Journal of Applied Botany and Food Quality 89, 299 - 306 (2016), DOI:10.5073/JABFQ.2016.089.039 1 Universidade de Trás-os-Montes e Alto Douro, UTAD, Quinta de Prados, Vila Real, Portugal 2 Centre for the Research and Technology of Agro-Environmental and Biological Sciences - CITAB, Universidade de Trás-os-Montes e Alto Douro, UTAD, Quinta de Prados, Vila Real, Portugal Leaf age, seasonal and annual variations in Salvia officinalis L. var. purpurascens biochemical characteristics F. Martins1, I. Oliveira2*, A. Barros2, C. Amaral2, S. Afonso2, H. Ferreira2, B. Gonçalves2 (Received September 15, 2016) * Corresponding author Summary Medicinal and aromatic plants (MAP’s) have gain new attention in the past years due to their content in bioactive compounds and recognized health-promoting effects. One of the most important species of MAP’s is Salvia officinalis L., rich in several phytoche- micals (essential oil, phenolic compounds) and vitamins. Besides, it has various uses and pharmacological effects (including antibacte- rial, antiviral, antioxidative, anti-inflammatory, antidiabetic and antitumour activities). Salvia officinalis L. has many cultivars, in- cluding Salvia officinalis L. var. purpurascens, which is currently understudied. As few is known about this specific cultivar, charac- terization of this plant, as well as the study of biochemical variations occurring during its development, is of great significance. Hence, in this work, young and adult leaves of Salvia officinalis L. var. purpurascens, were collected in two different seasons (June and September) and in two different years (2011 and 2013). Several biochemical traits were analyzed, namely carbohydrate content, photosynthetic pigments concentration, total phenolics, soluble proteins, as well as oxidation parameters (thiobarbituric acid re- active substances, thiols and electrolyte leakage). The Year factor significantly influenced carbohydrate content (higher in 2013 for non-structural carbohydrates and soluble sugars, but lower for starch), but also chlorophyll and carotenoid content (higher in 2011), with a similar influence recorded for the Season of harvest (higher values for starch, chlorophyll and carotenoids in September, but lower for soluble sugars). The developmental stage of leaves showed significant influence mainly in the content of photosynthetic pigments, with higher values of chlorophyll and carotenoids recorded in young leaves. The results show the biochemical variations oc- curring in plants of Salvia officinalis L. var. purpurascens, during developmental stages, and others associated to season of harvest and year, and their relation to climatic factors. The gathered data, besides useful for the characterization of this plant, is also valuable when aiming for the optimization of sage cultivation. Keywords Salvia officinalis L. var. purpurascens; carbohydrates; chlorophyll, carotenoids; total phenolics Introduction In recent years, there has been an increased interest in herbs and spices, due to their documented and studied beneficial health effects. These plants have in their composition a large number of bioactive and health-promoting compounds, including vitamins, terpenoids and polyphenols, with several studies showing their beneficial ef- fects in cancer, cardiovascular disease and neurodegenerative dis- orders (Halliwell, 1996). One of the most studied aromatic plants is Salvia officinalis L. – common sage – native to the Mediterranean region and Asia Minor, which has been used in folk medicine for centuries, it is known to have pharmacological effect, which resulted in its inclusion in pharmacopoeias throughout the world (Tepe, 2008). Together with the increased demand of new sources of bio- active compounds, based in a global trade of herb-based products that reached an estimated amount S$ 60 000 million in 2000 (world HealTH organizaTion, 2003), renovated interest in sage has been triggered. Due to its economic value, this plant has been included in cultivation systems, which can help to achieve higher plant quality (ScHippmann et al., 2006). However, sage is a drought- susceptible species (TounekTi et al., 2011), and in the Mediterranean areas, this plant in under summer drought stress, together with high temperatures, which can lead to variations on several characteristics. Some available works regarding Salvia officinalis L. focused on the variations of growth parameters, volatile composition, essential oils and phenolics, caused by the type of cultivation (field or greenhouse) (Yi and weTzSTein, 2010), saline stress (TaâriT et al., 2012), low light conditions (mapeS and Xu, 2014) or water deficit (BeTTaieB et al., 2011) rather than in biochemical parameters of this plant. Furthermore, Salvia officinalis L. has many known varieties, being Salvia officinalis var. purpurascens one of the less studied ones. Hence, it is of essential interest to study the biochemical variations occurring in sage leaves that can be of great importance to achieve maximum quality, from the producers’ standpoint, but also from consumer’s point of view. Therefore, in this work we present results from biochemical characteristics, and their variation caused by leaf age, season or year in Salvia officinalis var. purpurascens. Materials and methods Plant material Salvia officinalis L. var. purpurascens plants were collected from the Botanical Garden of the University of Trás-os-Montes e Alto Douro (UTAD), Vila Real (41º19’ N, 7º44’ W, 450 m above sea le- vel), having the herbarium specimen number “HVR13737, Gerês, 05-11-2007, J.M. Neves”. Plants are on a dystric cambisol (Non- humic litholic) derived from shale. Is presents a medium texture (fine-sandy) with acidic pH (5.4), a percentage of organic matter of 1.45 and average phosphorus (63 ppm) and very high potassium (348 ppm) contents. No fertilization is applied, and watering of plants is performed regularly. Climatic data was recorded by a stan- dard weather station located near the experimental site. The study was carried out in 2011, 2012 and 2013, but, considering the diffe- rences regarding several climatic conditions (namely precipitation, temperature