Night-time transpiration in barley (Hordeum vulgare) facilitates respiratory carbon dioxide release and is regulated during salt stress

Night-time transpiration in barley (Hordeum vulgare) facilitates respiratory carbon dioxide... Abstract Background and Aims Night-time transpiration accounts for a considerable amount of water loss in crop plants. Despite this, there remain many questions concerning night-time transpiration – its biological function, regulation and response to stresses such as salinity. The aim of the present study was to address these questions on 14- to 18-d-old, hydroponically grown barley plants. Methods Plants were either stressed for the last 4–7 d prior to, and during subsequent continuous (24 h), diurnal gravimetric transpiration analyses; or subjected to salt stress just before analyses; or stressed for 4–7 d and then transferred to control medium before analyses. The idea behind this experimental setup was to distinguish between a longer- (cuticle, stomata) and shorter-term (stomata) response of transpiration to treatments. Cuticular conductance was assessed through residual transpiration measurements in detached leaves. Cuticle wax load and dark respiration rate of leaves were determined. Leaf conductance to CO2 was calculated. Key Results Night-time and daytime transpiration rates were highly, and positively, correlated with each other, across all treatments. Night-time transpiration rates accounted for 9–17 % of daytime rates (average: 13.8 %). Despite minor changes in the ratio of night- to daytime transpiration rates, the contribution of cuticular and stomatal conductance to leaf (epidermal) conductance to water vapour differed considerably between treatments. Salt stress did not affect cuticle wax load. The conductance for CO2 of the cuticle was insufficient to support rates of dark respiratory CO2 release. Conclusions The main biological function of night-time transpiration is the release of respiratory CO2 from leaves. Night-time transpiration is regulated in the short and long term, also under salt stress. Stomata play a key role in this process. We propose to refer, in analogy to water use efficiency (WUE) during the day, to a CO2 release efficiency (‘CORE’) during the night. Barley (Hordeum vulgare L.), carbon dioxide, cuticular permeance, night-time transpiration, residual transpiration, respiration, salt stress, stomata INTRODUCTION Night-time transpirational water loss can account for a considerable portion of daily water use of plants (Caird et al., 2007; Yoo et al., 2009; Resco de Dios et al., 2015). Rates of night-time water loss amount typically to 5–15 % of rates of daytime water loss across species, yet can exceed 50 % depending on genotype and environmental conditions (Rogiers and Clarke, 2013; Schoppach et al., 2014; Coupel-Ledru et al., 2016; for a review, see Caird et al., 2007). Strong correlations were found for the vapour-pressure deficit (VPD) sensitivity of transpiration under day- and night-time conditions, and altering VPD only during the night increased specifically night-time transpiration rates (expressed as percentage of day rates), without an effect on daytime rates (where VPD was not changed; Schoppach et al., 2014). These data suggest that the rate of night-time transpiration can be regulated. It is not clear whether night-time transpiration has any benefits to plants, and any biological function at all. For example, night-time transpiration may simply arise as an inevitable consequence of some intrinsic cuticle permeability to water vapour. Night-time transpiration may also permit a hydraulic lift of nutrients to shoot tissue to support growth during the dark period (for a review, see Caird et al., 2007). Yet, it is also possible that night-time transpiration facilitates the passage at sufficiently high rates of gases other than water vapour, in particular O2 (in) and CO2 (out of leaf) during dark respiration. Knowing the structural means and their conducting properties through which water is lost from shoot surfaces into the atmosphere during the night will help to address these questions. Prime candidates of such structural means are stomata, which may not be entirely closed during the night, or the cuticle, which has some intrinsic water permeability (Caird et al., 2007; Rogiers & Clarke, 2013; Coupel-Ledru et al., 2016; Claverie et al., 2016). Reports in the literature support the role of either candidate, and this role may be species- and environment-dependent (e.g. Rogiers & Clarke, 2013; Resco de Dios et al., 2015; Coupel-Ledru et al., 2016; Claverie et al., 2016; Hasanuzzaman et al., 2017). One inherent difference between stomata and cuticle is, based on our current knowledge, that the hydraulic properties of stomata but not cuticle can be regulated in the short term, say within hours to 1 d, although leaf turgor may impact on cuticle conductance (Boyer, 2015). Treatments such as salt stress, which can affect daytime transpirational water loss and stomatal conductance significantly, should have different effects on the relationship between day- and night-time transpiration depending on the exposure time of plants to these stresses. For example, (1) it is possible that longer-term salt stress reduces the water permeability (permeance; Richardson et al., 2007) of the cuticle, and that most of the water exits leaves during the night through the cuticle. If so, plants which are exposed to salt stress for several days should show a lower rate of night-time (cuticle) compared with daytime (cuticle, stomata) transpirational water loss than plants which are exposed to salt stress just prior to transpiration analyses. This is because there would be too little time to reduce the water permeability of cuticle in these latter plants. Similarly, (2) the possibility exists that cuticle hydraulic properties are not affected by salt stress yet dominate the night-time transpiration response. In this case, one would predict that the rate of night-time water loss increases relative to that of daytime water loss in plants, because any partial closure of stomata in response to sudden exposure to salt stress would only affect daytime transpiration. (3) Furthermore, by measuring rates of dark respiratory release of CO2 and leaf conductance to CO2, it is possible, with the aid of literature data (Boyer et al., 1997; Boyer, 2015), to calculate a cuticle conductance to CO2. This in turn makes it possible to test whether respiratory CO2 could be released entirely through the cuticle or requires stomata to be open during the night. To test these possibilities, we exposed hydroponically grown barley plants to various concentrations of NaCl (50, 100, 150 mm) in the nutrient solution and also varied the duration and sequence of treatments. Transpirational water loss rates were recorded continuously and determined gravimetrically (balance) during a 24-h period on intact plants. Plant transpiration rates were related to shoot surface area, and the resulting values were used to calculate leaf (epidermal) conductance, based on water vapour concentrations inside and outside the leaf, at the given temperature and relative humidity (Noble, 1991) during growth of plants. To assess the contribution of stomata and cuticle conductance to leaf conductance of water vapour, cuticular (minimum) conductance (permeance; for terminology, see Schuster et al., 2016) was determined by measuring residual transpiration of detached shoots (e.g. Svenningsson, 1988; Kerstiens, 1996). To obtain information about the mechanisms underlying any changes in cuticular and leaf conductance in response to salt stress, cuticle wax load (GC-MS) and stomatal density (leaf replica technique) were analysed. Rates of dark respiration and leaf conductance to CO2 were measured using a portable photosynthesis measuring unit (Li-Cor 6400, Lincoln, NE, USA). MATERIALS AND METHODS Plant material and growth conditions Barley (Hordeum vulgare L. ‘Quench’) plants were grown on modified half-strength Hoagland solution in a growth chamber (Microclima, MC1000HE, CEC Technology, Glasgow, UK) as described previously (Knipfer and Fricke, 2011). The root medium was aerated, and plants grew at a day/night length of 16/8 h and temperature of 21/15 °C. Relative humidity was 75 % and photosynthetically active radiation at plant level was 300–350 μmol m−2 s−1. VPD was 0.427 kPa during the night and 0.622 kPa during the day. All plants were germinated for 7 d, and then put initially (d7) on control nutrient solution, containing also 1 mm NaCl. Plants were analysed when they were 14–18 d old. At that developmental stage, leaf 2 was the main photosynthesizing and transpiring leaf, leaf 3 was expanding and leaf 4 had not yet emerged. Plants were subjected to a range of salt (NaCl) concentrations (50, 100, 150 mm NaCl final concentration in nutrient medium) and exposure times to salt (Fig. 1). Plants were either transferred to medium containing high NaCl on d10, and then kept on this medium for the last 4–7 d prior to, and during subsequent continuous 24-h diurnal transpiration analyses (‘normal-stress’); or kept initially on control nutrient solution, and subjected to salt stress just before the start of transpiration analyses (‘up-stress’); or stressed for 4–7 d prior to transpiration analyses, as done for normal-stressed plants, and then transferred to control medium just before transpiration analyses began (‘down-stress’). All treatments which were analysed within each type of experimental setup (either normal, up- or down-stress) were derived from the same batch of plants. Fig. 1. View largeDownload slide Schematic diagram summarizing the experimental setup of salt stress treatments (50, 100, 150 mm) and the type of analyses carried out for each treatment. CTRL, control; soln, solution; min, minutes. Fig. 1. View largeDownload slide Schematic diagram summarizing the experimental setup of salt stress treatments (50, 100, 150 mm) and the type of analyses carried out for each treatment. CTRL, control; soln, solution; min, minutes. The water potential (ψ) of media was determined with a VAPRO (Wescor Inc., South Logan, UT, USA) osmometer for four to five replicate samples and was found to average −0.036 MPa for control nutrient solution and −0.312, −0.570 and −0.780 MPa for nutrient solution containing 50, 100 and 150 mm NaCl, respectively. Transpiration measurements and leaf conductance Transpirational water loss of plants growing in the growth chamber was determined gravimetrically (Knipfer and Fricke, 2011) using balances (Model CP323P, Sartorius, Göttingen, Germany; and Model SL500, Scientific and Chemical Supplies Ltd, Bilston, UK). Changes in weight were recorded every 1–2 min using computer software (sartoCollect 1.0; Sartorius; and SCOUT Pro USB interface kit with SPDC software, Ohaus Corp., Pine Brook, NJ, USA).Transpiration analyses started 8 h into the photoperiod and lasted for 24 h. The first light period lasted from 0 to 8 h, the dark period lasted from 8 to 16 h, and the second, next-day light period lasted from 16 to 24 h. The average rate of transpirational water loss was calculated for each of the three periods, not including the first and last hour of each period, and at least including four continuous hours of measurement with a steady rate of water loss. This was done to avoid effects of plant transfer (start of experiment) or transient effects of day/night/day changes including changes in VPD on transpiration rates and also effects of changing air pressure (day/night) in the growth chamber which impacted on the balance output during transitional (day to night, night to day) periods. The values for the first and second light period were used to calculate an average light-period transpiration value for a particular plant. Each plant was contained within a 250-mL Erlenmeyer flask, which was wrapped in aluminium foil during analyses, and supported through a foam piece to hold the plant in the flask. Bubbling or not bubbling the nutrient solution during transpiration measurements did not affect the value of transpiration, yet bubbling increased the amount and error of background water loss significantly (not shown). This was probably due to variable amounts of water vapour escaping between the foam piece, which supported the plant, and the Erlenmeyer flask which contained the nutrient solution. Having a low and steady background water loss was particularly important for the 150 mm NaCl treatment of the normal-stress experiment, as this treatment showed very low night-time water loss rates. Background water loss was determined by having an identical setup as for plant analyses, except that the plant was missing (only Erlenmeyer flask, nutrient solution and foam piece). The background water loss was recorded over a 24-h day/night/day period as described above, and the average day- and night-time background water loss rate was determined using 4–8 replicates in each experiment. To calculate leaf conductance, transpirational water loss rates were first related to shoot surface area and then divided by the difference in water vapour concentration between the inside and outside of a leaf, as this represents the driving force for water vapour loss from leaves. Using values given in Noble (1991) for 100 % relative humidity (RH; approaching conditions inside a leaf, also for NaCl-stressed plants) and 75 % RH (ambient air) at 21 °C (day) and 15 °C (night) and neglecting any possible differences in temperature between leaf and air and effects of unstirred (boundary) layers, water vapour concentration differences amounted to 4.59 g m−3 during the day and 3.21 g m−3 during the night. Cuticular water loss from detached leaves: residual transpiration Cuticular water loss was determined by measuring residual transpiration (Kerstiens, 1996) using detached leaves (compare, e.g. Larsson and Svenningsson, 1986; Svenningsson, 1988). Plants were grown as detailed for the normal-stress experiments, and the first, second and third leaf was removed from the shoot of a plant when plants were 16 d old. All three leaves were weighed (initial f. wt) and then taped at their open end with a small piece of masking tape, so that all three leaves were aligned parallel next to each other. The loose end of the masking tape was clamped with a paper clip, and the clip was fixed to a hook on a horizontally mounted bar, with leaves being suspended in the air (dim light with photosynthetically active radiation of <5 μmol m−2 s−1; 41.4 % RH, 21 °C; measured close to leaf level throughout the experiment). The weight of leaf setup (paper clip not included) was recorded at time zero, 30 min, 60 min and then at hourly intervals up to 6 h. At the end of experiment, leaf surface area was determined. The rate of water loss from leaves was calculated for each measurement period (0–0.5, 0.5–1, 1–2, 2–3, 3–4, 4–5 and 5–6 h). The rate of residual transpiration, being dominated by cuticular water loss (‘minimum cuticular conductance’, Schuster et al., 2016), was calculated from the final part of the timecourse (last three measurment periods), by which time stomatal water loss should have contributed negligibly to leaf water loss (Larsson and Svenningsson, 1986; Svenningsson, 1988). This residual water loss rate was related to leaf surface area and divided by the difference in water vapour concentration between the inside and outside of a leaf to calculate residual (miniumum) leaf conductance (approximating cuticle permeance) (Schuster et al., 2016). The RH inside leaves will have been close to 100 % (>99 %), even in NaCl-stressed plants, and this led [21 °C; see appendix 1 in Noblel (1991)] to a water vapour concentration of 18.35 g m−3 inside leaves; the calculated water vapour concentration in the ambient air (41.4 % RH) was 7.60 g m−3, and the difference in water vapour concentration between the two locations was 10.75 g m−3. Four replicate plants were analysed for each treatment, and all treatments were analysed in parallel, at the same time. The identical leaves studied for residual transpiration analyses were subsequently used for extraction and quantification of cuticular wax components. Surface area Following transpiration analyses, the shoot of each plant was scanned (Canon 9900F model) for subsequent determination of shoot surface area. The root system was used for determination of root surface area. Scanned images were analysed with the freely available software ImageJ (www.imagej.nih.gov/ij/). To increase the contrast of root images, roots were stained with 0.25 % Coomassie Brilliant Blue for 2 d prior to scanning (Kano-Nakata et al., 2012). Staining or not staining roots had no apparent effect on the actual root surface area values (not shown), yet