Water stress effects on growth, yield and quality traits of red beet

Scientia Horticulturae 165 (2014) 13–22

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Water stress effects on growth, yield and quality traits of red beet Fabio Stagnari ∗ , Angelica Galieni, Stefano Speca, Michele Pisante Agronomy and Crop Sciences Research and Education Center, Department of Food Science, University of Teramo, Via Carlo Lerici, 1, I-64023 Teramo, Italy

a r t i c l e

i n f o

Article history: Received 20 November 2012 Received in revised form 17 September 2013 Accepted 23 October 2013 Keywords: Water stress Red beet Betalains Antioxidant activity Phenolic content

a b s t r a c t The response of red beet to drought stress was investigated in order to explore the adaptive changes in plant growth, dry mass production and partitioning, yield, and accumulation of nutrients and bioactive molecules. Glasshouse experiments were conducted in 2012. Three water stress treatments were applied: (W100) 100% of water holding capacity (WHC), (W50) 50% of WHC, (W30) 30% of WHC. Water stress reduced storage root weight by 62% at W50 and 75% at W30 as well as leaf water content (LWC). With the progressive water stress, plant allocated less dry matter into roots leading to reductions of 32% and 43% in W50 and W30, respectively as compared to W100. Stomatal conductance was strongly reduced (from 496 to 211 mmol m−2 s−1 in W100 and W30, respectively); canopy temperature (CT) reflected the available water, with differences of 11 ◦ C. Drought induced a significantly higher concentration of total phenolic content (a 86% increase) and betalains (52% and 70% increases in betacyanin and betaxanthin) and consequently, a higher antioxidant activity was obtained. Minerals such as Mg, P and especially Zn (2.9 and 1.1 mg 100 g−1 DW in W50 and W100, respectively) and Fe (5.6 and 2.4 mg 100 g−1 DW in W30 and W100, respectively) were highly concentrated in water stressed roots alike NDF and ADF. In contrast, ◦ Brix, pH and total not-structural sugars were reduced by water stress, although the sucrose fractions of fructose and glucose concentrated more in W30 plant roots than W100 (18% and 33% higher, respectively). Red beet showed a strong plasticity in its adaptation to drought thanks to avoidance mechanisms (constrained leaf and storage root development) and tolerance mechanisms (increased FLV and thermal dissipation). Interestingly, the high concentration in phytochemicals and nutrients may contribute to the maintenance of human health and may reduce the risk of chronic diseases. © 2013 Elsevier B.V. All rights reserved.

1. Introduction Water availability is considered as one of the most important environmental factors affecting plant growth and productivity (Boyer, 1982). Variations in water availability induce morphological, anatomical and physiological responses such as higher leaf and cuticle thickness (Guerfel et al., 2009), adjustments in gas exchange and assimilate translocation (Morgan et al., 2004), alteration in water uptake and evapotranspiration (Katerji et al., 2010), antioxidant reactions (Apel and Hirt, 2004), gene expression and enzyme activity (Jiang and Zhang, 2002). Phenotypic plasticity is considered the major means by which plants cope with environmental change and in particular water stress (Valladares et al., 2007). Under drought, the changes in plant dry mass allocation patterns often lead to lower leaf area/root biomass ratio changes. These changes relate closely to the water use efficiency (WUE) and acclimation mechanisms to water stress intensity (Navas and Garnier, 2002). Subsequent stomata closure can reduce leaf water potential, thus maintaining water uptake, photosynthesis and growth for as

∗ Corresponding author. Tel.: +39 861 266940; fax: +39 861 266940. E-mail address: [email protected] (F. Stagnari). 0304-4238/$ – see front matter © 2013 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.scienta.2013.10.026

long as possible (Clarke et al., 1993). Indeed, stomatal closure leads to a lower level of water loss per unit of carbon assimilation, thereby improving the WUE in water stressed plants (Gonzáles et al., 2008). However, stomatal closure is also coupled with inhibition of CO2 flow and nutrient uptake by roots, eventually resulting in reduced photosynthesis and subsequent carbohydrate production (Dunham and Clarke, 1992). In addition, evapotranspiration tends to cease, which in turn raises the temperature of the leaf (Lourtie et al., 1995). Water stress affects crop quality significantly. In soybean and wheat seed, protein accumulation was respectively inhibited (Rotundo and Westgate, 2009) and increased (Ozturk and Aydin, 2004). In several crops, reduction in starch accumulation was observed under water stress, although the results were very variable (Debon et al., 1998; Bethke et al., 2009). Since water plays an important role in mineral mobilization, water deficit may reduce uptake of Fe, Zn and Cu (Oktem, 2008) although other studies observed higher mineral concentrations (Keutgen and Pawelzik, 2009). In addition, studies dealing with horticultural crops reported increases in antioxidant concentrations under water stress (Favati et al., 2009). Red beet (Beta vulgaris var. conditiva Alef.) is a potential source of minerals, antioxidants, sugars, dietary fibers, vitamins, fatty acids and natural pigments that possess several biological activities,

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F. Stagnari et al. / Scientia Horticulturae 165 (2014) 13–22

Fig. 1. Patterns of temperature (◦ C) and relative humidity (%) during the course of experimentation.

including antioxidant, anticancer and radio-protective properties (Escribano et al., 1998). Nevertheless, to date, no studies have been conducted to study the effects of abiotic stress, and particularly water stress, on yield and nutrient accumulation in this crop. A few studies conducted on the subject regard dry matter partitioning (Hole et al., 1984; Benjamin and Sutherland, 1989) but in non-limiting growing conditions. Some works on sugar beet, a crop relative to red beet, showed that the environment strongly affects sugar beet growth, root yield and sugar quality (Tsialtas and Maslaris, 2006; Hoffmann et al., 2009; Tsialtas et al., 2010, 2011). Nevertheless the effect of water shortages on dry matter partitioning is unclear (Abdollahian-Noghabi and Froud-Williams, 1998), although the greatest reduction in dry matter accumulation usually occurs in the storage roots. Therefore, to study the effects of water stress on the adaptive changes in plant growth, red beets were subjected to three water regimes (100%, 50% and 30% of water holding capacity). The main objectives were to assess the drought tolerance of red beet and the accumulation in roots of elements and molecules with putative biological activity.

2. Materials and methods Two experiments were carried out from March to mid June 2012, at the greenhouse of Agronomy and Crop Sciences Research and Education Center, Department of Food Science, University of Teramo (42◦ 53 N and 13◦ 55 E, 15 m a.s.l.). Environmental conditions were constantly monitored during the crop cycle (Fig. 1) using temperature and humidity sensors connected to a data logger (EM50 Data Collection System, Decagon Devices, USA).