and total radiation) recorded for 2011 and 2013 (Fig. 1) (while conditions were similar between 2012 and 2013), we choose to present result concerning these two years. Healthy leaves, pre- senting two developmental stages (young, collected from the upper part of the plant and adult, collected from the middle third), were collected at two different harvest dates (June and September) and 300 F. Martins, I. Oliveira, A. Barros, C. Amaral, S. Afonso, H. Ferreira, B. Gonçalves years (2011 and 2013). Samples were obtained from twelve 4 years- old plants and eight repetitions of all methodologies were performed in randomly selected leaves. Leaf discs were prepared in the field, deep-frozen in liquid nitrogen and stored at -80 ºC until analysis. Carbohydrate content Carbohydrate content was measured using the methodology of irigoYen et al. (1992), by heating (80 °C) one leaf disc in 80 % (v/v) ethanol/distilled water solution, for 1 hour. Afterwards, 0.2 mL of the previous extract and 3 mL of anthrone were mixed and placed in a water bath at 100 ºC, during 10 minutes. The liquid fraction was used for soluble sugar quantifications and the solid fraction was used for starch analysis. The solid fraction was extracted with 30 % perchloric acid and quantified according to oSaki et al. (1991), following the anthrone procedure described in the soluble sugars methodology, using glucose as standard in both methodologies. Photosynthetic pigments The quantification of chlorophyll (Cla and Clb) and total caroteno- ids was performed using the methods of SeSTák et al. (1971) and licHTenTHaler (1987), respectively, by spectrophotometry in ext- racts of 80 % acetone with distilled water (v/v). Total phenolics A modified procedure of the Folin-Ciocalteu method (TSao et al., 2003) was used for accessing the concentration of phenolic com- pounds, using the same extracts obtained for the quantification of photosynthetic pigments. Results are expressed as mg of gallic acid equivalents, using a calibration curve obtained by preparing diffe- rent known concentrations of gallic acid, measured using the same procedure. Soluble proteins Soluble proteins were quantified by homogenising samples in a grinding medium containing 50 mM phosphate buffer (pH 7.5), 0.1 mM ethylenediaminetetraacetic acid (EDTA), 100 mM phenyl- methylsulfonyl fluoride (PMSF) and 2 % (w/v) polyvinylpyrolli- done (PVP), followed by centrifugation at 22 000 g for 30 minutes, at 4 ºC. Absorbance was read at 595 nm, and bovine serum albumin (BSA) was used as a standard (Bradford, 1976). Thiobarbituric acid reactive substances The concentration of total thiobarbituric acid reactive substances (TBARS) was calculated to evaluate membrane integrity. Lipid peroxidation in Salvia officinalis var. purpurascens leaves was esti- mated following the method described in Bacelar et al. (2006). Briefly, samples previously frozen with liquid nitrogen were ground in 3 mL of 20 % (w/v) trichloroacetic acid (TCA) using mortar and pestle, homogenized and centrifuged at 3500 g for 20 min. Afterwards, 1 mL of the supernatant was added to 1 mL of 20 % TCA containing 0.5 % (w/v) thiobarbituric acid and to 100 μL 4 % (w/v) butylated hydroxytoluene (BHT). This mixture was heated at 95 ºC for 30 min, quickly cooled in an ice bath and centrifuged at 10,000 g for 20 min and the absorbance of the supernatant was measured at 532 nm. The value for the non-specific absorption at 600 nm was subtracted. The TBARS concentration was expressed in terms of nmol/g and nmol/cm2, using an extinction coefficient of 155,000 M-1 cm-1. Thiols Total thiol content (–SH) of soluble protein extract was assayed as described in Bacelar et al. (2006), using 5,5-dithiobis (2-nitroben- zoic acid) (DTNB). Electrolyte leakage Electrolyte leakage was measured following the methodology of luTTS et al. (1996). Leaf discs were washed with deionised water to remove surface-adhered electrolytes, placed in closed vials con- taining 10 mL of deionised water and incubated at 25 ºC on a rota- ry shaker for 24 h. Afterwards, electrical conductivity (EC1) of the solution was determined. Samples were then autoclaved at 120 ºC for 20 min and the electrical conductivity (EC2) was obtained after equilibration at 25 ºC. The electrolyte leakage was calculated as fol- lows: Electrolyte leakage = × 100. Statistical analysis Data are presented as mean ± standard deviation, and the results presented by weight refer to dry weight of sage leaves. Differences among means were determined by analysis of variance (ANOVA), using SPSS (Statistical Package for Social Sciences) software, ver- sion 19.0 (IBM Corporation, New York, U.S.A.) software. The fulfil- ment of the ANOVA requirements, namely the normal distribution of the residuals and the homogeneity of variance, were evaluated by means of the Kolmogorov-Smirnov with Lilliefors correction (if n > 50) or the Shapiro-Wilk’s test (if n < 50), and the Levene’s tests, respectively. Fig. 1: Average monthly temperature (°C), total monthly precipitation (mm) and global solar radiation (kJ/m2) for 2011 and 2013. EC1 EC2 Salvia officinalis L. biochemical dynamics 301 Results and discussion There are few previous works regarding the analyzed biochemi- cal parameters of Salvia officinalis var. purpurascens, thus, most of the comparisons here presented are made with Salvia officina- lis related works (rather than with var. purpurascens), unless stated otherwise. The sampling Year proved to be the factor that signifi- cantly influenced a higher number of parameters (Tab. 1, 2 and 3). Considering all the results, sixteen of the twenty-five analyzed bio- chemical parameters were affected by the Year of study. Of those, non-structural carbohydrates, soluble sugars, soluble sugars/starch ratio, total chlorophyll/total carotenoids ratio, total phenolics and electrolytes leakage presented higher values in 2013, while starch, chlorophyll a (expressed as mg/g), total chlorophyll (expressed as mg/g), total carotenoids, and TBARS (expressed as nmol/g) showed higher values in 2011. Seasonal variations of the studied biochemi- cal parameters were also detected (Tab. 1, 2 and 3). Of those