made it easier to use the ‘set-threshold’ function in ImageJ. Root exudation analyses Plants exposed to the normal-stress treatments were analysed for root exudation rate as described previously (Suku et al., 2014; Meng et al., 2016). All analyses were carried out in a normal laboratory environment, at ambient air temperatures of 17–21 °C. Plants were analysed either 4–6 h into the photoperiod (‘light’) or 2–6 h into the 8h dark period (‘dark’). In short, the shoot was excised about 1 cm above the root–shoot junction. The root system was attached to a glass capillary (Harvard Apparatus Ltd, Edenbridge, UK) of known diameter with the aid of superglue (Loctite, super glue ‘Gel Control’) and silicon tubing. The root system was bathed in the identical nutrient solution (control plants) used during growth of the plant, and the osmotically driven water uptake was recorded at 5-min intervals as a rise of liquid in the capillary, for a total of 30–50 min (light period) or for up to 80 min (dark period; lower exudation rates). Exudation rates during the longer measurement period in the dark changed little with time and were generally in the range 85–115 % of the average exudation rate (100 %) over the measurement period (Supplementary Data Fig. S1). When root systems of plants, which had been exposed to salt stress, were kept on salt-stress media also during root exudation analyses, exudation could either not be observed at all, or rates were near the limit of resolution of marking the meniscus of exudate liquid at different time points with a fine marker on the glass capillary. Therefore, it was decided to transfer root systems of salt-stressed plants to control media at the start of exudation analyses, to allow significant exudation rates. We were aware that this may have resulted in root hydraulic properties in salt-stressed plants which differed from those originally present in those plants prior to analyses. However, transfer of salt-stressed plants to control media during exudation analyses, which resembled down-stress experiments, was the only experimental approach which enabled us to conduct these analyses successfully. Stomatal density The number of stomata per unit projected leaf area (stomatal density) was determined through a double-replica technique (Fricke et al., 1995) on intact plants of the normal-stress experiment. Six plants were analysed for each treatment (control, 50 mm, 100 mm and 150 mm NaCl). Leaf 2 was covered halfway along the blade over a length of about 1 cm with dental impression material (Coltène President, Light body, Type 3 consistency; Coltène Whaledent Inc., OH, USA) on both the adaxial (upper) and abaxial (lower) surface. Once the dental impression material had hardened (5–10 min), it was carefully peeled off. This ‘negative’ of the leaf surface was then covered with a thin layer of fast-drying clear nail varnish. The nail varnish was allowed to dry for 15–20 min and peeled off, providing a negative of a negative (and therefore positive) replica of the leaf surface. The nail varnish peel was placed on a microscope slide, covered with a cover slip and viewed at bright light illumination under a Leica microscope (DM IL; Leica, Wetzlar, Germany) at 40× magnification. Pictures (1.06 mm2 area) were captured with a digital camera (DFC300 FX; Leica). Three pictures were taken of each nail varnish peel (one peel each for the adaxial and abaxial leaf surface of a plant), making sure to include regions across the entire width of the leaf. The number of stomata per picture was counted and amounted typically to between 35 and 55 stomata mm–2. The average of the three readings was calculated for each surface of a leaf, and the average of values for the adaxial and abaxial surface was taken as a measure of the stomatal density of leaf 2 for a particular plant. Dark respiration rate and CO2 conductance in leaves The rate of dark respiration (µmol CO2 released m−2 s−1) in leaves was determined for plants of the normal-stress experiment, 3–6 h into the 8-h dark period. Respiration rates were determined halfway along the blade of leaf 2 using a Li-Cor 6400 portable photosynthesis analysis system equipped with a 3 × 2 cm large measuring chamber. The CO2 concentration in the chamber ambient air was set to 400 ppm. The temperature of air and leaf varied little between measurements and averaged 20.3 and 19.9 °C, respectively. RH averaged 63 % and the VPD averaged 0.834 kPa across all measurements, with little variation in either of the two. Six plants were analysed of each treatment (control, 50 mm, 100 mm, 150 mm NaCl), totalling 24 plant analyses. These analyses were carried out within the same dark period and at a random sequence of treatments. Three recordings were obtained for each leaf (and plant) and averaged to give one final value for a particular plant. Once a leaf had been analysed, a picture of a leaf clamped in the chamber was taken. This picture was used to determine leaf surface area, using ImageJ and the chamber dimensions for calibration. Leaf conductance (mol m−2 s−1) for CO2 was obtained as one of the outputs of the data spreadsheet provided through the Li-Cor software. Cuticular wax analyses The amount of leaf cuticular wax was determined for all treatments of the normal-stress experiment using GC-MS following procedures described previously (Richardson et al., 2005). The same plants studied for residual transpiration were used for analysis of cuticular wax, with four plants being analysed for each treatment. All leaves (leaves 1–3) of a plant used for residual transpiration analyses had been cut at the base of the blade and fixed with a minimum of tape onto a piece of paper, before being scanned for determination of (original) leaf surface area as described above. Following the scan, the sections of leaves which had not been taped directly were removed with a razor blade, cut into smaller pieces, transferred into an open-lid 2-mL microcentrifuge tube and left to dry for several weeks at an ambient laboratory environment; these samples were then used for analysis of cuticular wax. The piece of paper containing the remaining, taped leaf sections was scanned again for determination of residual leaf surface area. The difference between the original and residual leaf surface area was the leaf surface area entered into cuticular wax analyses. Statistical analyses Data were subjected to one-way (factor: salt treatments) or two-way (see Fig. 9A, factors: salt treatments and 24-h day period) ANOVAs (General Linear Model and Tukey post-hoc analysis; see Figs 2–4, 6, 8–9) and correlation analyses (Fig. 5) using functions in Minitab. RESULTS Transpiration Normal-stress. The rates of day- and night-time transpirational water loss decreased significantly in response to salt stress (Fig. 2A). The rate of night-time transpirational water loss amounted to 14.3 % of the rate of daytime water loss in control plants (Fig. 2B). This percentage decreased to 8.9 % at the highest NaCl concentrations tested (150 mm), yet the decrease was statistically non-significant. Shoot but not root surface area also decreased with increasing NaCl concentration (Fig. 2C), as did the water loss rate during day and night per unit shoot surface area (Fig. 2D). Fig. 2. View largeDownload slide Transpiration and root and shoot surface area of barley plants, which were exposed to salt stress prior to and during transpiration analyses (‘normal-stress’ experiments). Plants were 14–18 d old at the time of analyses and exposed to high NaCl-containing root media for the last 4–7 d prior to analyses. (A) Rates of daytime and night-time transpirational water loss was recorded gravimetrically and continuously over a 24-h day/night/day period. (B) Night-time transpiration rate expressed as a percentage of daytime rate. (C) Shoot and root surface area of plants. (D) Daytime and night-time transpiration rate expressed per unit shoot surface area (SSA). Results are averages and SE (error bars) of n = 5–6 plant analyses. Statistically significant (P < 0.05) differences in values between treatments are indicated by different lower-case letters. Fig. 2. View largeDownload slide Transpiration and root and shoot surface area of barley plants, which were exposed to salt stress prior to and during transpiration analyses (‘normal-stress’ experiments). Plants were 14–18 d old at the time of analyses and exposed to high NaCl-containing root media for the last 4–7 d prior to analyses. (A) Rates of daytime and night-time transpirational water loss was recorded gravimetrically and continuously over a 24-h day/night/day period. (B) Night-time transpiration rate expressed as a percentage of daytime rate. (C) Shoot and root surface area of plants. (D) Daytime and night-time transpiration rate expressed per unit shoot surface area (SSA). Results are averages and SE (error bars) of n = 5–6 plant analyses. Statistically significant (P < 0.05) differences in values between treatments are indicated by different lower-case letters. Down-stress. When NaCl-stressed plants were transferred from media containing high NaCl concentrations to media containing only 1 mm NaCl (control nutrient solution) just prior to 24-h transpiration analyses, day- and night-time transpirational water loss rates differed much less, and were not statistically significant, between treatments (Fig. 3A). The rate of night-time transpirational water loss amounted to 12.9 % of the rate of daytime water loss in plants which had been exposed previously to 50 mm NaCl and were now growing on control nutrient solution (Fig. 3B). This percentage increased slightly, to 17.4 %, in plants which had been exposed previously to 150 mm NaCl (Fig. 3B), although this increase was not statistically significant. None of the other sizes analysed differed significantly between treatments, and this included transpirational water loss rate per unit shoot surface area during the day and night, which was highest in plants previously exposed to 150 mm NaCl (Fig. 3C, D). Fig. 3. View largeDownload slide Transpiration and root and shoot surface area of barley plants, which were originally exposed to salt stress and then transferred to control media just before transpiration analyses (‘down-stress’ experiments). Plants were 14–18 d old at the time of analyses and exposed to high NaCl-containing root media for the last 4–7 d prior to analyses. Just before being analysed for transpiration, NaCl-stressed plants were transferred to control media containing only 1 mm NaCl. (A) Rates of daytime- and night-time transpirational water loss were recorded gravimetrically and continuously over a 24-h day/night/day period. (B) Night-time transpiration rate expressed as a percentage of daytime rate. (C) Shoot and root surface area of plants. (D) Daytime and night-time transpiration rate expressed per unit shoot surface area (SSA). Results are averages and SE (error bars) of n = 5–6 plant analyses. Statistically significant (P < 0.05) differences in values between treatments are indicated by different lower-case letters. Fig. 3. View largeDownload slide Transpiration and root and shoot surface area of barley plants, which were originally exposed to salt stress and then transferred to control media just before transpiration analyses (‘down-stress’ experiments). Plants were 14–18 d old at the time of analyses and exposed to high NaCl-containing root media for the last 4–7 d prior to analyses. Just before being analysed for transpiration, NaCl-stressed plants were transferred to control media containing only 1 mm NaCl. (A) Rates of daytime- and night-time transpirational water loss were recorded gravimetrically and continuously over a 24-h day/night/day period. (B) Night-time transpiration rate expressed as a percentage of daytime rate. (C) Shoot and root surface area of plants. (D) Daytime and night-time transpiration rate expressed per unit shoot surface area (SSA). Results are averages and SE (error bars) of n = 5–6 plant analyses. Statistically significant (P < 0.05) differences in values between treatments are indicated by different lower-case letters. Up-stress. When plants were kept on control nutrient solution throughout their growth and transferred to media containing high concentrations of NaCl just prior to 24-h transpiration analyses, rates of daytime transpirational water loss were slightly lower in the 100 and 150 mm NaCl compared with 50 mm treatment, yet none of these differences was statistically significant (Fig. 4A). The rate of night-time transpirational water loss was between 13.6 and 16.3 % of the rate of daytime losses across all three treatments (Fig. 4B). Neither shoot nor root surface area changed in response to treatments (Fig. 4C). Daytime transpirational water loss rate per unit shoot surface area decreased by 30 % at the highest NaCl concentration tested, although this was not statistically significant (Fig. 4D). Fig. 4. View largeDownload slide Transpiration and root and shoot surface area of barley plants, which were grown on control medium (containing 1 mm NaCl) throughout and then exposed to salt stress just before transpiration analyses (‘up-stress’ experiments). Plants were 14–18 d old at the time of analyses. (A) Rates of daytime- and night-time transpirational water loss were recorded gravimetrically and continuously over a 24-h day/night/day period. (B) Night-time transpiration rate expressed as a percentage of daytime rate. (C) Shoot and root surface area of plants. (D) Daytime and night-time transpiration rate expressed per unit shoot surface area (SSA). Results are averages and SE (error bars) of n = 5–6 plant analyses. Statistically significant (P < 0.05) differences in values between treatments are indicated by different lower-case letters. Fig. 4. View largeDownload slide Transpiration and root and shoot surface area of barley plants, which were grown on control medium (containing 1 mm NaCl) throughout and then exposed to salt stress just before transpiration analyses (‘up-stress’ experiments). Plants were 14–18 d old at the time of analyses. (A) Rates of daytime- and night-time transpirational water loss were recorded gravimetrically and continuously over a 24-h day/night/day period. (B) Night-time transpiration rate expressed as a percentage of daytime rate. (C) Shoot and root surface area of plants. (D) Daytime and night-time transpiration rate expressed per unit shoot surface area (SSA). Results are averages and SE (error bars) of n = 5–6 plant analyses. Statistically significant (P < 0.05) differences in values between treatments are indicated by different lower-case letters. Correlation analyses. Individual plant data from the three types of experiments were pooled to test for universal correlations between night- and daytime transpiration. The rate of night-time transpirational water loss of plants was highly correlated with the rate of daytime transpirational water loss (P < 0.001, r2 = 0.713; Fig. 5A). The rate of night-time transpiration, expressed as a percentage of the day value, was correlated weakly (P = 0.031, r2 = 0.088) with the rate of daytime transpiration, increasing by about 5 % across the entire range of daytime transpiration rates measured (Fig. 5B; see linear regression line). Fig. 5. View largeDownload slide Correlation analyses between night- and daytime transpiration rates of barley plants exposed to various regimes and levels of NaCl stress. Data were taken from Figs 2–4, and each point represents a pair of values of one individual plant. (A) Correlation between the rates of night- and daytime transpirational water loss of plants. (B) Correlation between the rate of night-time transpiration, expressed as percentage of the day value, and the rate of daytime transpirational water loss. The Pearson correlation coefficient (a), P-values (b) and (c) regression coefficients (r2) were (a/b/c) (A) 0.844/<0.001/0.713; (B) 0.296/0.031/0.088. The dotted lines in A and B are linear regressions. Fig. 5. View largeDownload slide Correlation analyses between night- and daytime transpiration rates of barley plants exposed to various regimes and levels of NaCl stress. Data were taken from Figs 2–4, and each point represents a pair of values of one individual plant. (A) Correlation between the rates of night- and daytime transpirational water loss of plants. (B) Correlation between the rate of night-time transpiration, expressed as percentage of the day value, and the rate of daytime transpirational water loss. The Pearson correlation coefficient (a), P-values (b) and (c) regression coefficients (r2) were (a/b/c) (A) 0.844/<0.001/0.713; (B) 0.296/0.031/0.088. The dotted lines in A and B are linear regressions. Residual transpirational water loss from detached leaves The