Giulia Carmassi

Laura Bacci

Matteo Bronzini

Luca Incrocci

Rita Maggini

Gianni Bellocchi

Daniele Massa

Alberto Pardossi
email: alberto.pardossi@agr.unipi.it

Modelling transpiration of greenhouse gerbera (Gerbera jamesonii H. Bolus) grown in substrate with saline water in a Mediterranean climate

Keywords:

Gerbera plants were grown in semi-closed rockwool culture under greenhouse conditions in different seasons in a Mediterranean climate. The plants were irrigated using either fresh (FW; 1.0 mol m -3 NaCl) or moderately saline (SW; 9.0 mol m -3 NaCl) water. In autumn, NaCl concentration did not influence significantly plant growth, flower production and transpiration (E), which instead were reduced in spring in the plants irrigated with SW. In both seasons, water salinity did not affect leaf stomatal resistance (r l ), which was determined by the inversion of the Penman-Monteith (PM) equation or measured with a diffusion porometer. The PM formula and two regression equations were calibrated and validated for estimating the hourly rate of daytime transpiration (E d ); a regression model was also fit to nocturnal transpiration (E n ). Regression models predicted E d as a function of vapour pressure deficit (VPD) and/or the radiation intercepted by the canopy. Leaf area index (LAI), which is required by all the equations, was modelled as function of crop thermal time (i.e. growing degree days). The PM model predicted E d using a constant value of r l . Model calibration and validation were performed using independent datasets. The irrigation with FW or SW did not require a different calibration of transpiration models. Both PM formula and regression equations provided accurate estimates of E d ; fitted equations explained between 80% and 96% of the variance in measured E d . A linear regression of E n against (LAI•VPD) accounted for 92% of measured E n .

Introduction

Greenhouse crops are generally over-irrigated and this results in water loss and environmental degradation due to fertilizers leaching [START_REF] Vox | Sustainable greenhouse systems[END_REF]. A major cause of over-irrigation is inadequate scheduling, which often is based on grower's experience rather than on accurate assessment of crop water requirements [START_REF] Pardossi | Traditional and new approaches to irrigation scheduling in vegetable crops[END_REF][START_REF] Thompson | Identification of irrigation and N management practices that contribute to nitrate leaching loss from an intensive vegetable production system by use of a comprehensive survey[END_REF].

Leaf transpiration (E) is the primary process affecting plant water uptake (W) and hence its knowledge is necessary to determine crop water needs. In greenhouse crops, particularly in substrate culture, irrigation control requires the determination of E over short time intervals (hourly or less). If E is known as a function of climatic variables, E models can be easily implemented for automated irrigation control. Modelling E can also provide a softsensor in an early warning system for growers [START_REF] Elings | Management of greenhouse crop transpiration: the way forward[END_REF]. For instance, a reduction of actual E with respect to the predictions may indicate alterations of plant water status resulting from a technical failure of irrigation system, mistakes in fertigation management and/or the occurrence of root diseases.

The use of the Penman-Monteith (PM) equation [START_REF] Allen | Effects of salinity and relative humidity on two melon cultivars differing in salt tolerance[END_REF] provides accurate E prediction; however, it requires several input parameters that are difficult to estimate, such as leaf stomatal resistance (r l ). Several authors (e.g. Baille et al., 1994a;Carmassi et al., 2007a;[START_REF] Kittas | Transpiration and canopy resistance of greenhouse soilless roses: measurements and modelling[END_REF] proposed simplified forms of the PM formula based on the assumption of constant r l .

The PM equation and its simplified versions have been used for predicting E in a variety of greenhouse crops, such as cucumber [START_REF] Medrano | Evaluation and modelling of greenhouse cucumber-crop transpiration under high and low radiation conditions[END_REF], geranium [START_REF] Montero | Transpiration from geranium grown under high temperatures and low humidities in greenhouses[END_REF], lettuce [START_REF] Pollet | Application of the Penman-Monteith model to calculate the evapotranspiration of head lettuce (Lactuca sativa L. var. capitata) in glasshouse conditions[END_REF], rose (Baille et al., 1994b;[START_REF] Kittas | Transpiration and canopy resistance of greenhouse soilless roses: measurements and modelling[END_REF], tomato (Carmassi et al., 2007a;[START_REF] Stanghellini | Transpiration of greenhouse crops. An aid to climate management[END_REF], zucchini [START_REF] Rouphael | Modelling the transpiration of a greenhouse zucchini crop grown under a Mediterranean climate using the Penman-Monteith equation and its simplified version[END_REF] and some pot ornamentals [START_REF] Bailey | Transpiration of Ficus benjamina: comparison of measurements with predictions of the Penman-Monteith model and a simplified version[END_REF]Baille et al., 1994a). However, less attention has been paid Abbreviation Symbol or abbreviation A empirical coefficient in Eqs. ( 9) and (12) B empirical coefficient in Eqs. ( 9) and ( 13) (kg m -2 h -1 kPa -1 ) c p specific heat of the air (J kg -1 K -1 ) d leaf dimensions (m) E transpiration rate (kg m -2 h -1 or kg m -2 day -1 ) E 24 h crop transpiration in the 24 h period (kg m -2 day -1 ) e a air vapour pressure (kPa) e * a saturated air vapour pressure (kPa) EC electrical conductivity (dS m -1 ) E d daytime transpiration rate (kg m -2 h -1 ) E n nocturnal crop transpiration rate (kg m -2 h -1 ) FW fresh water g gravity acceleration (m s -2 ) GDD growing degree days ( • C) Gr

Grashof number h heat transfer coefficient (W m -2 K -1 ) I indoor global radiation (MJ m -2 ; W m -2 ) I c global radiation intercepted by crop canopy (MJ m -2 ; W m -2 ) I n net radiation (MJ m -2 ; W m -2 ) k light extinction coefficient (dimensionless) k c thermal conductivity of air (W m -1 K -1 ) lt leaf length (m) LAI leaf area index NS nutrient solution PM Penman-Monteith r a aerodynamic resistance of the canopy to vapour transfer (s m -1 ) r c canopy resistance (s m -1 ) Re

Reynolds number r l leaf stomatal resistance (s m -1 ) SW saline water T a air temperature ( • C) T l leaf temperature ( • C) u air velocity (m s -1 ) VPD vapour pressure deficit (kPa) v kinematic viscosity of air (m 2 s -1 ) w leaf width (m) W water uptake (kg m -2 ) ˇ thermal expansion coefficient of air (K -1 ) slope of the relationship of saturation vapour pressure on temperature (kPa • C -1 ) psychrometric constant (kPa • C -1 ) latent heat of water vaporization (J kg -1 ) air density (kg m -3 ) ˝ decoupling coefficient to cut-flower gerbera (Gerbera jamesonii H. Bolus), one of the most important greenhouse ornamental crops [START_REF] Vidalie | Varietal richness and technology for gerbera[END_REF]. To the best of our knowledge, only a short paper on modelling E in gerbera was published in the proceedings of an international symposium [START_REF] Marfà | Water consumption of a closed soilless culture of gerbera: usefulness of model to estimate evapotranspiration[END_REF].

In this work, we used the PM model and two regression equations to predict E of gerbera plants grown in semi-closed substrate (rockwool) culture under the typical greenhouse conditions of Mediterranean area. With respect to the paper published by [START_REF] Marfà | Water consumption of a closed soilless culture of gerbera: usefulness of model to estimate evapotranspiration[END_REF], different approaches were used to estimate leaf area index (LAI) and r l . Besides, we investigated the effect of NaCl salinity on crop growth and water relations, and its possible influence on modelling E. In many regions, particularly in the Mediterranean area, protected horticulture is increasingly facing the salinization of water resources [START_REF] Pardossi | Mediterranean greenhouse technology[END_REF] and the knowledge of crop response to salinity is important for optimal crop management [START_REF] Stanghellini | What limits the application of wastewater and/or closed cycle in horticulture?[END_REF]. Greenhouse crops cannot be grown with highly saline water for being profitable [START_REF] Stanghellini | What limits the application of wastewater and/or closed cycle in horticulture?[END_REF]. Therefore, in our study a moderately saline water (NaCl concentration of 9.0 mol m -3 against 1.0 mol m -3 in the fresh or control water) was tested.

Materials and methods

Plant material and growing conditions

Gerbera (cv. Vital) plants were cultivated between 29 May 2004 and 30 November 2005 in a glasshouse at the University of Pisa (Pisa, Italy, latitude 43 • 43 N, longitude 10 • 23 E). The glasshouse was equipped with automated side and roof windows (with insect screens) and heating system; ventilation and minimum temperatures were 27 and 15 • C, respectively. The glasshouse was heated sporadically (generally only in the night) and was covered by black plastic net (30% shading rate) from late May to the end of August in both years.

The plants were grown in rockwool slabs at a density of approximately 5 plants m -2 . The glasshouse had six separate growing units, each consisting of two benches with 12 slabs (48 plants in total) and an 80 l mixing tank collecting the drainage NS. The total amount of recirculating NS, including the substrate and the mixing tank, was approximately 150 l (i.e. 15.6 l m -2 expressed per unit of ground area). In order to compensate crop W, the mixing tank was automatically refilled with full-strength NS. Drip irrigation was controlled by a timer; the plants were watered 2-6 times a day, depending on growth stage and seasons, with a watering dose of 1.5-2.0 l m -2 (leaching fraction was roughly 0.30-0.50).

Nutrient solution was made up with either fresh water (FW; 1.0 mol m -3 NaCl) or saline water (SW; 9.0 mol m -3 NaCl), which were prepared by dissolving appropriate doses of NaCl to rainwater. Each treatment was applied to three separate growing units (replicates). All the plants were initially grown with FW; SW was applied at the beginning of September 2004. The EC of the NS prepared with FW and SW was 1.45 and 2.25 dS m -1 , respectively. The nutrient solution also contained 9.1 mol m -3 NO 3 -, 1.0 mol m -3

H 2 PO 4 -, 4.3 mol m -3 K + , 1.1 mol m -3 Mg 2+ , 3.0 mol m -3 Ca 2+ , plus
Hoagland concentration of trace elements. In each growing unit, NS was checked almost daily for EC and pH; the latter was kept between 5.5 and 6.0 by frequent addition of sulphuric acid. Nutrient solution was discharged whenever EC exceeded 3.0 or 4.0 dS m -1 in the FW and SW cultures, respectively. Older leaves were recurrently removed following growers' practice and in February of 2005 the plants were intensively defoliated in order to stimulate a new flush of growth.

Determinations

Crop growth, flower production and water relations were monitored in three periods (Table 1): (i) between 22 September 2004 and 9 January 2005 (110 days); (ii) between 11 April and 2 July 2005 (83 days); (iii) between 10 October and 20 November 2005 (42 days). In the third period, only E and W were measured.

Fresh and recirculating NS was periodically sampled for laboratory analyses of macronutrients and Na, as reported by [START_REF] Massa | Strategies to decrease water drainage and nitrate emission from soilless cultures of greenhouse tomato[END_REF].

Crop shoot biomass and LAI were determined by sampling six individual plants from each treatment on 9 January and 3 July 2005. The plants were separated in leaves and inflorescences (stem and flower head), which were dried to constant weight at 80 in a ventilated oven. Total biomass accumulation was computed including the leaves and the flowers detached in occasion of pruning and harvesting. Leaf area index was also determined weekly by non-destructive measurements of leaf dimensions (maximum length and width) of individual leaves using the equation reported by Carmassi et al. (2007b).