signi- ficantly affected by the sampling date, starch, chlorophyll a, total chlorophyll (expressed as mg/g) and total carotenoids were present in higher amounts in leaves collected in September, while soluble sugars, soluble sugars/starch, total chlorophyll (expressed as mg/ dm2) and thiols were detected in higher concentrations when leaves were collected in June. Finally, the leaf developmental stage caused fewer significant variations in biochemical parameters of sage. The leaf age (young or adult) only significantly affected ten out of 25 parameters. Of those, only sugars/starch ratio was higher in adult leaves, while content of chlorophyll a, chlorophyll b (expressed as mg/dm2), total chlorophyll, total carotenoids and TBARS was higher in young leaves. Few works are available regarding carbohydrate (soluble sugars and/ or starch) content of Salvia officinalis. SaHar and colleagues (2011) recorded contents for soluble sugars of about 9 mg/g of fresh leaf, while caSTrillo et al. (2005) refer about 1.25 g/m2. When reporting our data in fresh weight (the leaves tested in this work had an ave- rage of 73 % of water content – data not shown), a content of about 50 mg/g of dry weight will correspond to about 13.5 mg/g fresh weight, similar to the reported 9 mg/g of SaHar et al. (2011). The values of 151.34±8.67 mg/g will represent over 40 mg/g expressed in fresh weight, considerably higher than those previous reports indicate. On the other hand, the values reported by caSTrillo et al. (2005) (1.25 g/m2, corresponding to 12.5 mg/dm2) can also be consi- dered similar to the ones detected in the present work (ranging from 4.57±0.31 mg/dm2 in leaves from 2011 to 15.36±0.76 in leaves from 2013). The concentration of soluble sugars has been correlated to specific leaf mass, as well as with irradiance, but also to water stress, as they are known osmoprotectants and carbon sources (caSTrillo et al., 2005). Total carbohydrate content of sage has been reported to be 15 μg/mg fresh weight (pellegrini et al., 2015), well below the content detected by us, of around 54 μg/mg fresh weight (again, if considering 73 % of water content). No reports concerning the starch content of sage are known. However, starch content in other aro- matic and medicinal plants has been reported to present seasonal changes, increasing through spring until autumn (kofidiS et al., 2007). The lower value of starch in June, combined with higher values of soluble sugars, with an inverse behaviour in September, can be related to the mobilization of starch and its conversion in soluble sugars, as detected in other species. This will take place in order to support the increased metabolism during the flowering period of sage, which occurs between April and July, but always depending of climatic conditions. As sage is an important aromatic plant, effects of the composition on processing parameters (inclu- ding cutting, drying or freezing) is of interest. No data regarding how carbohydrate content of sage can influence or be influenced by processing parameters is available. Nonetheless, reports concer- ning the effects of drying methodologies in the sugar content of se- veral plants show considerable variations, depending on the selected process (e.g. gao et al., 2012). Concerning the chlorophyll content found in leaves of sage in the present work, similar amounts have been previously reported (caSTrillo et al., 2005; BeTTaieB et al., 2011; TounekTi et al., 2012). However, many reports also indicate higher (mapeS and Xu, 2014; pellegrini et al., 2015) or lower values (naSTa et al., 2014). Several factors affecting the content of chlorophyll in sage, inclu- ding ozone stress, light conditions, salinity, drought and tempera- ture, can help to explain some of the variations detected between 2011 and 2013. Higher values for chlorophyll June, with a decrease in September can be related to the flowering period of sage. In fact, the work of coiSin et al. (2010), with Salvia nemorosa, recorded an increase in chlorophyll content when plants are in the anthesis stage, probably due to increased sugar synthesis, to support the me- tabolism of the plant. Furthermore, values of precipitation show a considerable difference between the amount of water that will be available for plants (average of both years for June is 5.6 mm, and is September of 67.8 mm). Considering that Salvia officinalis is a drought-susceptible species (TounekTi et al., 2011) this factor can also help to explain the recorded variations on chlorophyll content between June and September. The beginning of leaf senescence can be the cause for the decrease of chlorophyll content in adult leaves. In fact, during the senescence process, were reserves are mobilized for younger tissues, like developing leaves or flowers (aBreu and munné-BoScH, 2007), chloroplasts are one of the first organelles to be subjected to senescence (dangl et al., 2000). Significant va- riations were also detected in total carotenoids, correlated to all the factors under study (age, season and year). Although similar va- lues have been previously published (TounekTi et al., 2012), other authors point out lower (TounekTi et al., 2011) or higher content (mapeS and Xu, 2014). Several factors are known to influence caro- tenoid content in sage, like ozone (pellegrini et al., 2015), salinity (TounekTi et al., 2012) or light levels (mapeS and Xu, 2014). Our results show significant differences between young and adult leaves in the total carotenoid content, as detected for the chlorophyll con- tent, which may be due to the onset of senescence that leads to losses of the compounds (aBreu and munné-BoScH, 2007). Furthermore, differences in total carotenoid content between seasons and years are likely related to climatic factors, known to influence carotenoid content (munné-BoScH and alegre 2002), as they protect cellu- lar structures by dissipating excess energy reaching the chloroplast, and by preventing the formation and/or scavenge any singlet oxygen that can result in lipid peroxidation in photosynthetic membranes. In fact, it was in 2011 that higher carotenoids and total radiation were recorded, results that may