Relationships among electrical conductivity measurements during ...

Journal of Horticultural Science & Biotechnology (2015) 90 (5) 571–577

Relationships among electrical conductivity measurements during saline irrigation of potted Osteospermum and their effects on plant growth By R. VALDÉS1, J. A. FRANCO1, M. J. SÁNCHEZ-BLANCO2 and S. BAÑÓN1* 1 Departamento de Producción Vegetal. Universidad Politécnica de Cartagena, Paseo Alfonso XIII 48, 30203 Cartagena, Spain 2 Departamento de Riego, Centro de Edafología y Biología Aplicada del Segura (CSIC), P.O. Box 164, Espinardo E-30100, Murcia, Spain (e-mail: [email protected]) (Accepted 2 June 2015) SUMMARY Potted Osteospermum hybrida plants grown in a greenhouse during the Winter were irrigated with water having electrical conductivities (EC) of 1.5, 2.0, 2.5, 3.0, 3.5, 4.0, 4.5 or 5.0 dS m–1. The following relationships were studied in order to improve the management of saline irrigation systems using soil moisture and EC sensors: pore water EC (ECPW) using the pour-through method (ECPWPT) vs. ECPW estimated using a GS3 sensor (ECPWGS3); ECPWPT vs. bulk EC (ECB); ECPWPT vs. leachate EC (ECL); and ECPWGS3 vs. ECB. The tolerance of Osteospermum plants to salinity was also determined. Bulk EC, ECPWGS3, and ECL values were closely and positively correlated with ECPWPT. ECL over-estimated ECPWPT, while ECPWGS3 underestimated ECPWPT. Estimation of ECPWGS3 (by the Hilhorst Model) was not accurate due to the influences of humidity, salinity, and temperature. The higher the irrigation water EC (ECIW), the greater the variability in all measurements made of EC. Increases in ECIW reduced plant height, diminished the aerial dry biomass, and encouraged the presence of basal leaves with necrotic damage. These results highlight the moderate salinity tolerance of Osteospermum, which was related to the efficient accumulation of Cl– and Na+ ions in its leaves.

F

reshwater depletion is leading to the use of alternative sources of water, including recycled wastewater and saline underground water to irrigate nurseries, greenhouses, and landscapes. Both types of water may contain high concentrations of salts (Bañón et al., 2011). The problem is that salts usually have an adverse effect on plant development, resulting in slowed growth, damaged leaves and, in the most severe cases, death.This means that there is an urgent need to identify plant species that can grow using saline water and to develop more efficient irrigation water management systems. High salinity causes osmotic effects in plants, which must expend more energy to extract water from the soil as that water becomes more saline (Benzarti et al., 2014). Salinity can increase the concentrations of ions that have an inhibitory effect on plant metabolism, with Na+ and Cl– ions usually being considered toxic to plants (Munns and Tester, 2008). Competition and interactions between saline and nutrient ions in the growing medium, as well as within the plant, frequently lead to ion imbalances that may result in nutrient deficiencies (Sánchez-Blanco et al., 2004). Plants vary widely in their tolerance to salts, and the extent of any damage will depend on their salt sensitivity. Many plants have developed a variety of physiological mechanisms to cope with the detrimental effects of salt stress; for example, the control of ion uptake by roots and subsequent ion transport to the leaves, the selective build-up or exclusion of salt ions, and compartmentalisation of ions (Adolf et al., 2013). In the *Author for correspondence.