Daily W was determined by recording with a water meter the amount of NS used to refill the mixing tank. Hourly E was measured by weighing a tray with six plants using an electronic balance. The balance (capacity: 30 kg; resolution: ±0.001 kg) was placed in the centre of a bench with other plants in order to form a continuous canopy. We assumed that weight loss was equal to E as evaporation from substrate was prevented by plastic film. Indoor incident radiation (I), air temperature (T a ), wet and dry bulb air temperature, and calculated vapour pressure deficit (VPD) were recorded with a weather station located in the central part of the glasshouse. Both climate sensors and electronic balance were scanned every minute by a data logger and averages were made over 60 min time periods. Data recorded in occasion of irrigation events (until 20 min after the start of watering, when the drainage from the tray had terminated) and E values below 0.005 kg m -2 h -1 were discarded. As only one balance was available, crop E was monitored in each salinity treatment every other week. Daytime (I ≥ 25 W m -2 ) values of E (E d ) were separated from those measured during the night (E n ; I < 25 W m -2 ); actually, for E d modelling we used the data recorded between 08.00 a.m. and 05.00 p.m. (10 h) in autumn, and between 07.00 a.m. and 07.00 p.m. (13 h) in spring.

On some days in autumn 2004 and in spring 2005, we measured leaf stomatal resistance (r l ) with a diffusion porometer (MK, Delta-T Devices, Cambridge, UK). The measurements were taken between 11.00 a.m. and 01.00 p.m.; in each treatment, 2-3 leaves were sampled from 4 to 6 individual plants.

Leaf temperature (T l ) and air velocity (u, m s -1 ) were measured discontinuously with a portable infrared thermometer and a hotwire anemometer.

Transpiration models

The first model was derived from the PM equation [START_REF] Allen | Effects of salinity and relative humidity on two melon cultivars differing in salt tolerance[END_REF]Baille et al., 1994b):

• E = • I c + * + ( • c p /r a )
• (e * ae a ) + *

(1)

where crop E (kg m -2 h -1 ) is based on ground area, (J kg -1 ) is the latent heat of vaporization of water, I c (W m -2 ) is the radiation intercepted by canopy, (kg m -3 ) is air density, c p (J kg -1 K -1 ) is the specific heat of air at constant pressure, e a (kPa) is the air vapour pressure, e * a (kPa) is the saturated air vapour pressure, r a (s m -1 ) is the aerodynamic resistance to vapour transfer, (kPa • C -1 ) is the slope of the relationship of saturation vapour pressure on temperature, * = (1 + r c /r a ) where (kPa • C -1 ) is the psychrometric constant, and r c (s m -1 ) is the mean canopy resistance.

The term I c in Eq. ( 1) was calculated as:

I c = I • (1 -exp -k•LAI ) (2)
where k (dimensionless) is the light interception coefficient. This coefficient was determined on the basis of Lambert-Beer's law from the radiation measured with a piranometer placed above and below the crop row [START_REF] Nobel | Canopy structure and light interception techniques[END_REF]. In Eq. ( 2), I was used instead of net radiation (I n ) because net radiometer was not available. This was possible because in unheated greenhouses I n matches I during the light period [START_REF] Bailey | Transpiration of Ficus benjamina: comparison of measurements with predictions of the Penman-Monteith model and a simplified version[END_REF]Baille et al., 1994a). In another experiment conducted in 2006 with gerbera grown in the same glasshouse (unpublished results), a close linear relationship was found between I n and I (I n = 0.981I; R 2 = 0.902; n = 487) in the range between 25 and 545 W m -2 .

Leaf area index was estimated as a function of growing degree days (GDD) assuming a base temperature of 8 • C.

Canopy resistance was computed as the ratio between r l and LAI while r a was calculated as follows:

r a = • c p 2 • LAI • h (3)
where h (W m -2 K -1 ) is the heat transfer coefficient for individual leaves [START_REF] Bailey | Transpiration of Ficus benjamina: comparison of measurements with predictions of the Penman-Monteith model and a simplified version[END_REF].

There is no consensus on how heat is transferred under greenhouse conditions and hence h was calculated according to the free [START_REF] Mcadams | Heat transmission[END_REF], forced [START_REF] Gröber | Fundamentals of heat transfer[END_REF] or mixed convection [START_REF] Stanghellini | Transpiration of greenhouse crops. An aid to climate management[END_REF] using the Grashof (Gr) and Reynolds (Re) numbers [START_REF] Bailey | Transpiration of Ficus benjamina: comparison of measurements with predictions of the Penman-Monteith model and a simplified version[END_REF]. In a preliminary data analysis, we found that the best predictions of E were obtained when h was computed assuming a mixed convection, as follows:

h = 0.37 • k c d • (Gr + 6.92Re 2 ) 1/4 (4)
where k c (W m -1 K -1 ) is the thermal conductivity of air and d (m) is the leaf dimension determined as:

d = 2 (1/lt) + (1/w) (5)
where lt (m) and w (m) are, respectively, the length and the width of the leaves. The numbers of Grashof and Reynolds correspond to the air flow occurring in free and forced convection, respectively.

The Grashof number was computed as a function of the difference between T l and T a :

Gr = ˇ • g • d 3 • |T l -T a | 2 (6)
where ˇ (K -1 ) is the thermal expansion coefficient of air, g (m s -2 ) is the acceleration due to gravity and (m 2 s -1 ) is the kinematic viscosity of air. The Reynolds number (Re) was obtained from u, d and , as follows

Re = u • d (7)
Leaves are generally very thin, thus the temperature of the upper and lower leaf surface was assumed equal. The dimensionless decoupling coefficient (˝) was calculated to analyze the dependence of E d on atmospheric environment and stomatal opening [START_REF] Jarvis | Stomatal control of transpiration: scaling up from leaf to region[END_REF], namely:

˝ = 1 1 + ( /( + )) • (r c /r a ) (8)
Transpiration rate was also modelled using the equation proposed by Baille et al. (1994a):

E d = A • I c + B • LAI • VPD (9)
The coefficients A (dimensionless) and B (kg m -2 h -1 kPa -1 ) were obtained by regressing measured E against I c (MJ m -2 h -1 ) and (LAI•VPD).

Statistics

The influence of growing season and irrigation water salinity on crop growth, flower production and seasonal W was assessed through ANOVA. Calibration and validation of E models was performed using independent datasets. Model accuracy was assessed by regression analysis of predictions against measurements; we computed the slope and the intercept of the linear regression, the determination coefficient (R 2 ), the standard error of estimates (SEE), the mean percentage error (MPE) and the mean absolute percentage error (MAPE). Statistical analysis was performed with Statgraphics Centurion XV (Statpoint Technologies, Inc., Warrenton, VA, USA).

Results and discussion

Growing conditions

Fig. 1 shows the seasonal variations of daily values of I, T a and VPD. Daily averages of I, T a and VPD were, respectively 2.27 MJ m -2 day -1 , 17.4 • C and 0.30 kPa in the autumn of 2004; 9.87 MJ m -2 day -1 , 22.6 • C and 1.02 kPa in the spring of 2005; 3.97 MJ m -2 day -1 , 16.6 • C and 0.34 kPa in the autumn of 2005 (Table 1). Over the daylight period, I, T a and VPD ranged, respectively; from 0.10 to 0.47 MJ m -2 h -1 , from 17.1 to 23.2 • C and from 0.22 to 0.95 kPa in autumn; from 0.14 to 1.10 MJ m -2 h -1 , from 20.6 to 28.8 • C and from 0.56 to 2.70 kPa in spring. Despite glasshouse shading, in late spring and summer T a exceeded frequently 30 • C during sunny hours. Significant positive correlations were found between I and T a (R 2 = 0.328; n = 1374) or VPD (R 2 = 0.381), and between T a and VPD (R 2 = 0.738). In the night, significant correlation (R 2 = 0.563; n = 908) was found between T a and VPD.

In the FW culture, the EC of recirculating NS ranged from 2.48 to 3.42 dS m -1 with a mean value of 2.78 dS m -1 in the autumn of 2004, and from 1.97 and 3.03 dS m -1 with a mean value of 2.28 dS m -1 in the spring of 2005; NS solution was discharged on two occasions in autumn and on four occasions in spring. In the SW culture, EC oscillated between 2.78 and 4.21 dS m -1 with a mean value of 3.62 dS m -1 in autumn, when NS was discharged four times, and between 2.78 and 4.21 dS m -1 with a mean value of 3.69 dS m -1 in the spring of 2005, when NS was discharged eight times.

Table 2

Crop water relations, growth and flower production in greenhouse gerbera grown in semi-closed substrate culture in different seasons and irrigated with fresh (FW; 1.0 mol m -3 NaCl) or saline (SW; 9.0 mol m -3 NaCl) water. Mean values (±SE); n = 3 or 247-358) of three replicates or 247-358 E d observations. Shoot dry biomass includes the older leaves recurrently removed during the cultivation while LAI refers to the values determined at the end of each season. In each column, the means separated by different letters are significantly different (p < 0.05) according to ANOVA. The interaction between growing season and water salinity was significant (p < 0.05) for all measured quantities.

Season

Water In all the cultures, salinity build-up in the recirculating NS was principally due to NaCl accumulation (data not shown) as found by other authors in closed-loop soilless cultures [START_REF] Massa | Strategies to decrease water drainage and nitrate emission from soilless cultures of greenhouse tomato[END_REF][START_REF] Savvas | Modelling Na and Cl concentrations in the recycling nutrient solution of a closedcycle pepper cultivation[END_REF]. Mean concentrations of both macronutrients and micronutrients in the recirculating NS were generally close to their content in the refill NS (data not shown).

Crop growth and production

NaCl salinity reduces crop growth and production in sensitive species [START_REF] Volkmar | Réponse physiologique des plantes à la salinité: Mise au point bibliographique[END_REF] due to its negative effects on water and mineral relations, carbon assimilation and biomass partitioning. Crop response to salinity depends on cultivar and growing conditions (e.g. [START_REF] Baas | Yield and quality of carnation (Dianthus caryophyllus L.) and gerbera (Gerbera jamesonii L.) in a closed nutrient system as affected by sodium chloride[END_REF][START_REF] De Kreij | Production and quality of gerbera in rockwool as affected by electrical conductivity of the nutrient solution[END_REF][START_REF] Sonneveld | Salt tolerance of flower crops grown in soilless culture[END_REF]. Gerbera is a crop moderately sensitive to salinity [START_REF] Baas | Yield and quality of carnation (Dianthus caryophyllus L.) and gerbera (Gerbera jamesonii L.) in a closed nutrient system as affected by sodium chloride[END_REF][START_REF] Sonneveld | Salt tolerance of flower crops grown in soilless culture[END_REF]. According to these authors, the maximum salinity (expressed as the EC of nutrient solution) without yield reduction in substrate-grown gerbera is 1.5-2.8 dS m -1 ; the flower production decreased by 10% for each unit increase of EC above the threshold. In our work, gerbera plants appeared much more sensitive to NaCl salinity, at least in spring, since an increase of 1.41 dS m -1 in average EC of the recirculating NS resulted in a reduction of flower production of about 19% (Table 2).