indicate a response to avoid oxida- tive damage caused by excess radiation. However, this same ratio- nale cannot be used for results regarding seasonal variation. In fact, total radiation was lower in September; contrarily to what was found to carotenoid content (higher in September), indicating that other stress-causing factors, namely low rainfall, that occurred in June, may be affecting carotenoids content. No data was found regarding the correlation between processing of sage and its content in chlo- rophylls and carotenoids. However, data concerning other aroma- tic plants indicate a considerable reduction of the content of those compounds with processing (divYa et al., 2012). It can be expected that, during processing, leaves containing higher levels of caroteno- ids are less prone to suffer oxidative processes, as these compounds are known to have strong antioxidant activity (e. g. krinSkY, 1989). For total phenolic content (Tab. 3), the recorded values can be con- sidered similar to those found in previous works (e.g. TaâriT et al., 2012; Yi and weTzSTein, 2012). However, other reports are avail- able (roBY et al., 2013) that obtained different values of phenolic content in sage. These may be linked to several factors, such as growing conditions, but also to different approaches in the quanti- fication of these compounds. For phenolics, interaction between 302 F. Martins, I. Oliveira, A. Barros, C. Amaral, S. Afonso, H. Ferreira, B. Gonçalves Tab. 1: Values (mean ± standard deviation) for carbohydrate content of Salvia officinalis leaves and probability levels of the effects of Age, Season and Year, as determined by ANOVA. ns: not significant. In bold, results that showed to be affected by the studied factors and/or their interaction. Non-structural Non-structural Starch Starch Soluble sugars Soluble sugars Soluble carbohydrates carbohydrates sugars/ (mg/dm2) (mg/g) (mg/dm2) (mg/g) (mg/dm2) (mg/g) Starch Age (A) Young 194.91±68.16 196.92±68.15 94.96±63.60 99.64±75.04 99.95±55.63 97.28±47.62 3.06±4.33 Old 202.30±80.35 213.69±80.35 102.95±80.93 109.27±83.19 99.35±71.19 104.43±75.93 6.02±10.03 Season (S) June 189.97±75.64 193.98±58.36 72.26±78.50 76.19±85.11 117.61±72.23 117.79±74.41 8.36±9.67 September 207.34±86.99 216.63±86.99 125.65±54.71 132.73±60.89 81.68±47.74 83.91±43.92 0.71±0.49 Year (Y) 2011 163.45±67.14 184.92±45.59 117.72±60.97 134.55±78.41 45.73±17.56 50.37±19.82 0.48±0.29 2013 233.76±63.79 225.70±67.34 80.19±78.64 74.36±67.69 153.57±43.03 151.34±49.04 8.59±9.49 A*S Young*June 164.71±46.24 149.49±46.24 47.02±36.94 41.47±28.61 117.68±64.91 108.02±60.65 5.52±5.08 Young*September 225.12±74.27 244.35±74.27 142.90±45.75 157.82±60.00 82.21±38.88 86.53±27.62 0.59±0.26 Old*June 215.04±56.57 238.48±59.57 97.49±100.07 110.90±107.62 117.55±81.05 127.58±86.97 11.21±12.26 Old*September 189.56±58.36 188.92±97.19 108.41±58.81 107.64±52.13 81.15±56.56 81.28±56.64 0.82±0.63 A*Y Young*2011 157.49±45.59 180.55±45.59 103.59±42.87 121.29±78.88 53.89±15.75 59.26±18.83 0.62±0.30 Young*2013 232.33±67.34 213.29±67.34 86.33±79.77 77.99±66.46 146.00±40.29 135.29±35.35 5.49±5.09 Old*2011 169.39±84.63 189.29±84.63 131.85±73.61 147.82±78.16 37.55±15.71 41.47±16.99 0.35±0.21 Old*2013 235.20±80.35 238.11±62.21 74.06±79.61 70.72±70.90 161.14±45.62 167.39±56.31 11.68±11.82 S*Y June*2011 182.32±75.64 190.03±75.54 130.87±73.33 139.06±80.72 51.45±18.15 50.97±9.09 0.54±0.36 June*2013 197.42±35.56 197.93±34.56 13.65±5.49 13.31±4.63 183.77±33.39 184.63±4.85 16.19±7.91 September*2011 144.56±53.28 179.80±53.24 104.57±43.98 130.04±78.40 39.99±15.42 49.76±26.99 0.43±0.21 September*2013 270.11±66.31 253.46±66.31 146.65±57.47 135.41±38.72 123.37±27.68 118.06±27.74 0.98±0.53 A*S*Y Young*June*2011 134.88±42.63 118.26±42.62 76.24±31.01 66.42±17.94 58.64±19.81 51.83±10.56 0.83±0.27 Young*June*2013 194.52±27.06 180.73±27.06 17.80±3.16 16.52±2.93 176.72±25.85 164.21±23.52 10.20±2.25 Young*September*2011 180.10±38.33 242.85±38.33 130.94±35.59 176.16±78.29 49.15±9.37 66.69±22.84 0.40±0.14 Young*September*2013 270.14±75.62 245.74±75.62 154.86±53.77 139.47±28.58 115.28±25.55 106.37±14.59 0.79±0.19 Old*June*2011 229.76±72.80 261.81±72.80 185.50±61.16 211.70±39.75 44.26±13.98 50.11±7.92 0.24±0.05 Old*June*2013 200.32±42.52 215.14±42.52 9.49±3.88 10.10±3.72 190.83±40.19 205.04±49.29 22.18±6.86 Old*September*2011 109.03±41.45 116.76±41.45 78.19±35.89 83.93±46.71 30.84±15.18 32.83±19.62 0.46±0.26 Old*September*2013 270.11±66.31 261.08±60.86 138.62±63.53 131.34±48.56 131.46±28.96 129.74±33.53 1.18±0.69 F values and probability levels Age (A) 0.314n.s. 1.762n.s. 0.575n.s. 0.884n.s. 0.010n.s. 1.212n.s. 21.232*** Season (S) 1.753n.s. 3.211n.s. 25.678*** 30.514*** 35.357*** 27.222*** 142.081*** Year (Y) 28.428*** 10.411** 12.685** 34.584*** 318.585*** 241.630*** 159.238*** A*S 10.604** 32.637*** 16.258*** 34.138*** 0.006n.s. 3.643n.s. 18.146*** A*Y 0.117n.s. 0.405n.s. 3.689n.s. 2.725n.s 6.790* 14.742*** 25.235*** S*Y 17.529*** 6.767* 57.211*** 41.022*** 16.408*** 25.310*** 138.255*** A*S*Y 9.208** 24.547*** 13.367*** 33.169*** 0.062n.s. 0.319n.s. 22.700*** Salvia officinalis L. biochemical dynamics 303 Ta b. 2 : V al ue s (m ea n ± st an da rd d ev ia tio n) fo r p ho to sy nt he tic p ig m en ts o f S al vi a of fic in al is le av es a nd p ro ba bi lit y le ve ls o f t he e ff ec ts o f A ge , S ea so n an d Y ea r, as d et er m in ed b y A N O VA . n s: n ot s ig ni fic an t. In b ol d, re su lts th at s ho w ed to b e af fe ct ed b y th e st ud ie d fa ct or s an d/ or th ei r i nt er ac tio n. C hl or op hy ll a C hl or op hy ll a C hl or op hy ll b C hl or op hy ll b To ta l To ta l C la /C lb To ta l To ta l To ta l ch lo ro ph yl l ch lo ro ph yl l ca ro te no id s ca ro te no id s ch lo ro ph yl l (m g/ dm 2 ) (m g/ g) (m g/ dm 2 ) (m g/ g) (m g/ dm 2 ) (m g/ g) (m g/ dm 2 ) (m g/ g) /C ar ot en oi ds A ge (A ) Y ou ng 3. 54 ±0 .6 3 3. 73 ±1 .5 3 1. 46 ±0 .5 9 1. 55 ±0 .8 5 4. 99 ±1 .1 8 5. 29 ±2 .2 9 2. 56 ±0 .4 2 1. 07 ±0 .2 0 1. 12 ±0 .4 3 4. 72 ±1 .0 5 O ld 2. 89 ±0 .6 3 3. 10 ±0 .7 9 1. 17 ±0 .4 4 1. 26 ±0 .5 1 4. 06 ±0 .9 6 4. 36 ±1 .1 9 2. 62 ±0 .5 1 0. 87 ±0 .1 2 0. 94 ±0 .1 9 4. 66 ±0 .8 3 Se as on (S ) Ju ne 2. 