case of ornamental plants, salt tolerance is often assessed based on the growth of the whole plant, or specific plant parts such as roots, shoots, leaves, or floral stems. Reduced growth parameters and the presence of foliar damage such as burning or chlorosis have a negative impact on the aesthetic value of the plant (Bañón et al., 2011). Vegetative cultivars of Osteospermum have high potential for ornamental plant production because they produce many attractive flowers, can form dramatic displays of colour when planted at high density, and bloom in early-Spring, with a prolonged flowering time (Gibson and Whipker, 2003). In recent years, Osteospermum cultivars have increased in popularity, becoming popular as bedding plants in borders or in pots. While Osteospermum is considered to be drought resistant, few studies have been conducted to measure its salt tolerance. Salt tolerance in plants can also be regarded in the context of irrigation management (Oron et al., 2002), which involves making decisions on when to irrigate and how much water to apply. In the case of salinity, the concentration of salt in the soil must be measured. In situ electrical conductivity (EC) measurements are often used to measure and control soil salinity in irrigated cropping systems (Van Der Laan et al., 2011). Such measurements usually include the combined (bulk) EC of substrate particles, air and solution (ECB), the EC of the water in the soil pores (ECPW), and the EC of the leachate (ECL). ECB has little practical value because it depends on the soil water content (Amente et al., 2000), and is usually regarded as a poor indicator of soil salinity.

572

Electrical conductivities and growth in potted Osteospermum

However, ECB is the only EC value that can be measured continuously in situ by soil moisture and EC sensors such as the GS3 (Decagon Devices Inc., Pullman, WA, USA). The availability of such soil moisture sensors, which can also measure ECB, has increased opportunities for the application of saline water to horticultural crops. In contrast, ECPW has an influence on the growth and development of plants because it represents the EC of the water extracted by plant roots from the medium. A considerable amount of research has been conducted to determine the relationship between ECPW and ECB (Kargas and Kerkides, 2012). One of the models developed by Hilhorst (2000) predicted ECPW using data on the bulk dielectric permittivity (B) and ECB, which can be obtained by soil moisture and EC sensors. However, several factors such as substrate moisture, temperature, and salinity can reduce the accuracy of such estimates (Kargas and Kerkides, 2010; Rosenbaum et al., 2011; Evett et al., 2012; Valdés et al., 2015). While growers often record average ECL values from various pots in an irrigation zone, ECL values rarely coincide with ECPW values, because ECL depends on factors such as the fraction of leaching, the salinity of the irrigation water, the physical characteristics of the substrate, and environmental conditions (Torres et al., 2010). Another way to measure ECPW in situ is the pour-through (PT) method described by Cavins et al. (2008). PT extraction occurs by displacement of the root zone solution by distilled water poured over the top of a substrate as a means to obtain a sample of the soil solution. The PT method has been widely accepted in both nurseries and greenhouses (Torres et al., 2010). The aims of this study were evaluate the relationships between these various EC values in potted Osteospermum plants irrigated with water of different salinity levels and to measure the growth, leaf damage, and ion accumulation in plants. These findings will be useful to improve the management of saline irrigation for potted plant production and to predict the responses of Osteospermum plants to salinity.

MATERIALS AND METHODS Plant material and cropping conditions Rooted cuttings of Osteospermum hybrida ‘Margarita Supreme Lilac’ were transplanted in the first week of October 2014 into black, 17-cm-diameter 2.8 l pots filled with a substrate consisting of a 40:40:20 (v/v/v) mix of sphagnum peat, coconut fibre, and perlite. The experiment took place in a greenhouse at Cartagena, Spain (37º 35’ N, 0º 59' W). The weather conditions were 7.8º ± 2.6ºC (minimum) and 26.8º ± 3.9ºC (maximum), with a relative humidity (RH) of 38.8 ± 16.6% (minimum) and 76.6 ± 9.3% (maximum). Irrigation treatments The eight irrigation treatments used solutions of increasing ECIW (1.5, 2.0, 2.5, 3.0, 3.5, 4.0, 4.5, or 5.0 dS m–1) achieved by adding NaCl to the irrigation solution. Fertiliser (pH 6.0) was added to the water at 80 mg l–1 N, 40 mg l–1 P2O5 and 80 mg l–1 K2O to increase each ECIW value by 0.5 dS m–1. Saline irrigation began on 17 November 2013 and finished on 6 February 2014. Each pot had two emitters