In spring, the use of SW also reduced significantly shoot dry weight and LAI as compared to FW (Table 2). The reduction of LAI was due to an inhibition of both leaf expansion and formation. In fact, at the end of the season the leaves of non-salinized and salinized plants were 26.5 ± 0.50 and 21.50 ± 0.60, respectively.

Negative effects of salinity on crop growth and/or fruit yield were alleviated in melon (An et al., 2002) and tomato [START_REF] Li | Effect of electrical conductivity and transpiration on production of greenhouse tomato (Lycopersicon esculentum L.)[END_REF] when the plants were grown under high relative humidity, which reduced E compared to standard conditions.

Leaf area model

Modelling E requires the determination of LAI, which can be achieved by direct (destructive or non-destructive) measurements or simulation models. In both greenhouse and field crops, LAI development is often modelled as a function of GDD using non-linear (e.g. exponential and sigmoid) equations since crop LAI tends to reach a plateau [START_REF] Thornley | Plant and Crop Modelling[END_REF]. In our study, LAI increased with time in spring (Fig. 2) whereas it remained fairly constant around 1.0 in autumn, when the formation of new leaves was balanced by the weekly removal of older leaves. Compared to the plants irrigated with SW, those grown with FW showed faster leaf development and reached a maximum LAI around 2.4 within eight weeks from the start of observations (Fig. 2). In the FW crop, the response of LAI to GDD was adequately described by an exponential function (Eq. ( 10); R 2 = 0.986; n = 11):

LAI = (1.043 -2.448) • exp -0.0066•GDD + 2.448 (10)
On the contrary, in salinized plants LAI never reached a plateau during the study period (Fig. 2). A linear model fitted well measured LAI in this culture (Eq. ( 11); R 2 = 0.938; n = 11):

LAI = 0.9354 + 0.0006 • GDD (11)
Transpiration model also required to estimate I c from LAI and k (Eq. ( 2)). The light extinction coefficient was determined when LAI was 1.03 ± 0.06 and 1.96 ± 0.08, with similar results. It was 0.60 ± 0.02 (n = 40), in agreement with [START_REF] Marfà | Water consumption of a closed soilless culture of gerbera: usefulness of model to estimate evapotranspiration[END_REF].

Crop water relations

The reliability of the electronic balance used for measuring E was assessed by comparing daily-cumulated E (E 24 h ;) of the six test-plants to the daily W of the whole growing unit (48 plants). A significant (R 2 = 0.885; n = 176) linear relationship was found between E 24 h and W with a slope close to 1 (0.986) and a negligible intercept (0.064 kg m -2 day -1 ).

Crop water uptake was not affected by NaCl salinity in autumn (Table 2); daily W was as high as 1.78 kg m -2 day -1 and averaged 0.55 kg m -2 day -1 . In spring, daily W was significantly higher when the plants were irrigated with FW (2.68 kg m -2 day -1 ) instead of SW (2.03 kg m -2 day -1 ); this resulted in large difference in seasonal W (222.4 versus 168.5 kg m -2 ).

In the autumn of 2004, the salinity of irrigation water did not influence E d , which ranged between 0.009 and 0.139 kg m -2 h -1 0 200 400 600 800 1000 0 1 2 3

Growing degree days (GDD) Leaf area index (LAI) Fig. 2. Relationships between leaf area index (LAI) and growing degree days (GDD) in greenhouse gerbera grown in semi-closed substrate culture in the spring of 2005. The plants were irrigated with fresh (FW; 1.0 mol m -3 NaCl) or saline (SW; 9.0 mol m -3 NaCl) water. Solid lines represent fits to the data (n = 3; ±SE) with a linear (SW, filled symbols) or non-linear (FW, empty symbols) function.

with an average of 0.050 kg m -2 h -1 (Table 2). On the contrary, in the following spring, the use of SW significantly reduced E d , which ranged between 0.020 and 0.354 kg m -2 h -1 in non-salinized plants (average was 0.203 kg m -2 h -1 ) and between 0.015 and 0.270 kg m -2 h -1 in salinized plant (average was 0.136 kg m -2 h -1 ; Table 2). Approximately, 75% of cumulative E d occurred between 10.00 a.m and 03.00 p.m. in autumn, and between 09.00 and 04.00 p.m. in spring (data not shown).

Night transpiration did not exceed 0.013 kg m -2 h -1 in autumn and 0.061 (FW) or 0.045 (SW) kg m -2 h -1 in spring and it accounted for about 12% and 8% of E 24 h in autumn and in spring, respectively, in agreement with previous findings in greenhouse cucumber grown in a Mediterranean area [START_REF] Medrano | Evaluation and modelling of greenhouse cucumber-crop transpiration under high and low radiation conditions[END_REF]. In contrast, E n contributed up to 36% of E 24 h in rose plants grown in rockwool during winter in a heated greenhouse (Baille et al., 1994b).

In the light period, T l was 0.2-1.5 • C lower than T a . In other greenhouse crops such as Ficus benjamina [START_REF] Bailey | Transpiration of Ficus benjamina: comparison of measurements with predictions of the Penman-Monteith model and a simplified version[END_REF], geranium [START_REF] Montero | Transpiration from geranium grown under high temperatures and low humidities in greenhouses[END_REF] and zucchini [START_REF] Rouphael | Modelling the transpiration of a greenhouse zucchini crop grown under a Mediterranean climate using the Penman-Monteith equation and its simplified version[END_REF]), the T l -T a difference was up to 5 • C.

Calculated r a , ranged from 80 and 198 s m -1 ; these values are among the typical values reported for standard greenhouse conditions (e.g. [START_REF] Stanghellini | Transpiration of greenhouse crops. An aid to climate management[END_REF]Baille et al., 1994b).

The analysis of daytime r l , as calculated by the inversion of the PM formula, did not disclose any important effect of NaCl salinity on stomatal behaviour, although on average r l was slightly lower in non-salinized plants than in salinized plants both in autumn (265.1 ± 17.8 s m -1 against 300.5 ± 18.4 s m -1 ) and in spring (439.9 ± 14.8 s m -1 against 475.4 ± 15.9 s m -1 ). This result was corroborated by the measurements with a leaf porometer; we never found significant differences in r l between the plants irrigated with FW and those irrigated with SW. The values of r l determined with a porometer ranged between 185 and 367 s m -1 .

In our work, minimum values of r l were higher than those reported for gerbera [START_REF] Issa | Seasonal and diurnal photosynthetic responses of two gerbera cultivars to different substrates and heating systems[END_REF] and other greenhouse crops (e.g. Baille et al., 1994b;[START_REF] Rouphael | Modelling the transpiration of a greenhouse zucchini crop grown under a Mediterranean climate using the Penman-Monteith equation and its simplified version[END_REF]; however, they were in the range determined by [START_REF] Tsirogiannis | Effect of irrigation scheduling on gerbera flower yield and quality[END_REF] in greenhouse gerbera grown in pumice.

The absence of a salinity effect on stomata was in contrast with the reduction of leaf growth observed in salinized plants in the spring of 2005 (Table 2 and Fig. 2). Leaf growth and stomata may show different sensitivity to the water availability in the growing medium [START_REF] Mohd | Leaf growth and stomatal sensitivity to ABA in droughted pepper plants[END_REF]. It has been reported that leaf growth was more sensitive to moderate salinity [START_REF] Plaut | Leaf development, transpiration and ion uptake and distribution in sugarcane cultivars grown under salinity[END_REF] or drought [START_REF] Saab | Non-hydraulic signals from maize roots in drying soil: inhibition of leaf elongation but not stomatal conductance[END_REF] than transpiration and stomatal conductance.

During daytime r l responded to changes in light conditions and tended to decrease with increasing I. However, the large day-today variability in stomata behaviour resulted in poor correlation between r l and climatic variables (data not shown). Mean hourly values of r l changed little in the central hours of the day and were consistently higher in spring than in autumn (Fig. 3,top). This difference was likely due to a reduction of r l induced by higher VPD in spring than in autumn (Figs. 1 and 3,bottom). Stomata are very sensitive to VPD and tend to close in dry atmosphere in order to reduce leaf water loss [START_REF] Bunce | Growth at elevated carbon dioxide concentration reduces hydraulic conductance in alfalfa and soybean[END_REF][START_REF] Kirkham | Elevated atmospheric carbon dioxide: transpiration and evapotranspiration[END_REF]. Saturation deficit higher than 1.5-2.0 kPa reduced E in tomato [START_REF] Boulard | Etude de différentes méthodes de refroidissement sur le climat et la transpiration de tomates de serre[END_REF] and in rose [START_REF] Baille | Microclimate and transpiration of greenhouse rose crops[END_REF].

Crop W and E d were also monitored for six weeks in the autumn of 2005, when indoor climate conditions were similar to those recorded in the autumn of 2004 (Table 1 and Fig. 1). In this season, the plants were irrigated with FW and half of them were defoliated in order to compare different LAI (1.95 ± 0.17 vs. 1.10 ± 0.10). Daily W and E d averaged, respectively, 1.22 ± 0.13 kg m -2 day -1 and 0.146 ± 0.068 kg m -2 h -1 in intact plants, and 0.79 ± 0.09 10 kg m -2 day -1 and 0.086 ± 0.038 kg m -2 h -1 in defoliated plants. 1)) and vapour pressure deficit (VPD) in greenhouse gerbera grown in substrate culture in the autumn of 2004 (filled symbols) and in the spring of 2005 (empty symbols). Each point is the mean (±SE) of 15-76 values.

PM model

The PM equation was run using a value of 0.10 m s -1 for u and a difference of 1.0 • C between T a and T l . For each day of the study period in the spring of 2005, LAI was interpolated from the measurements on the basis of GDD using Eq. ( 10) (FW) or (11) (SW). Instead, a constant LAI was used for autumn crops: 0.98 in 2004 and 1.95 or 1.10 in 2005 (see previous section).

The calibration dataset (n = 593), which included the measurements taken in the autumn of 2004 (n = 257) and in the spring of 2005 (n = 336), was used to develop empirical relations of r l against VPD, I, I c and T a . Several functions were tested, including the multiplicative models reported by [START_REF] Jarvis | Interpretation of variations in leaf water potential and stomatal conductance found in canopies in field[END_REF] and by Baille et al. (1994b). The latter authors modelled r l in a variety of greenhouse pot ornamentals as a function of I and/or VPD. In most cases, the models explained more than 50% of the variability of r l with the exception of poinsettia; R 2 was much lower (0.29) for this species.

Unfortunately, none of the tested equations acceptably described the relationship between r l and climatic variables (the values of R 2 were 0.30 or lower). Therefore, the PM model predicted E d using a constant value of r l . Other authors estimated daytime E in greenhouse crops with the assumption of a constant r l (200 s m -1 ; [START_REF] Aikman | Influence of radiation and humidity on transpiration -implications for calcium levels in tomato leaves[END_REF][START_REF] Chalabi | Simulation of the energy balance in a greenhouse[END_REF].

The PM model was validated using an independent dataset (n = 781), which included the data collected in the autumn of 2005. The validation was performed using separate values of r l for autumn (282 s m -1 ) and spring (458 s m -1 ), or their average (370 s m -1 ); these values were calculated using the calibration dataset.