95 ±0 .6 6 3. 00 ±0 .7 1 1. 25 ±0 .5 6 1. 28 ±0 .6 1 4. 19 ±1 .1 2 4. 28 ±1 .2 2 2. 53 ±0 .5 1 0. 94 ±0 .1 6 0. 95 ±0 .1 5 4. 53 ±1 .1 2 Se pt em be r 3. 48 ±0 .6 8 3. 83 ±1 .5 2 1. 38 ±0 .5 0 1. 54 ±0 .7 8 4. 86 ±1 .1 3 5. 37 ±2 .2 4 2. 64 ±0 .4 2 1. 01 ±0 .2 2 1. 11 ±0 .4 5 4. 84 ±0 .6 9 Y ea r (Y ) 20 11 3. 33 ±0 .7 5 3. 82 ±1 .5 5 1. 32 ±0 .5 2 1. 51 ±0 .7 8 4. 65 ±1 .2 4 5. 33 ±2 .2 7 2. 66 ±0 .3 9 1. 05 ±0 .2 1 1. 18 ±0 .4 2 4. 44 ±0 .8 2 20 13 3. 09 ±0 .6 7 3. 02 ±0 .6 7 1. 31 ±0 .5 5 1. 30 ±0 .6 2 4. 41 ±1 .0 9 4. 32 ±1 .1 9 2. 51 ±0 .5 2 0. 89 ±0 .1 4 0. 87 ±0 .1 3 4. 92 ±0 .9 9 A *S Y ou ng *J un e 3. 33 ±0 .6 4 3. 10 ±0 .7 9 1. 39 ±0 .6 9 1. 31 ±0 .7 5 4. 72 ±1 .2 8 4. 41 ±1 .4 9 2. 55 ±0 .4 3 1. 04 ±0 .1 4 0. 96 ±0 .1 4 4. 60 ±1 .3 5 Y ou ng *S ep te m be r 3. 74 ±0 .6 3 4. 37 ±1 .8 4 1. 53 ±0 .4 8 1. 79 ±0 .8 9 5. 27 ±1 .0 4 6. 16 ±2 .6 4 2. 56 ±0 .4 4 1. 10 ±0 .2 5 1. 28 ±0 .5 6 4. 83 ±0 .6 3 O ld *J un e 2. 57 ±0 .4 2 2. 90 ±0 .6 3 1. 09 ±0 .3 7 1. 24 ±0 .4 6 3. 67 ±0 .5 9 4. 14 ±0 .8 9 2. 52 ±0 .5 9 0. 83 ±0 .0 9 0. 94 ±0 .1 7 4. 46 ±0 .8 6 O ld *S ep te m be r 3. 21 ±0 .6 5 3. 29 ±0 .9 1 1. 24 ±0 .4 9 1. 28 ±0 .5 6 4. 46 ±1 .1 1 4. 57 ±1 .4 2 2. 72 ±0 .4 0 0. 92 ±0 .1 4 0. 94 ±0 .2 2 4. 84 ±0 .7 8 A *Y Y ou ng *2 01 1 3. 63 ±0 .7 3 4. 25 ±1 .9 5 1. 48 ±0 .5 0 1. 73 ±0 .9 2 5. 11 ±1 .1 7 5. 98 ±2 .7 9 2. 55 ±0 .3 7 1. 17 ±0 .2 1 1. 34 ±0 .5 2 4. 37 ±0 .7 4 Y ou ng *2 01 3 3. 44 ±0 .5 8 3. 22 ±0 .6 9 1. 45 ±0 .6 8 1. 38 ±0 .7 5 4. 88 ±1 .2 2 4. 59 ±1 .4 3 2. 56 ±0 .4 9 0. 97 ±0 .1 4 0. 90 ±0 .1 0 5. 06 ±1 .2 1 O ld *2 01 1 3. 03 ±0 .6 7 3. 39 ±0 .8 8 1. 16 ±0 .5 2 1. 29 ±0 .5 6 4. 19 ±1 .6 5 4. 68 ±1 .4 0 2. 76 ±0 .4 1 0. 92 ±0 .1 3 1. 03 ±0 .1 9 4. 52 ±0 .9 2 O ld *2 01 3 2. 75 ±0 .5 7 2. 81 ±0 .5 9 1. 17 ±0 .3 5 1. 22 ±0 .4 6 3. 93 ±0 .7 2 4. 04 ±0 .8 6 2. 47 ±0 .5 7 0. 82 ±0 .0 9 0. 84 ±0 .1 4 4. 79 ±0 .7 4 S* Y Ju ne *2 01 1 2. 79 ±0 .3 9 2. 94 ±0 .6 9 1. 01 ±0 .1 9 1. 06 ±0 .2 8 3. 81 ±0 .5 8 4. 00 ±0 .9 7 2. 79 ±0 .2 0 0. 97 ±0 .1 7 1. 00 ±0 .1 7 3. 97 ±0 .3 9 Ju ne *2 01 3 3. 11 ±0 .8 3 3. 06 ±0 .7 4 1. 48 ±0 .7 1 1. 49 ±0 .7 7 4. 59 ±1 .3 9 4. 55 ±1 .4 0 2. 28 ±0 .6 0 0. 90 ±0 .1 4 0. 89 ±0 .1 1 5. 09 ±1 .3 2 Se pt em be r* 20 11 3. 87 ±0 .6 4 4. 69 ±1 .6 9 1. 63 ±0 .5 8 1. 96 ±0 .8 7 5. 49 ±1 .1 5 6. 65 ±2 .4 4 2. 53 ±0 .5 0 1. 13 ±0 .2 2 1. 36 ±0 .5 1 4. 92 ±0 .8 7 Se pt em be r* 20 13 3. 09 ±0 .6 7 2. 97 ±0 .6 1 1. 14 ±0 .2 4 1. 11 ±0 .3 4 4. 22 ±0 .6 9 4. 08 ±0 .9 3 2. 75 ±0 .5 9 0. 89 ±0 .1 4 0. 85 ±0 .1 4 4. 75 ±0 .4 8 A *S *Y Y ou ng *J un e* 20 11 3. 04 ±0 .3 3 2. 81 ±0 .5 9 1. 15 ±0 .1 3 1. 06 ±0 .2 3 4. 18 ±0 .4 5 3. 87 ±0 .8 2 2. 65 ±0 .1 0 1. 08 ±0 .1 6 0. 99 ±0 .1 8 3. 91 ±0 .3 1 Y ou ng *J un e* 20 13 3. 62 ±0 .7 5 3. 39 ±0 .8 9 1. 65 ±0 .9 2 1. 56 ±1 .0 0 5. 27 ±1 .6 3 4. 96 ±1 .8 6 2. 46 ±0 .5 9 1. 00 ±0 .1 2 0. 93 ±0 .0 9 5. 29 ±1 .6 5 Y ou ng *S ep te m be r* 20 11 4. 23 ±0 .4 7 5. 68 ±1 .7 5 1. 81 ±0 .5 2 2. 40 ±0 .8 6 6. 03 ±0 .8 8 8. 08 ±2 .4 4 2. 46 ±0 .5 1 1. 26 ±0 .2 3 1. 69 ±0 .5 3 4. 84 ±0 .7 6 Y ou ng *S ep te m be r* 20 13 3. 26 ±0 .2 9 3. 05 ±0 .4 4 1. 25 ±0 .2 2 1. 19 ±0 .3 7 4. 50 ±0 .4 2 4. 24 ±0 .7 8 2. 66 ±0 .3 6 0. 94 ±0 .1 5 0. 88 ±0 .1 1 4. 82 ±0 .5 3 O ld *J un e* 20 11 2. 55 ±0 .3 0 3. 07 ±0 .8 4 0. 88 ±0 .1 4 1. 06 ±0 .3 4 3. 43 ±0 .4 4 4. 13 ±1 .1 5 2. 93 ±0 .1 9 0. 86 ±0 .0 9 1. 01 ±0 .1 8 4. 03 ±0 .4 7 O ld *J un e* 20 13 2. 59 ±0 .5 4 2. 73 ±0 .3 9 1. 32 ±0 .4 0 1. 41 ±0 .5 1 3. 91 ±0 .6 6 4. 15 ±0 .6 3 2. 11 ±0 .5 9 0. 81 ±0 .0 8 0. 86 ±0 .1 2 4. 89 ±0 .9 7 O ld *S ep te m be r* 20 11 3. 51 ±0 .5 9 3. 70 ±0 .8 9 1. 45 ±0 .6 1 1. 52 ±0 .6 7 4. 96 ±1 .1 7 5. 22 ±1 .4 9 2. 60 ±0 .5 2 0. 99 ±0 .1 2 1. 04 ±0 .2 1 5. 01 ±1 .0 2 O ld *S ep te m be r* 20 13 2. 92 ±0 .5 9 2. 89 ±0 .7 8 1. 03 ±0 .2 3 1. 03 ±0 .3 2 3. 95 ±0 .8 1 3. 92 ±1 .0 8 2. 84 ±0 .2 1 0. 84 ±0 .1 2 0. 83 ±0 .1 8 4. 69 ±0 .4 7 F va lu es a nd p ro ba bi lit y le ve ls A ge (A ) 25 .3 24 ** * 7. 79 9* * 6. 09 1* 3. 92 8n .s . 17 .1 83 ** * 7. 02 3* 0. 34 8n .s . 31 .3 35 ** * 9. 40 4* * 0. 07 4n .s . Se as on (S ) 17 .1 54 ** * 13 .4 85 ** 1. 32 6n .s . 2. 98 9n .s . 8. 69 6* * 9. 67 9* * 0. 31 6n .s . 4. 43 7* 7. 35 2* * 1. 96 1n .s . Y ea r ( Y ) 3. 44 3n .s . 12 .3 77 ** 0. 00 7n .s . 2. 02 1n .s . 1. 19 7n .s . 8. 29 8* * 0. 18 0n .s . 17 .9 10 ** * 26 .7 66 ** * 4. 83 3* A *S 0. 80 7n .s . 3. 67 8n .s . 0. 00 4n .s . 2. 23 5n .s . 0. 29 4n .s . 3. 52 3n .s . 0. 36 0n .s . 0. 07 4n .s . 7. 37 0* * 0. 13 0n .s . A *Y 0. 11 5n .s . 0. 99 5n .s . 0. 02 8n .s . 0. 88 6n .s . 0. 01 1n .s . 1. 09 4n .s . 0. 17 4n .s . 1. 88 4n .s . 4. 41 6* 0. 89 8n .s . S* Y 18 .4 80 ** * 16 .4 86 ** * 16 .3 37 ** * 18 .3 29 ** * 20 .7 78 ** * 19 .7 96 ** * 0. 00 1n .s . 5. 85 8* 11 .5 54 ** 8. 85 4n .s . A *S *Y 3. 27 1n .s . 9. 13 8* * 0. 17 8n .s . 2. 11 2n .s . 1. 55 0n .s . 6. 62 5* 0. 11 9n .s . 0. 90 5n .s . 8. 23 0* * 0. 06 3n .s . 304 F. Martins, I. Oliveira, A. Barros, C. Amaral, S. Afonso, H. Ferreira, B. Gonçalves Ta b. 3 : V al ue s (m ea n ± st an da rd d ev ia tio n) f or p he no lic , T B A R S, p ro te in a nd th io ls c on te nt , a nd e le ct ro ly te le ak ag e, o f Sa lv ia o ffi ci na lis le av es a nd p ro ba bi lit y le ve ls o f th e ef fe ct s of A ge , S ea so n an d Y ea r, as de te rm in ed b y A N O VA . n s: n ot s ig ni fic an t. In b ol d, re su lts th at s ho w ed to b e af fe ct ed b y th e st ud ie d fa ct or s an d/ or th ei r i nt er ac tio n. To ta l p he no lic s To ta l p he no lic s T B A R S T B A R S P ro te in P ro te in T hi ol s E le ct ro ly te s (m g G A /d m 2 ) (m g G A /g ) (n m ol /c m 2 ) (n m ol /g ) (m g/ dm 2 ) (m g/ g) (n m ol /m g pr ot ei n) le ak ag e (% ) A ge (A ) Y ou ng 39 .4 4± 12 .6 7 37 .4 9± 12 .5 5 3. 02 ±1 .7 8 31 3. 89 ±1 91 .8 4 13 6. 45 ±1 51 .0 8 14 6. 26 ±1 76 .9 2 52 .5 9± 60 .4 6 14 .8 7± 2. 48 O ld 36 .3 1± 11 .2 0 40 .1 2± 10 .3 4 1. 43 ±0 .4 9 15 3. 19 ±5 2. 29 12 8. 72 ±9 3. 58 13 6. 33 ±9 7. 18 41 .6 9± 34 .7 6 15 .1 2± 4. 90 Se as on (S ) Ju ne 38 .4 9± 9. 86 38 .9 9± 10 .4 8 2. 18 ±1 .7 8 21 5. 25 ±1 61 .9 2 14 5. 72 ±1 57 .1 2 15 0. 33 ±1 63 .2 4 76 .3 6± 54 .9 2 14 .7 0± 2. 31 Se pt em be r 37 .2 5± 13 .8 9 38 .6 2± 12 .5 7 2. 27 ±1 .2 3 25 1. 83 ±1 61 .0 5 11 9. 44 ±8 1. 