(Netafim Ltd., Tel Aviv, Israel) providing 1.2 l h–1. Irrigation was controlled using dielectric sensors (GS3; Decagon Devices Inc.) connected to a CR1000 measurement and control system with a 16-channel relay controller (SMD-CD16D; Campbell Scientific Inc., Logan, UT, USA) operating solenoid valves on each of the eight 250 l tanks that contained the different irrigation solutions. Three sensors per treatment were placed vertically and fully inserted into the substrate in the East-facing part of each pot. The CR1000 data-logger was programmed using Loggernet 3 (Campbell Scientific Inc.) to collect the GS3 outputs every 1 min, and 30 min averages were recorded regularly during the experiment. The CR1000 converted B values from the GS3 measurements to a water volume () based on a substrate-specific calibration ( = –0.0001B2 + 0.0168B + 0.0356; R2 = 0.97). The average values for all treatments at 09.00 h were automatically determined and stored each day by the data-logger. Irrigation was activated manually when the average value was approx. 0.40 m3 m–3, meaning a 50% reduction in the available water in the substrate. Irrigation events were applied consecutively at 20 min intervals in order to facilitate measuring ECPW by the PT method and the collection of leachate in each treatment. The volume of water applied per irrigation event per pot (470 ± 12 ml) and irrigation frequency (17 irrigation events during the experimental period) were the same in all treatments, which led to different leaching fractions being collected. These ranged from 18% (v/v) in the control, to 28% (v/v) in the treatment involving 5.0 dS m–1 ECIW. The CR1000 determined ECPW values according to Hilhorst (2000). Measurements of EC using the PT method Forty minutes after irrigation, distilled water was poured evenly over the substrate surface of each pot (three pots per treatment) to obtain a leachate volume of 50 ml (Cavins et al., 2008). The distilled water was applied to the same part of the surface of each substrate between the two emitters and the EC of the leachate was measured immediately after collection using a conductivity-meter (Dist® 6; Hanna Instruments S.L., Eibar, Spain). Different pots were used for each irrigation event. Plant growth, development, and SPAD values At the end of the experiment (14 weeks after salt application), plant heights, canopy widths, shoot dry weights (DW), the number of leaves per plant, leaf areas, the number of inflorescences per plant, foliar SPAD values (the relative amount of chlorophyll), and the number of damaged leaves per plant were determined in six plants per treatment. Leaf areas were measured using a LI-3100C meter (LI-COR Biosciences, Lincoln, NE, USA). SPAD values were measured by selecting South-facing, midcanopy-height leaves and using a SPAD-502 chlorophyll meter (Konica Minolta Sensing Inc., Osaka, Japan). Leaf burn, scorch, or necrosis were considered to be foliar damage. Cl–, Na+ and K+ ion concentrations in leaves and roots At the end of the experiment, six plants per treatment were separated into leaves and roots. Tissues were dried

R. VALDÉS, J. A. FRANCO, M. J. SÁNCHEZ-BLANCO and S. BAÑÓN to constant weight in an oven at 60ºC. Four samples of roots and leaves per treatment were selected at random for analysis of ion concentrations. Dried plant tissue samples were ground and 0.2 g of each tissue was added to 50 ml of distilled water. Each solution was mixed for 30 min by shaking on a magnetic stirrer at 117 rpm and 27ºC (Model ACS-100 C/C; ITC, SL, Barcelona, Spain) then filtered and passed through a 0.45 µm nylon membrane. Ten ml of each filtered solution were analysed by chromatography in a Metrohm 850 Ion chromatography system (Metrohm AG, Herisau, Switzerland) equipped with a conductometric detector and an autosampler (Metrohm 815 Robotic USB Sample Processor XL), which also in-line filtered the samples through a 0.20 µm pore diameter cellulose acetate membrane filter. Anion separation was carried out using a Metrosep A Supp 5-50 column (Metrohm AG) with carbonate-bicarbonate eluant (3.2 mM Na2CO3 1.0 mM NaHCO3) at a flow rate of 0.7 ml min–1. Cations were separated on a Metrosep C3-100 column (Metrohm AG) with 3.5 mM nitric acid as eluant at a flow rate of 1.0 ml min–1. Injections were performed at 25ºC. Statistical analysis The experiment was arranged in a randomised complete block design on crop benches with three blocks of seven plants per treatment (21 plants or repetitions per treatment). The experiment was carried out once. Regression analyses was performed using SigmaPlot 10.0 software (Systat Software Inc., San Jose, CA, USA).