The PM equation accurately predicted E d in both seasons, with the slopes of the regression equations about to 1, negligible intercepts and R 2 values close to 0.90 or higher (Table 3). Accurate

Table 3

Validation of the Penman-Monteith equation (Eq. ( 1) in the text) used to estimate the hourly rate of daytime transpiration (E d ) of greenhouse gerbera grown in semi-closed substrate culture in different seasons: the slope and the intercept of the linear regression between predicted and measured E d ; standard error of the estimates (SSE); coefficient of determination (R 2 ); mean absolute percentage error (MAPE); mean percentage error (PME).

Season

Slope Calibration of the regression models (Eqs. ( 9) and ( 12) in the text) of the hourly rate of daytime transpiration (E d ) of greenhouse gerbera grown in semi-closed substrate culture in different seasons: regression coefficients (A and B), coefficient of determination (R 2 ) and number of observations (n).

Intercept (kg m -2 h -1 ) R 2 SEE (kg m -2 h -1 )
Season estimates of E d were also obtained using the average r l (Table 3 and Fig. 4).

A (±SE) B (±SE) (kg m -2 h -1 kPa -1 ) R 2 n Eq. (

Regression models

Eq. ( 9) was initially parameterized separating, for each growing season, the FW culture from the SW culture. Water salinity influenced the coefficient A much less than the growing season, although this coefficient was higher for the FW culture than for the SW culture, both in autumn (0.639 ± 0.020 against 0.609 ± 0.027) and in spring (0.559 ± 0.019 against 0.495 ± 0.001). Both water salinity and growing season had no important effect on the coefficient B, which ranged from 0.019 to 0.024 kg m -2 h -1 kPa -1 (Table 4). 1) in the text) and assuming a constant value of leaf stomatal resistance (370 s m -1 ). Solid line represents the linear regression (the equation is reported inside the graph) between predicted and measured E d while dotted line is the 1:1 relationship. The slope and the intercept of the linear regression were not significantly different from 1 and 0, respectively.

When data collected in FW and SW crops were pooled in each season, the coefficients A and B were, respectively: 0.626 and 0.024 kg m -2 h -1 kPa -1 in autumn; 0.553 and 0.019 kg m -2 h -1 kPa -1 in spring (Table 4). Higher A in autumn is consistent with lower r l in this season compared to spring (Fig. 3, top). Using the validation datasets, we found a good agreement between predicted and measured E d (Table 5), although the models tended to overestimate E d (MPEs were negative) with MAPE ranging from 15.4% to 17.7%.

A joint regression analysis of data from different seasons produced the following results (Table 4): A was 0.547 and B was 0.019 kg m -2 h -1 kPa -1 . With these coefficients, Eq. ( 9) predicted accurately measured E d ; the slope was close to 1 (0.949) and the intercept (0.002 kg m -2 h -1 ) was negligible (Table 5 andFig A linear regression (forced through the origin) of E d against I c was also evaluated:

E d = A • I c (12)
The calibration yielded a slope of 0.847 in autumn and 0.770 in spring; the slope was 0.774 when data for autumn and spring were pooled (Table 4). Therefore, gerbera plants converted around 80% of the incident energy into latent heat in agreement with previous findings in greenhouse crops (e.g. Baille et al., 1994a;Carmassi et al., 2007a;[START_REF] Teitel | Wind driven ventilation of a monospan greenhouse with a rose crop and continuous screened side vents and its effect on flow patterns and microclimate[END_REF]. Eq. ( 12) predicted satisfactorily E d , although model accuracy was lower compared to the PM model and Eq. ( 9), as indicated by the differences in R 2 , SEE and MAPE (Tables 3 and5).

In substrate cultures of tomato in unheated greenhouse, [START_REF] Massa | Simulation of crop water and mineral relations in greenhouse soilless culture[END_REF] found that a linear regression with I c explained 81-93% of the variation in daily W, which was dominated by E (it corresponded to more than 93% of W). According to [START_REF] Stanghellini | Transpiration of greenhouse crops. An aid to climate management[END_REF], in most climates the E of greenhouse crops can be better estimated as a function of measured radiation than of VPD.

A simple model that predicts E as a function of radiation can be easily applied in low-technology greenhouses that may have only a simple solarimeter or gather meteorological data from local weather station. In modern greenhouses, indoor climate is automatically monitored and E models responding to changes of both radiation and air humidity can be easily implemented in algorithms for irrigation and climate control.

A linear regression was also fitted to E n using the whole calibration dataset (n = 338), with VPD ranging from approximately 0.1 to 1.0 kPa:

E n = B • LAI • VPD (13)
The calibration yielded a slope of 0.015 kg m -2 h -1 kPa -1 (R 2 = 0.876; n = 338). There was a good correspondence between predicted and measured E n (R 2 = 0.918; n = 569) with a slope close to 1 (0.929) and a negligible intercept (0.0005 kg m -2 h -1 ); SEE, MPE and MAPE were 0.002 kg m -2 h -1 , -0.1% and 13.9%, respectively

The same linear regression (with B = 0.026 kg m -2 h -1 kPa -1 ) accounted for 80% of measured E n in greenhouse cucumber [START_REF] Medrano | Evaluation and modelling of greenhouse cucumber-crop transpiration under high and low radiation conditions[END_REF].

Radiative and aerodynamic components of transpiration

The first term on the right-hand side of Eq. ( 1) is referred to as the "radiation term" while the second as the "aerodynamic term" [START_REF] Seginer | The Penman-Monteith evapotranspiration equation as an element in greenhouse ventilation design[END_REF]; they correspond to the coefficients A and B of Eq. ( 9) (Baille et al., 1994a;[START_REF] Seginer | The Penman-Monteith evapotranspiration equation as an element in greenhouse ventilation design[END_REF]. Baille et al. (1994a) reported that the contribution of the two PM terms was similar in some ornamental species (e.g. begonia, cyclamen and gloxinia) grown under greenhouse in a Mediterranean climate while the radiation term was the main component in other species (e.g. gardenia, impatiens, pelargonium and schefflera). In our work, the radiative component of gerbera E d (calculated using Eq. ( 9)) averaged 76% in autumn and 66% in spring.

From a practical point of view, the estimation of radiative and aerodynamic components can suggest the efficacy of climate control devices, such as shading net and fog system, for E reduction, which may be necessary during plant recovery from root disease or salinity stress, for instance. For crops with high values of A (like gerbera, for instance) shading screen will be much more effective in reducing E d than fog system.

According to [START_REF] Jones | Modelling water relations of horticultural crops[END_REF], the aerodynamic term may be not necessary to predict E in greenhouse crops, since greenhouses are generally scantily ventilated, unlike the open field, and thus 'decoupled' from the atmospheric air. In a 'decoupled' greenhouse, VPD is positively correlated to I, as it was found in our work, and there is large uncertainty of partitioning between the radiative and aerodynamic components of E. On the other hand, I and VPD could become uncorrelated under greenhouse conditions [START_REF] Bakker | Leaf conductance of four glasshouse vegetable crops as affected by air humidity[END_REF] due to strong climate conditioning (Baille et al., 1994a).

The values of the coefficients A and B determined for gerbera in our work were within those reported for other greenhouse crops in Mediterranean regions (Table 6). The pairs (A,B) reported in Table 6 and those determined for gerbera in our study using the complete calibration dataset (Table 4) are shown in Fig. 6; the pair with zero B (Eq. ( 12)) was also included. The divergence among the crops could be ascribed to differences in plant habit, stomatal resistance and growing conditions. In spite of scatter, there is an apparent negative correlation between A and B, with a significant R 2 (0.366). 2004); (7) zucchini: [START_REF] Rouphael | Modelling the transpiration of a greenhouse zucchini crop grown under a Mediterranean climate using the Penman-Monteith equation and its simplified version[END_REF].

Table 6

Values of coefficients A and B of Eq. ( 9) in the text for some greenhouse crops.

Crop

Growing conditions a A B (kg m -2 h -1 kPa b The original data were converted to B (kg m -2 h -1 kPa -1 ) of this paper.

The relationship between A and B and its significance for greenhouse ventilation design have been analyzed by [START_REF] Seginer | The Penman-Monteith evapotranspiration equation as an element in greenhouse ventilation design[END_REF]. According to this author, two reasons may account for negative correlation between A and B:

(i) a difference in greenhouse (reference) temperature. As increases with temperature, the first and the second term of Eq.

(1) are functions of temperature, if r c and r a do not change; however, A augments with temperature while B decreases when the temperature increases. (ii) The decoupling of greenhouse from the atmospheric air as a result of poor ventilation, as previously discussed.

Several authors calculated the Jarvis and McNaughton's (1986) decoupling coefficient ˝ (Eq. ( 8)) to analyze the influence of physical and physiological factors on canopy E both in natural vegetation (e.g. [START_REF] Magnani | Modelling the surface conductance of a broad-leaf canopy: effects of partial decoupling from the atmosphere[END_REF] and in crop plantations in open field or under cover (e.g. [START_REF] Dayan | Transpiration of roses in greenhouses[END_REF][START_REF] Nicolàs | Environmental and stomatal control of transpiration, canopy conductance and decoupling coefficient in young lemon trees under shading net[END_REF]. The coefficient ˝ describes the degree to which E is controlled by radiation rather than by stomata [START_REF] Jarvis | Stomatal control of transpiration: scaling up from leaf to region[END_REF][START_REF] Polhamus | What controls the error structure in evapotranspiration models?[END_REF]. It ranges from 0 (strong influence of stomata on E, because VPD at canopy surface is coupled to air VPD) to 1 (decoupled canopy; E is controlled by radiation and independent on stomata behaviour).

Under greenhouse, the degree of coupling between the crop and the ambient air depends on ventilation [START_REF] Boulard | Caracterisation et modélisation du climat des serres. Application à la climatisation estivale[END_REF]. Our experiments were conducted in a greenhouse that was poorly ventilated (discontinuous measurements of u never exceeded 0.2 m s -1 ) due to its urban location and, more notably, to the presence of insect screens and, in late spring and summer, shading net. The coefficient ˝ averaged 0.69 ± 0.11 in autumn and 0.65 ± 0.11 in spring. Gerbera vegetation is short and compact and this seemingly contributed to canopy decoupling [START_REF] Jones | Modelling water relations of horticultural crops[END_REF].

Therefore, in our experiment gerbera crop was poorly coupled to the ambient air and this explains why E d was accurately predicted either using the PM equation (Table 3) with the assumption of a constant r l (this assumption is also implicit in the regression models) or as a function of the sole radiation (Eq. ( 12)), although the accuracy of E d predictions increased when VPD was also considered (Eq. ( 9); Table 5).

Conclusions

In greenhouse gerbera grown in substrate in different seasons, moderate NaCl salinity of irrigation water reduced plant growth, flower production and E in spring while no significant effects on all measured quantities were observed in autumn.

NaCl salinity affected E through an inhibition of leaf area development and not through stomatal closure, as r l did not differ significantly in salinized and non-salinized plants both in autumn and in spring. This avoided the necessity of a different calibration of E models for the crop irrigated with FW or SW. However, it required the use of different sub-models of leaf area development depending on water salinity.

The PM model was run using a constant value of r l . Both the PM formula and the regression equations predicted satisfactorily E d in both seasons. Our findings are consistent with the concept of greenhouse crop decoupling from the atmosphere.

The models could be easily implemented for irrigation and climate control. All the equations require LAI, which can be estimated either from recurrent, non-destructive measurements of leaf dimensions or as a function of crop thermal time.

Fig. 1 .