07 13 2. 26 ±1 18 .2 3 17 .9 3± 12 .1 3 15 .1 8± 4. 53 Y ea r (Y ) 20 11 32 .6 7± 12 .3 8 35 .2 9± 11 .5 2 2. 96 ±1 .7 5 31 2. 12 ±1 79 .5 5 11 8. 98 ±1 03 .6 1 13 6. 88 ±1 33 .2 9 52 .5 3± 62 .7 0 12 .8 8± 2. 72 20 13 43 .0 8± 9. 05 42 .3 1± 10 .4 8 1. 49 ±0 .7 3 14 5. 96 ±6 9. 23 14 6. 19 ±1 43 .1 7 14 5. 71 ±1 51 .6 2 41 .7 6± 30 .5 5 15 .6 3± 3. 94 A *S Y ou ng *J un e 39 .6 6± 9. 91 36 .3 2± 9. 11 2. 99 ±2 .1 9 27 6. 02 ±2 05 .4 3 15 2. 13 ±1 96 .4 1 14 9. 44 ±2 07 .6 9 88 .1 2± 68 .7 5 15 .4 2± 2. 54 Y ou ng *S ep te m be r 39 .2 1± 15 .2 8 38 .6 6± 15 .4 8 3. 04 ±1 .3 1 35 1. 76 ±1 75 .5 0 12 0. 77 ±8 9. 85 14 3. 07 ±1 46 .7 2 17 .0 7± 11 .6 1 14 .5 3± 2. 47 O ld *J un e 37 .3 4± 9. 98 41 .6 6± 11 .3 5 1. 36 ±0 .5 8 15 4. 48 ±6 4. 40 13 9. 32 ±1 11 .1 5 15 1. 21 ±1 09 .2 3 64 .6 0± 34 .7 9 13 .9 9± 2. 31 O ld *S ep te m be r 35 .2 9± 12 .5 5 38 .5 7± 9. 32 1. 51 ±0 .3 9 15 1. 90 ±3 8. 72 11 8. 11 ±7 4. 19 12 1. 45 ±8 4. 35 18 .7 9± 12 .9 5 15 .8 3± 5. 95 A *Y Y ou ng *2 01 1 36 .3 1± 14 .5 7 35 .1 3± 13 .9 6 4. 34 ±1 .4 0 46 9. 21 ±1 31 .1 2 11 1. 28 ±9 9. 56 13 4. 63 ±1 53 .4 8 58 .9 3± 77 .5 3 14 .9 7± 2. 03 Y ou ng *2 01 3 42 .5 6± 9. 93 39 .8 5± 10 .8 9 1. 69 ±0 .9 0 15 8. 67 ±8 6. 05 16 1. 63 ±1 89 .5 0 15 7. 88 ±2 02 .0 9 46 .2 6± 38 .1 9 14 .8 4± 2. 65 O ld *2 01 1 29 .0 4± 8. 75 35 .4 5± 8. 90 1. 57 ±0 .5 0 17 3. 04 ±5 1. 46 12 6. 67 ±1 10 .2 3 13 9. 13 ±1 14 .6 8 46 .1 3± 45 .0 3 10 .8 0± 1. 29 O ld *2 01 3 43 .5 9± 8. 36 44 .7 8± 9. 76 1. 29 ±0 .4 5 13 3. 35 ±4 6. 49 13 0. 75 ±7 7. 08 13 3. 54 ±7 9. 69 37 .2 6± 20 .6 8 16 .4 2± 4. 85 S* Y Ju ne *2 01 1 31 .7 1± 8. 86 32 .5 2± 8. 25 3. 27 ±1 .9 3 31 9. 55 ±1 66 .0 8 10 8. 56 ±9 8. 76 11 4. 43 ±9 8. 16 96 .0 5± 63 .5 1 n. a. Ju ne *2 01 3 45 .2 9± 4. 89 45 .4 6± 8. 35 1. 09 ±0 .5 5 11 0. 95 ±5 8. 59 18 2. 90 ±1 95 .7 5 18 6. 23 ±2 06 .6 1 56 .6 8± 37 .0 4 14 .7 0± 2. 31 Se pt em be r* 20 11 33 .6 4± 15 .3 8 38 .0 7± 13 .7 7 2. 65 ±1 .5 4 32 2. 69 ±1 97 .5 7 12 9. 40 ±1 10 .4 6 15 9. 33 ±1 61 .2 7 9. 01 ±7 .2 1 12 .8 8± 2. 72 Se pt em be r* 20 13 40 .8 7± 11 .6 1 39 .1 6± 11 .6 7 1. 90 ±0 .6 7 18 0. 97 ±6 2. 10 10 9. 48 ±3 4. 19 10 5. 19 ±3 6. 32 26 .8 5± 9. 08 16 .5 6± 4. 89 A *S *Y Y ou ng *J un e* 20 11 33 .9 3± 10 .9 9 30 .2 1± 7. 26 4. 84 ±1 .4 4 44 3. 94 ±1 48 .0 6 98 .9 0± 69 .4 9 94 .7 3± 68 .4 7 10 9. 71 ±8 3. 25 n. a. Y ou ng *J un e* 20 13 45 .3 8± 3. 84 42 .4 3± 6. 32 1. 14 ±0 .6 4 10 8. 09 ±6 3. 68 20 5. 37 ±2 67 .1 3 20 4. 16 ±2 84 .4 4 66 .5 3± 46 .1 9 15 .4 2± 2. 55 Y ou ng *S ep te m be r* 20 11 38 .6 8± 17 .9 2 40 .0 6± 17 .6 0 3. 84 ±1 .2 5 49 4. 47 ±1 16 .0 3 12 3. 66 ±1 26 .7 2 17 4. 53 ±2 05 .3 1 8. 14 ±7 .3 7 14 .9 7± 2. 04 Y ou ng *S ep te m be r* 20 13 39 .7 5± 13 .3 6 37 .2 7± 14 .1 2 2. 24 ±0 .8 0 20 9. 04 ±7 7. 38 11 7. 89 ±3 4. 97 11 1. 61 ±4 1. 38 25 .9 9± 7. 23 14 .2 6± 2. 76 O ld *J un e* 20 11 29 .4 8± 6. 02 34 .8 3± 9. 01 1. 69 ±0 .4 9 19 5. 16 ±4 2. 70 11 8. 21 ±1 25 .9 3 13 4. 13 ±1 14 .2 4 82 .3 8± 35 .8 8 n. a. O ld *J un e* 20 13 45 .1 9± 6. 04 48 .4 9± 9. 39 1. 03 ±0 .4 7 11 3. 81 ±5 7. 29 16 0. 43 ±9 7. 96 16 8. 29 ±9 9. 13 46 .8 2± 24 .1 9 13 .9 9± 2. 31 O ld *S ep te m be r* 20 11 28 .5 9± 11 .2 8 36 .0 8± 9. 36 1. 45 ±0 .5 2 15 0. 91 ±5 2. 28 13 5. 14 ±1 00 .0 6 14 4. 12 ±1 14 .2 4 9. 89 ±7 .4 4 10 .8 0± 1. 29 O ld *S ep te m be r* 20 13 41 .9 9± 10 .3 7 41 .0 6± 9. 17 1. 56 ±0 .2 3 15 2. 89 ±2 1. 84 10 1. 08 ±3 3. 47 98 .7 8± 31 .9 4 27 .7 0± 11 .0 7 18 .8 5± 5. 58 F va lu es a nd p ro ba bi lit y le ve ls A ge (A ) 1. 32 2n .s . 0. 93 4n .s . 58 .4 65 ** * 61 .5 02 ** * 0. 07 5n .s . 0. 05 9n .s . 1. 35 4n .s . 1. 78 4n .s . Se as on (S ) 0. 21 0n .s . 0. 01 9n .s . 0. 22 4 3. 18 7n .s . 0. 24 8n .s . 0. 68 0n .s . 38 .9 46 ** * 3. 26 4n .s . Y ea r ( Y ) 14 .6 94 ** * 6. 68 7* 49 .9 75 ** * 73 .0 76 ** * 0. 05 9n .s . 0. 72 9n .s . 1. 32 3n .s . 9. 59 0* * A *S 0. 08 7n .s . 1. 00 4n .s . 0. 05 2 0. 36 5n .s . 0. 10 4n .s . 0. 02 5n .s . 1. 81 8n .s . 8. 60 3* * A *Y 2. 33 3n .s . 0. 72 0n .s . 32 .7 85 ** * 43 .7 16 ** * 0. 15 8n .s . 0. 52 7n .s . 0. 04 1n .s . 13 .6 65 ** S* Y 1. 36 7n .s . 4. 76 1* 11 .9 63 ** * 2. 66 3n .s . 3. 01 3n .s . 2. 18 6n .s . 9. 33 4* * n. a. A *S *Y 0. 55 1n .s . 0. 34 0n .s . 2. 53 0 0. 16 1n .s . 0. 40 9n .s . 0. 08 0n .s . 0. 04 2n .s . n. a. Salvia officinalis L. biochemical dynamics 305 Season and Year factors showed influence in the results reported by leaf weight (Tab. 3). Considerable variation of the content on phe- nolics present in aromatic and medicinal plants has been reported by other authors (kofidiS et al., 2007). The relationship to harvest season, with increase in summer months, has been linked to their protective properties against excessive UV-B radiation that might reach mesophyll chloroplasts and nuclei, therefore shielding leaf cells from structural and functional damages (manukYan, 2013). However, our results do not show this behaviour, and the detected influence caused by the Season*Year interaction appears to be more likely caused by the year factor. As referred before, total phenolic compounds present in the leaves of sage were influenced by the year of study, with higher values recorded in 2013, with the same pattern observed for electrolyte leakage. These results appear to indicate that in 2013, the plants were under increased stress conditions, as it is well established that phenolics act as defense mechanisms against stress conditions (e.g. manukYan, 2013), while electrolyte leakage is used to estimate membrane integrity (rolnY et al., 2011). Climatic data concerning precipitation and temperature show that 2011 was one of the hottest years in Portugal since 1930, and that precipitation was also considerably lower than common records (IPMA, 2015), while 2013 was considered an average year. This information about climatic data gives more consistency with the results observed for TBARS. This methodology allows an overview regarding peroxi- dation of membrane, and usually, higher values indicate a higher exposure to stress, which apparently, and as stated above, occurred in 2011. Therefore, some other factors would have been implicated in this higher amount of phenolics and of electrolyte leakage. By one