RESULTS AND DISCUSSION Effect of increasing ECIW on mean ECL, ECPWPT, and ECPWGS3 values Mean ECL, ECPWPT, and ECPWGS3 values during the

573

experimental period increased as ECIW increased (Figure 1A). Regression analysis indicated that the three linear regression models shown in Figure 1A were significant. The greater the magnitude of the slope in the ECL-ECIW equation than in the ECPWPT-ECIW equation indicated that ECL values were higher than ECPWPT values for the same ECIW. This was because the first part of the leachate contained more salts than the last part that was similar to the leachate collected using the PT method (Torres et al., 2010). The scatter of the ECL data increased as ECIW increased, leading to greater differences between ECPWPT and ECL values. This variability in ECL was due to the strong influence that the leaching fraction had on ECL (Ku and Hershey, 1992), since the irregular physiological state of salinised plants (Gómez-Bellot et al., 2013) and the lack of uniformity in substrate moisture under drip irrigation (Valdés et al., 2014a) can disrupt leaching. The slope of the ECPWGS3 – ECIW plot was the lowest, therefore ECPWGS3 values were lower than ECL and ECPWPT values for the same ECIW (Figure 1A). As was the case for ECL, increasing ECIW resulted in greater variability in ECPWGS3 values. The method used to estimate ECPWGS3 (Hilhorst, 2000) was responsible for this variability, since soil moisture (Rosenbaum et al., 2011; Van Der Laan et al., 2011), salinity (Kargas and Kerkides, 2010; Valdés et al., 2015), and soil type (Kargas and Kerkides, 2012) affected the estimates. Relationships among EC measurements The three linear regression models shown in Figure 1B show significant relationships for ECPWPT – ECB, ECPWPT – ECPWGS3, and ECPWPT – ECL. All the fits were strong (R2 ≥ 0.82), suggesting that ECB, ECPWGS3 and ECL can be used as indicators to estimate the true salinity of the substrate solution. Their slopes indicated

FIG. 1 Changes in the electrical conductivity (EC) of the leachate (ECL), pour-through soil pore water (ECPWPT), and GS3 pore water (ECPWGS3) using irrigation water of eight different EC (ECIW) values (Panel A). Relationships between ECPWPT and ECL, ECPWGS3, and bulk EC (ECB) are shown in Panel B. The data shown in Panel A are mean values (n = 3) measured throughout the 14-week experimental period. *** indicates significant at P ≤ 0.001.

574


FIG. 2 Changes in soil water content (solid black lines), soil pore water electrical conductivity (ECPW, solid grey lines), and bulk EC (ECB, dotted grey lines) from 14 December 2013 to 23 January 2014 during irrigation with eight different saline solutions. Panel A, ECIW 1.5 dS m–1; Panel B, ECIW 2.0 dS m–1; Panel C, ECIW 2.5 dS m–1; Panel D, ECIW 3.0 dS m–1; Panel E, ECIW 3.5 dS m–1; Panel F, ECIW 4.0 dS m–1; Panel G, ECIW 4.5 dS m–1; and Panel H, ECIW 5.0 dS m–1.

that ECPWGS3 values under-estimated the level of ECPWPT, while ECL values over-estimated the same. Kargas and Kerkides (2012) found that the Hilhorst Model over-estimated ECPW for salinity values up to 1.2 dS m–1, while it significantly under-estimated ECPW for

higher EC values, as observed in our experiment. The slope of the ECPWPT – ECB plot was steeper than that of the ECPWPT – ECPWGS3 plot.Therefore, ECPWGS3 values were closer to ECPWPT values than ECB values. Despite this, the ECPWPT was more closely related to ECB

R. VALDÉS, J. A. FRANCO, M. J. SÁNCHEZ-BLANCO and S. BAÑÓN

575

presence of a high substrate moisture content in potted poinsettia (Valdés et al., 2014b).