 1 Fig. 1. Daily values of incident radiation and average air temperature and vapour pressure deficit (VPD) in the glasshouse during the experiments conducted with gerbera grown in semi-closed substrate culture in different seasons between 2004 and 2005. Data refer to three periods: (i) 22 September 2004 to 9 January 2005 (110 days); (ii) 11 April to 2 July 2005 (83 days); (iii) 10 October to 20 November 2005 (42 days). Arrows indicate when the greenhouse was shaded with plastic net during the spring of 2005.

Fig. 3 .

 3 Fig. 3. Mean values of leaf stomatal resistance (as calculated with the Penman-Monteith equation, Eq. (1)) and vapour pressure deficit (VPD) in greenhouse gerbera grown in substrate culture in the autumn of 2004 (filled symbols) and in the spring of 2005 (empty symbols). Each point is the mean (±SE) of 15-76 values.

Fig. 4 .

 4 Fig. 4. Relationship between predicted and measured values of daytime transpiration (E d ) in greenhouse gerbera grown in substrate culture in different seasons (autumn, filled symbols; spring, empty symbols). Transpiration was predicted using the Penman-Monteith equation (Eq. (1) in the text) and assuming a constant value of leaf stomatal resistance (370 s m -1 ). Solid line represents the linear regression (the equation is reported inside the graph) between predicted and measured E d while dotted line is the 1:1 relationship. The slope and the intercept of the linear regression were not significantly different from 1 and 0, respectively.

Fig. 5 .

 5 Fig. 5.Relationship between predicted and measured values of daytime transpiration (E d ) in greenhouse gerbera grown in substrate culture in different seasons (autumn, filled symbols; spring, empty symbols). Transpiration was predicted using an empirical function (Eq. (9) in the text) of Ed against intercepted radiation and vapour pressure deficit. Solid line represents the linear regression (the equation is reported inside the graph) between predicted and measured E d while dotted line is the 1:1 relationship. The intercept of the linear regression was not significantly different from 0.

Fig. 6 .

 6 Fig. 6. Relationship between the values of A and B coefficients of Eq. (9) in the text as computed for gerbera in this study or reported in the literature for other greenhouse crops. Solid line represents the linear regression (the equation is reported inside the graph). References: (1) cucumber: Medrano et al. (2005); (2) geranium: Montero et al. (2001); (3) gerbera: Marfà et al. (2000); (4) pot ornamentals: Baille et al. (1994a,b); (5) rose: Kittas et al. (1999) and Gonzalez-Real (1994); (6) tomato: Medrano et al. (2004); (7) zucchini:[START_REF] Rouphael | Modelling the transpiration of a greenhouse zucchini crop grown under a Mediterranean climate using the Penman-Monteith equation and its simplified version[END_REF].

Table 1

 1 Basic information on the experiments conducted for modelling the transpiration of greenhouse gerbera grown in semi-closed substrate culture in different seasons and irrigated with fresh (FW; 1.0 mol m -3 NaCl) or saline (SW; 9.0 mol m -3 NaCl) water. In autumn 2005, all gerbera plants were irrigated with FW.

	Season (start date)	Days of	Mean air	Daily solar	Mean VPD	EC oscillation (dS m -1 )
		observation	temperature	radiation	(kPa)
			( • C)	(MJ m -2 )		FW	SW
	Autumn 2004 (22 September 2004)	110	17.4	2.27	0.30	2.48-3.42	3.08-4.05
	Spring 2005 (11 April 2005)	83	22.6	9.87	1.02	1.97-3.03	2.78-4.21
	Autumn 2005 (10 October 2005)	42	16.6	3.97	0.34	2.18-3.02	-

• C

Table 4

 4

	MAPE (%)	MPE (%)	n

Table 5

 5 Validation of the regression models (Eqs. (9) and (12) in the text) of the hourly rate of daytime transpiration (E d ) of greenhouse gerbera grown in semi-closed substrate culture in different seasons: the slope and the intercept of the linear regression between predicted and measured E d ; standard error of the estimates (SSE); coefficient of determination (R 2 ); mean absolute percentage error (MAPE); mean percentage error (PME).

	Season	Slope	Intercept (kg m -2 h -1 )	R 2	SEE (kg m -2 h -1 )	MAPE (%)	MPE (%)	n
	Eq. (9)
	Autumn	0.950 ± 0.009	0.007 ± 0.001	0.960	0.012	17.7	-10.9	457
	Spring	0.945 ± 0.016	0.014 ± 0.003	0.910	0.026	14.6	-6.0	324
	Autumn + spring	0.949 ± 0.009	0.002 ± 0.001	0.939	0.021	15.4	1.1	781
	Eq. (12)
	Autumn	0.944 ± 0.015	0.007 ± 0.001	0.900	0.020	24.3	-10.8	457
	Spring	0.951 ± 0.027	0.003 ± 0.005	0.793	0.043	22.6	2.7	324
	Autumn + spring	0.939 ± 0.013	0.0031 ± 0.002	0.875	0.031	22.0	0.2	781

  Location, season, crop density and type of substrate.

				-1 )	Reference
	Begonia		0.20	0.026
	Cyclamen		0.32	0.019
	Gardenia		0.46	0.019
	Gardenia Hibiscus Impatiens	Angers, France; spring, summer or autumn; 10-20 plants m -2 ; peat-rockwool (pot plants).	0.53 0.37 0.67	0.013 0.037 0.013	Baille et al. (1994a)
	Pelargonium		0.61	0.017
	Poinsettia		0.12	0.017
	Schefflera		0.60	0.014
	Cucumber	Almeria, Spain; autumn (2 plants m -2 ) and spring (1.33 plants m -2 ); perlite	0.24-0.42	0.022-0.038	Medrano et al. (2005)
	Geranium	Barcelona, Spain; May-July; pot plants (unknown crop density and substrate)	0.56	0.012 b	Montero et al. (2001)
	Gerbera	Barcelona, Spain; July-March; 5.7 plants m -2 ; perlite	0.30	0.038 b	Marfà et al. (2000)
	Rose	Volos, Greece; winter; 6 plants m -2 ; perlite	0.24	0.017	Kittas et al. (1999)
	Rose	Valencia, Spain; summer; 7 plants m -2 ; rockwool	0.36	0.021	Gonzalez-Real (1994)
	Tomato	Almeria, Spain; autumn and spring; 7 plants m -2 ; perlite bag	0.58	0.025	Medrano et al. (2004)
	Zucchini	Viterbo, Italy; autumn and spring; 2.1 plants m -2 ; pumice	0.63	0.007 b	Rouphael and Colla (2004)

a

Acknowledgements

This work was supported by Ministry of University and Research (MIUR-PRIN 2004-2005) and by the European Commission, Directorate General for Research (7th Framework RTD Programme, Project EUPHOROS, 2008-2012). We are grateful to two anonymous referees for their constructive comments to the manuscript.


Arnaud A Bridier

M. D Maria P Del Pilar

Dominique D Sanchez-Vizuete

Stephane S Le Coq

Thierry T Aymerich

Jean-Yves Meylheuc

J.-Y Maillard

Vincent V Thomas

Florence F Dubois-Brissonnet

Romain Briandet
email: romain.briandet@jouy.inra.fr

Maria Del Pilar Sanchez-Vizuete

Dominique Le Coq

Ste ´phane Aymerich

Thierry Meylheuc

Jean-Yves Maillard

Biofilms of a Bacillus subtilis hospital isolate protect Staphylococcus aureus from biocide action

ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

In response to environmental conditions, bacteria have developed different strategies to adapt and survive. The formation of multicellular communities known as biofilms is one such strategy, which is associated with increased bacterial resistance to environmental stress accompanying antimicrobial treatments [START_REF] Hoiby | Antibiotic resistance of bacterial biofilms[END_REF][START_REF] Bridier | Resistance of bacterial biofilms to disinfectants: a review[END_REF]. It has indeed been shown that non-lethal concentrations of antibiotics or disinfectants can stimulate biofilm formation [START_REF] Hoffman | Aminoglycoside antibiotics induce bacterial biofilm formation[END_REF][START_REF] Shemesh | The Biocide Chlorine Dioxide Stimulates Biofilm Formation in Bacillus subtilis by Activation of the Histidine Kinase KinC[END_REF] which constitutes a defensive response to the toxic effects of the biocides. Mechanisms involved in the resistance of biofilms remain unclear but appear to result from multifactorial processes related to the architecture of the edifice and the phenotypic features of the cells. The presence of a protective extracellular matrix via the expression of specific genes in the biofilm, the metabolic state of cells due to microenvironmental conditions have all been identified as playing a role in biofilm resistance to antimicrobial agents [START_REF] Donlan | Biofilms: Survival mechanisms of clinically relevant microorganisms[END_REF]. In the clinical settings, biofilms promote infection through, for example, the persistence of bacteria on medical devices and thus can act as reservoir for pathogens [START_REF] Potera | Microbiology -Forging a link between biofilms and disease[END_REF][START_REF] Francolini | Prevention and control of biofilm-based medicaldevice-related infections[END_REF]. It has been estimated that 65% of nosocomial infections directly involve biofilms [START_REF] Costerton | Bacterial biofilms: A common cause of persistent infections[END_REF]. Of all medical devices used, flexible endoscopes are among the most frequently associated with outbreaks of infectious organisms [START_REF] Spach | Transmission of Infection by Gastrointestinal Endoscopy and Bronchoscopy[END_REF][START_REF] Kressel | Pseudo-outbreak of Mycobacterium chelonae and Methylobacterium mesophilicum caused by contamination of an automated endoscopy washer[END_REF][START_REF] Srinivasan | An outbreak of Pseudomonas aeruginosa infections associated with flexible bronchoscopes[END_REF][START_REF] Rutala | RE processing endoscopes: United States perspective[END_REF][START_REF] Diazgranados | Outbreak of Pseudomonas aeruginosa Infection Associated With Contamination of a Flexible Bronchoscope[END_REF]. Indeed, some studies have reported the presence of persistent bacteria on endoscopes despite cleaning and disinfection procedures [START_REF] Deva | Detection of persistent vegetative bacteria and amplified viral nucleic acid from in-use testing of gastrointestinal endoscopes[END_REF][START_REF] Machado | Microbiologic profile of flexible endoscope disinfection in two brazilian hospitals[END_REF]. Interestingly, a viable strain of B. subtilis was recently isolated from an endoscope washerdisinfector after high level disinfection with chlorine dioxide [START_REF] Martin | Resistance and cross-resistance to oxidising agents of bacterial isolates from endoscope washer disinfectors[END_REF]. The authors showed that this isolate had developed crossresistance against other oxidising agents using a standard suspension test. Recently, we showed that this stable isolate was able to produce a thick immersed biofilm with specific protruding structures [START_REF] Bridier | The Spatial Architecture of Bacillus subtilis Biofilms Deciphered Using a Surface-Associated Model and In Situ Imaging[END_REF]. In this work, we have now investigated the resistance of this strain in biofilm to peracetic acid (PAA), an oxidizing agent commonly used in formulations used for endoscope disinfection. In addition, we examined the ability of the ND medical strain to protect Staphylococcus aureus, a pathogen responsible of a large number of hospital acquired infections [START_REF] Perl | New approaches to reduce Staphylococcus aureus nosocomial infection rates: treating S. aureus nasal carriage[END_REF], from biocidal action in a mixed biofilm.