rate of transpirational water loss from detached leaves started to level off about 3–4 h following leaf excision (Fig. 6A). By this time, water loss through stomata, which caused initial high transpiration rates, will have contributed negligibly to water loss rates, and the residual transpiration past 3–4 h will have been dominated by cuticular water loss. The residual transpiration rate per unit leaf surface area (Fig. 6B) decreased significantly with previous exposure of plants to NaCl stress. The same applied to residual leaf (epidermal) conductance (approximating minimum cuticular conductance; Fig. 6C). Values decreased from 7.42 × 10−4 m s−1 in control plants to 2.42 × 10−4 m s−1 in plants exposed to 150 mm NaCl. In comparison, cuticular permeance determined previously (Richardson et al., 2007) for barley plants (‘Golf’) grown under control conditions, using a different approach and fully turgid leaves, was 4.9 × 10−4 m s−1 (see dotted line in Fig. 6C). Fig. 6. View largeDownload slide Residual transpiration and leaf (epidermal) conductance of barley plants. Plants used for measurement of residual transpiration were exposed to salt stress for 6 d prior to analyses (‘normal-stress’ setup) and were 16 d old. All three leaves of a plant were excised, taped at their end together with a small piece of masking tape, and weighed at 0 min, 30 min, 1 h, 2 h, 3 h, 4 h, 5 h and 6 h. The rate of fresh weight decrease was calculated for every time interval and plotted against the end point of interval. Leaf surface area (LSA) was determined at the end of the experiment. (A) Rate of fresh weight decrease with time following leaf excision. The last three measurements were taken for calculation of residual transpiration rate. (B) Residual transpiration rate per unit leaf surface area. (C) Residual leaf conductance, which is a close approximation of minimum cuticular conductance (or ‘permeance’; Schuster et al., 2016), calculated from values shown in B and using differences in water vapour concentration between the inside and outside of the leaf; for details, see Materials and Methods. The dotted line gives the value of cuticular permeance determined previously for the barley cultivar ‘Golf’ grown under control conditions and using a different approach (Richardson et al., 2007). (D) Leaf conductance during day and night calculated for the normal-, down- and up-stress treatments shown in Figs 2–4, using average values of transpiration rate per shoot surface area and following the same approach as in C; for details, see Materials and Methods section. Results in A–C are averages and SE (error bar) of n = 4 replicate plant analyses of each treatment. All treatments were derived from the same batch of plants and were analysed at the same time. (A–C) Statistically significant (P < 0.05) differences in values between treatments are indicated through different letters. Fig. 6. View largeDownload slide Residual transpiration and leaf (epidermal) conductance of barley plants. Plants used for measurement of residual transpiration were exposed to salt stress for 6 d prior to analyses (‘normal-stress’ setup) and were 16 d old. All three leaves of a plant were excised, taped at their end together with a small piece of masking tape, and weighed at 0 min, 30 min, 1 h, 2 h, 3 h, 4 h, 5 h and 6 h. The rate of fresh weight decrease was calculated for every time interval and plotted against the end point of interval. Leaf surface area (LSA) was determined at the end of the experiment. (A) Rate of fresh weight decrease with time following leaf excision. The last three measurements were taken for calculation of residual transpiration rate. (B) Residual transpiration rate per unit leaf surface area. (C) Residual leaf conductance, which is a close approximation of minimum cuticular conductance (or ‘permeance’; Schuster et al., 2016), calculated from values shown in B and using differences in water vapour concentration between the inside and outside of the leaf; for details, see Materials and Methods. The dotted line gives the value of cuticular permeance determined previously for the barley cultivar ‘Golf’ grown under control conditions and using a different approach (Richardson et al., 2007). (D) Leaf conductance during day and night calculated for the normal-, down- and up-stress treatments shown in Figs 2–4, using average values of transpiration rate per shoot surface area and following the same approach as in C; for details, see Materials and Methods section. Results in A–C are averages and SE (error bar) of n = 4 replicate plant analyses of each treatment. All treatments were derived from the same batch of plants and were analysed at the same time. (A–C) Statistically significant (P < 0.05) differences in values between treatments are indicated through different letters. Leaf conductance calculated from transpiration data of the normal-, up-stress and down-stress experiments ranged from 1.83 × 10−3 to 4.95 × 10−3 m s−1 during the day and from 2.17 × 10−4 to 1.17 × 10−3 m s−1 during the night (Fig. 6D). Contribution of cuticular and stomatal conductance to day- and night-time transpiration Leaf conductance is the sum of stomatal and cuticular conductance. Using values of leaf conductance (see Fig. 6D) and values of cuticular conductance, which was either determined previously (Richardson et al., 2007) or here as residual leaf conductance (Fig. 6C), it was possible to calculate the percentage of water which was lost through either cuticle or stomata during the day and night (Fig. 7). Residual leaf conductance had been determined for plants which had been grown under the ‘normal-stress’ setup. Therefore, the value of residual leaf conductance of control plants was used as a good indicator of residual leaf conductance in all treatments of the up-stress experiment, as cuticle properties will probably not have changed within 24 h. Similarly, the residual leaf conductance values determined for NaCl treatments were used as a good indicator of residual leaf conductance in the respective NaCl treatments of the down-stress experiment. Fig. 7. View largeDownload slide Contribution of cuticular water loss (cuticular conductance) to leaf (epidermal) conductance in barley plants, which were exposed to different salt stress treatments [normal stress: control (CTRL), 50, 100 and 150 mm NaCl; up-stress, CTRL-to-50, CTRL-to-100, CTRL to 150 mm NaCl; down-stress, 50-to-CTRL, 100-to-CTRL, 150 mm NaCl to CTRL; for details, see legends to Figs 2–4). Values of leaf (epidermal) conductance, which is the additive of stomatal and cuticular conductance, were taken from Fig. 6D. Cuticular conductance was expressed as percentage of leaf conductance (=100 %). In A, a universal value of cuticular permeance (conductance) was used (4.9 × 10−4 m s−1) as determined previously for fully turgid leaves of the barley cultivar ‘Golf’ (grown under control conditions) using a benzoic acid approach (Richardson et al., 2007). In B cuticular conductance was assumed to approach values of residual leaf conductance shown in Fig. 6C. It was further assumed that cuticular conductance did not change significantly within 24 h following transfer of plants from either stress to control (down-stress) or control to stress media (up-stress). That meant that all three treatments of the down-stress experiment had the same cuticular conductance as the respective NaCl treatments of the normal stress plants, and that all three treatments of the up-stress experiment had the same cuticular conductance as the control plants of the normal-stress experiment shown in Fig. 6C. The dotted lines in A and B indicate 10, 50 and 100 % levels. Fig. 7. View largeDownload slide Contribution of cuticular water loss (cuticular conductance) to leaf (epidermal) conductance in barley plants, which were exposed to different salt stress treatments [normal stress: control (CTRL), 50, 100 and 150 mm NaCl; up-stress, CTRL-to-50, CTRL-to-100, CTRL to 150 mm NaCl; down-stress, 50-to-CTRL, 100-to-CTRL, 150 mm NaCl to CTRL; for details, see legends to Figs 2–4). Values of leaf (epidermal) conductance, which is the additive of stomatal and cuticular conductance, were taken from Fig. 6D. Cuticular conductance was expressed as percentage of leaf conductance (=100 %). In A, a universal value of cuticular permeance (conductance) was used (4.9 × 10−4 m s−1) as determined previously for fully turgid leaves of the barley cultivar ‘Golf’ (grown under control conditions) using a benzoic acid approach (Richardson et al., 2007). In B cuticular conductance was assumed to approach values of residual leaf conductance shown in Fig. 6C. It was further assumed that cuticular conductance did not change significantly within 24 h following transfer of plants from either stress to control (down-stress) or control to stress media (up-stress). That meant that all three treatments of the down-stress experiment had the same cuticular conductance as the respective NaCl treatments of the normal stress plants, and that all three treatments of the up-stress experiment had the same cuticular conductance as the control plants of the normal-stress experiment shown in Fig. 6C. The dotted lines in A and B indicate 10, 50 and 100 % levels. Using a previously determined value of cuticular permeance for fully turgid leaf tissue of control plants of the barley cultivar ‘Golf’ (Richardson et al., 2007), cuticular conductance accounted for 10–27 % of leaf conductance during the day, and for 42 % to more than 100 % of leaf conductance during the night (Fig. 7A; for an explanation of values exceeding 100 %, see the next paragraph and Fig. 8). The two treatments which had values higher than 100 % were the 100 mm NaCl (132 %) and 150 mm NaCl (226 %) treatments of the normal-stress experiment; in particular the value for 150 mm NaCl plants pointed to a decrease in cuticular permeance at the highest level(s) of salt, as supported through data on residual leaf conductance (compare Fig. 6C). Using values of residual leaf conductance (Fig. 6C), cuticular conductance accounted for about 100 % of leaf conductance during the night in plants which had been exposed to 150 mm NaCl throughout (normal stress) and in all three treatments of the up-stress experiment. The lowest percentage contribution to leaf conductance during the night was observed for plants of the down-stress experiment (21 %, Fig. 7B). Similarly, the contribution of cuticular conductance to leaf conductance during the day was generally largest for up-stress and smallest for down-stress treatments, ranging from 5 to 27 % (Fig. 7B). Fig. 8. View largeDownload slide Correlation between the percentage contribution of stomatal conductance (L) to leaf conductance (L) during the day and night period in barley plants exposed to different regimes of salt treatments. Values were derived from the data shown in Fig. 7B, by assuming that stomatal and cuticular conductance account, together, for 100 % of leaf conductance. The Pearson correlation coefficient was 0.827, and the P-value of correlation was 0.003. The dotted line is a linear regression. Fig. 8. View largeDownload slide Correlation between the percentage contribution of stomatal conductance (L) to leaf conductance (L) during the day and night period in barley plants exposed to different regimes of salt treatments. Values were derived from the data shown in Fig. 7B, by assuming that stomatal and cuticular conductance account, together, for 100 % of leaf conductance. The Pearson correlation coefficient was 0.827, and the P-value of correlation was 0.003. The dotted line is a linear regression. Using values in Fig. 7B, the per cent contribution of stomatal conductance to leaf conductance, being the sum of cuticular and stomatal conductance, during the day and night period was calculated. The two were highly and positively correlated with each other (Fig. 8). A negative percentage contribution of stomatal conductance to leaf conductance is de facto not possible, and nor is a more than 100 % contribution of cuticle conductance (compare Fig. 7). The few slightly negative values in Fig. 8 resulted from the circumstance that stomatal conductance was calculated as the difference between leaf conductance and cuticular conductance. These latter two values were derived from independent experiments (leaf conductance, transpiration data; cuticle conductance, residual transpiration analyses). It is possible that the cuticle conductance values were artificially large (>100 %) compared with the leaf conductance values. The most likely explanation is that there was a stomatal component which contributed still significantly to residual transpirational water loss from detached leaves, leading to a significant overestimation of true cuticle conductance through the residual leaf transpiration approach. Exudation rate of excised root systems To facilitate exudate flow in NaCl-stressed plants, excised root systems had to be suspended during exudation analyses in the low-osmotic control media. Therefore, the experimental setup resembled that of the ‘down-stress’ plants during transpiration analyses. The exudation rate of excised root systems of plants analysed during the light period averaged 7.93 ± 0.67 × 10−12 m3 s−1 for plants grown under control conditions and decreased, non-significantly, in response to NaCl treatments (Fig. 9A). The same applied to plants analysed during the dark period, where exudation rates averaged 3.72 ± 0.35 × 10−12 m3 s−1 for plants grown under control conditions (Fig. 9A). The exudation rate of plants analysed during the night period accounted for 42–57 % of the exudation rate of plants analysed during the light period across treatments; the difference between exudation rates during the dark and light periods was significant (two-way ANOVAs of treatment × day-period, P < 0.001; not shown). Fig. 9. View largeDownload slide (A) Root exudation rate, and leaf (B) stomatal density, (C, D) dark respiration rate and (E) conductance for CO2, and (F) cuticle wax load of barley plants (‘normal-stress’ experiment). Plants were 14–18 d old at the time of analyses and exposed to high NaCl-containing root media for the last 4–7 d prior to analyses. The exudation rate of excised root systems was analysed for plants during the light- and dark-day period. Stomatal density and dark respiration rate was determined halfway along leaf 2, which comprised 53–64 % of the photosynthesizing and transpiring leaf area of the plants analysed, across treatments (four plants analysed per treatment; not shown). The calculated rate of gravimetric weight loss associated with dark respiration is shown in D; it accounted for less than 1 % of the measured rate of gravimetric weight loss during continuous night-time transpiration analyses; the latter data were derived from Fig. 2A. Results are averages and SE of (A) seven to eight, (B, C) six and (E, F) four plant analyses of each treatment. Statistically significant (P < 0.05) differences in values between treatments are indicated by different lower-case letters. In A, two-way ANOVA, followed by Tukey post-hoc analyses, was used to assess the statistical significance of difference in exudation rates between light and dark day-period and between treatments. The quantity of cuticular wax components and total wax load did not differ significantly between treatments. Fig. 9. View largeDownload slide (A) Root exudation rate, and leaf (B) stomatal density, (C, D) dark respiration rate and (E) conductance for CO2, and (F) cuticle wax load of barley plants (‘normal-stress’ experiment). Plants were 14–18 d old at the time of analyses and exposed to high NaCl-containing root media for the last 4–7 d prior to analyses. The exudation rate of excised root systems was analysed for plants during the light- and dark-day period. Stomatal density and dark respiration rate was determined halfway along leaf 2, which comprised 53–64 % of the photosynthesizing and transpiring leaf area of the plants analysed, across treatments (four plants analysed per treatment; not shown). The calculated rate of gravimetric weight loss associated with dark respiration is shown in D; it accounted for less than 1 % of the measured rate of gravimetric weight loss during continuous night-time transpiration analyses; the latter data were derived from Fig. 2A. Results are averages and SE of (A) seven to eight, (B, C) six and (E, F) four plant analyses of each treatment. Statistically significant (P < 0.05) differences in values between treatments are indicated by different lower-case letters. In A, two-way ANOVA, followed by Tukey post-hoc analyses, was used to assess the statistical significance of difference in exudation rates between light and dark day-period and between treatments. The