

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phenolic compound to variability of antioxidant activity, multiple regression analysis

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was performed using a stepwise linear regression model. In this model, single phenolic

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compound contents were independent variables and antioxidant activity measured as

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ABTS and FRAP assays were dependent variables. .

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For comparative analysis on metabolite abundance across different samples and

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conditions, the data was normalized. The normalization procedure consisted of mean-

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centering and division by the standard deviation of each variable. The resulting data

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matrix was subjected to hierarchical clustering using the Euclidean distance method

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associated with complete-linkage based on each phenolic trait variation among the four

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times of the day evaluated for each cultivar which grown under light-dark conditions.

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All statistical analyses including clustering and heatmap representations were done

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using R 18.

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For phytochemical rhythmicity determination, we used data from plants

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transferred into continuous light conditions after the light-dark entrainment cycles (16 h

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of light/8 h of dark). The circadian parameters, period and phase were studied on the

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content (µmol g-1 DW) of phenolic compounds, selected as significantly (P ≤ 0.05)

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correlated with the antioxidant activity. The period was stated as the necessary time for

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a cycle to be completed, measured as the time between two consecutive maximum

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(peaks) periods. The phase was determined as the time of the day of maximal phenolic


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trait accumulation. Period and phase analysis were carried out using the online platform

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BioDare2 (biodare2.ed.ac.uk) 19.

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3. Results and discussion

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3.1. Phenolic analysis: relationship with antioxidant activity

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It is well established that antioxidant activity is related with the content and composition

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of several antioxidant metabolites in plant extracts, including polyphenols. We aim to

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study whether the antioxidant potential of different Brassica cultivars is under circadian

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regulation and its relationship with polyphenol content. To accomplish that, first we

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studied the polyphenolic profile of each Brassica cultivar and then we addressed the

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phenolic traits with a major influence on the antioxidant activity. Our results confirmed

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the polyphenolic composition according to previously reported data on flavonoids and

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hydroxycinnamic acids in B. oleracea and B. rapa cultivars

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compounds were identified and quantified among cultivars (Table S1). Regard to

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flavonoids, flavonols of kaempferol glycosilated and/or acylated by different

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hydroxycinnamic acids were the most abundant in these Brassica cultivars.

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Hydroxycinnamic acids were mainly represented by quinic acids of caffeic, ferulic, p-

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coumaric and sinapic acids in conjugation with sugar moieties or other

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hydroxycinnamics. They were divided into two major categories, sum of total quinic

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acids and sinapoyl derivatives.


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. In total, 27 individual


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As it was suggested by our previous results, we corroborated that the

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polyphenolic profile was similar among cultivars belonging to the same species (Table

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S2). The B. rapa cultivars, were rich in hydrocycinnamic acids, mainly represented by

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the sinapic acid and its derivatives, accounting for 60-75% of total phenolics. In

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addition,

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(methoxycaffeoyl)diglucoside-7-O-glucoside and Kaempferol-3,7-di-O-glucoside were

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the flavonoids present in higher contents, each corresponding to 5-9% of total

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phenolics. The B. oleracea cultivars showed similar contents of hydroxycinnamic acids

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and flavonoids being the major compounds the sinapoyl derivatives, 1,2,2′-

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trisinapoylgentiobioside and 1,2′-disinapoyl-2-feruloylgentiobioside, followed by the 3-

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caffeoyl quinic acid and the flavonoid kaempferol-3-O-(sinapoyl)-diglucoside. In these

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cultivars, each compound corresponded to 9-17% of total phenolics.