2.1. Plant material and experimental design Seeds of red beet (B. vulgaris L. var. conditiva Alef., cv. Piatta d’Egitto) were sown on a nursery potting soil (Huminsubstrat N3, Neuhaus, Germany) and were irrigated till crop emergence (7 days after sowing). Seven days after emergence, plants were transplanted into 20 cm diameter pots (5 l) at a density of 1 plant/pot. Pots were filled with sphagnum peat moss, perlite and vermiculite at the ratio of 2:1:1.5. At transplanting, simple superphosphate at a rate of 3 kg m−3 was incorporated into the potting soil substrate. At 11 and 19 days after transplanting plants were fertilized with

an NPK fertilizer 20-20-20 (Linea Master 20.20.20, Valagro S.p.a., Italy) at a rate of 6 g per pot. The experimental design was a randomized complete block design with three replicates, where three water regimes represented the thesis under comparison, as follows: pots kept at 100% (W100) of water holding capacity (WHC), 50% (W50) of WHC and 30% (W30) of WHC. Each thesis (treatment) consisted of 240 pots (hence, 80 pots represented one experimental unit). The water regimes were imposed starting from the transplanting. Water loss, due to evapotranspiration, was constantly monitored by injecting into the pot soil moisture sensors (EC-5, Decagon Devices, USA), which were connected to a data logger (EM50 Data Collection system, Decagon Devices, USA), in order to maintain the initial water content. The pots were manually re-watered with tap water (pH 7.2, EC 0.23 mS cm−1 ) every day at 18:00. The soil volumetric water content was maintained at 0.230, 0.115 and 0.069 m3 m−3 for W100, W50 and W30, respectively. 2.2. Determinations of physiological traits 2.2.1. Stomatal conductance Starting from 19 days after emergence (DAE), the leaf stomatal conductance (mmol m−2 s−1 ) was measured weekly with a steady state diffusion porometer (Model SC-1, Decagon Devices, USA). This hand held porometer measures leaf stomatal conductance (gs ), by electronically timing a given amount of air movement through the leaf under pressure (Rebetzke et al., 2000). Measurements were taken in one fully expanded leaf of four randomly selected plants per experimental unit. 2.2.2. Canopy temperature Canopy temperature was assessed with a portable infrared thermometer (Everest Interscience Inc., Az, USA) on the day following an irrigation either around midday or in the early afternoon on warm, relatively cloudless days, according to Amani et al. (1996). Temperature was measured with the instruments held at 45◦ to the horizontal and at a distance of 20 cm from the leaf surface. Measurements were taken on the same leaf of four different plants per experimental unit. 2.2.3. Leaf water content Following the procedure of Turner (1981), leaf water content (LWC [%]) was calculated as: LWC (%) = [(FW − DW)/FW] × 100];

F. Stagnari et al. / Scientia Horticulturae 165 (2014) 13–22

where FW and DW represent fresh and dry mass of the leaves, respectively. 2.3. Growth analysis Three plants per each experimental unit were sampled at week intervals until the final harvest (7, 13, 19, 26, 33, 40, 47, 54, 60 and 65 DAE). Plants were separated into leaf blades, petioles and storage roots for fresh (FW) and dry weight (DW) determinations after oven-drying at 80 ◦ C for 72 h. Storage roots were cut half for equatorial diameter measurements (cm) and then were cut into smaller pieces to ensure thorough drying. Growth indices, early relative root growth rate (ERGR, g g−1 DAE/GDD−1 ) and initial leaf growth rate (ILGR, g g−1 DAE/GDD−1 ), were calculated as proposed by Hunt (1982). They were expressed in DAE and growing degree-days (GDD), where GDD is the number of degree-days (above Tbase ) for that day based on mean air temperature (Tmean ), using 5.6 ◦ C as Tbase value (Brewster and Sutherland, 1993). Alike the results of Tei et al. (1996), dry weights of leaves and roots, after log-transformation, were approximately linearly related to DAE and GDD over the first four harvests, so regressions fitted to these data were used to calculate the average ERGR, and ILGR. Dry matter partitioning to the leaves (FLV) was measured by calculating the fraction of the total amount of new dry weight between two subsequent harvests directed to the leaves (Tei et al., 1996). The fraction was related to the DAE between harvests.

15

60 Hz for 15 min. The work conditions were: eluent flow 1 ml/min, column pressure 9.31 MPa, total conductibility 26 ␮S, injection loop 10 ␮l. The calibration curves were linear in the range of 2.5–10 ppm and the correlation coefficients were respectively 0.9999, 0.9993 and 0.9996 for glucose, fructose and sucrose. All peaks were detected by a retention time with a maximum variation of the standard deviation of 5%. All data obtained were expressed as mean of three replications, each one was repeated twice. 2.4.4. Mineral analysis The 2 g samples test portion were dried and then incinerated in a muffle furnace at 460 ◦ C for 15 h. The ash was bleached after cooling by adding 2 ml of 2 N nitric acid, drying it on a thermostatic hotplate and maintaining it in a muffle furnace at 460 ◦ C for 1 h. Ash recovery was performed with 5 ml of 2 N suprapure nitric acid, making up to 15 ml with 0.1 N suprapure nitric acid. The determination of the P was carried out by the 991.25 colorimetric method indicated by the AOAC (1990) in solutions of samples resulting from the drying treatment previously described. The determinations were carried out by flame atomic absorption spectrophotometry (Perkin-Elmer model 23801, Waltham, MA, USA), except for K, which was analyzed by flame photometry. For the determination of Fe and Zn, a 1/100 dilution was necessary. 2.4.5. Total dietary fiber analysis The neutral detergent fiber (NDF) and acid detergent fiber (ADF) were determined following the method of Ververis et al. (2007).