quantity of cuticular wax components and total wax load did not differ significantly between treatments. Stomatal density Stomatal density of leaf 2 averaged 3.32 × 106 stomata per m2 of projected leaf surface in plants grown under control conditions (Fig. 9B). Stomatal density increased significantly in response to the two higher NaCl treatments (Fig. 9B). There was no significant difference in stomatal density between the adaxial and abaxial leaf surface in any of the treatments studied, with ratios (adaxial/abaxial) ranging from 1.14 to 1.22 (not shown). Dark respiration rate, associated mass loss and leaf conductance to CO2 The dark respiration rate of leaf 2 averaged 0.717 µmol CO2 produced/released m−2 s−1 in control plants. The respiration rate changed little in response to the 50 and 100 mm NaCl treatments, yet decreased significantly, by 38 %, in response to the 150 mm NaCl treatment (Fig. 9C). We can use the balance equation of respiration (C6H12O6 + 6O2 → 6H2O + CO2) to assess how much the mass loss associated with respiration may have contributed to the gravimetric weight loss recorded during night-time transpiration measurements. For this, we can ignore the origin of elements in the respiration equation, for example from where the O in CO2 is derived. We can neglect the 6 H2O being produced, equivalent to the 12 H and 6 O in C6H12O6, as this water will have either contributed to night-time transpirational water loss or, if kept inside the plant, led to an underestimation of true night-time gravimetric water loss through transpiration. The 12 O in the 6 CO2 are equivalent to the 12 O taken up through 6 O2. That leaves a net mass loss of 6 C, or 1 mol of C atoms (12 g) for every 1 mol of CO2 produced through respiration. Given the dark respiration rates measured, this carbon mass loss amounted to 0.27–0.76 % of the weight loss measured during night-time gravimetric transpiration analyses across all four treatments of the normal-stress experiment (Fig. 9D). Leaf conductance to CO2 averaged 5.21 × 10−3 mol m−2 s−1 in control plants and decreased non-significantly in response to salt stress (Fig. 9D). Conductance values at the highest salt treatment showed a large plant-to-plant variation (error bar in Fig. 9E). This was due to low respiration rates, causing comparatively large errors in the calculation of leaf internal CO2 concentration (Ci), and therefore CO2 conductance by the Li-Cor software. Cuticle conductance to CO2 Cuticle conductance to CO2 was calculated. If we take, for example, plants grown throughout under control conditions, dark respiration rates averaged 0.717 µmol CO2 m−2 s−1. Leaf conductance to CO2 averaged 5.21 × 10−3 mol m−2 s−1 in these plants. The question is: ‘How much of this leaf conductance to CO2 was attributable to a conductance of the cuticle?’. It is generally considered that the conductance of the cuticle, unlike that of stomata (ratio of diffusivity in air of CO2 to water vapour about 0.63; Boyer, 2015), to CO2 is much smaller than that for water vapour, as CO2 moves not only through a gaseous but also a liquid phase before reaching intercellular air spaces (Boyer, 2015; Tominaga and Kawamitsu, 2015). Cuticle conductance values for CO2 are hard to come by. Boyer et al. (1997) observed for young grapevine leaves that the cuticle conductance averaged 0.27 mmol m−2 s−1, which corresponded to 2.8 % of the leaf conductance (stomata sealed) to CO2. If we take this latter relationship, we can calculate that the leaf conductance to CO2 obtained here during dark respiration measurements of control plants equated to a cuticle conductance for CO2 of (0.028 × 5.21 × 10−3 mol m−2 s−1) 0.148 mmol m−2 s−1; this is a value close to the one determined for the cuticle of grapevine leaves (Boyer et al., 1997). The quotient of dark respiration rate and CO2 conductance equals the difference in partial pressure of CO2 between the inside and outside of the leaf (driving force). Using the above values, this driving force was ((0.716 × 10−6 mol CO2 m−2 s−1)/(0.148 × 10−3 mol m−2 s−1)) 4.84 × 10−3, or 4840 ppm. Given the ‘ambient’, external CO2 concentration during respiration measurements (approx. 400 ppm), the leaf internal CO2 partial pressure would have exceeded 5000 ppm. Similar leaf internal CO2 concentrations could be calculated for normal-stress plants exposed to salt treatments using data on dark respiration and leaf CO2 conductance shown in Fig. 9. A leaf internal partial pressure of CO2 of 5000 ppm seems to be unphysiologically high and could not only feedback negatively on CO2 production during dark respiration, but also potentially lead to acidosis of cells: an aqueous solution equilibrated with air of 350 ppm CO2 has a pH of 5.65, and solutions equilibrated with 1000 and 10 000 ppm CO2 have a pH of 5.42 and 4.92, respectively. Cuticular wax load Cuticular wax load averaged 10.6 µg cm−2 in control plants and did not change significantly in response to salt stress (Fig. 9F). This applied to the five major classes of wax components. Alcohols made up about 80 % of the cuticular wax load, with the C26 primary alcohol hexacosanol dominating this portion (not shown; see also Richardson et al., 2005) DISCUSSION Biological significance of night-time transpiration It has been argued that night-time transpiration facilitates mineral nutrient supply to the shoot to support diurnal growth (for a review, see Caird et al., 2007), although studies on nutrient-limited Arabidopsis plants do not support this idea (Christman et al., 2009a). The present data suggest that the biological function of night-time transpiration is related to the release of respiratory CO2 rather than to the release of water vapour from leaves (see also Marks and Lechowicz, 2007; Easlon and Richards, 2008). It appears that plants, such as barley, not only face the ubiquitous challenge during the day to take up as much CO2 as possible per unit water vapour lost, but also face a similar challenge during the night. Here, the challenge seems to be to allow as much CO2 to escape from leaves for as little water vapour to escape in parallel. In analogy to water-use efficiency (WUE) during the day, we may have to consider a CO2-release efficiency (‘CORE’) during the night. The present observation that rates of night-time and daytime water loss are highly correlated with each other under conditions of salt stress treatments, where absolute rates differ significantly between treatments and can change rapidly, further points to some form of regulation of night-time transpiration. The prime candidate for such regulation are stomata. One could predict that future climate change (e.g. high CO2) or experimental treatments which selectively alter the differences in VPD and CO2 partial pressure between the inside and outside of a leaf should affect the CO2/H2O release efficiency. For example, increased VPD during the night increased night-time and decreased daytime transpiration rates in wheat genotypes, yet did not affect plant biomass (carbon cost) (Claverie et al., 2016). It is likely that the changed VPD in the experiments by Claverie et al. (2016) did not impact on the driving force for night-time diffusion rates of O2 and CO2 through stomata. In addition, strong positive correlations between night-time and daytime leaf (epidermal) conductance have been reported among species and among accessions of a single species (Jordan et al., 1984; Snyder et al., 2003; Christman et al., 2008). These data, and the present observation that night- and daytime water loss rates are highly correlated with each other, could be explained through a mechanism which links night-time carbon consumption and respiration to daytime CO2 assimilation and carbon gain (or vice versa), and where this mechanism affects stomatal aperture. Night- and daytime rates of transpirational water loss The quantitative relationship between the rate of night-time and daytime transpiration hardly changed and did not differ significantly between any of the treatments tested. However, at the same time, stomata and cuticle conductance contributed to different degrees to night- and daytime water loss. Being the more dynamic of the two, the data suggest that stomata are the means through which barley plants adjust the relationship between day- and night-time water loss rates, also under salt stress. Short-term (<24 h) transpirational responses to changes in external water availability in down- and up-stress experiments exclude a significant contribution of leaf anatomical properties such as vein density, venation pattern or stomatal density (Claverie et al., 2016). Similarly, stomatal density (stomata m−2) of leaf 2 of plants which were exposed for longer periods to salt (normal-stress) increased by a maximum of 23 %, probably as a result of reduced cell expansion rates as leaf 2 had started to develop at the time stress was applied. At the same time, day- and night-time transpiration rates per unit leaf surface area decreased significantly in these plants. Recent studies on other species, including cereals, where night-time transpiration was measured in response to changes in the root (temperature, water availability) and shoot (vapour pressure deficit, VPD) environment or found to be responsive to the stomata-closing plant hormone abscisic acid, support a significant role of stomatal water loss during night-time transpiration (Mott and Peak, 2010; Rogiers and Clarke, 2013; Schoppach et al., 2014; Coupel-Ledru et al., 2016). Correlation analyses of all individual plant data gave a weak and positive correlation between the rate of night-time transpiration, expressed as percentage of the day value, and the rate of daytime transpiration. Water was lost during the night at 9–17 % the rate at which it was lost during the day, averaging 13.8 ± 0.8 % (means ± SE, n = 10) across all treatments. These values are within the range of values reported previously for plants, including cereals (Caird et al., 2007; Knipfer and Fricke, 2011; Rogiers and Clarke, 2013; Claverie et al., 2016) and saltgrass (Distichilis spicata) plants exposed to 300 and 600 mm NaCl (Christman et al., 2009b). Some of the changes in the quantitative relationship between night-time and daytime transpiration reported in the literature have been related to a dehydration or osmotic stress of plants (Coupel-Ledru et al., 2016; Claverie et al., 2016). The present data on salt- and, therefore, osmotically stressed, barley plants do not support this idea. However, what the present data show is that osmotic stress affected the relative contribution of stomatal and cuticular conductance to leaf conductance. Treatments which exposed plants either throughout to high NaCl (normal-stress, 100 and 150 mm NaCl) or suddenly (up-stress) to even moderate NaCl concentrations (50 mm NaCl, ‘moderate’ for barley) caused a large increase, whereas those treatments which caused sudden downward osmotic shock and increase in water availability to plants (down-stress experiment) caused a large decrease in the contribution of cuticular water loss to night-time transpiration. Night-time transpiration – forces driving water uptake The present data suggest that the contribution of osmotic forces and xylem tension to root water uptake during night-time transpiration can change in response to salt stress. The exudation rates measured here during the dark period on plants of the normal-stress experiment did not differ significantly between treatments. The dark-period exudation rates accounted for 41–57 % of the exudation rate measured during the light period for a particular treatment. This may reflect diurnal differences in root aquaporin activity (for a review, see Maurel et al., 2015). The experimental setup of root exudation analyses resembled that of down-stress plants, even though only the first 80 min following down-osmotic shock was analysed. When comparing the average exudation rate of plants during the dark period with night-time transpiration rates of down-stressed plants, the former amounts to 33–41 % of the latter. In down-stressed plants, mechanisms which facilitated water uptake at root level during exudation analyses could have facilitated the uptake of a significant portion of water during night-time transpiration. However, the same cannot be said about plants which had their root system exposed to NaCl throughout, including during exudation analyses. These plants showed no or very low rates of exudate flow. Small amounts of xylem tension, as a result of night-time transpirational water loss through stomata or cuticle, could provide an alternative if not additional driving force for water and mineral nutrient delivery to the shoot under such conditions. Cuticular permeance Richardson et al. (2007) used a benzoic acid approach, on intact turgid leaves, to determine cuticular permeance for barley plants (‘Golf’) grown under non-stress conditions. The authors reported a value of 4.9 × 10−4 m s−1. This value is within the range of values obtained here, using a different approach (residual transpiration) and studying a range of treatments and a different cultivar, and of permeance values reported for other plants (for reviews, see Noble, 1991; Kerstiens, 1996). The residual leaf conductance (7.42 × 10−4 m s−1) obtained here for control plants was slightly higher than the cuticle permeance reported by Richardson et al. (2007). This could point to some significant contribution of stomatal water loss and conductance to residual water loss rates determined for detached leaves. If so, the contribution of stomatal water loss to night-time transpiration would have been higher than suggested by the values in Fig. 7B. The interpretation of slightly negative values in Fig. 8 (see Results) and data on cuticle wax load (see next paragraph) supports this view. Fricke et al. (2006) found no difference in cuticular wax load between barley plants (‘Golf’) grown under control conditions and plants which had been exposed for 2–3 d to 100 mm NaCl. Similarly, no significant differences in cuticular wax load were found in the present study for treatments of the normal-stress experiments. The leaves which had been entered into wax analyses had been used before for residual transpiration analyses – and these analyses showed significant differences in residual transpiration rates between treatments. This suggests that residual transpiration also included a stomatal component, with cuticular water loss possibly not differing between treatments. An alternative explanation would be that there is no direct, positive relationship between cuticle wax load and permeance. Larsson and Svenningsson (1986) and Svenningsson (1988), studying several barley cultivars, did not find correlations between cuticular transpiration and the amount or composition of cuticular lipids in response to treatments causing water stress. In contrast, González and Ayerbe (2010) observed a negative correlation between epicuticular wax load and residual transpiration, which was not significant, in a range of barley genotypes exposed to terminal drought. However, there are reports on species other than barley which point to a decrease in leaf cuticular water loss in response to salt and drought stress (Cameron et al., 2006; Kosma et al., 2009; for a review, see Shepherd and Wynne, 2006) and where negative (cor)relations were observed between cuticular wax load and residual transpiration of detached leaves (Jordan et al., 1984; Premachandra et al., 1992; Hasanuzzaman et al., 2017). We do not know whether these differences between barley and other plant species reflect a species-specific response or result from differences in the developmental stage or experimental setup (treatments, growth conditions, analyses) between studies. Boyer (2015) demonstrated that cuticular conductance for water vapour and CO2 decreased with large decreases in leaf turgor, due to a wrinkling of the epidermal surface and tightening of the cuticle. Barley plants which are exposed to high salt concentrations retain a significant amount of turgor (0.7 MPa and more) in leaf epidermal cells (Fricke and Peters, 2002). This makes it unlikely that leaf wrinkling caused decreases in cuticular permeance in response to salt stress in intact plants, in addition to any decreases in cuticular permeance as suggested by data on residual transpiration for detached leaves. CONCLUSIONS The rates of night- and daytime transpiration in salt-stressed barley are highly correlated with each other. The present data can best be explained through stomata playing a key role in adjusting the two rates. Furthermore, the data suggest that the evolutionary driver for the occurrence of night-time transpiration in plants is not so much the facilitation of water vapour exchange and delivery of xylem-borne nutrients to the leaf, but the facilitation of sufficiently high export rates of respiratory CO2 from leaves to sustain night-time cellular metabolic activity and leaf growth. Plants such as barley not only face a water-use efficiency (WUE) but also a CO2-release efficiency (CORE) challenge. Whether a similar reasoning applies to the uptake of respiratory O2 into leaves during the night needs to be tested. SUPPLEMENTARY DATA Supplementary data are available online at https://academic.oup.com/aob and consist of the following. Figure S1: Time course of exudation rates. ACKNOWLEDGEMENTS Part of this work was carried out during internship visits by M.E. (Ecole d’Ingénieurs de PURPAN, France) and M.S (Université de Toulousse III Paul Sabatier, France) to University College Dublin, funded in part through the ERASMUS+ Mobility Traineeship Scheme. D.M. was funded through a joint CSC (Chinese Scholarship Council)/UCD PhD fellowship. Financial support by the Deutsche Forschungsgemeinschaft (GRK 2064) to L.S. and T.K. is highly appreciated. W.F. would like to thank Eugene Sherry (UCD) for help with the setup for continuous transpiration analyses and Charilaos (‘Harry’) Yiotis for help with Li-Cor analyses. W.F. would also like to thank two anonymous reviewers for some very helpful and constructive comments, and Gerhard Kerstiens for some very helpful discussions. LITERATURE CITED Boyer JS. 2015. Turgor and the transport of CO2 and water across the cuticle (epidermis) of leaves. Journal of Experimental Botany  66: 2625– 2633. Google Scholar CrossRef Search ADS PubMed  Boyer JS, Wong SC, Farquhar GD. 1997. 