Kaempferol-3-O-(caffeoyl)diglucoside-7-O-glucoside,

Kaempferol-3-O-

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In order to evaluate the relationship between the content and composition of

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phenolics and the antioxidant activity expressed by the two different antioxidant assays

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(ABTS and FRAP), Pearson’s correlation coefficient were performed with data from all

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samples collected at different times of the day in the plants grown under light-dark

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cycles. Since cultivars of each species shared the same phenolic profile we presented the

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results by specie. High and significant (P ⩽ 0.01) correlations were found between total

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quinic acids, total flavonoids, total sinapoyl derivatives and total phenolics for both

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antioxidants assays in B. oleracea cultivars, ABTS (0.90, 0.79, 0.88 and 0.85

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respectively) and FRAP (0.83, 0.74, 0.79 and 0.79 respectively). For B. rapa cultivars,

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we only found significant correlations of ABTS and FRAP with total flavonoid content

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(0.81 and 0.63, respectively).


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Several authors have found significant and high correlations between antioxidant

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activities measured with electron-transfer based assays and total phenolic content,

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employing the Folin-Ciocalteu method, in different samples of Brassica cultivars

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However, from the overwhelming diversity of plant phenolics, only a limited number of

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compounds appear to promote protection via antioxidant action. Thus, to create a better

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model linking individual phenolic compounds to the antioxidant properties of Brassica

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extracts, we used a stepwise regression analysis on which single phenolic compound

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contents were independent variables and antioxidant activity measured as ABTS and

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FRAP assays were dependent variables. The coefficient of determination (R2) is the

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proportion of variability in a data set that is accounted by the statistical model and

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provides a measure of how well future outcomes are likely to be predicted by the model.

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The analysis generated a model where variation of p-coumaroyl quinic acid in B. rapa

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cultivars and variation of 1,2,2′-trisinapoylgentiobioside in B. oleracea cultivars

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explained 81% and 66% of total variation of the variability in ABTS, respectively. For

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FRAP, this analysis generated a model where variation of few phenolic traits explained

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97% and 94% of the antioxidant variability in B. rapa and B. oleracea, respectively. For

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the B. rapa extracts, the flavonoid kaempferol-3,7-di-O-glucoside was the compound

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with the strongest influence on FRAP (59%) followed by kaempferol-3-O-

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(methoxycaffeoyl)diglucoside-7-O-glucoside (25%) and p-coumaroyl quinic acid

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(13%). For the B. oleracea extracts, the sinapoyl derivative 1,2′-disinapoyl-2-

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feruloylgentiobioside showed the highest influence on FRAP variation (63%) followed

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by kaempferol-3,7-di-O-glucoside (31%). In concordance with our correlation analysis,

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the relationships between the individual compounds and antioxidant traits were positive.

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Our results corroborate the importance of hydroxycinnamic acids together flavonoid


9, 21

.


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compounds in the antioxidant behavior of the extracts and also show the significant

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contribution of a single phenolic to the total antioxidant capacity of Brassica plants.

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3.2. Daily polyphenolic variation in Brassica cultivars induces changes in

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antioxidants properties

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To study whether temporal accumulation pattern of phenolic contents can influence the

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antioxidant activity of Brassica cultivars, we entrain plants of each Brassica cultivar to

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light-dark cycles and then monitored the phenolic content and antioxidant activity at

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four different time points of the day during two consecutive days. Analysis of variance

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showed that phenolic traits and antioxidant activity significantly varied among time

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points and cultivars (Table 1). In addition, the variation of antioxidant assays as well as

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of most of the phenolic traits was contingent upon the time as demonstrated by the

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significant interaction between plant cultivars and time points for those traits (Table 1).

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The phenolic variation among the four times of the day evaluated for each cultivar by

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each individual trait was further summarized (Table S2) and clustered (Figure 1).

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Samples were grouped into two clades. In clade I, all samples collected during the light

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hours as well as most of the samples collected in early night were clustered. This clade

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also represents low content of phenolic traits. In contrast with that, in clade II samples

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harvested at the end of the night period exhibiting high accumulation of phenolic traits

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were clustered. Therefore, in general, all cultivars showed highest total phenolic content

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at the end of the dark period. However, changes of phenolic traits related with

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antioxidant potential exhibit a species-specific pattern. The B. oleracea cultivars

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(broccoli and cabbage) accumulated higher levels of antioxidant traits during the dark

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period. The B. rapa cultivars (Chinese cabbage and turnip greens) accumulated the 14 ACS Paragon Plus Environment

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highest quantities of phenolic traits related with antioxidant activity at the beginning of

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the day (Figure 1). Therefore, in B. rapa cultivars not all the phenolic traits reached the

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maximum values at the same time of the day.