2.4. Quality The analyses on quality traits were carried out on the roots harvested at 65 DAE. 2.4.1. Total phenolic content Roots were peeled, cut into small pieces and thoroughly mixed. A 5 g sample from each root was treated with methanol (10 ml) and homogenized with the T-25 Ultra-Turrax (IKA-LAB, Seneco S.r.l., Italy), then sonicated with Sonis 4 for 1 h in a cooled water bath. The extracts were centrifuged for 10 min at 15,000g at 4 ◦ C. The supernatant was filtered through a Chromafill AO-22/25 polyamide filter and transferred to a vial. The total phenolic content (TPC) of each extract was assessed using the Folin–Ciocalteu phenol reagent method (Singleton and Rossi, 1965). The spectrophotometer used was a UV/VIS spectrophotometer (Lambda Bio20, Perkin-Elmer, Waltham, MA). The TPC was expressed as gallic acid equivalents (GAE) in mg per root g FW. ◦

2.4.2. pH and Brix The pH of root juice was measured using a pH-meter (OrionResearch Inc., model 701 Al Digital Ioanalyzer, Cambridge, MA, USA). Soluble solids were measured at 20 ◦ C using a digital refractometer (model Brix PR-1, Atago CO., LTD., Tokyo, Japan) and ◦ expressed as Brix, following the sampling procedure described in the manufacturer’s manual (Schneider, 1979). 2.4.3. Analysis of individual carbohydrates Sugar fractions were determined by ion chromatography. The ion chromatograph was a Dionex Model ICS 3000 Free Reagent (Dionex corp., Palo Alto, CA, USA), consisting of a carbohydrates separation column (CarboPac PA1, 4 × 250 mm) with a pre-guard column (CarboPac PA1, 4 × 50 mm). The detector was a conductivity cell composed of a gold electrode (Disposable electrode, Dionex corp., Palo Alto, CA, USA) and AgCl electrode as reference. The eluent was a NaOH 150 mM solution, previously sonicated by a Starsonic 90 equipment (Liarre s.r.l., Casalfiumanese, Italy) at

2.4.6. Determination of total pigment The total betalain pigment content was measured on a UV/VIS spectrophotometer (Lambda Bio20, Perkin-Elmer, Waltham, MA, USA) following the method proposed by Jiratanan and Liu (2004). The wavelengths of 535 and 476 nm were used for betacyanin and betaxanthin analysis, respectively (Fernandez-Lopez and Almela, 2001). 2.4.7. Antioxidant activity The total antioxidant activity of the extracts from red beet roots was measured by a TEAC assay (Miller et al., 1993; Rice-Evans et al., 1996). 2.5. Statistical analysis All the reported data were obtained as the mean of the two experiments since no significant interaction was detected. Collected data were used to parameterize the logistic, strait line, logistic with lower asymptote and exponential decay equations, using the non-linear regression statistical package BIOASSAY97 (Onofri, 2005). A logistic function was fitted against DAE for root dry weight, diameter and leaf dry weight: Y

=

[1 + C

wf × exp (−rx)]

(1)

where Y is the root and leaf dry weight (g plant−1 ) or root diameter (cm), wf is the maximum root and leaf dry weight or root diameter, C is the x values corresponding to the maximum root and leaf dry weight or root diameter, r is a parameter describing the rate of increment of growth rate, and x represents the time (DAE). A straight line function was fitted against DAE for the rate of decrement of LWC estimation: Y

=

C

+ rx

(2)

where Y is LWC (%), C is the y-intercept, r is the rate of decrement of LWC, and x represents the time (DAE).

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F. Stagnari et al. / Scientia Horticulturae 165 (2014) 13–22

Fig. 2. Dynamic of root dry weight (A) and diameter (B), as observed through the red beet cycle under different water regimes (: W100; : W50; : W30, where W100, W50 and W30 respond to watering at 100%, 50% and 30%, respectively of the water holding capacity) and the corresponding parameters (with standard errors) of the fitted logistic functions.

A Gompertz function as proposed by Visser (1994) was fitted to describe the dry matter partitioning to the leaves (FLV) in relation to the DAE: Y

=

FLV0

+ K

×

exp (− exp[r(x − FLVx )])

(3)

where Y is the fraction of dry matter increase partitioned to the leaves, FLV0 is the lowest FLV value, K is a parameter of position of the curve, r is the steepness of the function, FLVx is the x value related to the lowest FLV and x represents the time (DAE). A graphical inspection of residuals did not show any violation of the basic assumption of normality and homoschedasticity for all investigated parameters. Furthermore, an F-test for lack of fit was applied to verify that fitted equations provided a good description of the observed data. Data regarding physiological and quality traits were subjected to analysis of variance (one-way ANOVA) with water regime as the main factor for each sampling occasion. If the ANOVA indicated significant differences, means separation was conducted by applying the Duncan test. The statistical analyses were performed using the package STATISTICA (Statsoft, Tulsa, OK, USA). 3. Results 3.1. Growth traits Root dry weight accumulation was significantly described by the logistic function 1 (Fig. 2A). The coefficients of correlations were very high (0.99 0.98 and 0.99 for W100, W50 and W30, respectively). The W100 produced significantly higher maximum estimated (29.9 g plant−1 ) and measured (26.8 g plant−1 ) root dry weights than the water-stressed treatments, while W50 yield was more than double that of W30 both at maximum estimated (12.2 and 4.2 g plant−1 for W50 and W30, respectively) and measured values (10.3 and 4.0 g plant−1 for W50 and W30, respectively) (Fig. 2A). Although the root growth rate was very similar, the ERGR was significantly higher in W100 (0.118 g g−1 day−1 ) than

W50 (0.056 g g−1 day−1 ) or W30 (0.066 g g−1 day−1 ) (Table 1). These trends were also confirmed by root diameter assessments (Fig. 2B). Water stress induced significant differences in leaf growth traits. Function 1 was fitted to the leaf dry matter obtaining high correlation coefficients (0.99, 0.97, 0.90) (Fig. 3A). The highest maximum leaf weight was obtained with W100 treatment (16.9 g plant−1 ) and the lowest with W30 (5.2 g plant−1 ). While the rate of increase in leaf weight was not affected by water stress, the ILGR values were significantly higher in W100 (0.163 g g−1 day−1 ) compared to the water-stressed treatments (Table 2). Also LWC was higher in W100 and decreased slower than in the W50 and W30 treatments (Fig. 3B). FLV at the early growth stages was about 90% in all treatments (Fig. 4), but in W100 plants the fraction allocated to the leaves Table 1 Early relative root growth rate (ERGR, g g−1 time−1 ) and standard errors of red beet grown under different water regimes, calculated using days after emergence (DAE) and growing degree-days (GDD). Water regime

DAE

R2

GDD

R2

W100 W50 W30

0.118 ± 0.011 0.056 ± 0.007 0.066 ± 0.005

0.98 0.96 0.99

0.009 ± 0.0008 0.004 ± 0.0007 0.005 ± 0.0005

0.98 0.94 0.98

W100, W50 and W30 respond to watering at 100%, 50% and 30%, respectively of the water holding capacity.