Materials and Methods

Bacterial Strains and Growth Conditions

The bacterial strains used in this study are listed in Table 1. The GFP-carrying Bacillus subtilis ND medical strain was obtained by transforming B. subtilis ND medical to spectinomycin resistance with chromosomal DNA of strain GM2812 [START_REF] Bridier | The Spatial Architecture of Bacillus subtilis Biofilms Deciphered Using a Surface-Associated Model and In Situ Imaging[END_REF], thus placing in the amyE locus the gfp (mut2) gene under the control of the IPTGregulated P hyperspank promoter. Transformation was performed according to standard procedures and the transformants were selected on Luria-Bertani (LB, Sigma, France) plates supplemented with spectinomycin at 100 mg/ml. Before each experiment, bacteria were subcultured twice in Tryptone Soya Broth (TSB, BioMe ´rieux, France). When necessary, IPTG at a final concentration of 200 mM was added to the medium to induce GFP production, and antibiotics at the following concentrations: spectinomycin, 100 mg/ml; erythromycin, 3 mg/ml.

Biofilms Architecture

Confocal Laser Scanning Microscopy (CLSM). Biofilms were formed in polystyrene 96-well microtiter plates with a mclearH base (Greiner Bio-one, France) enabling high-resolution fluorescence imaging as previously described [START_REF] Bridier | The biofilm architecture of sixty opportunistic pathogens deciphered using a high throughput CLSM method[END_REF]. For single species biofilms, 250 ml of an overnight culture in TSB adjusted to an OD 600nm of 0.02 were added to the wells of the microtiter plate. For mixed species biofilm, overnight cultures in TSB of S. aureus AH478 mCherry and the B. subtilis GFP strains were adjusted to an OD 600nm of 0.02 in TSB and mixed at a ratio of 1:2. The microtiter plate was then kept at 30uC for 90 min to enable bacteria to attach to the bottom of the wells. After this adhesion step, the wells were rinsed with TSB to eliminate non-adherent bacteria and then refilled with 250 ml sterile TSB. The microtiter plate was then incubated for 24 h at 30uC to allow biofilm development. After development, biofilms were rinsed with 150 mM NaCl and series of xy images with a z-step of 1 mm were then acquired to explore the three-dimensional structure of the biofilms. Both single and mixed biofilms were scanned using an excitation wavelength of 458 nm (argon laser, 25% intensity) and 543 nm (helium-neon laser, 50% intensity), with emission wavelengths collected from 480 to 530 nm and from 580 to 700 nm respectively for GFP and mCherry fluorescence. Threedimensional projections of biofilm structures were reconstructed using the Easy 3D function of the IMARIS 7.0 software (Bitplane, Switzerland) directly from xyz images series.

Scanning Electronic Microscopy (SEM). For SEM observations, B. subtilis biofilms were prepared by immersing coupons in the wells of a 24-well polystyrene plate containing bacterial suspensions adjusted to an OD 600nm of 0.02. After 90 min of adhesion, coupons were rinsed and wells were refilled with 1 ml of TSB. The plate was then incubated at 30uC for 24 h. After development, biofilms were rinsed with 150 mM NaCl and attached bacterial cells were fixed in a solution containing 2.5% glutaraldehyde, 0.1 M sodium cacodylate (pH 7.4), 0.075% ruthenium red and 0.015% Alcian blue for 20 h. Ruthenium red and Alcian blue were added to the fixing solution because it have been showed that their presence could promote the visualization of extrapolymeric substances such as bofilm matrix components [START_REF] Erlandsen | High-resolution visualization of the microbial glycocalyx with low-voltage scanning electron microscopy: Dependence on cationic dyes[END_REF][START_REF] Fassel | Bacterial biofilms: Strategies for preparing glycocalyx for electron microscopy[END_REF]. Samples were then washed three times for 10 min with a solution containing 0.1 M sodium cacodylate, 0.075% ruthenium red and 0.015% Alcian blue before being transferred into 50% ethanol. Samples were progressively dehydrated by passage through a graded series of ethanol solutions from 50% to 100%. Finally, the samples were critical point dehydrated (Emitech K850, UK) using carbon dioxide as the transition fluid and coated with gold-palladium in an automatic sputter coater (Polaron SC7640, UK). Scanning electron microscopy Quanta 650 FEG-SEM (FEI, Japan) was used to observe the samples.

Congo red indicator assay on macrocolonies. The morphology of macrocolonies formed by both B. subtilis strains and their Congo Red binding properties were tested using indicator agar plates. Experimentally, 5 ml of an overnight culture in TSB were inoculated on TS agar (1.5%) containing 40 mg/ml Congo Red (Sigma-Aldrich, France). Plates were then incubated for 72 h at 30uC. Determination of the sugar and protein contents of the biofilm matrix. The protein and sugar levels of the matrix of B. subtilis 168 and ND medical biofilms were determined after 24 h of development in TSB. Biofilms were rinsed in distilled water and recovered from the microtiter plate by scraping the bottom of the wells with tips and aspirating and expelling the suspension at least 10 times. The suspensions were then vortexed during 30 seconds before being centrifuged at 4000 g during 20 minutes. After, the supernatants were transferred in sterile tubes and vortexed 30 seconds before being keeped at 20uC until biochemical assays were performed. Protein contents were evaluated using the Bradford assay [START_REF] Bradford | Rapid and Sensitive Method for Quantitation of Microgram Quantities of Protein Utilizing Principle of Protein-Dye Binding[END_REF] with bovine serum albumin as the standard. Sugar levels were determined by using the phenol-sulfuric acid assay procedure [START_REF] Dubois | Colorimetric methods for determination of sugars and related substances[END_REF] with glucose as the standard. Each experiment was performed in triplicate on three independent biofilm extractions.

Biocide Treatments

Biocide testing. After development, biofilms in the microtiter plates were rinsed and the wells refilled with 100 ml of TSB. Then, 100 ml of peracetic acid (PAA) (32 wt. % in dilute acetic acid (Sigma-Aldrich, France)) at 7000 ppm were then added in the wells to obtain a final concentration of 3500 ppm. After 5 min of contact, biocide solutions were gently removed and wells were refilled with a quenching solution (3 g/L L-a-phosphatidyl cholin, 30 g/L Tween 80, 5 g/L sodium thiosulfate, 1 g/L L-histidine,

S. aureus AH478

Strain RN4220 with a plasmid harbouring a mCherry gene (eryR) [START_REF] Malone | Fluorescent reporters for Staphylococcus aureus[END_REF] a spec and ery stand for spectinomycin and erythromycin resistance markers respectively. doi:10.1371/journal.pone.0044506.t001

30 g/L saponine) and left for 5 min to stop biocide action. The bottom of the wells was then scraped with tips and the suspension aspirated and expelled many times to detach and recover survivor cells from biofilms. The suspensions were then serially diluted in 150 mM NaCl and plated on Tryptone Soya Agar (TSA, Biome ´rieux, France) before being incubated at 30uC for 24-48 h.

To determine the sensitivity of B. subtilis ND medical cells to PAA following disruption of the biofilm, biofilms were rinsed with TSB and cells were recovered by scraping the bottom of the wells with tips and aspirating and expelling many times the suspension. The recovered cells were mixed with 150 mM NaCl containing glass beads and suspension vortexed for 30 s to separate cells and extracellular matrix. The suspension was then washed after centrifugation (7000 g, 10 min, 20uC) and adjusted to 10 8 CFU/ ml in 150 mM NaCl. In parallel, planktonic bacteria were harvested from a 24 h culture in TSB at 30uC by centrifugation (7000 g, 10 min, 20uC) followed vortexing with glass beads (0.5 mm of diameter) for 30 s and then washed in 150 mM NaCl before also adjusting to 10 8 CFU/mL. Peracetic acid activity was then evaluated according to the standard European NF EN 1040 procedure [START_REF]Chemical disinfectants and antiseptics-basic bactericidal acitvity-test method and requirements (phase 1)[END_REF] at a final concentration of 5 ppm with the adjusted cell suspension. Survivors were counted after incubation by comparing the number of colonies with those obtained when biocide was replaced by distilled water. Each experiment was done in triplicate.

In parallel, the susceptibility to peracetic acid at 5 ppm of planktonic suspensions of B. subtilis 168, B. subtilis ND medical and S. aureus AH478 was evaluated. The resistance of S. aureus AH478 suspension in absence or presence of extracellular matrix extracted from B. subtilis 168 or ND medical biofilm was also determined. In this aim, biofilm matrix extracts were directly added to S. aureus AH478 suspension at a 1/10 (vol/vol) concentration before disinfection step according to the NF EN 1040 standard procedure. Finally, we determined the susceptibility of mixed suspensions of S. aureus with B. subtilis 168 or ND medical strain to evaluate to potential role of a soluble effector in the resistance of the pathogen in mixed communities. In this end, S. aureus AH478 and B. subtilis 168 or ND medical were grown together in TSB overnight before peracetic acid treatment at 5 ppm using NF EN 1040 standard procedure.

Real-time visualization of PAA activity in biofilms. Time lapse CLSM analysis of PAA action was performed in B. subtilis biofilms as previously described [START_REF] Bridier | Dynamics of the Action of Biocides in Pseudomonas aeruginosa Biofilms[END_REF]. This technique permits the direct visualization of cell inactivation patterns in biofilm structures during biocide action. The method is based on the monitoring of fluorescence loss caused by the leak of an unbound fluorophore outside the cells after disruption of the bacterial membrane by antimicrobial agents. Experimentally, 24 h biofilms in a microtiter plate were rinsed with TSB in order to eliminate planktonic cells. The wells were then refilled with 100 ml of TSB containing Chemchrome V6 (1:100 of commercial solution (AES Chemunex, France)). Chemchrome V6 is an esterasic marker which enter cells passively and is then cleaved by cytoplasmic esterases, leading to the intracellular release of fluorescent residues (green fluorescence). Microtiter plates were incubated in the dark at 20uC for 1 h in order to reach fluorescence equilibrium. Biofilms were then rinsed to eliminate excess Chemchrome V6 and refilled with 100 ml of TSB. The microtiter plate was then mounted on the motorized stage of a Leica TCS SP2 AOBS Confocal laser scanning microscope (LEICA Microsystems, France) at the MIMA2 microscopy platform (http://voxel.jouy. inra.fr/mima2). The CLSM control software was set to take a series of time-lapse xyzt scans (2566256 pixels) at intervals of 15 s at five different depths in the biofilm. Biofilms were scanned at 400 Hz using a 636 oil objective with a 1.4 numerical aperture with a 488 nm argon laser set at 10% of its maximal intensity. These settings, which were shown to avoid photobleaching of the sample by performing preliminary scans using distilled water instead of biocides, were used in all time-lapse experiments. Emitted V6 Chemchrome green fluorescence was recorded within the range 500-600 nm. After the starting of the xyzt scan series, 100 ml of PAA at 7000 ppm were gently added to the wells just after the completion of the first scan. Biofilms were then scanned every 15 s at five different depths over 10 min, and fluorescence loss within the structure was recorded. Three independent experiments were performed for each strain.

Quantification of green fluorescence intensity from the timelapse (xyzt) CLSM image series was performed using confocal software LCS Lite (Leica Microsystems, France). Intensity values were then normalized by dividing the fluorescence intensity recorded by the initial fluorescence intensity value at the same location. Fluorescence intensity curves shown are the mean of three experiments, each experiment constituting the average of five horizontal sections along the depth of the biofilm.