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Since the interaction between plant cultivars and time points for both antioxidant assays

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it was also significant (Table 1) we performed individual analysis by each cultivar

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(Figure 2). In particular, we found that broccoli and cabbage showed the lowest levels

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of antioxidant activity at the end of the light period. The antioxidant activity in those

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cultivars goes increasing thought darkness reaching the maximum levels at the end of

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dark period. For Chinese cabbage and turnip greens the highest antioxidant potential

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was found at the beginning of the light period while remain almost constant at the others

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time points evaluated (Figure 2). Broccoli and cabbage showed the highest variation (2-

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fold) of antioxidant activity between the end of the light period and the end of the dark

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period. Thus, it has been evidenced the existence of daily oscillations of antioxidant

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activity in the studied Brassica cultivars when they grow under light-dark cycles. In

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addition, both antioxidant assays consistently showed that those fluctuations were

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similar among cultivars belonging to the same species. This suggests that temporal

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regulation of antioxidant traits is under genetic control, may be because antioxidant

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compounds are essential for sustaining important plant physiological processes.

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Phenolic compounds contribute to the color, sensory characteristics and

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antioxidant potential of vegetables. However, those metabolites also perform a variety

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of functions in the plant. They generally act also as potent antioxidants protecting the

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plant in response to UV light. Once light reaches a plant, provides the energy for

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photosynthesis, the principal source of substrates for all other biosynthetic pathways.

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However, an increased photorespiration during the light period, induce the production 15 ACS Paragon Plus Environment


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of ROS, which are important in signaling, but become harmful for the plants if

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accumulated 3. The production of highly reactive ROS can damage the ultra structure

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and function of chloroplasts, affecting PSII activity and photosynthetic pigments 22. In

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plants acclimated to sunlight, ROS production is counterbalanced by inner defenses,

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including antioxidant enzymes and antioxidant metabolites, such as phenolic

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compounds. Some phenolics provide stress protection, for example, acting as

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scavengers of ROS, as well as chelating metals that generate ROS via the Fenton

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reaction 23. Similar mechanism of action that have been described about the beneficial

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effects of those compounds as antioxidants in humans can be applied to plant

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protections against excess light damages 10. In the present work, we found significantly

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higher production of antioxidant polyphenols in late night and/or early morning.

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Therefore, our results evidenced that Brassica plants do not simply respond to light but,

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rather, anticipate the dawn and adjust their biology accordingly. Although it is unclear

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whether the circadian clock is involved in the antioxidant plant defense system, the

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existence of a master clock regulation behind this process it is suggested.

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3.3. Endogenous circadian rhythms in antioxidant phenolic traits

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Plants have adapted their growth and development to use the daily cycling of

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light and dark. This is manifested at both the physiological level (i.e hypocotyl growth,

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flowering time, stomatal opening and photosynthesis) and the molecular level with the

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expression of some genes occurring only at certain times of the day24 . The day-night

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cycling of these processes is called a diurnal rhythm and is achieved primarily by two

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mechanisms: first, by light, and second, by a free-running internal circadian clock.


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An attribute of circadian rhythms is that they are endogenously generated and

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self-sustaining, so they persist under constant environmental conditions, typically

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constant light and constant temperature. To date, most that is known about the effect of

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the endogenous plant circadian clock in secondary metabolites is based on Arabidopsis,

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and it is important to determine how the clock regulates plant phytochemicals,

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especially in edible crop species. To address these questions, after an entrainment phase

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of light-dark conditions we transferred the plants under constant light conditions “free

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running period”. Samples from each cultivar were collected at the same time points

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defined by the light-dark conditions during two consecutive days.