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Epi- and intracuticular lipids and cuticular transpiration rates of primary leaves of eight barley (Hordeum vulgare) cultivars. Physiologia Plantarum  73: 512– 517. Google Scholar CrossRef Search ADS   Tominaga J, Kawamitsu Y. 2015. Cuticle affects calculations of internal CO2 in leaves closing their stomata. Plant and Cell Physiology  56: 1900– 1908. Google Scholar CrossRef Search ADS PubMed  Yoo CY, Pence HE, Hasegawa PM, Mickelbart MV. 2009. Regulation of transpiration to improve crop water use. Critical Reviews in Plant Sciences  28: 410– 431. Google Scholar CrossRef Search ADS   © The Author(s) 2018. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com. 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Night-time transpiration in barley (Hordeum vulgare) facilitates respiratory carbon dioxide release and is regulated during salt stress

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Abstract

Abstract Background and Aims Night-time transpiration accounts for a considerable amount of water loss in crop plants. Despite this, there remain many questions concerning night-time transpiration – its biological function, regulation and response to stresses such as salinity. The aim of the present study was to address these questions on 14- to 18-d-old, hydroponically grown barley plants. Methods Plants were either stressed for the last 4–7 d prior to, and during subsequent continuous (24 h), diurnal gravimetric transpiration analyses; or subjected to salt stress just before analyses; or stressed for 4–7 d and then transferred to control medium before analyses. The idea behind this experimental setup was to distinguish between a longer- (cuticle, stomata) and shorter-term (stomata) response of transpiration to treatments. Cuticular conductance was assessed through residual transpiration measurements in detached leaves. Cuticle wax load and dark respiration rate of leaves were determined. Leaf conductance to CO2 was calculated. Key Results Night-time and daytime transpiration rates were highly, and positively, correlated with each other, across all treatments. Night-time transpiration rates accounted for 9–17 % of daytime rates (average: 13.8 %). Despite minor changes in the ratio of night- to daytime transpiration rates, the contribution of cuticular and stomatal conductance to leaf (epidermal) conductance to water vapour differed considerably between treatments. Salt stress did not affect cuticle wax load. The conductance for CO2 of the cuticle was insufficient to support rates of dark respiratory CO2 release. Conclusions The main biological function of night-time transpiration is the release of respiratory CO2 from leaves. Night-time transpiration is regulated in the short and long term, also under salt stress. Stomata play a key role in this process. We propose to refer, in analogy to water use efficiency (WUE) during the day, to a CO2 release efficiency (‘CORE’) during the night. Barley (Hordeum vulgare L.), carbon dioxide, cuticular permeance, night-time transpiration, residual transpiration, respiration, salt stress, stomata INTRODUCTION Night-time transpirational water loss can account for a considerable portion of daily water use of plants (Caird et al., 2007; Yoo et al., 2009; Resco de Dios et al., 2015). Rates of night-time water loss amount typically to 5–15 % of rates of daytime water loss across species, yet can exceed 50 % depending on genotype and environmental conditions (Rogiers and Clarke, 2013; Schoppach et al., 2014; Coupel-Ledru et al., 2016; for a review, see Caird et al., 2007). Strong correlations were found for the vapour-pressure deficit (VPD) sensitivity of transpiration under day- and night-time conditions, and altering VPD only during the night increased specifically night-time transpiration rates (expressed as percentage of day rates), without an effect on daytime rates (where VPD was not changed; Schoppach et al., 2014). These data suggest that the rate of night-time transpiration can be regulated. It is not clear whether night-time transpiration has any benefits to plants, and any biological function at all. For example, night-time transpiration may simply arise as an inevitable consequence of some intrinsic cuticle permeability to water vapour. Night-time transpiration may also permit a hydraulic lift of nutrients to shoot tissue to support growth during the dark period (for a review, see Caird et al., 2007). Yet, it is also possible that night-time transpiration facilitates the passage at sufficiently high rates of gases other than water vapour, in particular O2 (in) and CO2 (out of leaf) during dark respiration. Knowing the structural means and their conducting properties through which water is lost from shoot surfaces into the atmosphere during the night will help to address these questions. Prime candidates of such structural means are stomata, which may not be entirely closed during the night, or the cuticle, which has some intrinsic water permeability (Caird et al., 2007; Rogiers & Clarke, 2013; Coupel-Ledru et al., 2016; Claverie et al., 2016). Reports in the literature support the role of either candidate, and this role may be species- and environment-dependent (e.g. Rogiers & Clarke, 2013; Resco de Dios et al., 2015; Coupel-Ledru et al., 2016; Claverie et al., 2016; Hasanuzzaman et al., 2017). One inherent difference between stomata and cuticle is, based on our current knowledge, that the hydraulic properties of stomata but not cuticle can be regulated in the short term, say within hours to 1 d, although leaf turgor may impact on cuticle conductance (Boyer, 2015). Treatments such as salt stress, which can affect daytime transpirational water loss and stomatal conductance significantly, should have different effects on the relationship between day- and night-time transpiration depending on the exposure time of plants to these stresses. For example, (1) it is possible that longer-term salt stress reduces the water permeability (permeance; Richardson et al., 2007) of the cuticle, and that most of the water exits leaves during the night through the cuticle. If so, plants which are exposed to salt stress for several days should show a lower rate of night-time (cuticle) compared with daytime (cuticle, stomata) transpirational water loss than plants which are exposed to salt stress just prior to transpiration analyses. This is because there would be too little time to reduce the water permeability of cuticle in these latter plants. Similarly, (2) the possibility exists that cuticle hydraulic properties are not affected by salt stress yet dominate the night-time transpiration response. In this case, one would predict that the rate of night-time water loss increases relative to that of daytime water loss in plants, because any partial closure of stomata in response to sudden exposure to salt stress would only affect daytime transpiration. (3) Furthermore, by measuring rates of dark respiratory release of CO2 and leaf conductance to CO2, it is possible, with the aid of literature data (Boyer et al., 1997; Boyer, 2015), to calculate a cuticle conductance to CO2. This in turn makes it possible to test whether respiratory CO2 could be released entirely through the cuticle or requires stomata to be open during the night. To test these possibilities, we exposed hydroponically grown barley plants to various concentrations of NaCl (50, 100, 150 mm) in the nutrient solution and also varied the duration and sequence of treatments. Transpirational water loss rates were recorded continuously and determined gravimetrically (balance) during a 24-h period on intact plants. Plant transpiration rates were related to shoot surface area, and the resulting values were used to calculate leaf (epidermal) conductance, based on water vapour concentrations inside and outside the leaf, at the given temperature and relative humidity (Noble, 1991) during growth of plants. To assess the contribution of stomata and cuticle conductance to leaf conductance of water vapour, cuticular (minimum) conductance (permeance; for terminology, see Schuster et al., 2016) was determined by measuring residual transpiration of detached shoots (e.g. Svenningsson, 1988; Kerstiens, 1996). To obtain information about the mechanisms underlying any changes in cuticular and leaf conductance in response to salt stress, cuticle wax load (GC-MS) and stomatal density (leaf replica technique) were analysed. Rates of dark respiration and leaf conductance to CO2 were measured using a portable photosynthesis measuring unit (Li-Cor 6400, Lincoln, NE, USA). MATERIALS AND METHODS Plant material and growth conditions Barley (Hordeum vulgare L. ‘Quench’) plants were grown on modified half-strength Hoagland solution in a growth chamber (Microclima, MC1000HE, CEC Technology, Glasgow, UK) as described previously (Knipfer and Fricke, 2011). The root medium was aerated, and plants grew at a day/night length of 16/8 h and temperature of 21/15 °C. Relative humidity was 75 % and photosynthetically active radiation at plant level was 300–350 μmol m−2 s−1. VPD was 0.427 kPa during the night and 0.622 kPa during the day. All plants were germinated for 7 d, and then put initially (d7) on control nutrient solution, containing also 1 mm NaCl. Plants were analysed when they were 14–18 d old. At that developmental stage, leaf 2 was the main photosynthesizing and transpiring leaf, leaf 3 was expanding and leaf 4 had not yet emerged. Plants were subjected to a range of salt (NaCl) concentrations (50, 100, 150 mm NaCl final concentration in nutrient medium) and exposure times to salt (Fig. 1). Plants were either transferred to medium containing high NaCl on d10, and then kept on this medium for the last 4–7 d prior to, and during subsequent continuous 24-h diurnal transpiration analyses (‘normal-stress’); or kept initially on control nutrient solution, and subjected to salt stress just before the start of transpiration analyses (‘up-stress’); or stressed for 4–7 d prior to transpiration analyses, as done for normal-stressed plants, and then transferred to control medium just before transpiration analyses began (‘down-stress’). All treatments which were analysed within each type of experimental setup (either normal, up- or down-stress) were derived from the same batch of plants. Fig. 1. View largeDownload slide Schematic diagram summarizing the experimental setup of salt stress treatments (50, 100, 150 mm) and the type of analyses carried out for each treatment. CTRL, control; soln, solution; min, minutes. Fig. 1. View largeDownload slide Schematic diagram summarizing the experimental setup of salt stress treatments (50, 100, 150 mm) and the type of analyses carried out for each treatment. CTRL, control; soln, solution; min, minutes. The water potential (ψ) of media was determined with a VAPRO (Wescor Inc., South Logan, UT, USA) osmometer for four to five replicate samples and was found to average −0.036 MPa for control nutrient solution and −0.312, −0.570 and −0.780 MPa for nutrient solution containing 50, 100 and 150 mm NaCl, respectively. Transpiration measurements and leaf conductance Transpirational water loss of plants growing in the growth chamber was determined gravimetrically (Knipfer and Fricke, 2011) using balances (Model CP323P, Sartorius, Göttingen, Germany; and Model SL500, Scientific and Chemical Supplies Ltd, Bilston, UK). Changes in weight were recorded every 1–2 min using computer software (sartoCollect 1.0; Sartorius; and SCOUT Pro USB interface kit with SPDC software, Ohaus Corp., Pine Brook, NJ, USA).Transpiration analyses started 8 h into the photoperiod and lasted for 24 h. The first light period lasted from 0 to 8 h, the dark period lasted from 8 to 16 h, and the second, next-day light period lasted from 16 to 24 h. The average rate of transpirational water loss was calculated for each of the three periods, not including the first and last hour of each period, and at least including four continuous hours of measurement with a steady rate of water loss. This was done to avoid effects of plant transfer (start of experiment) or transient effects of day/night/day changes including changes in VPD on transpiration rates and also effects of changing air pressure (day/night) in the growth chamber which impacted on the balance output during transitional (day to night, night to day) periods. The values for the first and second light period were used to calculate an average light-period transpiration value for a particular plant. Each plant was contained within a 250-mL Erlenmeyer flask, which was wrapped in aluminium foil during analyses, and supported through a foam piece to hold the plant in the flask. Bubbling or not bubbling the nutrient solution during transpiration measurements did not affect the value of transpiration, yet bubbling increased the amount and error of background water loss significantly (not shown). This was probably due to variable amounts of water vapour escaping between the foam piece, which supported the plant, and the Erlenmeyer flask which contained the nutrient solution. Having a low and steady background water loss was particularly important for the 150 mm NaCl treatment of the normal-stress experiment, as this treatment showed very low night-time water loss rates. Background water loss was determined by having an identical setup as for plant analyses, except that the plant was missing (only Erlenmeyer flask, nutrient solution and foam piece). The background water loss was recorded over a 24-h day/night/day period as described above, and the average day- and night-time background water loss rate was determined using 4–8 replicates in each experiment. To calculate leaf conductance, transpirational water loss rates were first related to shoot surface area and then divided by the difference in water vapour concentration between the inside and outside of a leaf, as this represents the driving force for water vapour loss from leaves. Using values given in Noble (1991) for 100 % relative humidity (RH; approaching conditions inside a leaf, also for NaCl-stressed plants) and 75 % RH (ambient air) at 21 °C (day) and 15 °C (night) and neglecting any possible differences in temperature between leaf and air and effects of unstirred (boundary) layers, water vapour concentration differences amounted to 4.59 g m−3 during the day and 3.21 g m−3 during the night. Cuticular water loss from detached leaves: residual transpiration Cuticular water loss was determined by measuring residual transpiration (Kerstiens, 1996) using detached leaves (compare, e.g. Larsson and Svenningsson, 1986; Svenningsson, 1988). Plants were grown as detailed for the normal-stress experiments, and the first, second and third leaf was removed from the shoot of a plant when plants were 16 d old. All three leaves were weighed (initial f. wt) and then taped at their open end with a small piece of masking tape, so that all three leaves were aligned parallel next to each other. The loose end of the masking tape was clamped with a paper clip, and the clip