Application of bacterial destruction models on fluorescence intensity curves. GinaFiT, a freeware Add-inn for MicrosoftH Excel developed by Geeraerd et al. [START_REF] Geeraerd | GInaFiT, a freeware tool to assess non-log-linear microbial survivor curves[END_REF] was used to modelize inactivation kinetics. This tool enables testing of nine different types of microbial survival models, and the choice of the best fit depends on five statistical measures (i.e., sum of squared errors, mean sum of squared errors and its root, R 2 , and adjusted R 2 ). During this study, the ''log-linear + tail'' inactivation model was fitted on fluorescence intensity curves obtained from CLSM image series during biocide treatment. The inactivation rate k max (min 21 ) was extracted from the fitting.

Detection of spores. In order to check the presence of spores in the biofilm after 24 h of development, cells were recovered from the microtiter plates as described above and resuspended in 150 mM NaCl and boiled at 100uC for 10 min. Bacterial numbers (cfu/ml) were determined before and after the heat treatment.

Statistical Analysis

One-way ANOVA was performed using Statgraphics v6.0 software (Manugistics, Rockville, USA). Significance was defined as a P value associated with a Fisher test value lower than 0.05.

Results

Phenotypic Characterization of Biofilms Formed by ND medical and 168 Strains

Biofilms formed by a non-domesticated B. subtilis strain (ND medical ) recently isolated from an endoscope washer-disinfector and by the laboratory B. subtilis 168 strain were characterized. First, the architecture of biofilms formed by both B. subtilis GFP strains was observed after 24 h of development using CLSM as presented in Fig. 1A. The images correspond to three-dimensional reconstructions obtained from confocal stack images by the IMARIS software, including virtual shadow projections on the right. In accordance with previously published observations [START_REF] Bridier | The Spatial Architecture of Bacillus subtilis Biofilms Deciphered Using a Surface-Associated Model and In Situ Imaging[END_REF], we found that the non-domesticated B. subtilis ND medical strain clearly developed a thicker biofilm with protruding structures in comparison to strain 168 in these experimental conditions.

In order to visualize the extracellular material produced in biofilms of both B. subtilis 168 and the ND medical strains, SEM observations were also performed. In both cases, the extracellular material detected appeared to be composed of tangled thread-like strands forming a complex network. However, this was clearly much denser in the biofilm of the ND medical strain as shown in Fig. 1B. It should be noted here that SEM observations required several dehydration steps during sample preparation and therefore the electron micrographs can not be considered as faithful representations of fully hydrated biofilms. However, these results clearly indicated the presence of larger amount of extracellular substances in ND medical strain biofilm in comparison to strain 168.

Since Congo Red is known to bind extracellular substances, it has been widely used in previous works to compare the ability of different strains to produce extracellular components in numerous bacterial species including B. subtilis [START_REF] Friedman | Genes involved in matrix formation in Pseudomonas aeruginosa PA14 biofilms[END_REF][START_REF] Romling | Characterization of cellulose produced by Salmonella enterica serovar Typhimurium[END_REF][START_REF] Romero | Amyloid fibers provide structural integrity to Bacillus subtilis biofilms[END_REF]. Macrocolonies of both B. subtilis strains grown for 72 h on Congo Red indicator plates are presented in Fig. 1C. We observed that ND medical produced highly wrinkled macrocolonies as compared to strain 168. In addition, the ND medical strain stained red more intensively on Congo Red indicator plates, suggesting a higher amount of exopolymeric substances.

In line with this, biochemical quantification of the extracellular matrix confirmed that ND medical produced more abundantly extracellular components than strain 168. Indeed, sugar and protein contents of biofilm matrix reached respectively 33.561.4 and 26.761.0 mg/l for ND medical strain whereas these values attained only 13.160.8 and 8.760.3 mg/l for the strain 168.

B. subtilis ND medical Biofilms Exhibit a Marked Resistance to PAA

The resistance of biofilms formed by both B. subtilis strains exposed to 3500 ppm of PAA for 5 min was then investigated. These conditions represent the in-use PAA concentration and time of exposure commonly used in hospitals for the disinfection treatment of endoscopes. The results showed substantial resistance of the B. subtilis ND medical strain which exhibited only 3.8 log of reduction while no survivor were detected on plates for strain 168, corresponding to a reduction greater than 5.6 log (Table 2). Using thermic treatment, we confirmed that ND medical biofilm did not contain any spores at 24 h of development showing that the resistance observed was displayed by vegetative cells.

The resistance of the ND medical biofilm was investigated further by time-lapse CLSM microscopy allowing to visualize biocide action in real-time within the biofilm structures of both B. subtilis strains. Figure 2A presents the dynamics of fluorescence loss (membrane permeabilisation) within the biofilms during treatment with 500 ppm of PAA. This concentration was chosen in order to enable the visualization of biofilm damage in approximately 10 min. When biofilms were treated with distilled water as a control, the loss of fluorescence observed was less than 1% (n = 4) of the initial fluorescence after 10 min of treatment. The GinaFIT ''log linear + tail'' inactivation model [START_REF] Geeraerd | GInaFiT, a freeware tool to assess non-log-linear microbial survivor curves[END_REF] was applied to these experimental data to extract the inactivation rate k max and this revealed satisfactory adjustment (R 2 .0.982). The results confirmed the greater resistance of the biofilm for strain ND medical as compared to the laboratory strain 168. While PAA treatment resulted in an immediate and uniform loss of fluorescence of cells in the biofilm for strain 168, the loss of fluorescence in the ND medical biofilm was slow and heterogeneous during disinfection treatment. The extracted k max inactivation rates showed a large and significant difference between strain 168 and ND medical (inset in Fig. 2, P,0.05) with values of 14.0 and 0.4 respectively. Spatial patterns of fluorescence loss in biofilms treated with 500 ppm PAA are presented in Figure 2B. A homogeneous and sharp loss of fluorescence was seen in the whole biofilm structure of strain 168 following the application of biocide. Conversely, PAA application led to a non-homogenous loss of fluorescence within the biofilm structure of the ND medical strain. Indeed, with this strain, we observed that spreading of PAA was difficult in some areas and these remained fluorescent even after 10 min of treatment, illustrating the high resistance and associated low inactivation rate k max displayed by this strain. The resistance to PAA (5 ppm) of cells following removal and washing from the biofilm of strain ND medical was investigated and compared to the resistance of the corresponding planktonic cells. Reductions of 2.960.3 and 2.860.1 log (cfu/ml) were obtained for planktonic cells and detached cells respectively i.e. no significant difference (P.0.05). The disruption of the biofilm and at least partial elimination of extracellular substances thus led to the disappearance of the PAA resistance.

The ND medical Strain Provides Protection to S. aureus Against PAA in a Mixed Biofilm

The previous results showed that the ND medical biofilm exhibited marked resistance to PAA treatment and suggested that the extracellular matrix likely plays an important role in this resistance. We next investigated whether the ND medical biofilm can provide protection in a mixed biofilm to S. aureus, a pathogenic strain present in medical environments and often incriminated in nosocomial infections.

As shown on Fig. 3A,S. aureus alone produced flat and regular biofilm with a thickness of 20-30 mm. When this single species biofilm was exposed to 3500 ppm of PAA for 5 min, the small numbers of survivors on plates corresponded to a more than 7.3 log of reduction compared to distilled water control (Table 2). However, when growing in a mixed biofilm with B. subtilis ND medical , the same PAA treatment produced a 5.9 log reduction of S. aureus suggesting that pathogenic strain acquired benefit from strain association. Note that B. subtilis ND medical resistance to PAA was similar in both single and mixed biofilms with 3.8 and 3.4 log reduction respectively. In contrast, mixed biofilm composed of the lab strain B. subtilis 168 and S. aureus AH478 did not gain a higher resistance to PAA compared to the single species biofilms.

Confocal observations showed that, in the presence of S. aureus AH478, B. subtilis ND medical was able to develop three-dimensional structures similar to those observed in the single species biofilm of this strain (Fig. 3 B). The S. aureus cells largely covered the surface of the bottom of the wells not occupied by the B. subtilis strain although some cells were trapped in the protruding structures formed by the ND medical strain.

Interestingly, when B. subtilis ND medical biofilm matrix extract was added to a S. aureus AH478 suspension before peracetic treatment at 5 ppm, we enumerated survivors on Petri dishes with a reduction of 3.660.3 log whereas no survivor (log reduction .4.1 log) was observed when matrix extract from B. subtilis 168 biofilm was added to S. aureus AH478 suspension in the same conditions. When examining the resistance of mixed overnight culture of S. aureus AH478 with each B. subtilis strains to peracetic acid, we did not observed, in both cases, a significant better resistance of the pathogen compared to single S. aureus culture (P.0.05).

Together, these results underline that a direct interaction of ND medical biofilm matrix components with peracetic acid likely plays a key role in the better resistance of S. aureus AH478 observed in mixed biofilm.