FIG. 3 Changes in soil water content (solid thick black lines), pore water electrical conductivity (ECPW; solid thin black lines), bulk EC (ECB; grey solid lines), and substrate temperature (dotted grey lines) between two irrigation events (from 22 December 2013 to 3 January 2014) using irrigation water of ECIW 1.5 dS m–1 (Panel A) or ECIW 5.0 dS m–1 (Panel B).

(higher R2) than to ECPWGS3. There are two possible explanations for this behaviour. First, ECB was measured immediately following irrigation and this measurement is known to be strongly influenced by the soil moisture content (Amente et al., 2000; Valdés et al., 2014b). Second, ECPWGS3 was calculated using the Hilhorst Model and, as mentioned above, this measurement is affected by soil moisture, salinity, and soil type. Thus, we think that ECB can also be regarded as an appropriate indicator of substrate salinity, as was seen when it was measured in the

Changes in substrate , ECPW and ECB values obtained using the GS3 sensor Irrigation at low ECIW values resulted in lower substrate values than irrigation at high ECIW values (Figure 2). This was because all treatments were irrigated with the same irrigation volume at the same frequency, while the less salinised plants had a drier substrate due to greater growth and higher transpiration. Substrate values decreased following irrigation in a stepwise pattern in all treatments due to plants using more water during the day than at night (Ferrarezi et al., 2015). Treatments with lower ECIW caused a more rapid decline in substrate values after irrigation than those with higher ECIW because: (i) salinised plants transpired less (Gómez-Bellot et al., 2013); (ii) a salt-affected substrate loses less water by evaporation (Valdés et al., 2014a); and (iii) before irrigating, substrate values at high ECIW values were higher than at low ECIW values. ECB increased immediately after irrigating. The higher the ECIW, the greater the increase in ECB (Figure 2). ECB values decreased gradually as the substrate dried out. The higher the ECIW, the sharper the decrease, because ECB was more susceptible to changes in moisture when the salinity was high (Amente et al., 2000). After irrigating, ECPWGS3 values increased in the ECIW ≤ 3 dS m–1 treatments (i.e., drier substrate) then gradually decreased as the substrate dried-out (Figure 2). However, one might have expected that the real ECPW should fall immediately after irrigating, because of the dilution effect and the leaching of salts from the substrate. The real ECPW then ought to have increased because the salt remained in the substrate while the water was removed. Under ECIW ≥ 3.5 dS m–1 (i.e., wetter substrate), ECPWGS3 values decreased after irrigation, then gradually increased as the substrate dried-out. Nevertheless, ECPWGS3 values moved erratically, with strong fluctuations in the ECPWGS3 curves (Figure 2). A more detailed amalysis of such fluctuations showed how the highest temperature values coincided with the lowest ECPWGS3 values, for both the lowest (Figure 3A) and, especially, the highest (Figure 3B) ECIW. This reveals the influence of temperature on ECPWGS3, which increased as salinity increased. Seyfried and Grant (2007) reported temperature effects on the dielectric properties of soil

TABLE I Linear regression models for growth parameters, ion concentrations in plant tissues, and the electrical conductivity of the irrigation water (ECIW) Parameter (Units) Plant height (cm) Plant width (cm) Shoot DW (g) Number of leaves per plant Leaf area (dm2) No. of inflorescences per plant Foliar SPAD value Foliar damage Leaf Cl– (mg g–1 DW) Root Cl– (mg g–1 DW) Leaf Na+ (mg g–1 DW) Root Na+ (mg g–1 DW) Leaf K+ (mg g–1 DW) Root K+ (mg g–1 DW) ‡

Equation y = 33.35 – 1.79ECIW y = 30.94 + 0.35ECIW y = 18.46 – 0.95ECIW y = 416.00 – 0.04ECIW y = 14.52 – 0.51ECIW y = 54.53 + 2.29ECIW y = 55.47 + 0.37ECIW y = 10.37 + 2.12ECIW y = 72.78 + 3.05ECIW y = 17.13 + 12.22ECIW y = 14.71 + 5.29ECIW y = 8.34 + 6.86ECIW y = 31.77 – 2.78ECIW y = 17.80 + 1.71ECIIW

ns, *, **, ***, non-significant or significant at P ≤ 0.05, P ≤ 0.01, or P ≤ 0.001, respectively.