was fixed to a hook on a horizontally mounted bar, with leaves being suspended in the air (dim light with photosynthetically active radiation of <5 μmol m−2 s−1; 41.4 % RH, 21 °C; measured close to leaf level throughout the experiment). The weight of leaf setup (paper clip not included) was recorded at time zero, 30 min, 60 min and then at hourly intervals up to 6 h. At the end of experiment, leaf surface area was determined. The rate of water loss from leaves was calculated for each measurement period (0–0.5, 0.5–1, 1–2, 2–3, 3–4, 4–5 and 5–6 h). The rate of residual transpiration, being dominated by cuticular water loss (‘minimum cuticular conductance’, Schuster et al., 2016), was calculated from the final part of the timecourse (last three measurment periods), by which time stomatal water loss should have contributed negligibly to leaf water loss (Larsson and Svenningsson, 1986; Svenningsson, 1988). This residual water loss rate was related to leaf surface area and divided by the difference in water vapour concentration between the inside and outside of a leaf to calculate residual (miniumum) leaf conductance (approximating cuticle permeance) (Schuster et al., 2016). The RH inside leaves will have been close to 100 % (>99 %), even in NaCl-stressed plants, and this led [21 °C; see appendix 1 in Noblel (1991)] to a water vapour concentration of 18.35 g m−3 inside leaves; the calculated water vapour concentration in the ambient air (41.4 % RH) was 7.60 g m−3, and the difference in water vapour concentration between the two locations was 10.75 g m−3. Four replicate plants were analysed for each treatment, and all treatments were analysed in parallel, at the same time. The identical leaves studied for residual transpiration analyses were subsequently used for extraction and quantification of cuticular wax components. Surface area Following transpiration analyses, the shoot of each plant was scanned (Canon 9900F model) for subsequent determination of shoot surface area. The root system was used for determination of root surface area. Scanned images were analysed with the freely available software ImageJ (www.imagej.nih.gov/ij/). To increase the contrast of root images, roots were stained with 0.25 % Coomassie Brilliant Blue for 2 d prior to scanning (Kano-Nakata et al., 2012). Staining or not staining roots had no apparent effect on the actual root surface area values (not shown), yet made it easier to use the ‘set-threshold’ function in ImageJ. Root exudation analyses Plants exposed to the normal-stress treatments were analysed for root exudation rate as described previously (Suku et al., 2014; Meng et al., 2016). All analyses were carried out in a normal laboratory environment, at ambient air temperatures of 17–21 °C. Plants were analysed either 4–6 h into the photoperiod (‘light’) or 2–6 h into the 8h dark period (‘dark’). In short, the shoot was excised about 1 cm above the root–shoot junction. The root system was attached to a glass capillary (Harvard Apparatus Ltd, Edenbridge, UK) of known diameter with the aid of superglue (Loctite, super glue ‘Gel Control’) and silicon tubing. The root system was bathed in the identical nutrient solution (control plants) used during growth of the plant, and the osmotically driven water uptake was recorded at 5-min intervals as a rise of liquid in the capillary, for a total of 30–50 min (light period) or for up to 80 min (dark period; lower exudation rates). Exudation rates during the longer measurement period in the dark changed little with time and were generally in the range 85–115 % of the average exudation rate (100 %) over the measurement period (Supplementary Data Fig. S1). When root systems of plants, which had been exposed to salt stress, were kept on salt-stress media also during root exudation analyses, exudation could either not be observed at all, or rates were near the limit of resolution of marking the meniscus of exudate liquid at different time points with a fine marker on the glass capillary. Therefore, it was decided to transfer root systems of salt-stressed plants to control media at the start of exudation analyses, to allow significant exudation rates. We were aware that this may have resulted in root hydraulic properties in salt-stressed plants which differed from those originally present in those plants prior to analyses. However, transfer of salt-stressed plants to control media during exudation analyses, which resembled down-stress experiments, was the only experimental approach which enabled us to conduct these analyses successfully. Stomatal density The number of stomata per unit projected leaf area (stomatal density) was determined through a double-replica technique (Fricke et al., 1995) on intact plants of the normal-stress experiment. Six plants were analysed for each treatment (control, 50 mm, 100 mm and 150 mm NaCl). Leaf 2 was covered halfway along the blade over a length of about 1 cm with dental impression material (Coltène President, Light body, Type 3 consistency; Coltène Whaledent Inc., OH, USA) on both the adaxial (upper) and abaxial (lower) surface. Once the dental impression material had hardened (5–10 min), it was carefully peeled off. This ‘negative’ of the leaf surface was then covered with a thin layer of fast-drying clear nail varnish. The nail varnish was allowed to dry for 15–20 min and peeled off, providing a negative of a negative (and therefore positive) replica of the leaf surface. The nail varnish peel was placed on a microscope slide, covered with a cover slip and viewed at bright light illumination under a Leica microscope (DM IL; Leica, Wetzlar, Germany) at 40× magnification. Pictures (1.06 mm2 area) were captured with a digital camera (DFC300 FX; Leica). Three pictures were taken of each nail varnish peel (one peel each for the adaxial and abaxial leaf surface of a plant), making sure to include regions across the entire width of the leaf. The number of stomata per picture was counted and amounted typically to between 35 and 55 stomata mm–2. The average of the three readings was calculated for each surface of a leaf, and the average of values for the adaxial and abaxial surface was taken as a measure of the stomatal density of leaf 2 for a particular plant. Dark respiration rate and CO2 conductance in leaves The rate of dark respiration (µmol CO2 released m−2 s−1) in leaves was determined for plants of the normal-stress experiment, 3–6 h into the 8-h dark period. Respiration rates were determined halfway along the blade of leaf 2 using a Li-Cor 6400 portable photosynthesis analysis system equipped with a 3 × 2 cm large measuring chamber. The CO2 concentration in the chamber ambient air was set to 400 ppm. The temperature of air and leaf varied little between measurements and averaged 20.3 and 19.9 °C, respectively. RH averaged 63 % and the VPD averaged 0.834 kPa across all measurements, with little variation in either of the two. Six plants were analysed of each treatment (control, 50 mm, 100 mm, 150 mm NaCl), totalling 24 plant analyses. These analyses were carried out within the same dark period and at a random sequence of treatments. Three recordings were obtained for each leaf (and plant) and averaged to give one final value for a particular plant. Once a leaf had been analysed, a picture of a leaf clamped in the chamber was taken. This picture was used to determine leaf surface area, using ImageJ and the chamber dimensions for calibration. Leaf conductance (mol m−2 s−1) for CO2 was obtained as one of the outputs of the data spreadsheet provided through the Li-Cor software. Cuticular wax analyses The amount of leaf cuticular wax was determined for all treatments of the normal-stress experiment using GC-MS following procedures described previously (Richardson et al., 2005). The same plants studied for residual transpiration were used for analysis of cuticular wax, with four plants being analysed for each treatment. All leaves (leaves 1–3) of a plant used for residual transpiration analyses had been cut at the base of the blade and fixed with a minimum of tape onto a piece of paper, before being scanned for determination of (original) leaf surface area as described above. Following the scan, the sections of leaves which had not been taped directly were removed with a razor blade, cut into smaller pieces, transferred into an open-lid 2-mL microcentrifuge tube and left to dry for several weeks at an ambient laboratory environment; these samples were then used for analysis of cuticular wax. The piece of paper containing the remaining, taped leaf sections was scanned again for determination of residual leaf surface area. The difference between the original and residual leaf surface area was the leaf surface area entered into cuticular wax analyses. Statistical analyses Data were subjected to one-way (factor: salt treatments) or two-way (see Fig. 9A, factors: salt treatments and 24-h day period) ANOVAs (General Linear Model and Tukey post-hoc analysis; see Figs 2–4, 6, 8–9) and correlation analyses (Fig. 5) using functions in Minitab. RESULTS Transpiration Normal-stress. The rates of day- and night-time transpirational water loss decreased significantly in response to salt stress (Fig. 2A). The rate of night-time transpirational water loss amounted to 14.3 % of the rate of daytime water loss in control plants (Fig. 2B). This percentage decreased to 8.9 % at the highest NaCl concentrations tested (150 mm), yet the decrease was statistically non-significant. Shoot but not root surface area also decreased with increasing NaCl concentration (Fig. 2C), as did the water loss rate during day and night per unit shoot surface area (Fig. 2D). Fig. 2. View largeDownload slide Transpiration and root and shoot surface area of barley plants, which were exposed to salt stress prior to and during transpiration analyses (‘normal-stress’ experiments). Plants were 14–18 d old at the time of analyses and exposed to high NaCl-containing root media for the last 4–7 d prior to analyses. (A) Rates of daytime and night-time transpirational water loss was recorded gravimetrically and continuously over a 24-h day/night/day period. (B) Night-time transpiration rate expressed as a percentage of daytime rate. (C) Shoot and root surface area of plants. (D) Daytime and night-time transpiration rate expressed per unit shoot surface area (SSA). Results are averages and SE (error bars) of n = 5–6 plant analyses. Statistically significant (P < 0.05) differences in values between treatments are indicated by different lower-case letters. Fig. 2. View largeDownload slide Transpiration and root and shoot surface area of barley plants, which were exposed to salt stress prior to and during transpiration analyses (‘normal-stress’ experiments). Plants were 14–18 d old at the time of analyses and exposed to high NaCl-containing root media for the last 4–7 d prior to analyses. (A) Rates of daytime and night-time transpirational water loss was recorded gravimetrically and continuously over a 24-h day/night/day period. (B) Night-time transpiration rate expressed as a percentage of daytime rate. (C) Shoot and root surface area of plants. (D) Daytime and night-time transpiration rate expressed per unit shoot surface area (SSA). Results are averages and SE (error bars) of n = 5–6 plant analyses. Statistically significant (P < 0.05) differences in values between treatments are indicated by different lower-case letters. Down-stress. When NaCl-stressed plants were transferred from media containing high NaCl concentrations to media containing only 1 mm NaCl (control nutrient solution) just prior to 24-h transpiration analyses, day- and night-time transpirational water loss rates differed much less, and were not statistically significant, between treatments (Fig. 3A). The rate of night-time transpirational water loss amounted to 12.9 % of the rate of daytime water loss in plants which had been exposed previously to 50 mm NaCl and were now growing on control nutrient solution (Fig. 3B). This percentage increased slightly, to 17.4 %, in plants which had been exposed previously to 150 mm NaCl (Fig. 3B), although this increase was not statistically significant. None of the other sizes analysed differed significantly between treatments, and this included transpirational water loss rate per unit shoot surface area during the day and night, which was highest in plants previously exposed to 150 mm NaCl (Fig. 3C, D). Fig. 3. View largeDownload slide Transpiration and root and shoot surface area of barley plants, which were originally exposed to salt stress and then transferred to control media just before transpiration analyses (‘down-stress’ experiments). Plants were 14–18 d old at the time of analyses and exposed to high NaCl-containing root media for the last 4–7 d prior to analyses. Just before being analysed for transpiration, NaCl-stressed plants were transferred to control media containing only 1 mm NaCl. (A) Rates of daytime- and night-time transpirational water loss were recorded gravimetrically and continuously over a 24-h day/night/day period. (B) Night-time transpiration rate expressed as a percentage of daytime rate. (C) Shoot and root surface area of plants. (D) Daytime and night-time transpiration rate expressed per unit shoot surface area (SSA). Results are averages and SE (error bars) of n = 5–6 plant analyses. Statistically significant (P < 0.05) differences in values between treatments are indicated by different lower-case letters. Fig. 3. View largeDownload slide Transpiration and root and shoot surface area of barley plants, which were originally exposed to salt stress and then transferred to control media just before transpiration analyses (‘down-stress’ experiments). Plants were 14–18 d old at the time of analyses and exposed to high NaCl-containing root media for the last 4–7 d prior to analyses. Just before being analysed for transpiration, NaCl-stressed plants were transferred to control media containing only 1 mm NaCl. (A) Rates of daytime- and night-time transpirational water loss were recorded gravimetrically and continuously over a 24-h day/night/day period. (B) Night-time transpiration rate expressed as a percentage of daytime rate. (C) Shoot and root surface area of plants. (D) Daytime and night-time transpiration rate expressed per unit shoot surface area (SSA). Results are averages and SE (error bars) of n = 5–6 plant analyses. Statistically significant (P < 0.05) differences in values between treatments are indicated by different lower-case letters. Up-stress. When plants were kept on control nutrient solution throughout their growth and transferred to media containing high concentrations of NaCl just prior to 24-h transpiration analyses, rates of daytime transpirational water loss were slightly lower in the 100 and 150 mm NaCl compared with 50 mm treatment, yet none of these differences was statistically significant (Fig. 4A). The rate of night-time transpirational water loss was between 13.6 and 16.3 % of the rate of daytime losses across all three treatments (Fig. 4B). Neither shoot nor root surface area changed in response to treatments (Fig. 4C). Daytime transpirational water loss rate per unit shoot surface area decreased by 30 % at the highest NaCl concentration tested, although this was not statistically significant (Fig. 4D). Fig. 4. View largeDownload slide Transpiration and root and shoot surface area of barley plants, which were grown on control medium (containing 1 mm NaCl) throughout and then exposed to salt stress just before transpiration analyses (‘up-stress’ experiments). Plants were 14–18 d old at the time of analyses. (A) Rates of daytime- and night-time transpirational water loss were recorded gravimetrically and continuously over a 24-h day/night/day period. (B) Night-time transpiration rate expressed as a percentage of daytime rate. (C) Shoot and root surface area of plants. (D) Daytime and night-time transpiration rate expressed per unit shoot surface area (SSA). Results are averages and SE (error bars) of n = 5–6 plant analyses. Statistically significant (P < 0.05) differences in values between treatments are indicated by different lower-case letters. Fig. 4. View largeDownload slide Transpiration and root and shoot surface area of barley plants, which were grown on control medium (containing 1 mm NaCl) throughout and then exposed to salt stress just before transpiration analyses (‘up-stress’ experiments). Plants were 14–18 d old at the time of analyses. (A) Rates of daytime- and night-time transpirational water loss were recorded gravimetrically and continuously over a 24-h day/night/day period. (B) Night-time transpiration rate expressed as a percentage of daytime rate. (C) Shoot and root surface area of