Discussion

In a previous study, Martin et al. [START_REF] Martin | Resistance and cross-resistance to oxidising agents of bacterial isolates from endoscope washer disinfectors[END_REF] isolated a strain of B. subtilis (called ND medical in this study) from an endoscope washerdisinfector and showed that this strain developed a high resistance against various oxidising agents using a standard suspension test. On the basis of SEM observations, they suggested that this resistance could be due to a higher production of matrix in comparison with sensitive strains. Recently, we showed that this stable isolate produces a very thick biofilm with specific protruding and elevated structures in comparison to other B. subtilis strains [START_REF] Bridier | The Spatial Architecture of Bacillus subtilis Biofilms Deciphered Using a Surface-Associated Model and In Situ Imaging[END_REF], and this was confirmed in our present observations. As biofilm formation is frequently associated with increased resistance to sanitizing treatments and antibiotic therapies [START_REF] Pan | Resistance of Listeria monocytogenes biofilms to sanitizing agents in a simulated food processing environment[END_REF][START_REF] Cooper | Resistance of Legionella pneumophila serotype 1 biofilms to chlorine-based disinfection[END_REF][START_REF] Ito | Increased Antibiotic Resistance of Escherichia coli in Mature Biofilms[END_REF], the enhanced biofilm-forming ability of strain ND medical can thus represent a strategy to survive despite the regular exposure to biocide treatments. In line with this, Shemesh et al. [START_REF] Shemesh | The Biocide Chlorine Dioxide Stimulates Biofilm Formation in Bacillus subtilis by Activation of the Histidine Kinase KinC[END_REF] showed that sublethal doses of chlorine actually stimulated biofilm formation by B. subtilis, reflecting an apparent defensive response against biocide action. In addition, it has been shown in P. aeruginosa that hyper-biofilm forming variants appear due to self-generated diversity occuring in the biofilm, and this was correlated with higher resistance of the whole community to hydrogen peroxide [START_REF] Boles | Self-generated diversity produces ''insurance effects'' in biofilm communities[END_REF]. Our present results showed a very high resistance of the ND medical biofilm to PAA, an oxidizing agent commonly used in formulations used in endoscope disinfection; highlighting that biofilm formation could indeed enable this strain to persist despite drastic disinfection treatments applied during endoscope decontamination. Some evidence appears to suggest that this high resistance could be mainly related to an increased production of extracellular matrix in agreement with the previous observations made by Martin et al. [16] with planktonic cells. First, the disruption of the three-dimensional biofilm structure and washing of cells led to the restoration of a PAA sensitivity similar to that observed for planktonic cells. In addition, SEM observations and Congo red assays showed that the ND medical strain produced a denser and more abundant extracellular substances when compared with strain 168, which was much more sensitive to PAA. Finally, biochemical assay showed that sugars and proteins contents in ND medical biofilm were respectively 2.6 and 3.1 times higher than in the biofilm formed by the strain 168. These results highlight the primordial role of the three-dimensional structure of the biofilm of ND medical strain and the abundant matrix that could play a protective role through the interaction with and the quenching of PAA reducing thus its penetration into the biofilm. Previous studies reported that penetration limitations encountered by chlorine, another oxidising agent, in biofilms of different species can explain at least partly the reduced activity of this molecule probably due to interactions with biofilm constituents [START_REF] Jang | Measurement of chlorine dioxide penetration in dairy process pipe biofilms during disinfection[END_REF][START_REF] Debeer | Direct Measurement of Chlorine Penetration into Biofilms during Disinfection[END_REF][START_REF] Grobe | Role of dose concentration in biocide efficacy against Pseudomonas aeruginosa biofilms[END_REF]. Kinetic profiles and spatial patterns of fluorescence loss (cell membrane permeabilization) obtained using CLSM time lapse visualization of PAA action in the ND medical biofilm (Fig. 2) were consistent with these observations. Indeed, the progressive action of PAA in the heterogeneous structure of biofilm, with cells in some internal areas remaining fluorescent even after 10 min of treatment illustrate the limited action of the biocide in these areas. In line with these observations, we can hypothesize that the presence of dense matrix domains in the ND medical biofilm may constitute the principal mechanism involved in resistance to PAA. Whether this phenotype is related to one or several matrix components needs to be addressed. In particular, the involvement of molecular constituents already known to participate to the matrix composition of B. subtilis such as epsA-O operon products [START_REF] Branda | Genes involved in formation of structured multicellular communities by Bacillus subtilis[END_REF][START_REF] Branda | Fruiting body formation by Bacillus subtilis[END_REF] or TasA amyloid fibers [START_REF] Romero | Amyloid fibers provide structural integrity to Bacillus subtilis biofilms[END_REF][START_REF] Branda | A major protein component of the Bacillus subtilis biofilm matrix[END_REF] for the most clearly identified, should be investigated. The nucleotide sequences of the epsA-O and yqxM/sipW/tasA operons, including their promoter regions, were identical in both the ND medical and 168 strains (data not shown). In addition, construction of transcriptional fusion genes with a fluorescent reporter associated with flow-cytometry showed no significant difference between expression of the epsA-O operon in NDmedical and 168 strains, whereas expression of the yqxM/sipW/tasA operon was significantly higher in biofilms of the reference strain as compared to the NDmedical strain (P,0.05, data not shown). Taken together, these data indicated that the resistance observed of the strain ND medical was likely not due to modification of any of these major elements involved in the B. subtilis matrix composition, but rather to different genes that remain to be identified.

We also investigated whether S. aureus can be protected from disinfection in a mixed biofilm with B. subtilis ND medical strain. S. aureus is a bacterial pathogen commonly found in hospitals and responsible for a large number of infections [START_REF] Perl | New approaches to reduce Staphylococcus aureus nosocomial infection rates: treating S. aureus nasal carriage[END_REF][START_REF] Gardam | Is methicillin-resistant Staphylococcus aureus an emerging community pathogen? A review of the litterature[END_REF], and numerous studies have reported the presence of S. aureus on endoscopes even after disinfection procedures [START_REF] Machado | Microbiologic profile of flexible endoscope disinfection in two brazilian hospitals[END_REF][START_REF] Lee | Risk of contamination of sterile biopsy forceps in disinfected endoscopes[END_REF]. Our results demonstrated that more than 7.3 log of reduction (no survivor enumerated) were obtained for S. aureus single species biofilm after PAA treatment at 3500 ppm whereas we found only 5.9 log of reduction when growing in mixed biofilm with ND medical strain (Table 2). These results showed a protective effect of the presence of B. subtilis ND medical strain to S. aureus against PAA activity. Confocal images revealed that some S. aureus cells were entrapped in the protruding structures formed by the ND medical strain and thus probably benefited from the protective matrix of the B. subtilis strain. Supporting this hypothesis,addition of B. subtilis ND medical biofilm matrix extract to a S. aureus AH478 planktonic suspension led to a better resistance of the pathogen to peracetic acid. Moreover, since the concomitant growth of S. aureus with the ND medical strain in suspension had no effect on the resistance of S. aureus, it is likely that the higher survival of S. aureus in mixed biofilm was mainly due to the quenching of the oxidizing agent by the abundant extracellular matrix produced by the B. subtilis ND medical strain, rather than a soluble effector which could trigger the pathogen resistance. Different works already reported that species associations in mixed biofilms can result in a higher resistance to disinfection compared to single species biofilms [START_REF] Burmolle | Enhanced biofilm formation and increased resistance to antimicrobial agents and bacterial invasion are caused by synergistic interactions in multispecies biofilms[END_REF][START_REF] Kara | Differences between single-and dualspecies biofilms of Streptococcus mutans and Veillonella parvula in growth, acidogenicity and susceptibility to chlorhexidine[END_REF][START_REF] Simoes | Influence of the Diversity of Bacterial Isolates from Drinking Water on Resistance of Biofilms to Disinfection[END_REF][START_REF] Simoes | Species association increases biofilm resistance to chemical and mechanical treatments[END_REF][START_REF] Van Der Veen | Mixed species biofilms of Listeria monocytogenes and Lactobacillus plantarum show enhanced resistance to benzalkonium chloride and peracetic acid[END_REF] and that some species can protect another throughout interspecies spatial associations. Leriche et al. [START_REF] Leriche | Ecology of mixed biofilms subjected daily to a chlorinated alkaline solution: spatial distribution of bacterial species suggests a protective effect of one species to another[END_REF] reported for instance that Staphylococcus sciuri was protected in a mixed biofilm against a chlorinated solution by microcolonies formed by Kocuria sp., a more resistant strain. As it is clear that microbial communities present in medical or industrial areas are complex multispecies associations rather than controlled single species model, these findings highlight the importance to challenge biocides on representative multispecies biofilm models of the environment considered. In this study, peracetic acid alone was tested but it should be highlighted that further studies are required to understand the impact on PAA-containing formulations. Product formulations can vary considerably on their activity against biofilms due to presence of other chemicals, such as chelating agents and detergents. These can help detach and disaggregate the biofilms, thus facilitating biocidal activity.

In conclusion, this work points out that the selection pressure maintained in healthcare environments by regular disinfection treatments can lead to the emergence of strains with hyperresistance phenotypes. This is related to the great ability of bacteria to adapt to their environments by developing efficient survival strategies such as biofilm formation. Particular attention should thus be paid to the choice of strains which are representative of the reality of medical areas in disinfectant testing. In addition, the necessity to consider the resident microbial ecosystem (including non-pathogenic but resistant strains as B. subtilis ND medical ) instead of pathogen alone is emphasized since the persistence of a strain can be related not directly to its intrinsic resistance but also to the interactions with other species present in the environment. Future works will focus on the understanding of the adaptation mechanisms leading to an increased resistance of bacteria to biocides in these environments.

Figure 1 .

 1 Figure 1. Architecture of B. subtilis communities. (A) Three-dimensional projection of B. subtilis 168 GFP and ND medical GFP biofilms obtained from xyz confocal images series using IMARIS software. Images present an aerial view of biofilm structure with the virtual shadow projection on the right. Scale bar correspond to 50 mm. (B) SEM images of 24 h-biofilms. (C) Dye binding properties of B. subtilis macrocolonies grown for 72 h on Congo red indicator plates. doi:10.1371/journal.pone.0044506.g001

Figure 2 .

 2 Figure 2. Real-time visualization of PAA (0.05%) activity in B. subtilis biofilms. (A) Quantification of Chemchrome V6 fluorescence intensity in B. subtilis 168 (white squares) and ND medical (black squares) biofilms during PAA treatment at 500 ppm. Values shown corresponds to the average of the fluorescence at five depths with standard deviation in the biofilm for a representative experiment. Inactivation rate k max was obtained after fitting GinaFIT ''log linear + tail'' inactivation model on experimental data. The means of three experiments 6 standard deviation are presented in the inset. (B) Visualization of Chemchrome V6 fluorescence loss (membrane permeabilisation) in B. subtilis 168 and ND medical biofilms at 0. 15 and 30 secondes and 0. 5 and 10 minutes respectively during PAA treatment (0.05%). Each image corresponds to the superimposition of a green fluorescence image of a representative experiment on a greyscale image of initial fluorescence at the same location. Scale bars correspond to 20 mm. doi:10.1371/journal.pone.0044506.g002

Figure 3 .

 3 Figure 3. Architecture of S. aureus AH478 mCherry biofilm and B. subtilis ND medical GFP/S.aureus AH478 mCherry mixed biofilm. (A) 3D reconstruction of S.aureus AH478 mCherry biofilms.(B) 3D reconstruction and section at higher magnification of mixed species biofilm of B. subtilis ND medical GFP (green)/S.aureus AH478 mCherry (red). Scale bars correspond to 20 mm. doi:10.1371/journal.pone.0044506.g003

Table 1 .

 1 Strains used in this study.

	Strain	Relevant genotype or description a	Reference or construction
	B. subtilis 168	trpC2	Bacillus Genetic Stock Center
	B. subtilis 168 GFP	amyE::Phyperspank-gfp (specR)	[17]
	B. subtilis ND medical	Freshly isolated from endoscope washer-disinfectors	[16]
	B. subtilis ND medical GFP	amyE::Phyperspank-gfp (specR)	B. subtilis GM2812 [17] ND medical

Table 2 .

 2 Bactericidal activity of water and 0.35% PAA on single and mixed species biofilms after 5 min of treatment.

			log (CFU/well)
		Strain	Water	PAA (0.35%)
	Single species	B. subtilis 168	7.660.2	-
	biofilm
		B. subtilis	7.760.1	3.960.6
		NDmedical
		S.aureus AH478	9.360.1	-
	Mixed species	B. subtilis 168	7.560.5	-
	biofilm
		S.aureus RN4220 8.260.4	-
		B. subtilis	7.360.3	3.960.3
		NDmedical
		S.aureus RN4220 8.460.1	2.660.5

Data shown are mean of three experiments 6 standard deviation. Samples from which no survivor were recovered are represented by

[START_REF] Bridier | Resistance of bacterial biofilms to disinfectants: a review[END_REF]

. Minimum detection of 2 logs CFU/well. doi:10.1371/journal.pone.0044506.t002

PLOS ONE | www.plosone.org

September 2012 | Volume 7 | Issue 9 | e44506

Acknowledgments

We would like to thank Dr C.L. Malone for S. aureus AH478 mCherry strain. Barry Holland is warmly acknowledged for the English revision of the text.

This project was funded by the Medicen, Ile-de-France, competitiveness cluster and the National Institute for Agronomic Research. Financial support of the confopcal microscope was provided by the the Essonne department. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Author Contributions

Conceived and designed the experiments: AB FDB VT RB. Performed the experiments: AB DLC TM MPSV RB. Analyzed the data: AB RB. Contributed reagents/materials/analysis tools: AB SA DL VT JYM RB. Wrote the paper: AB RB.