Table 2 Initial relative leaf growth rate (ILGR, g g−1 time−1 ) and standard errors of red beet grown under different water regimes, calculated in days after emergence (DAE) and growing degree-days (GDD). Water regime

DAE

R2

GDD

R2

W100 W50 W30

0.163 ± 0.0165 0.109 ± 0.0177 0.107 ± 0.0200

0.98 0.95 0.93

0.012 ± 0.0017 0.008 ± 0.0014 0.008 ± 0.0016

0.96 0.94 0.93

W100, W50 and W30 respond to watering at 100%, 50% and 30%, respectively of the water holding capacity.

F. Stagnari et al. / Scientia Horticulturae 165 (2014) 13–22

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Fig. 3. Dynamic of leaves dry weight (A) and leaf water content (LWC) (B), as observed through the red beet cycle under different water regimes (: W100; : W50; : W30, where W100, W50 and W30 respond to watering at 100%, 50% and 30%, respectively of the water holding capacity) and the corresponding parameters (with standard errors) of the fitted logistic and strait line functions.

decreased earlier (26 DAE) than in the W50 and W30 plants (33 DAE). 3.2. Physiological traits The gs values of W100 plants almost doubled compared to that of the water stressed (at 40 DAE: 496, 234 and 211 mmol m−2 s−1 for W100, W50 and W30, respectively) (Table 3). Starting from 40 DAE, W50 plants showed higher gs values than W30. Canopy temperature (CT) values (Table 4) confirmed the data of stomatal conductance. Till 40 DAE the W100 plants had the lowest CT; after 40 DAE we recorded differences between W50 and W30. Interestingly, at the end of the crop cycle, W30 still had the highest CT values, while similar values were recorded for W100 and W50 (23, 23.5 ◦ C at 54 DAE and 28.3, 29.7 ◦ C at 60 DAE, respectively). 3.3. Quality

Fig. 4. Dynamic of fraction of dry weight partitioned to leaves (FLV) as observed through the red beet cycle under different water regimes (: W100; : W50; : W30, where W100, W50 and W30 respond to watering at 100%, 50% and 30%, respectively of the water holding capacity) and the corresponding parameters (with standard errors) of the fitted Gompertz equation.

TPC concentration in roots was greatly increased by water stress, from 58% to 86% in W30 and W50 plants, respectively as compared to unstressed plants (53.4 mg GAE 100 g−1 FW) (Fig. 5). Also the antioxidant activity, expressed as Trolox equivalent (TE), was significantly affected by water availability. A value of 0.930 ␮M TE g−1 FW was recorded in W100 plants, while it ranged from 1.54 to 1.65 ␮M TE g−1 FW in W30 and W50, respectively (Fig. 6). A significantly positive linear correlation (r2 = 0.97) between the TPC and the antioxidant activity was also found. The pH was higher in W100 plants (6.38), while differences between W50 and W30 were not found; the TSS concentration ◦ ◦ ranged from 13.87 Brix in W100 to 11.67 Brix in W50 and 7.90 ◦ Brix in W30 (Table 5). Sucrose was the most abundant sugar in roots, whereas glucose and fructose were detected only in small amounts (Table 5). Water stress decreased the total concentration (−22% and −48% in W50 and W30, respectively), although the response of each individual sugar was different; glucose and fructose concentration increased

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F. Stagnari et al. / Scientia Horticulturae 165 (2014) 13–22

Table 3 Stomatal conductance (mmol m−2 s−1 ) recorded through the red beet cycle grown under different regimes. For each column, means labeled with the same letter did not differ significantly. Days after emergence

Water regime

W100 W50 W30 F-test

19

26

33

40

47

54

60

457a 254b 247b

459a 226b 234b

461a 216b 206b

496a 234b 211b

477a 156b 75c

457a 233b 173c

432a 234b 167c

**

**

**

**

**

**

**

W100, W50 and W30 respond to watering at 100%, 50% and 30%, respectively of the water holding capacity. * P < 0.05. ** P < 0.01. n.s. = not-significant. Table 4 Canopy temperature (◦ C) recorded through the red beet cycle grown under different water regimes. For each column, means labeled with the same letter did not differ significantly. Days after emergence

Water regime

W100 W50 W30 F-test

19

26

33

40

47

54

60

23.2b 30.2a 31.0a

21.2b 30.2a 32.0a

23.5b 26.4a 26.7a

22.7b 28.5a 27.6a

18.8c 19.9b 22.7a

23.0b 23.5b 25.6a

28.3b 29.7b 31.8a

**

**

**

**

**

**

**

Where W100, W50 and W30 respond to watering at 100%, 50% and 30%, respectively of the water holding capacity. * P < 0.05. ** P < 0.01. n.s. = not-significant.

significantly while sucrose decreased (−19% and −54% in W50 and W30, respectively). Of the seven elements measured in roots, K, P, Mg and Ca were the most abundant (Table 6). Water deficit increased significantly the concentrations of P, Mg, Fe and Zn. In particular Fe was doubled (5.6 and 2.4 mg 100 g−1 DW in W30 and W100, respectively) and Zn nearly tripled compared to control plants (Table 6). Water stress also increased fiber and pigment concentration in roots (Fig. 7 and Table 7, respectively). NDF and ADF increased significantly in W50 (20.7% and 16.8%) and W30 (20.5% and 16.9%) compared to control plants (15.6% and 11.5%). Betacyanin and betaxanthin concentration of the unstressed plants (W100) was 28.08 and 33.96 mg 100 g FW−1 , respectively. When the plants were subjected to drought stress, the betacyanin content was increased by 52% and 47% and betaxanthin by 70% and 69% in W50 and W30, respectively. Nevertheless, the BC/BX ratio seemed to be unaffected.