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We found that after a period of continuous light, the antioxidant activity of both

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assays in all studied crops showed a robust circadian rhythm (Figure 3). Thus, the

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circadian parameters (period and phase) of compounds correlated with antioxidant

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properties were studied. We also corroborated clear daily patterns in those compounds.

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As expected for traits regulated by the circadian clock, the circadian period of the

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studied individual phenolics was not exactly but close to 24h even in the absence of

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external timing cues (Figure 4). It has generally been assumed that circadian clocks

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have periods close to 24h in order to maintain a stable phase relationship to the Earth’s

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rotational cycle. Proper matching of the internal circadian time with the environment

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not only confers fitness advantages but also allows the clock to temporally gate the

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responses to environmental stresses 25.

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The phase of a circadian rhythm reflects where the maximum peak of

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accumulation occurs within a period of 24h. Interestingly, in absence of environmental

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time cues, all cultivars keep the rhythm and maintain the circadian phase (Figure 4).

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Similarly to our previous results, Chinese cabbage and turnip greens showed a peak of 17 ACS Paragon Plus Environment


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antioxidants accumulation during the subjective early morning. Broccoli and cabbage

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still accumulated significantly more levels of antioxidant compounds when it would

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have been night during the entrainment period (subjective night) even in absence of a

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dark period. Thus, this phenolic phytochemicals maintain a time-of-day-specific phase

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of accumulation even under free running conditions, implying a role of the circadian

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clock in the regulation of these metabolites. These results are in concordance with the

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endogenous circadian rhythmicity of antioxidative enzymes and low-molecular

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antioxidants in different organisms, including plants

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Chalcone Synthase (CHS), an important control step in the biosynthesis of flavonoids

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showed circadian rhythm regulation

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activity occurring in the late subjective night. It may be advantageous for the plant to

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accumulate photoprotective pigments in advance of the daily photoperiod 11; the timing

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of higher polyphenol production in our Brassica cultivars before and during dawn is

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consistent with this notion.

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In the present work, we reported for first time that the antioxidant activity of extracts

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from different Brassica cultivars fluctuates rhythmically though the day. Interestingly,

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those variations were related with endogenous circadian rhythms in polyphenol

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composition and exhibit a species-specific pattern. This precise timing and amplitude of

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daily phenolic variation patterns suggest a tight genetic control. Presumably this is

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related with the fact that the antioxidant defense system's role in balancing free radicals

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is highly essential for sustaining important plant physiological processes. The fact that

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each Brassica cultivar grown under light-dark cycles have an optimal time during a

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single day with increased levels of polyphenols, could be applied as a simple

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mechanism to promote the nutritional value of Brassica-derived food. More detailed

26

. In Arabidopsis, the enzyme

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. These authors found phase of peak enzyme


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understanding of how precisely these rhythms vary under field conditions and how this

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variation influences other phenotypes has broad implications for plant biology.

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Funding

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This research was supported by The Spanish Ministry of Economy and Competitiveness

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through a ‘Juan de la Cierva-incorporación’ program (IJCI-2014-19653) to MF and by

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the project AGL2015-66256-C2-R; and by the European Regional Development Fund

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(ERDF) and by La Xunta de Galicia (IN607A 2016/13)

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Conflict of interest

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The authors declare that there is no conflict of interest regarding the publication of this

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paper.

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Supporting Information

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Table S1. Abbreviations and identification data of phenolic compounds found in the studied Brassica cultivars (broccoli, cabbage, Chinese cabbage and turnip greens). Table S2. Phenolic variation (µmol g-1 DW) among the four times of the day (BD: beginning of the day light; ED: end of the day light; BN: beginning of the night; EN: end of the night) evaluated for each cultivar (broccoli, cabbage, Chinese cabbage and turnip greens). Samples were collected during two consecutive days in plants entrained to light-dark cycles (16h light/8h dark). Each cultivar within each time point is represented by the mean and standard deviation (SD) of six independent measurements.