Significance‡

R2

*** ns ** ns ns ns ns ** *** *** *** *** *** *

0.32 0.01 0.22 < 0.01 0.09 0.11 0.13 0.38 0.55 0.83 0.71 0.76 0.77 0.27

576


measured at 50 MHz using a Hydra-Probe sensor. Rosenbaum et al. (2011) found that B was underestimated at low temperatures and over-estimated at high temperatures when using capacitive soil sensors, while Evett et al. (2014) indicated that ECB varied strongly with temperature in salt-affected soils. Both behaviours were observed in our experiment, especially at high salinity (Figure 3B). Plant development and growth Plant height and shoot DW decreased linearly with increasing ECIW, while plant width was not affected (Table I). Cassaniti et al. (2009) indicated that declines in shoot DWs and leaf areas were the first visible effects of salinity on plants. However, in our experiment neither leaf areas nor the number of leaves per plant were altered by increasing ECIW. The number of inflorescences per plant was also not affected by increasing ECIW, which contrasts with the findings of other authors, who found that the number of flowers was reduced substantially in other species, such as rose, as a result of salinity (Cai et al., 2014). In our plants, the frequency of leaves with necrotic damage increased with increasing ECIW; however, the damage was restricted to the basal leaves. Plants irrigated at the lowest ECIW had approx. 15% of their basal leaves damaged. No sign of yellowing (lower foliar SPAD values) associated with increasing ECIW were observed in Osteospermum (Table I). Cl–, Na+, and K+ ion concentrations in leaves and roots Leaf and root Cl– concentrations exhibited linear responses to increasing ECIW (Table I). However, the increase in Cl– ions in roots was greater than in leaves. Despite high leaf Cl– ion concentrations, which ranged from 75 mg g–1 DW (control) to 90 mg g–1 DW (5 dS m–1 ECIW), necrosis was only observed in the basal leaves of Osteospermum. Such behaviour could be related to the efficient compartmentalisation of Cl– ions in vacuoles (Roy et al., 2014). Leaf and root Na+ ion concentrations also responded linearly to increasing ECIW. The higher the ECIW, the higher the Na+ concentration in both organs. Nevertheless, Osteospermum plants accumulated less Na+ than Cl– ions

in both leaves and roots. Foliar Na+ ion concentrations ranged from 23 mg g–1 DW (control) to 41 mg g–1 DW (5 dS m–1 ECIW). Na+ ion accumulation in roots was similar to that in leaves, suggesting that Osteospermum did not possess a mechanism to limit the transport of Na+ ions to the aerial parts (Yadav et al., 2011). So, the hypothesis of more efficient Na+ ion compartmentalisation in vacuoles becomes more defensible. Concentrations of K+ ions in the leaves of Osteospermum decreased linearly with increasing ECIW, whereas the reverse occurred in roots (Table I). A reduction in K+ ion concentrations as salinity increased was also detected in the leaves of Arbutus unedo (Navarro et al., 2008). In some studies, the cause of such a reduction in leaves was reported to be due to an antagonistic relationship between Na+ and K+ ions at the root surface (Meloni et al., 2008). However, other studies have attributed this result to suppression of K+ ion transport to the shoot, rather than to any antagonism (Song and Fujiyama, 1998). This last assumption was consistent with our observations, because the slope of the leaf K+ – ECIW plot was negative, but was positive for the root K+ – ECIW plot (Table I). CONCLUSIONS Post-irrigation values of ECB and the decrease in ECB values might be helpful to control substrate salinity. ECL and ECPWGS3 were good indicators of the salinity of soil pore water, but the former over-estimated it, while the latter under-estimated it. Furthermore, as salinity increased, both estimates became less accurate. Substrate moisture influenced estimates of ECPWGS3. Lower substrate moisture values increased the underestimation. Increasing the salinity of the irrigation water increased fluctuations in the ECPWGS3 data because the soil temperature effect became greater. Osteospermum was found to be a moderately salt-tolerant plant. This research was funded by the Spanish Ministry of Economy and Competitiveness MINECO (FEDER Cofinancing Projects. AGL2011-30022-C02-1 and AGL2011-30022-C02-2).