4. Discussion It is well-known that plants adapt to environmental change, usually by growth and anatomical modifications. Red beet root growth was dramatically influenced by water shortage. The decrease in root FW seemed to be related to a shift of the beginning

of growth rather than to a reduction in growth rate. The ERGR was indeed clearly constrained by water stress. The water limitation also influenced strongly the aerial portion of the crop due to a combination of both reduced expansion and dry matter accumulation. Water shortage sharply affected the leaf biomass accumulation at very early stages, in accordance with previous works (Li et al., 2011; Tei et al., 1996). Chenopodiaceae use leaf succulence as a mechanism to avoid dehydration (Tsialtas et al., 2010), as confirmed by the inconsistent reduction of LWC values in water stressed leaves. Additionally, the red beet adapted to water stress by partitioning relatively less dry matter to the storage roots, as indirectly emerged by the enhancement of the fraction of DW partitioned to the leaves (FLV). Conversely, the fibrous roots, which are directly involved in water and mineral uptake, were more highly developed in waterstressed red beets (data not reported), in accordance with previous findings (Gonzáles et al., 2008; Markesteijn and Poorter, 2009). A reduction of 46% in dry matter allocation to the storage roots has previously been reported for water stressed sugar beet (Shaw et al., 2002), where the fibrous roots growth was favored. The level of water stress seemed to affect the partitioning of dry matter at a whole plant level, particularly at the end of the growth cycle. Plants, indeed, respond to water deficit with a relative increase of assimilates’ allocation to the roots, leading to an increased root mass ratio (Brouwer, 1963). Conversely to sugar beet (Tsialtas et al., 2011),

Table 5 ◦ pH, Brix and concentrations of individual sugars (g kg−1 FW) in roots of red beet grown under different water regimes. For each column, means labeled with the same letter did not differ significantly. ◦

Water regime

pH

Brix

Sucrose

Glucose

Fructose

Total sugars

W100 W50 W30 F-test

6.38a 5.86b 5.63b

13.87a 11.67b 7.90c

24.80a 20.0b 11.4c

0.67b 0.80a 0.82a

1.87b 1.90b 2.80a

27.3a 21.3b 14.3c

**

**

**

**

**

**

Where W100, W50 and W30 respond to watering at 100%, 50% and 30%, respectively of the water holding capacity. * P < 0.05. ** P < 0.01. n.s. = not-significant.

F. Stagnari et al. / Scientia Horticulturae 165 (2014) 13–22

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Table 6 Mineral concentrations (mg 100 g−1 DW) in roots of red beet grown under different water regimes. For each column, means labeled with the same letter did not differ significantly. Mineral content (mg 100 g DW−1 )

Water regime

W100 W50 W30 F-test

Ca

P

Mg

K

Fe

Mn

Zn

122.5 112.7 130.6 n.s.

561.3b 876.9a 893.1a

111.7b 199.5a 227.2a

2.4b 4.7a 5.6a

**

5.4 7.1 6.1 n.s.

1.1b 2.9a 2.5a

**

2315.8 2645.3 2590.7 n.s.

**

*

W100, W50 and W30 respond to watering at 100%, 50% and 30%, respectively of the water holding capacity. * P < 0.05. ** P < 0.01. n.s. = not-significant. Table 7 Betacyanin and betaxanthin concentrations (mg 100 g−1 FW) in roots of red beet grown under different water regimes. For each column, means labeled with the same letter did not differ significantly. Pigments (mg 100 g−1 FW)

Water regime

W100 W50 W30 F-test

Betacyanin

Betaxanthin

Total

BC/BX

28.08b 53.83a 48.59a

33.96b 71.73a 70.33a

62.04b 125.57a 118.92a

**

**

**

0.82 0.75 0.71 n.s.

W100, W50 and W30 respond to watering at 100%, 50% and 30%, respectively of the water holding capacity. * P < 0.05. ** P < 0.01. n.s. = not-significant.

defoliation do not seem an adaptation means under severe water shortage. Reduction of evapotranspiration rates to higher stomata resistance is considered another physiological modification of red beets to water shortages (Fischer et al., 1998). Higher gs favored photosynthesis and biomass accumulation. An early effect of drought results in partial stomatal closure and a metabolic adjustment takes

Fig. 5. Total phenolic content (TPC) of red beet as influenced by different water regimes ( : W100; : W50; : W30, where W100, W50 and W30 respond to watering at 100%, 50% and 30%, respectively of the water holding capacity) expressed as gallic acid equivalents (GAE) in mg 100 g−1 FW. Average values ± standard errors are depicted. Different letters stand for statistically significant differences at P < 0.05 (Duncan test).

place through limited RuBP-regeneration (Lawlor, 1995). Further reduction of gs as drought progresses, probably leads to reduced photochemistry and carboxylation efficiency and under severe drought condition (saying W30) photoinhibition eventually occurs, accompanied by a complete stomatal closure. Drought stress is considered among the main factors (Stagnari and Pisante, 2012) responsible for changes in physiology and, consequently, in phytochemicals content in various plant species (Kannan and Kulandaivelu, 2011).

Fig. 6. Atioxidant activity of red beet as influenced by different water regimes ( :W100; : W50; : W30, where W100, W50 and W30 respond to watering at 100%, 50% and 30%, respectively of the water holding capacity) expressed as ␮M Trolox equivalents per 100 g−1 FW. Average values ± standard errors are depicted. Different letters stand for statistically significant differences at P < 0.05 (Duncan test).

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Fig. 7. NDF and ADF content of red beet as influenced by different water regimes ( :W100; : W50; : W30, where W100, W50 and W30 respond to watering at 100%, 50% and 30%, respectively of the water holding capacity) expressed as % of DM. Average values ± standard errors are depicted. Different letters stand for statistically significant differences at P < 0.05 (Duncan test).

In this respect, we found that red beet roots under moderate water stress conditions tend to concentrate TPC as has already been reported in grapes (Deluc et al., 2009), Hypericum brasiliense Choisy (De Abreu and Mazzafera, 2005) and potato (Andre et al., 2009). Probably, as it was addressed in previous works, water shortage stimulates the activity of phenylpropanoid pathway enzymes such as l-phenylalanine ammonia-lyase (Tovar et al., 2002; Guo et al., 2008). Besides an accumulation of TPC, we observed a significant increase in antioxidant activity, which also is correlated with TPC as observed in fruits and vegetables (Kugler et al., 2007). However, it should be noticed that the phenolic substances are not the only components of the antioxidant activity of beet root; other important compounds are betacyanin and betaxanthin (Escribano et al., 1998), two molecules known as betalain (Gasztonyi et al., 2001). Also, water shortage strongly stimulated the concentration of both, while the BC/BX ratio seemed to be unaffected. To date, data regarding the effect of water stress on betalain accumulation are not available. Stintzing and Carle (2004) suggested that betalains accumulate in water shortage conditions because they might function as osmolytes to uphold physiological processes as the amino acid proline. The influence of drought on the accumulation of other important antioxidants is well documented since it increased in ␣-tocopherol in rosemary and soybean (Britz and Kremer, 2002), lycopene in tomato (Favati et al., 2009) and carotenoids in lettuce (Sorensen et al., 1997). The high concentration of total phenolic and betalains obtained in the same roots is of great interest, since it seems to associate with high antioxidant and anticancer activities and might be indicative of synergistic effects (Chavez-Santoscoy et al., 2009). In vegetarian diets, the sugar content and composition in vegetables is gaining increasing interest, (Rodríguez-Sevilla et al., 1999), and these factors are also of relevance for diabetic patients, as they need to adapt insulin dosage accordingly (Hecke et al., 2006). In red beet, total non-structural carbohydrate concentration seems constrained by water stress, in contrast to previous studies on tomatoes (Wu and Kubota, 2008) and cucumbers (Huang et al., 2009). However, the findings are relatively inconsistent; in the case of sugar beets some authors reported an increase (Bloch and