hand, the higher values of total phenolics in 2013, quantified using the Folin-Ciocalteu method can be due to the higher amount of sugars found is this year, compounds, that among others, are known to interfere with this methodology (prior et al., 2005). Sugars may also be associated to the values of electrolyte leakage, as they have been correlated to an increase in this parameter (SHi et al., 2012), although they are known as key osmolytes, improving stress tole- rance by protecting and stabilizing membranes. The age factor also significantly influenced the TBARS content (ex- pressed as nmol/g), with higher values recorded in young leaves. Although several reports indicate that the amount of these com- pounds may be higher in adult leaves of several species (lepeduš et al., 2011), higher lipid peroxidation measured by the TBARS assay in young leaves has been reported (carvalHo et al., 2015). Interestingly, the total carotenoid content in young leaves was also higher (Tab. 2), and it can be argued that their accumulation in young leaves can be related not to their photosynthetic role, but instead to their known protective antioxidant characteristics (krinSkY, 1989). There is a lack of information about how the presence of phenolics can influence the processing of aromatic plants. It can be expected that leaves with higher content of phenolics can be less suscepti- ble to oxidation, as those compounds are proved to be antioxidants (e.g. gião et al., 2013). The presence of these compounds can also influence leaf sensorial attributes, as they have associated two main descriptors, namely bitterness and astringency, which are linked to negative consumer reactions (leSScHaeve and noBle, 2005). For thiol content (Tab. 3), a strong influence of season was found, with samples collected in June presenting higher values than those re- corded in September. These compounds act like intracellular anti- oxidants, either through scavenging free radicals or by enzymatic reactions, and some of them, although being water-soluble, are able to protect biological membranes against lipid peroxidation (maScio et al., 1991). Interestingly, none of the other studied parameters that evaluate oxidation processes show this behavior pattern of higher values in June. In this month, although temperatures were similar to those recorded in September (average of 18.2 °C in June and 19.6 °C in September), rain was considerably lower (average of 5.6 mm in June and 67.8 mm in September), and, furthermore, total radiation was significantly higher (average of 27.6 kj/m2 in June and 16.9 kj/m2 in September). Hence, this increase in thiols concentra- tion can be a response to those stresses, in order to reduce oxidation (maScio et al., 1991) and cell damage. Conclusions This work allowed a detailed characterization of several biochemi- cal parameters of Salvia officinalis L. var. purpurascens, as well as an evaluation of their dynamics, considering developmental stage, season and year factors. This latter factor was the one that exerted a significant influence in a higher number of parameters, situation that is likely linked to differences in climatic conditions (consider- able difference of precipitation between the years of study, but also of temperature values), while, on the other hand, the developmen- tal stage of leaves influenced almost only the content on photosyn- thetic pigments. These results are key to understand biochemical variations occurring in Salvia officinalis L. var. purpurascens, and helpful when designing cultivation strategies for this specific plant. Acknowledgements This work is supported by: European Investment Funds by FEDER/ COMPETE/POCI – Operacional Competitiveness and Internacio- nalization Programme, under Project POCI-01-0145-FEDER-006958 and National Funds by FCT – Portuguese Foundation for Science and Technology, under the project UID/AGR/04033.” References ABREU, M., munné-BOSCH, S., 2007: Photo- and antioxidant protection and salicylic acid accumulation during post-anthesis leaf senescence in Salvia lanigera grown under Mediterranean climate. Physiol. Plant. 131, 590-598. BETTAIEB, I., HAMROUNI-SELLAMI, I., BOURGOU, S., LIMAM, F., MARZOUK, B., 2011: Drought effects on polyphenol composition and antioxidant activities in aerial parts of Salvia officinalis L. Acta Physiol. Plant. 33, 1103-1111. BRADFORD, M., 1976: A rapid and sensitive method for the quantification of microgram quantities of protein using the principle of protein-dye binding. Anal. Biochem. 72, 248-254. CARVALHO, F., WARE, M., RUBAN, A., 2015: Quantifying the dynamics of light tolerance in Arabidopsis plants during ontogenesis. Plant Cell. Environ. 38, 2603-2617. CASTRILLO, M., VIZCAÍNO, D., MORENO, E., LATORRACA, Z., 2005: Specific leaf mass, fresh:dry weight ratio, sugar and protein contents in species of Lamiaceae from different light environments. Rev. Biol. Trop. 53, 23-28. COISIN, M., PADURARIU, C., ANDRO, R., BOZ, I., ZAMFIRACHE, M., BURZO, I., 2010: Biochemical and physyological researches researches in Salvia nemorosa L. An. Stiint. Univ. Biologie vegetal. LVI, 31-37. DANGL, J., DIETRICH, R., THOMAS, H., 2000: Senescence and programmed cell death. In: Buchanan, B., Gruissem, W., Jones, R. (eds.), Biochemistry and Molecular Biology of Plants, 1044–1100. ASPB, Rockville. DIVYA, P., PUTHUSSERI, B., NEELWARNE, B., 2012: Carotenoid content, its stability during drying and the antioxidant activity of commercial co- riander (Coriandrum sativum L.) varieties. Food Res. Int. 45, 342-350. GAO, Q., WU, C., WANG, M., XU, B., DU, L., 2012: Effect of drying of ju- jubes (Ziziphus jujuba Mill.) on the contents of sugars, organic acids, α-tocopherol, β-carotene, and phenolic compounds. J. Agric. Food Chem. 60, 9642-9648. GIÃO, M., PEREIRA, C., PINTADO, M., MALCATA, F., 2013: Effect of tech- nological processing upon the antioxidant capacity of aromatic and 306 F. Martins, I. Oliveira, A. Barros, C. Amaral, S. Afonso, H. Ferreira, B. Gonçalves medicinal plant infusions: From harvest to packaging. LWT Food Sci. Technol. 