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References

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18. Team, R. C., R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. 2014; Vol. URL http://www.Rproject.org/. 19. Moore, A.; Zielinski, T.; Millar, A. J., Online Period Estimation and Determination of Rhythmicity in Circadian Data, Using the BioDare Data Infrastructure. In Plant Circadian Networks: Methods and Protocols, Staiger, D., Ed. Springer New York: New York, NY, 2014; pp 13-44. 20. Cartea, M. E.; Francisco, M.; Soengas, P.; Velasco, P., Phenolic Compounds in Brassica Vegetables. Molecules 2011, 16 (1), 251-280. 21. Kusznierewicz, B.; Bartoszek, A.; Wolska, L.; Drzewiecki, J.; Gorinstein, S.; Namieśnik, J., Partial characterization of white cabbages (Brassica oleracea var. capitata f. alba) from different regions by glucosinolates, bioactive compounds, total antioxidant activities and proteins. LWT - Food Science and Technology 2008, 41 (1), 1-9. 22. Aro, E.-M.; Virgin, I.; Andersson, B., Photoinhibition of Photosystem II. Inactivation, protein damage and turnover. Biochimica et Biophysica Acta (BBA) Bioenergetics 1993, 1143 (2), 113-134. 23. Williams, R. J.; Spencer, J. P. E.; Rice-Evans, C., Flavonoids: antioxidants or signalling molecules? Free Radical Biology and Medicine 2004, 36 (7), 838-849. 24. Greenham, K.; McClung, C. R., Integrating circadian dynamics with physiological processes in plants. Nat Rev Genet 2015, 16 (10), 598-610. 25. Seo, P. J.; Mas, P., STRESSing the role of the plant circadian clock. Trends in Plant Science 2015, 20 (4), 230-237. 26. Lai, A. G.; Doherty, C. J.; Mueller-Roeber, B.; Kay, S. A.; Schippers, J. H. M.; Dijkwel, P. P., CIRCADIAN CLOCK-ASSOCIATED 1 regulates ROS homeostasis and oxidative stress responses. Proceedings of the National Academy of Sciences of the United States of America 2012, 109 (42), 17129-17134. 27. Thain, S. C.; Murtas, G.; Lynn, J. R.; McGrath, R. B.; Millar, A. J., The Circadian Clock That Controls Gene Expression in Arabidopsis Is Tissue Specific. Plant Physiology 2002, 130 (1), 102.

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Table 1. ANOVA results comparing the antioxidant and phenolics response of four

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Brassica cultivars (broccoli, cabbage, Chinese cabbage and turnip greens) entrained for

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one month to light-dark cycles (16h light/8h dark) at four different time points of the

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day. F-values, degrees of freedom (df), and associated significance levels (P) are shown.

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Significant effects (P < 0.05) are in bold.

df

Cultivar 3 F P-value

Antioxidant assays 159.31 ABTS 162.36 FRAP Phenolic compounds 57.08 QA1 18.09 QA2 483.89 QA3 21.27 QA4 500.14 QA5 35.04 F1 22.19 F2 12.69 F3 7.22 F4 37.67 F5 57.81 F6 37.39 F7 52.92 F8 19.65 F9 28.61 F10 16.92 F11 30.88 F12 18.22 F13 136.82 F14 121.37 F15 7.69 Sinap1 75.16 Sinap2 387.71 Sinap3 176.83 Sinap4 10.25 Sinap5 21.41 Sinap6 133.79 Sinap7 113.40 Total_QA 104.57 Total_Flav 5.49 Total_Sinap Total_Phenolics 64.98

Time point Cultivar × Time point 3 9 F P-value F P-value

0.001 0.001

9.50 4.30

0.001 0.008

3.36 2.31

0.002 0.028

0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001

4.90 2.70 6.03 3.06 66.79 7.44 2.36 8.88 4.14 0.18 6.30 5.50 2.20 0.15 0.68 1.51 3.92 2.51 7.62 3.05 5.80 0.64 8.43 15.68 2.93 4.05 6.15 11.96 8.45 4.92 3.09