REFERENCES ADOLF, V. I., JACOBSEN, S. E. and SHABALA, S. (2013). Salt tolerance mechanisms in quinoa (Chenopodium quinoa Willd.). Environmental and Experimental Botany, 92, 43–54. AMENTE, G., BAKER, J. M. and REECE, C. F. (2000). Estimation of soil solution electrical conductivity from bulk soil electrical conductivity in sandy soils. Soil Science Society of America Journal, 64, 1931–1939. BAÑÓN, S., MIRALLES, J., FRANCO, J. A., OCHOA, J. and SÁNCHEZBLANCO, M. J. (2011). Effects of diluted and pure treated wastewater on the growth, physiological status and visual quality of potted lantana and polygala plants. Scientia Horticulturae, 129, 869–876. BENZARTI, M., REJEB, K. B., MESSEDI, D., MNA, A. B., HESSINI, K., KSONTINI, M. and DEBEZ, A. (2014). Effect of high salinity on Atriplex portulacoides: Growth, leaf water relations and solute accumulation in relation with osmotic adjustment. South African Journal of Botany, 95, 70–77.

CAI, X., NIU, G., STARMAN, T. and HALL, C. (2014). Response of six garden roses (Rosa hybrida L.) to salt stress. Scientia Horticulturae, 168, 27–32. CASSANITI, C., LEONARDI, C. and FLOWERS, T. J. (2009). The effects of sodium chloride on ornamental shrubs. Scientia Horticulturae, 122, 586–593. CAVINS, T., WHIPKER, B. and FONTENO, W. (2008). Pour-through: A method for monitoring nutrition in the greenhouse. Acta Horticulturae, 779, 289–297. EVETT, S., SCHWARTZ, R. CASANOVA, J. and HENG, L. (2012). Soil water sensing for water balance, ET and WUE. Agricultural Water Management, 104, 1–9. EVETT, S., SCHWARTZ, R., CASANOVA, J. and ANDERSON, S. (2014). A new soil water and bulk electrical conductivity sensor technology for irrigation and salinity management. Soils Newsletter, 36, 7–8. FERRAREZI, R. S., VAN IERSEL, M. W. and TESTEZLAF, R. (2015). Monitoring and controlling ebb-and-flow subirrigation with soil moisture sensors. HortScience, 50, 447–453.