plants. (D) Daytime and night-time transpiration rate expressed per unit shoot surface area (SSA). Results are averages and SE (error bars) of n = 5–6 plant analyses. Statistically significant (P < 0.05) differences in values between treatments are indicated by different lower-case letters. Correlation analyses. Individual plant data from the three types of experiments were pooled to test for universal correlations between night- and daytime transpiration. The rate of night-time transpirational water loss of plants was highly correlated with the rate of daytime transpirational water loss (P < 0.001, r2 = 0.713; Fig. 5A). The rate of night-time transpiration, expressed as a percentage of the day value, was correlated weakly (P = 0.031, r2 = 0.088) with the rate of daytime transpiration, increasing by about 5 % across the entire range of daytime transpiration rates measured (Fig. 5B; see linear regression line). Fig. 5. View largeDownload slide Correlation analyses between night- and daytime transpiration rates of barley plants exposed to various regimes and levels of NaCl stress. Data were taken from Figs 2–4, and each point represents a pair of values of one individual plant. (A) Correlation between the rates of night- and daytime transpirational water loss of plants. (B) Correlation between the rate of night-time transpiration, expressed as percentage of the day value, and the rate of daytime transpirational water loss. The Pearson correlation coefficient (a), P-values (b) and (c) regression coefficients (r2) were (a/b/c) (A) 0.844/<0.001/0.713; (B) 0.296/0.031/0.088. The dotted lines in A and B are linear regressions. Fig. 5. View largeDownload slide Correlation analyses between night- and daytime transpiration rates of barley plants exposed to various regimes and levels of NaCl stress. Data were taken from Figs 2–4, and each point represents a pair of values of one individual plant. (A) Correlation between the rates of night- and daytime transpirational water loss of plants. (B) Correlation between the rate of night-time transpiration, expressed as percentage of the day value, and the rate of daytime transpirational water loss. The Pearson correlation coefficient (a), P-values (b) and (c) regression coefficients (r2) were (a/b/c) (A) 0.844/<0.001/0.713; (B) 0.296/0.031/0.088. The dotted lines in A and B are linear regressions. Residual transpirational water loss from detached leaves The rate of transpirational water loss from detached leaves started to level off about 3–4 h following leaf excision (Fig. 6A). By this time, water loss through stomata, which caused initial high transpiration rates, will have contributed negligibly to water loss rates, and the residual transpiration past 3–4 h will have been dominated by cuticular water loss. The residual transpiration rate per unit leaf surface area (Fig. 6B) decreased significantly with previous exposure of plants to NaCl stress. The same applied to residual leaf (epidermal) conductance (approximating minimum cuticular conductance; Fig. 6C). Values decreased from 7.42 × 10−4 m s−1 in control plants to 2.42 × 10−4 m s−1 in plants exposed to 150 mm NaCl. In comparison, cuticular permeance determined previously (Richardson et al., 2007) for barley plants (‘Golf’) grown under control conditions, using a different approach and fully turgid leaves, was 4.9 × 10−4 m s−1 (see dotted line in Fig. 6C). Fig. 6. View largeDownload slide Residual transpiration and leaf (epidermal) conductance of barley plants. Plants used for measurement of residual transpiration were exposed to salt stress for 6 d prior to analyses (‘normal-stress’ setup) and were 16 d old. All three leaves of a plant were excised, taped at their end together with a small piece of masking tape, and weighed at 0 min, 30 min, 1 h, 2 h, 3 h, 4 h, 5 h and 6 h. The rate of fresh weight decrease was calculated for every time interval and plotted against the end point of interval. Leaf surface area (LSA) was determined at the end of the experiment. (A) Rate of fresh weight decrease with time following leaf excision. The last three measurements were taken for calculation of residual transpiration rate. (B) Residual transpiration rate per unit leaf surface area. (C) Residual leaf conductance, which is a close approximation of minimum cuticular conductance (or ‘permeance’; Schuster et al., 2016), calculated from values shown in B and using differences in water vapour concentration between the inside and outside of the leaf; for details, see Materials and Methods. The dotted line gives the value of cuticular permeance determined previously for the barley cultivar ‘Golf’ grown under control conditions and using a different approach (Richardson et al., 2007). (D) Leaf conductance during day and night calculated for the normal-, down- and up-stress treatments shown in Figs 2–4, using average values of transpiration rate per shoot surface area and following the same approach as in C; for details, see Materials and Methods section. Results in A–C are averages and SE (error bar) of n = 4 replicate plant analyses of each treatment. All treatments were derived from the same batch of plants and were analysed at the same time. (A–C) Statistically significant (P < 0.05) differences in values between treatments are indicated through different letters. Fig. 6. View largeDownload slide Residual transpiration and leaf (epidermal) conductance of barley plants. Plants used for measurement of residual transpiration were exposed to salt stress for 6 d prior to analyses (‘normal-stress’ setup) and were 16 d old. All three leaves of a plant were excised, taped at their end together with a small piece of masking tape, and weighed at 0 min, 30 min, 1 h, 2 h, 3 h, 4 h, 5 h and 6 h. The rate of fresh weight decrease was calculated for every time interval and plotted against the end point of interval. Leaf surface area (LSA) was determined at the end of the experiment. (A) Rate of fresh weight decrease with time following leaf excision. The last three measurements were taken for calculation of residual transpiration rate. (B) Residual transpiration rate per unit leaf surface area. (C) Residual leaf conductance, which is a close approximation of minimum cuticular conductance (or ‘permeance’; Schuster et al., 2016), calculated from values shown in B and using differences in water vapour concentration between the inside and outside of the leaf; for details, see Materials and Methods. The dotted line gives the value of cuticular permeance determined previously for the barley cultivar ‘Golf’ grown under control conditions and using a different approach (Richardson et al., 2007). (D) Leaf conductance during day and night calculated for the normal-, down- and up-stress treatments shown in Figs 2–4, using average values of transpiration rate per shoot surface area and following the same approach as in C; for details, see Materials and Methods section. Results in A–C are averages and SE (error bar) of n = 4 replicate plant analyses of each treatment. All treatments were derived from the same batch of plants and were analysed at the same time. (A–C) Statistically significant (P < 0.05) differences in values between treatments are indicated through different letters. Leaf conductance calculated from transpiration data of the normal-, up-stress and down-stress experiments ranged from 1.83 × 10−3 to 4.95 × 10−3 m s−1 during the day and from 2.17 × 10−4 to 1.17 × 10−3 m s−1 during the night (Fig. 6D). Contribution of cuticular and stomatal conductance to day- and night-time transpiration Leaf conductance is the sum of stomatal and cuticular conductance. Using values of leaf conductance (see Fig. 6D) and values of cuticular conductance, which was either determined previously (Richardson et al., 2007) or here as residual leaf conductance (Fig. 6C), it was possible to calculate the percentage of water which was lost through either cuticle or stomata during the day and night (Fig. 7). Residual leaf conductance had been determined for plants which had been grown under the ‘normal-stress’ setup. Therefore, the value of residual leaf conductance of control plants was used as a good indicator of residual leaf conductance in all treatments of the up-stress experiment, as cuticle properties will probably not have changed within 24 h. Similarly, the residual leaf conductance values determined for NaCl treatments were used as a good indicator of residual leaf conductance in the respective NaCl treatments of the down-stress experiment. Fig. 7. View largeDownload slide Contribution of cuticular water loss (cuticular conductance) to leaf (epidermal) conductance in barley plants, which were exposed to different salt stress treatments [normal stress: control (CTRL), 50, 100 and 150 mm NaCl; up-stress, CTRL-to-50, CTRL-to-100, CTRL to 150 mm NaCl; down-stress, 50-to-CTRL, 100-to-CTRL, 150 mm NaCl to CTRL; for details, see legends to Figs 2–4). Values of leaf (epidermal) conductance, which is the additive of stomatal and cuticular conductance, were taken from Fig. 6D. Cuticular conductance was expressed as percentage of leaf conductance (=100 %). In A, a universal value of cuticular permeance (conductance) was used (4.9 × 10−4 m s−1) as determined previously for fully turgid leaves of the barley cultivar ‘Golf’ (grown under control conditions) using a benzoic acid approach (Richardson et al., 2007). In B cuticular conductance was assumed to approach values of residual leaf conductance shown in Fig. 6C. It was further assumed that cuticular conductance did not change significantly within 24 h following transfer of plants from either stress to control (down-stress) or control to stress media (up-stress). That meant that all three treatments of the down-stress experiment had the same cuticular conductance as the respective NaCl treatments of the normal stress plants, and that all three treatments of the up-stress experiment had the same cuticular conductance as the control plants of the normal-stress experiment shown in Fig. 6C. The dotted lines in A and B indicate 10, 50 and 100 % levels. Fig. 7. View largeDownload slide Contribution of cuticular water loss (cuticular conductance) to leaf (epidermal) conductance in barley plants, which were exposed to different salt stress treatments [normal stress: control (CTRL), 50, 100 and 150 mm NaCl; up-stress, CTRL-to-50, CTRL-to-100, CTRL to 150 mm NaCl; down-stress, 50-to-CTRL, 100-to-CTRL, 150 mm NaCl to CTRL; for details, see legends to Figs 2–4). Values of leaf (epidermal) conductance, which is the additive of stomatal and cuticular conductance, were taken from Fig. 6D. Cuticular conductance was expressed as percentage of leaf conductance (=100 %). In A, a universal value of cuticular permeance (conductance) was used (4.9 × 10−4 m s−1) as determined previously for fully turgid leaves of the barley cultivar ‘Golf’ (grown under control conditions) using a benzoic acid approach (Richardson et al., 2007). In B cuticular conductance was assumed to approach values of residual leaf conductance shown in Fig. 6C. It was further assumed that cuticular conductance did not change significantly within 24 h following transfer of plants from either stress to control (down-stress) or control to stress media (up-stress). That meant that all three treatments of the down-stress experiment had the same cuticular conductance as the respective NaCl treatments of the normal stress plants, and that all three treatments of the up-stress experiment had the same cuticular conductance as the control plants of the normal-stress experiment shown in Fig. 6C. The dotted lines in A and B indicate 10, 50 and 100 % levels. Using a previously determined value of cuticular permeance for fully turgid leaf tissue of control plants of the barley cultivar ‘Golf’ (Richardson et al., 2007), cuticular conductance accounted for 10–27 % of leaf conductance during the day, and for 42 % to more than 100 % of leaf conductance during the night (Fig. 7A; for an explanation of values exceeding 100 %, see the next paragraph and Fig. 8). The two treatments which had values higher than 100 % were the 100 mm NaCl (132 %) and 150 mm NaCl (226 %) treatments of the normal-stress experiment; in particular the value for 150 mm NaCl plants pointed to a decrease in cuticular permeance at the highest level(s) of salt, as supported through data on residual leaf conductance (compare Fig. 6C). Using values of residual leaf conductance (Fig. 6C), cuticular conductance accounted for about 100 % of leaf conductance during the night in plants which had been exposed to 150 mm NaCl throughout (normal stress) and in all three treatments of the up-stress experiment. The lowest percentage contribution to leaf conductance during the night was observed for plants of the down-stress experiment (21 %, Fig. 7B). Similarly, the contribution of cuticular conductance to leaf conductance during the day was generally largest for up-stress and smallest for down-stress treatments, ranging from 5 to 27 % (Fig. 7B). Fig. 8. View largeDownload slide Correlation between the percentage contribution of stomatal conductance (L) to leaf conductance (L) during the day and night period in barley plants exposed to different regimes of salt treatments. Values were derived from the data shown in Fig. 7B, by assuming that stomatal and cuticular conductance account, together, for 100 % of leaf conductance. The Pearson correlation coefficient was 0.827, and the P-value of correlation was 0.003. The dotted line is a linear regression. Fig. 8. View largeDownload slide Correlation between the percentage contribution of stomatal conductance (L) to leaf conductance (L) during the day and night period in barley plants exposed to different regimes of salt treatments. Values were derived from the data shown in Fig. 7B, by assuming that stomatal and cuticular conductance account, together, for 100 % of leaf conductance. The Pearson correlation coefficient was 0.827, and the P-value of correlation was 0.003. The dotted line is a linear regression. Using values in Fig. 7B, the per cent contribution of stomatal conductance to leaf conductance, being the sum of cuticular and stomatal conductance, during the day and night period was calculated. The two were highly and positively correlated with each other (Fig. 8). A negative percentage contribution of stomatal conductance to leaf conductance is de facto not possible, and nor is a more than 100 % contribution of cuticle conductance (compare Fig. 7). The few slightly negative values in Fig. 8 resulted from the circumstance that stomatal conductance was calculated as the difference between leaf conductance and cuticular conductance. These latter two values were derived from independent experiments (leaf conductance, transpiration data; cuticle conductance, residual transpiration analyses). It is possible that the cuticle conductance values were artificially large (>100 %) compared with the leaf conductance values. The most likely explanation is that there was a stomatal component which contributed still significantly to residual transpirational water loss from detached leaves, leading to a significant overestimation of true cuticle conductance through the residual leaf transpiration approach. Exudation rate of excised root systems To facilitate exudate flow in NaCl-stressed plants, excised root systems had to be suspended during exudation analyses in the low-osmotic control media. Therefore, the experimental setup resembled that of the ‘down-stress’ plants during transpiration analyses. The exudation rate of excised root systems of plants analysed during the light period averaged 7.93 ± 0.67 × 10−12 m3 s−1 for plants grown under control conditions and decreased, non-significantly, in response to NaCl treatments (Fig. 9A). The same applied to plants analysed during the dark period, where exudation rates averaged 3.72 ± 0.35 × 10−12 m3 s−1 for plants grown under control conditions (Fig. 9A). The exudation rate of plants analysed during the night period accounted for 42–57 % of the exudation rate of plants analysed during the light period across treatments; the difference between exudation rates during the dark and light periods was significant (two-way ANOVAs of treatment × day-period, P < 0.001; not shown). Fig. 9. View largeDownload slide (A) Root exudation rate, and leaf (B) stomatal density, (C, D) dark respiration rate and (E) conductance for CO2, and (F) cuticle wax load of barley plants (‘normal-stress’ experiment). Plants were 14–18 d old at the time of analyses and exposed to high NaCl-containing root media for the last 4–7 d prior to analyses. The exudation rate of excised root systems was analysed for plants during the light- and dark-day period. Stomatal density and dark respiration rate