Hoffmann, 2004) while others a decrease (Tsialtas et al., 2009) in sugar concentration. The reduction in carbohydrate accumulation in the storage root of drought stressed plant could be a function of vegetative tissues supporting current growth rather than storage of reserves (Richardson et al., 2004). Although total non-structural carbohydrates decreased, an accumulation of glucose and fructose was observed. Interestingly, the induction of water stress seemed to lead to an increase in fiber accumulation for all its fractions in accordance with Lee et al. (2007). In red beet an increase in fiber accumulation has also been observed under severe light reduction (Stagnari et al., 2013). The role of red beet fiber as an anticancer food has been investigated and a pronounced hypocholesterolemic effect was found (Bobek et al., 2000). In addition, dietary fiber may lead to improvements in virtually all non-infectious intestinal disorders and glucose tolerance (Yoshioka et al., 1995). Since water availability plays a significant role in mineral mobilization, water deficit can reduce mineral uptake. Nevertheless, in some circumstances the concentration of minerals might increase due to dilution/concentration effects: this happens when dry matter accumulates to a lesser extent than minerals. This was observed for P, Mg and especially Zn and Fe in roots supporting the findings of Ti et al. (2010) who assumed that drought improved routes and/or transport mechanisms for those elements in water stressed maize. Contrary to sugar beet, K was not affected by water stress, despite that it is considered to play a key role in plant water economy affecting water cell function (Tsialtas and Maslaris, 2006). In conclusion, red beets showed high adaptivity to drought due to changes in growth and physiological traits, which modified yield and quality of the final product. The plants constrained leaf and root dry weight, as well as increased FLV and thermal dissipation in leaves. The high concentration of phytochemicals and nutrients obtained by induced stress led to the production of roots which might contribute to the maintenance of health and reduction of the risk of chronic diseases such as cancer, diabetes and Alzheimer’s disease. Thus, deficit irrigation strategies could be regarded as new means for managing plant growth to improve food quality (Stagnari and Pisante, 2010) and water use efficiency with limited yield loss.

References Abdollahian-Noghabi, M., Froud-Williams, R.J., 1998. Effect of moisture stress and re-watering on growth and dry matter partitioning in three cultivars of sugar beet. Asp. Appl. Biol. 52, 71–78. Amani, I., Fisher, R.A., Reynolds, M.P., 1996. Canopy temperature depression association with yield of irrigated spring wheat cultivars in a hot climate. J. Agron. Crop Sci. 176, 119–129. Andre, C.M., Schafleitner, R., Guignard, C., Oufir, M., Aliaga, C.A.A., Nomberto, G., Hoffmann, L., Hausman, J.F., Evers, D., Larondelle, Y., 2009. Modification of the health-promoting value of potato tubers field grown under drought stress: emphasis on dietary antioxidant and glycoalkaloid contents in five native Andean cultivars (Solanum tuberosum L). J. Agric. Food Chem. 57, 599–609. AOAC, 1990. Official Methods of Analysis of the Association of Official Analytical Chemists, 15th ed. Association of Official Analytical Chemists, Washington, DC. Apel, K., Hirt, H., 2004. Reactive oxygen species: metabolism, oxidative stress, and signal transduction. Annu. Rev. Plant Biol. 55, 373–399. Benjamin, L.R., Sutherland, R.A., 1989. Storage-root weight, diameter and length relationships in carrot (Daucus carota) and red beet (Beta vulgaris). J. Agric. Sci. 113, 73–80. Bethke, P.C., Sabba, R., Bussan, A.J., 2009. Tuber water and pressure potentials decrease and sucrose contents increase in response to moderate drought and heat stress. Am. J. Potato Res. 86, 519–532. Bloch, D., Hoffmann, C., 2004. Drought stress as affecting yield and quality development of different sugar beet genotypes. Zuckerindustrie 129, 727–734. Bobek, P., Galbavy, S., Mariássyová, M., 2000. The effect of red beet (Beta vulgaris var. rubra) fiber on alimentary hypercholesterolemia and chemically induced colon carcinogenesis in rats. Nahrung 44, 184–187. Boyer, J.S., 1982. Plant production and environment. Science 218, 443–448. Brewster, J.L., Sutherland, R.A., 1993. The rapid determination in controlled environments of parameters for predicting seedling growth rates in natural conditions. Ann. Appl. Biol. 122, 123–133.