50, 320-325 HALLIWELL, B., 1996: Antioxidants in human health and disease. Annu. Rev. Nutr. 16, 33-50. IPMA, 2015: http://www.ipma.pt/pt/index.html. IRIGOYEN, J., EMERICH, D., SÁNCHEZ-DÍAZ, M., 1992: Water stress induced changes in concentrations of proline and total soluble sugars in nodula- ted alfalfa (Medicago sativa) plants. Physiol. Plant. 84, 55-60. KOFIDIS, G., BOSABALIDIS, M., MOUSTAKAS, M., 2007: Combined effects of altitude and season on leaf characteristics of Clinopodium vulgare L. (Labiatae). Environ. Exper. Bot. 60, 69-76. KRINSKY, N., 1989. Antioxidant functions of carotenoids. Free Radic. Biol. Med. 7, 617-635. LEPEDUŠ, H., GAĆA, V., VILJEVAC, M., KOVAČ, S., FULGOSI, H., ŠIMIĆ, D., CESAR, V., 2011: Changes in photosynthetic performance and antioxi- dative strategies during maturation of Norway maple (Acer platanoides L.) leaves. Plant Physiol. Biochem. 49, 368-376. LESSCHAEVE, I., NOBLE, A., 2005: Polyphenols: factors influencing their sensory properties and their effects on food and beverage preferences. Am. J. Clin. Nutr. 81, 330-335. LICHTENTHALER, H., 1987: Chlorophylls and carotenoids: Pigments of pho- tosynthetic biomembranes. Methods Enzymol. 148, 350-382. LUTTS, S., KINET, J., BOUHARMONT, J., 1996 : NaCl-induced senescence in leaves of rice (Oryza sativa L.) cultivars differing in salinity resistance. Ann. Bot. 78, 389-398. MANUKYAN, A., 2013: Effects of PAR and UV-B Radiation on herbal yield, bioactive compounds and their antioxidant capacity of some medici- nal plants under controlled environmental conditions. Photochem. Photobiol. 89, 406-414. MAPES, C., XU, Y., 2014: Photosynthesis, vegetative habit and culinary pro- perties of sage (Salvia officinalis) in response to low-light conditions. Can. J. Plant Sci. 94, 881-889. MASCIO, P., MURPHY, M., SIES, H., 1991: Antioxidant defense systems: the role of carotenoids, tocopherols, and thiols. Am. J. Clin. Nutr. 53, 194- 200. MUNNÉ-BOSCH, S., ALEGRE, L., 2002: The function of tocopherols and to- cotrienols in plants. Crit. Rev. Plant Sci. 21, 31-57. NASTA, O., AKOUMIANAKI-IOANNIDOU, A., LIAKOPOULOS, G., NIKOLOPOULOU, A., 2014: Effects of salinity in the form of simulated sea-spray (NaCl or NaCl+ H3BO3 solution) on growth and photosynthe- tic performance of sage (Salvia officinalis). Aust. J. Biol. Sci. 8, 1186- 1194. OSAKI, M., SHINANO, T., TADANO, T., 1991: Redistribution of carbon and nitrogen compounds from the shoot to the harvesting organs during ma- turation in field crops. Soil Sci. Plant Nutr. 37, 117-128. PELLEGRINI, E., FRANCINI, A., LORENZINI, G., NALI, C., 2015: Ecophysiological and antioxidant traits of Salvia officinalis under ozo- ne stress. Environ. Sci. Pollut. R. 22, 13083-13093. PRIOR, R., WU, X., SCHAICH, K., 2005: Standardized methods for the de- termination of antioxidant capacity and phenolics in foods and dietary supplements. J. Agric. Food Chem. 53, 4290-4302 ROBY, M., SARHAN, M., SELIM, K., KHAEL, K., 2013: Evaluation of anti- oxidant activity, total polyphenols and phenolic compounds in thy- me (Thymus vulgaris L.), sage (Salvia officinalis L.) and marjoram (Origanum majorana L.) extracts. Ind. Crops Prod. 43, 827-831. ROLNY, N., COSTA, L., CARRIÓN, C., GUIAMET, J., 2011: Is the electrolyte leakage assay an unequivocal test of membrane deterioration during leaf senescence? Plant Physiol. Biochem. 49, 1220-1227. SAHAR, K., AMIN, B., TAHER, N., 2011: The salicylic acid effect on the Salvia officinalis L. sugar, protein and proline contents under salinity (NaCl) stress. J. Stress Physiol. Biochem. 7, 80-87. SCHIPPMANN, U., LEAMAN, D., CUNNINGHAM, A., 2006: A comparison of cultivation and wild collection of medicinal and aromatic plants un- der sustainability aspects. In: Boger, R., Craker, L., Lange, D. (eds.), Medicinal and Aromatic Plants Springer, 75-95. The Netherlands. SESTÁK, Z., CASTKY, J., JARVIS, P., 1971: Plant photosynthetic production. Manual of Methods. Dr. W. Junk Publishers, Hague, Netherlands. SHI, H., WANG, Y., CHENG, Z., YE, T., CHAN, Z., 2012: Analysis of natural variation in bermudagrass (Cynodon dactylon) reveals physiological re- sponses underlying drought tolerance. PLoS ONE. 7, e53422. TAÂRIT, M., MSAADA, K., HOSNI, K., MARZOUK, B., 2012: Physiological changes, phenolic content and antioxidant activity of Salvia officinalis L. grown under saline conditions. J. Sci. Food. Agric. 92, 1614-1619. TEPE, B., 2008: Antioxidant potentials and rosmarinic acid levels of the me- thanolic extracts of Salvia virgata (Jacq), Salvia staminea (Montbret & Aucher ex Bentham) and Salvia verbenaca (L.) from Turkey. Bioresour. Technol. 99, 1584-1588. TOUNEKTI, T., ABREU, M., KHEMIRA, H., MUNNÉ-BOSCH, S., 2012: Canopy position determines the photoprotective demand and antioxidant pro- tection of leaves in salt-stressed Salvia officinalis L. plants. Environ. Exp. Bot. 78, 146-156. TOUNEKTI, T., HERNÁNDEZ, I., MÜLLER, M., KHEMIRA, H., MUNNÉ- BOSCH, S., 2011: Kinetin applications alleviate salt stress and improve the antioxidant composition of leaf extracts in Salvia officinalis. Plant Physiol. Biochem. 49, 1165-1176. TSAO, R., YANG, R., YOUNG, J., ZHU, H., 2003: Polyphenolic profiles in eight apple cultivars using high-performance liquid chromatography (HPLC). J. Agric. Food Chem. 51, 6347-6353. WORLD HEALTH ORGANIZATION, 2003: WHO guidelines on good agricul- tural and collection practices (GACP) for medicinal plants. Geneva: World Health Organization. YI, W., WETZSTEIN, H., 2010: Biochemical, biological and histological eva- luation of some culinary and medicinal herbs grown under greenhouse and field conditions. J. Sci. Food Agr. 90, 1063-1070. Address of the authors: F. Martins, Universidade de Trás-os-Montes e Alto Douro, UTAD, Quinta de Prados, 5000-801 Vila Real, Portugal I. Oliveira, A. Barros, C. Amaral, S. Afonso, H. Ferreira, B. Gonçalves, Centre for the Research and Technology of Agro-Environmental and Biological Sciences – CITAB, Universidade de Trás-os-Montes e Alto Douro, UTAD, Quinta de Prados, 5000-801 Vila Real, Portugal E-mail of the corresponding author: ivo.vaz.oliveira@utad.pt © The Author(s) 2016. This is an Open Access article distributed under the terms of the Creative Commons Attribution Share-Alike License (http://creative- commons.org/licenses/by-sa/4.0/).