0.001 0.055 0.001 0.036 0.001 0.001 0.082 0.001 0.010 0.910 0.001 0.002 0.099 0.926 0.568 0.223 0.013 0.069 0.001 0.036 0.001 0.590 0.001 0.001 0.042 0.011 0.001 0.001 0.001 0.001 0.035

1.91 4.51 6.71 3.91 25.07 3.10 4.00 5.86 1.58 3.74 3.99 4.59 3.94 0.62 3.38 0.59 1.22 0.62 1.80 1.54 2.71 1.50 4.04 3.47 3.77 3.85 2.27 2.67 3.60 3.79 1.45

0.071 0.001 0.001 0.001 0.001 0.004 0.001 0.001 0.146 0.001 0.001 0.001 0.001 0.772 0.002 0.795 0.302 0.770 0.090 0.157 0.011 0.173 0.001 0.002 0.001 0.001 0.031 0.012 0.001 0.001 0.191

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Figure captions

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Figure 1. Clustering dendrogram and heatmap of phenolic traits variation at different times of the day in Brassica cultivars.

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Clustering of samples was based on phenolic variation among the four times of the day (BD: beginning of the day light (1 h after the lights turned on); ED: end of the day light (1h before lights turned off); BN: beginning of the night (1h after lights turned off) ; EN: end of the night (1h before lights turned on)). Samples were collected during two consecutive days in plants entrained to light-dark cycles (16h light/8h dark). Each cultivar within each time point is represented by the mean of six independent measurements. Samples were grouped into two clades (highlighted by a dotted line). Colors of the heatmap can be interpreted using the scale bar where red represents the lowest and yellow represents the highest relative level of phenolic content. Black squares highlight the significant highest levels of traits related with antioxidant potential by cultivar. See Table S1 for abbreviations and Table S2 for quantitative data.

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Figure 3. Time series of ABTS and FRAP antioxidant activities in Brassica cultivars.

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Plants of broccoli, cabbage, Chinese cabbage and turnip greens were grown in light-dark cycles (16h light/8h dark) for one month and then transferred into constant light conditions (starting at Time 0). Samples for antioxidant activity (µmol of Trolox g-1 of DW) were collected during two consecutive days at four time points per day, two times at subjective dark and two times at subjective light as were defined by the entrainment period of light-dark cycles. The error bars represent standard deviation across replicates. Each cultivar within each time point is represented by the mean of three independent measurements.

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Figure 4. Circadian period and phase of the antioxidant phenolics presents in Brassica cultivars.

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Circadian period (time to complete one cycle) and phase of maximal antioxidants accumulation (µmol g-1 DW) in plants of Brassica cultivars subjected to continuous light for 48h after an entrainment period of light-dark conditions (16h light/8h dark). Shown are the individual phenolic traits selected as significantly (P < 0.05) related with the antioxidant activity in the stepwise regression analysis. For the phase diagrams the circle denotes the period length of 24h. From 0 to 8h means subjective night and from 8 to 24h means subjective day. The length of the ellipse from the origin of coordinates is proportional to the circadian amplitude and its orientation gives the acrophase of the rhythm.

Figure 2. Daily oscillation of antioxidant activity in Brassica cultivars. Quantification of antioxidant activity (ABTS and FRAP) (µmol of Trolox g-1 of DW) from four Brassica cultivars (broccoli, cabbage, Chinese cabbage and turnip greens) entrained for one month to light-dark cycles (16h light/8h dark). Samples were collected during two consecutive days at four different time points defined by the light-dark conditions. BD: beginning of the day light (1 h after the lights turned on); ED: end of the day light (1h before lights turned off); BN: beginning of the night (1h after lights turned off) ; EN: end of the night (1h before lights turned on). Different letters indicate significant differences between time points (ANOVA, P < 0.05). The error bars represent standard deviation across replicates and days. Each cultivar within each time point is represented by the mean of six independent measurements.

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Figure 1.

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Figure 2.

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Figure 3

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Figure 4

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Graphical abstract

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Endogenous circadian rhythms in polyphenolic composition induce

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