F. Stagnari et al. / Scientia Horticulturae 165 (2014) 13–22 Britz, S.J., Kremer, D.F., 2002. Warm temperatures or drought during seed maturation increase free alpha-tocopherol in seeds of soybean (Glycine max L Merr.). J. Agric. Food Chem. 50, 6058–6063. Brouwer, R., 1963. Some Aspects of the Equilibrium Between Overground and Underground Plant Parts. Jaarboek IBS, Wageningen, pp. 31–39. Chavez-Santoscoy, R.A., Gutierrez-Uribe, J.A., Serna-Saldivar, S.O., 2009. Phenolic composition, antioxidant capacity and in vitro cancer cell cytotoxicity of nine prickly pear (Opuntia spp.) juices. Plant Foods Hum. Nutr. 64, 146–152. Clarke, N.A., Hetschkun, H., Jones, C., Boswell, E., Marfaing, H., 1993. Identification of stress tolerance traits in sugar beet. In: Jackson, M.B., Black, C.R. (Eds.), Interaction Stresses on Plants in a Changing Climate. Springer-Verlag, Berlin, pp. 511–524. De Abreu, I.N., Mazzafera, P., 2005. Effect of water and temperature stress on the content of active constituents of Hypericum brasiliense Choisy. Plant Physiol. Biochem. 43, 241–248. Debon, S.J.J., Tester, R.F., Millam, S., Davies, H.V., 1998. Effect of temperature on the synthesis, composition and physical properties of potato microtuber starch. J. Sci. Food Agric. 76, 599–607. Deluc, L.G., Quilici, D.R., Decendit, A., Grimplet, J., Wheatley, M.D., Schlauch, K.A., Merillon, J.M., Cushman, J.C., Cramer, G.R., 2009. Water deficit alters differentially metabolic pathways affecting important flavor and quality traits in grape berries of Cabernet Sauvignon and Chardonnay. BMC Genomics 10, 212–245. Dunham, R., Clarke, N.A., 1992. Coping with stress. Br. Sugar Beet Rev. 66, 10–13. Escribano, J., Pedreno, M.A., Garcia-Carmona, F., Munoz, R., 1998. Characterization of the antiradical activity of betalains from Beta vulgaris L. roots. Phytochem. Anal. 9, 124–127. Favati, F., Lovelli, S., Galgano, F., Miccolis, V., Di Tommaso, T., Candido, V., 2009. Processing tomato quality as affected by irrigation scheduling. Sci. Hortic.—Amsterdam 122, 562–571. Fernandez-Lopez, J.A., Almela, L., 2001. Application of high-performance liquid chromatography to the characterization of the betalain pigments in prickly pear fruits. J. Chromatogr. A 913, 414–420. Fischer, R.A., Rees, D., Sayre, K.D., Lu, Z.M., Condon, A.G., Saavedra, A.L., 1998. Wheat yield progress associated with higher stomatal conductance and photosynthetic rate and cooler canopies. Crop Sci. 38, 1467–1475. Gasztonyi, M.N., Daood, H., Hajos, M.T., Biacs, P., 2001. Comparison of red beet (Beta vulgaris var conditiva) varieties on the basis of their pigment components. J. Sci. Food Agric. 81, 932–933. Gonzáles, W.L., Suárez, L.H., Molina-Montenegro, M.A., Gianoli, E., 2008. Water availability limits tolerance of apical damage in the Chilean tarweed Madia sativa. Acta Oecol. 34, 104–110. Guerfel, M., Baccouri, O., Boujnah, D., Chaïbi, W., Zarrouk, M., 2009. Impacts of water stress on gas exchange, water relations, chlorophyll content and leaf structure in the two main Tunisian olive (Olea europaea L.) cultivars. Sci. Hortic.—Amsterdam 119, 257–263. Guo, J., Han, W., Wang, M.H., 2008. Ultraviolet and environmental stresses involved in the induction and regulation of anthocyanin biosynthesis: a review. Afr. J. Biotechnol. 7, 4966–4972. Hecke, K., Herbinger, K., Veberie, R., Trobee, M., Toplak, H., Stampar, F., Keppel, H., Grill, D., 2006. Sugar-acid and phenol contents in apple cultivars from organic and integrated fruit cultivation. Eur. J. Clin. Nutr. 60, 1136–1140. Hoffmann, C.M., Huijbregts, T., van Swaaij, N., Jansen, R., 2009. Impact of different environments in Europe on yield and quality of sugar beet genotypes. Eur. J. Agron. 30, 17–26. Hole, C.C., Thomas, T.H., Barnes, A., Scott, P.A., Rankin, W.E.F., 1984. Dry matter distribution between shoot and storage root of carrot, parsnip, radish and beet. Ann. Bot.—London 53, 625–631. Huang, Y., Tang, R., Cao, Q.L., Bie, Z.L., 2009. Improving the fruit yield and quality of cucumber by grafting onto the salt tolerant rootstock under NaCl stress. Sci. Hortic.—Amsterdam 122, 26–31. Hunt, R., 1982. Plant Growth Curves: The Functional Approach to Plant Growth Analysis. Edward Arnold, London. Jiang, M., Zhang, J., 2002. Water stress-induced abscisic acid accumulation triggers the increased generation of reactive oxygen species and up-regulates the activities of antioxidant enzymes in maize leaves. J. Exp. Bot. 53, 2401–2410. Jiratanan, T., Liu, R.H., 2004. Antioxidant activity of processed table beets (Beta vulgaris var conditiva) and green beans (Phaseolus vulgaris L). J. Agric. Food Chem. 52, 2659–2670. Kannan, N.D., Kulandaivelu, G., 2011. Drought induced changes in physiological, biochemical and phytochemical properties of Withania somnifera Dun. J. Med. Plant Res. 5, 3929–3935. Katerji, N., Rana, G., Mastrorilli, M., 2010. Modelling of actual evapotranspiration in open top chambre (OTC) at daily and seasonal scale: multi-annual validation on soybean in contrasted conditions of water stress and air ozone concentration. Eur. J. Agron. 33, 218–230. Keutgen, A.J., Pawelzik, E., 2009. Impacts of NaCl stress on plant growth and mineral nutrient assimilation in two cultivars of strawberry. Environ. Exp. Bot. 65, 170–176. Kugler, F., Sintzing, F., Carle, R., 2007. Evaluation of the antioxidant capacity of betalainic fruits and vegetables. J. Appl. Bot. Food Qual. 81, 69–76. Lawlor, D.W., 1995. The effects of water deficit on photosynthesis. In: Smirnoff, N. (Ed.), Environment and Plant Metabolism. Flexibility and Acclimation. BIOS Scientific Publisher, Oxford. Lee, B.R., Kim, K.Y., Jung, W.J., Avice, J.C., Ourry, A., Kim, T.H., 2007. Peroxidases and lignification in relation to the intensity of water-deficit stress in white clover (Trifolium repens L). J. Exp. Bot. 58, 1271–1279.