R. VALDÉS, J. A. FRANCO, M. J. SÁNCHEZ-BLANCO and S. BAÑÓN GIBSON, J. L. and WHIPKER, B. E. (2003). Efficacy of plant growth regulators on the growth of vigorous Osteospermum cultivars. HortTechnology, 13, 132–135. GÓMEZ-BELLOT, M. J., ÁLVAREZ, S., BAÑÓN, S., ORTUÑO, M. F. and SÁNCHEZ-BLANCO, M. J. (2013). Physiological mechanisms involved in the recovery of Euonymus and Laurustinus subjected to saline water. Agricultural Water Management, 128, 131–139. HILHORST, M. A. (2000). A pore water conductivity sensor. Soil Science Society of America Journal, 64, 1922–1925. KARGAS, G. and KERKIDES, P. (2010). Evaluation of a dielectric sensor for measurement of soil-water electrical conductivity. Journal of Irrigation and Drainage Engineering, 136, 553–558. KARGAS, G. and KERKIDES, P. (2012). Comparison of two models in predicting pore water electrical conductivity in different porous media. Geoderma, 189, 563–573. KU, C. S. and HERSHEY, D. R. (1992). Leachate electrical conductivity and growth of potted geranium with leaching fractions of 0 to 0.4. Journal of the American Society for Horticultural Science, 117, 893–897. MELONI, D. A., GULOTTA, M. R. and MARTINEZ, C. A. (2008). Salinity tolerance in Schinopsis quebracho Colorado: Seed germination, growth, ion relations and metabolic responses. Journal of Arid Environments, 72, 1785–1792. MUNNS, R. and TESTER, M. (2008). Mechanisms of salinity tolerance. Annual Review of Plant Biology, 59, 651–681. NAVARRO, A., BAÑÓN, S., CONEJERO, W. and SÁNCHEZ-BLANCO, M. J. (2008). Ornamental characters, ion accumulation and water status in Arbutus unedo seedlings irrigated with saline water and subsequent relief and transplanting. Environmental and Experimental Botany, 66, 362–371. ORON, G., DEMALACH, Y., GILLERMAN, L., DAVID, I. and LURIE, S. (2002). Effect of water salinity and irrigation technology on yield and quality of pears. Biosystems Engineering, 81, 237–247. ROSENBAUM, U., HUISMAN, J. A., VRBA, J., VEREECKEN, H. and BOGENA, H. R. (2011). Correction of temperature and electrical conductivity effects on dielectric permittivity measurements with ECHO sensors. Vadose Zone Journal, 10, 582–593.

577

ROY, S. J., NEGRÃO, S. and TESTER, M. (2014). Salt resistant crop plants. Current Opinion in Biotechnology, 26, 115–124. SÁNCHEZ-BLANCO, M. J., FERRÁNDEZ, T., MORALES, M. A., MORTE, A. and ALARCÓN, J. J. (2004). Variation in water status, gas exchange, and growth in Rosmarinus officinalis plants infected with Glomus deserticola under drought conditions. Journal of Plant Physiology, 161, 675–682. SEYFRIED, M. S. and GRANT, L. E. (2007). Temperature effects on soil dielectric properties measured at 50 MHz. Vadose Zone Journal, 6, 759–765. SONG, J. Q. and FUJIYAMA, H. (1998). Importance of Na+ content and water status for growth in Na-salinized rice and tomato plants. Soil Science and Plant Nutrition, 44, 197–208. TORRES, A. P., MICKELBART, M. V. and LOPEZ, R. G. (2010). Leachate volume effects on pH and electrical conductivity measurements in containers obtained using the pour-through method. HortTechnology, 20, 608–611. VALDÉS, R., MIRALLES, J., OCHOA, J., SÁNCHEZ-BLANCO, M. J. and BAÑÓN, S. (2014a). The number of emitters alters salt distribution and root growth in potted Gerbera. HortScience, 49, 160–165. VALDÉS, R. MIRALLES, J., FRANCO, J. A., SÁNCHEZ-BLANCO, M. J. and BAÑÓN, S. (2014b). Using soil bulk electrical conductivity to manage saline irrigation in the production of potted Poinsettia. Scientia Horticulturae, 170, 1–7. VALDÉS, R., OCHOA, J., FRANCO, J. A., SÁNCHEZ-BLANCO, M. J. and BAÑÓN, S. (2015). Saline irrigation scheduling for potted Geranium based on soil electrical conductivity and moisture sensors. Agricultural Water Management, 149, 123–130. VAN DER LAAN, M., STIRZAKER, R. J., ANNANDALE, J. G., BRISTOW, K. L. and DUPREEZ, C. C. (2011). Interpretation of electrical conductivity measurements from ceramic suction cups, wetting front detectors and ECH20-TE sensors. South African Journal of Plant and Soil, 28, 244–247. YADAV, S., IRFAN, M., AHMAD, A. and HAYAT, S. (2011). Causes of salinity and plant manifestations to salt stress: a review. Journal of Environmental Biology, 32, 667–685.