21

Li, F.L., Bao, W.K., Wu, N., 2011. Morphological, anatomical and physiological responses of Campylotropis polyantha (Franch.) Schindl. seedlings to progressive water stress. Sci. Hortic.—Amsterdam 127, 436–443. Lourtie, E., Bonnet, M., Bosschaert, L., 1995. New glyphosate screening technique by infrared thermometry. In: Fourth International Symposium on Adjuvant for Agrochemicals, Australia, pp. 297–302. Markesteijn, L., Poorter, L., 2009. Seedling root morphology and biomass allocation of 62 tropical tree species in relation to drought- and shade-tolerance. J. Ecol. 97, 311–325. Miller, N.J., Rice-Evans, C.A., Davies, M.J., Gopinathan, V., Milner, A., 1993. A novel method for measuring antioxidant capacity and its application to monitoring the antioxidant status in premature neonates. Clin. Sci. 84, 407–412. Morgan, P.B., Bernacchi, C.J., Ort, D.R., Long, S.P., 2004. An in vivo analysis of the effect of season-long-open-air elevation of ozone to anticipated 2050 levels on photosynthesis in soybean. Plant Physiol. 135, 2348–2357. Navas, M.L., Garnier, E., 2002. Plasticity of whole plant and leaf traits in Rubia peregrina in response to light, nutrient and water availability. Acta Oecol. 23, 375–383. Oktem, A., 2008. Effect of water shortage on yield, and protein and mineral compositions of drip-irrigated sweet corn in sustainable agricultural systems. Agric. Water Manage. 95, 1003–1010. Onofri, A., 2005. BIOASSAY97: a new EXCELVBAmacro to perform statistical analyses on herbicide dose–response data. Riv. Ital. Agrometeorol. 3, 40–45. Ozturk, A., Aydin, F., 2004. Effect of water stress at various growth stages on some quality characteristics of winter wheat. J. Agron. Crop Sci. 190, 93–99. Rebetzke, G.J., Read, J.J., Barbour, M.M., Condon, A.G., Rawson, H.M., 2000. A handheld porometer for rapid assessment of leaf conductance in wheat. Crop Sci. 40, 277–280. Rice-Evans, C.A., Miler, N.J., Paganga, G., 1996. Structure-antioxidant activity relationship of flavonoids and phenolic acids. Free Radical Biol. Med. 20, 933–956. Richardson, A.C., Marsh, K.B., Boldingh, H.L., Pickering, A.H., Bulley, S.M., Frearson, N.J., Ferguson, A.R., Thornber, S.E., Bolitho, K.M., Macrae, E.A., 2004. High growing temperatures reduce fruit carbohydrate and vitamin C in kiwifruit. Plant Cell Environ. 27, 423–435. Rodríguez-Sevilla, M., Villanueva-Suarez, M.J., Redondo-Cuenca, A., 1999. Effects of processing conditions on soluble sugars content of carrot beetroot and turnip. Food Chem. 66, 81–85. Rotundo, J.L., Westgate, M.E., 2009. Meta-analysis of environmental effects on soybean seed composition. Field Crop Res. 110, 147–156. Schneider, F., 1979. Sugar Analysis: ICUMSA Methods. XIV , Peterborough. Shaw, B., Thomas, T.H., Cooke, D.T., 2002. Responses of sugar beet (Beta vulgaris L.) to drought and nutrient deficiency stress. Plant Growth Regul. 37, 77–83. Singleton, V.L., Rossi, J.A., 1965. Colorimetry of total phenolics with phosphomolybdic-phosphotungstic acid reagents. Am. J. Enol. Vitic. 16, 144–158. Sorensen, J.N., Jorgensen, U., Kuhn, B.F., 1997. Drought effects on the marketable and nutritional quality of carrots. J. Sci. Food Agric. 74, 379–391. Stagnari, F., Pisante, M., 2010. Managing faba bean residues to enhance the fruit quality of the melon (Cucumis melo L.) crop. Sci. Hortic.—Amsterdam 126, 317–323. Stagnari, F., Pisante, M., 2012. Slow release and conventional N fertilizers for nutrition of bell pepper. Plant Soil Environ. 58, 268–274. Stagnari, F., Galieni, A., Cafiero, G., Pisante, M., 2013. Application of photo-selective films to manipulate wavelength of transmitted radiation and photosynthate composition in red beet (Beta vulgaris var. conditiva Alef.). J. Sci. Food Agric., http://dx.doi.org/10.1002/jsfa.6312. Stintzing, F.C., Carle, R., 2004. Functional properties of anthocyanins and betalains in plants, food, and in human nutrition. Trends Food Sci. Technol. 15, 19–38. Tei, F., Scaife, A., Aikman, D.P., 1996. Growth of lettuce, onion and reed beet. 1. Growth analysis, light interception, and radiation use efficiency. Ann. Bot.—London 78, 633–643. Tovar, M.J., Romero, M.P., Girona, J., Motilva, M.J., 2002. l-phenylalanine ammonialyase activity and concentration of phenolics in developing fruit of olive tree (Olea europaea L. cv Arbequina) grown under different irrigation regimes. J. Sci. Food Agric. 82, 892–898. Tsialtas, J.T., Maslaris, N., 2006. Leaf carbon isotope discrimination relationships to element conten in soil, roots and leaves of sugar beets grown under Mediterranean conditions. Field Crop Res. 99, 125–135. Tsialtas, J.T., Soulioti, E., Maslaris, N., Papakosta, D., 2009. Genotypic response to re-growth of defoliated sugar beets after re-watering in a water-limited environment: effects on yield and quality. Int. J. Plant Prod. 3, 1–18. Tsialtas, J.T., Matsi, T., Maslaris, N., 2010. Plasticity of leaf anatomy, chemistry and water economy of irrigated sugar beets grown under Mediterranean conditions. Int. J. Plant Prod. 4, 99–114. Tsialtas, J.T., Soulioti, E., Maslaris, N., Papakosta, D.K., 2011. Effect of defoliation on leaf physiology of sugar beet cultivars subjected to water stress and re-watering. Int. J. Plant Prod. 5, 207–222. Turner, N.C., 1981. Techniques and experimental approaches for the measurement of plant water status. Plant Soil 58, 339–366. Ti, D.G., Sui, F.G., Nie, S.A., Sun, N.B., Xiao, H.A., Tong, C.L., 2010. Differential responses of yield and selected nutritional compositions to drought stress in summer maize grains. J. Plant Nutr. 33, 1811–1818. Valladares, F., Gianoli, E., Gómez, J.M., 2007. Ecological limits to plant phenotypic plasticity. New Phytol. 176, 749–763.

22

F. Stagnari et al. / Scientia Horticulturae 165 (2014) 13–22

Ververis, C., Georghiou, K., Danielidis, D., Hatzinikolaou, D.G., Santas, P., Santas, R., Corleti, V., 2007. Cellulose, hemicelluloses, lignin and ash content of some organic materials and their suitability for use as paper pulp supplements. Bioresour. Technol. 98, 296–301. Visser, C.L.M. de, 1994. ALCEPAS, an onion growth model based on SUCROS87. I. Development of the model. J. Hortic. Sci. 69, 501–518.

Wu, M., Kubota, C., 2008. Effects of electrical conductivity on nutrient solution and its application timing on lycopene, chlorophyll and sugar concentrations of hydroponic tomatoes during ripening. Sci. Hortic.—Amsterdam 116, 122–129. Yoshioka, M., Shimomura, Y., Suzuki, M., 1995. Dietary cellulose improves decreased muscular layer weight of the large intestine in rats fed the diet containing polydextrose. Nutr. Res. 15, 1473–1476.