was determined halfway along leaf 2, which comprised 53–64 % of the photosynthesizing and transpiring leaf area of the plants analysed, across treatments (four plants analysed per treatment; not shown). The calculated rate of gravimetric weight loss associated with dark respiration is shown in D; it accounted for less than 1 % of the measured rate of gravimetric weight loss during continuous night-time transpiration analyses; the latter data were derived from Fig. 2A. Results are averages and SE of (A) seven to eight, (B, C) six and (E, F) four plant analyses of each treatment. Statistically significant (P < 0.05) differences in values between treatments are indicated by different lower-case letters. In A, two-way ANOVA, followed by Tukey post-hoc analyses, was used to assess the statistical significance of difference in exudation rates between light and dark day-period and between treatments. The quantity of cuticular wax components and total wax load did not differ significantly between treatments. Fig. 9. View largeDownload slide (A) Root exudation rate, and leaf (B) stomatal density, (C, D) dark respiration rate and (E) conductance for CO2, and (F) cuticle wax load of barley plants (‘normal-stress’ experiment). Plants were 14–18 d old at the time of analyses and exposed to high NaCl-containing root media for the last 4–7 d prior to analyses. The exudation rate of excised root systems was analysed for plants during the light- and dark-day period. Stomatal density and dark respiration rate was determined halfway along leaf 2, which comprised 53–64 % of the photosynthesizing and transpiring leaf area of the plants analysed, across treatments (four plants analysed per treatment; not shown). The calculated rate of gravimetric weight loss associated with dark respiration is shown in D; it accounted for less than 1 % of the measured rate of gravimetric weight loss during continuous night-time transpiration analyses; the latter data were derived from Fig. 2A. Results are averages and SE of (A) seven to eight, (B, C) six and (E, F) four plant analyses of each treatment. Statistically significant (P < 0.05) differences in values between treatments are indicated by different lower-case letters. In A, two-way ANOVA, followed by Tukey post-hoc analyses, was used to assess the statistical significance of difference in exudation rates between light and dark day-period and between treatments. The quantity of cuticular wax components and total wax load did not differ significantly between treatments. Stomatal density Stomatal density of leaf 2 averaged 3.32 × 106 stomata per m2 of projected leaf surface in plants grown under control conditions (Fig. 9B). Stomatal density increased significantly in response to the two higher NaCl treatments (Fig. 9B). There was no significant difference in stomatal density between the adaxial and abaxial leaf surface in any of the treatments studied, with ratios (adaxial/abaxial) ranging from 1.14 to 1.22 (not shown). Dark respiration rate, associated mass loss and leaf conductance to CO2 The dark respiration rate of leaf 2 averaged 0.717 µmol CO2 produced/released m−2 s−1 in control plants. The respiration rate changed little in response to the 50 and 100 mm NaCl treatments, yet decreased significantly, by 38 %, in response to the 150 mm NaCl treatment (Fig. 9C). We can use the balance equation of respiration (C6H12O6 + 6O2 → 6H2O + CO2) to assess how much the mass loss associated with respiration may have contributed to the gravimetric weight loss recorded during night-time transpiration measurements. For this, we can ignore the origin of elements in the respiration equation, for example from where the O in CO2 is derived. We can neglect the 6 H2O being produced, equivalent to the 12 H and 6 O in C6H12O6, as this water will have either contributed to night-time transpirational water loss or, if kept inside the plant, led to an underestimation of true night-time gravimetric water loss through transpiration. The 12 O in the 6 CO2 are equivalent to the 12 O taken up through 6 O2. That leaves a net mass loss of 6 C, or 1 mol of C atoms (12 g) for every 1 mol of CO2 produced through respiration. Given the dark respiration rates measured, this carbon mass loss amounted to 0.27–0.76 % of the weight loss measured during night-time gravimetric transpiration analyses across all four treatments of the normal-stress experiment (Fig. 9D). Leaf conductance to CO2 averaged 5.21 × 10−3 mol m−2 s−1 in control plants and decreased non-significantly in response to salt stress (Fig. 9D). Conductance values at the highest salt treatment showed a large plant-to-plant variation (error bar in Fig. 9E). This was due to low respiration rates, causing comparatively large errors in the calculation of leaf internal CO2 concentration (Ci), and therefore CO2 conductance by the Li-Cor software. Cuticle conductance to CO2 Cuticle conductance to CO2 was calculated. If we take, for example, plants grown throughout under control conditions, dark respiration rates averaged 0.717 µmol CO2 m−2 s−1. Leaf conductance to CO2 averaged 5.21 × 10−3 mol m−2 s−1 in these plants. The question is: ‘How much of this leaf conductance to CO2 was attributable to a conductance of the cuticle?’. It is generally considered that the conductance of the cuticle, unlike that of stomata (ratio of diffusivity in air of CO2 to water vapour about 0.63; Boyer, 2015), to CO2 is much smaller than that for water vapour, as CO2 moves not only through a gaseous but also a liquid phase before reaching intercellular air spaces (Boyer, 2015; Tominaga and Kawamitsu, 2015). Cuticle conductance values for CO2 are hard to come by. Boyer et al. (1997) observed for young grapevine leaves that the cuticle conductance averaged 0.27 mmol m−2 s−1, which corresponded to 2.8 % of the leaf conductance (stomata sealed) to CO2. If we take this latter relationship, we can calculate that the leaf conductance to CO2 obtained here during dark respiration measurements of control plants equated to a cuticle conductance for CO2 of (0.028 × 5.21 × 10−3 mol m−2 s−1) 0.148 mmol m−2 s−1; this is a value close to the one determined for the cuticle of grapevine leaves (Boyer et al., 1997). The quotient of dark respiration rate and CO2 conductance equals the difference in partial pressure of CO2 between the inside and outside of the leaf (driving force). Using the above values, this driving force was ((0.716 × 10−6 mol CO2 m−2 s−1)/(0.148 × 10−3 mol m−2 s−1)) 4.84 × 10−3, or 4840 ppm. Given the ‘ambient’, external CO2 concentration during respiration measurements (approx. 400 ppm), the leaf internal CO2 partial pressure would have exceeded 5000 ppm. Similar leaf internal CO2 concentrations could be calculated for normal-stress plants exposed to salt treatments using data on dark respiration and leaf CO2 conductance shown in Fig. 9. A leaf internal partial pressure of CO2 of 5000 ppm seems to be unphysiologically high and could not only feedback negatively on CO2 production during dark respiration, but also potentially lead to acidosis of cells: an aqueous solution equilibrated with air of 350 ppm CO2 has a pH of 5.65, and solutions equilibrated with 1000 and 10 000 ppm CO2 have a pH of 5.42 and 4.92, respectively. Cuticular wax load Cuticular wax load averaged 10.6 µg cm−2 in control plants and did not change significantly in response to salt stress (Fig. 9F). This applied to the five major classes of wax components. Alcohols made up about 80 % of the cuticular wax load, with the C26 primary alcohol hexacosanol dominating this portion (not shown; see also Richardson et al., 2005) DISCUSSION Biological significance of night-time transpiration It has been argued that night-time transpiration facilitates mineral nutrient supply to the shoot to support diurnal growth (for a review, see Caird et al., 2007), although studies on nutrient-limited Arabidopsis plants do not support this idea (Christman et al., 2009a). The present data suggest that the biological function of night-time transpiration is related to the release of respiratory CO2 rather than to the release of water vapour from leaves (see also Marks and Lechowicz, 2007; Easlon and Richards, 2008). It appears that plants, such as barley, not only face the ubiquitous challenge during the day to take up as much CO2 as possible per unit water vapour lost, but also face a similar challenge during the night. Here, the challenge seems to be to allow as much CO2 to escape from leaves for as little water vapour to escape in parallel. In analogy to water-use efficiency (WUE) during the day, we may have to consider a CO2-release efficiency (‘CORE’) during the night. The present observation that rates of night-time and daytime water loss are highly correlated with each other under conditions of salt stress treatments, where absolute rates differ significantly between treatments and can change rapidly, further points to some form of regulation of night-time transpiration. The prime candidate for such regulation are stomata. One could predict that future climate change (e.g. high CO2) or experimental treatments which selectively alter the differences in VPD and CO2 partial pressure between the inside and outside of a leaf should affect the CO2/H2O release efficiency. For example, increased VPD during the night increased night-time and decreased daytime transpiration rates in wheat genotypes, yet did not affect plant biomass (carbon cost) (Claverie et al., 2016). It is likely that the changed VPD in the experiments by Claverie et al. (2016) did not impact on the driving force for night-time diffusion rates of O2 and CO2 through stomata. In addition, strong positive correlations between night-time and daytime leaf (epidermal) conductance have been reported among species and among accessions of a single species (Jordan et al., 1984; Snyder et al., 2003; Christman et al., 2008). These data, and the present observation that night- and daytime water loss rates are highly correlated with each other, could be explained through a mechanism which links night-time carbon consumption and respiration to daytime CO2 assimilation and carbon gain (or vice versa), and where this mechanism affects stomatal aperture. Night- and daytime rates of transpirational water loss The quantitative relationship between the rate of night-time and daytime transpiration hardly changed and did not differ significantly between any of the treatments tested. However, at the same time, stomata and cuticle conductance contributed to different degrees to night- and daytime water loss. Being the more dynamic of the two, the data suggest that stomata are the means through which barley plants adjust the relationship between day- and night-time water loss rates, also under salt stress. Short-term (<24 h) transpirational responses to changes in external water availability in down- and up-stress experiments exclude a significant contribution of leaf anatomical properties such as vein density, venation pattern or stomatal density (Claverie et al., 2016). Similarly, stomatal density (stomata m−2) of leaf 2 of plants which were exposed for longer periods to salt (normal-stress) increased by a maximum of 23 %, probably as a result of reduced cell expansion rates as leaf 2 had started to develop at the time stress was applied. At the same time, day- and night-time transpiration rates per unit leaf surface area decreased significantly in these plants. Recent studies on other species, including cereals, where night-time transpiration was measured in response to changes in the root (temperature, water availability) and shoot (vapour pressure deficit, VPD) environment or found to be responsive to the stomata-closing plant hormone abscisic acid, support a significant role of stomatal water loss during night-time transpiration (Mott and Peak, 2010; Rogiers and Clarke, 2013; Schoppach et al., 2014; Coupel-Ledru et al., 2016). Correlation analyses of all individual plant data gave a weak and positive correlation between the rate of night-time transpiration, expressed as percentage of the day value, and the rate of daytime transpiration. Water was lost during the night at 9–17 % the rate at which it was lost during the day, averaging 13.8 ± 0.8 % (means ± SE, n = 10) across all treatments. These values are within the range of values reported previously for plants, including cereals (Caird et al., 2007; Knipfer and Fricke, 2011; Rogiers and Clarke, 2013; Claverie et al., 2016) and saltgrass (Distichilis spicata) plants exposed to 300 and 600 mm NaCl (Christman et al., 2009b). Some of the changes in the quantitative relationship between night-time and daytime transpiration reported in the literature have been related to a dehydration or osmotic stress of plants (Coupel-Ledru et al., 2016; Claverie et al., 2016). The present data on salt- and, therefore, osmotically stressed, barley plants do not support this idea. However, what the present data show is that osmotic stress affected the relative contribution of stomatal and cuticular conductance to leaf conductance. Treatments which exposed plants either throughout to high NaCl (normal-stress, 100 and 150 mm NaCl) or suddenly (up-stress) to even moderate NaCl concentrations (50 mm NaCl, ‘moderate’ for barley) caused a large increase, whereas those treatments which caused sudden downward osmotic shock and increase in water availability to plants (down-stress experiment) caused a large decrease in the contribution of cuticular water loss to night-time transpiration. Night-time transpiration – forces driving water uptake The present data suggest that the contribution of osmotic forces and xylem tension to root water uptake during night-time transpiration can change in response to salt stress. The exudation rates measured here during the dark period on plants of the normal-stress experiment did not differ significantly between treatments. The dark-period exudation rates accounted for 41–57 % of the exudation rate measured during the light period for a particular treatment. This may reflect diurnal differences in root aquaporin activity (for a review, see Maurel et al., 2015). The experimental setup of root exudation analyses resembled that of down-stress plants, even though only the first 80 min following down-osmotic shock was analysed. When comparing the average exudation rate of plants during the dark period with night-time transpiration rates of down-stressed plants, the former amounts to 33–41 % of the latter. In down-stressed plants, mechanisms which facilitated water uptake at root level during exudation analyses could have facilitated the uptake of a significant portion of water during night-time transpiration. However, the same cannot be said about plants which had their root system exposed to NaCl throughout, including during exudation analyses. These plants showed no or very low rates of exudate flow. Small amounts of xylem tension, as a result of night-time transpirational water loss through stomata or cuticle, could provide an alternative if not additional driving force for water and mineral nutrient delivery to the shoot under such conditions. Cuticular permeance Richardson et al. (2007) used a benzoic acid approach, on intact turgid leaves, to determine cuticular permeance for barley plants (‘Golf’) grown under non-stress conditions. The authors reported a value of 4.9 × 10−4 m s−1. This value is within the range of values obtained here, using a different approach (residual transpiration) and studying a range of treatments and a different cultivar, and of permeance values reported for other plants (for reviews, see Noble, 1991; Kerstiens, 1996). The residual leaf conductance (7.42 × 10−4 m s−1) obtained here for control plants was slightly higher than the cuticle permeance reported by Richardson et al. (2007). This could point to some significant contribution of stomatal water loss and conductance to residual water loss rates determined for detached leaves. If so, the contribution of stomatal water loss to night-time transpiration would have been higher than suggested by the values in Fig. 7B. The interpretation of slightly negative values in Fig. 8 (see Results) and data on cuticle wax load (see next paragraph) supports this view. Fricke et al. (2006) found no difference in cuticular wax load between barley plants (‘Golf’) grown under control conditions and plants which had been exposed for 2–3 d to 100 mm NaCl. Similarly, no significant differences in cuticular wax load were found in the present study for treatments of the normal-stress experiments. The leaves which had been entered into wax analyses had been used before for residual transpiration analyses – and these analyses showed significant differences in residual transpiration rates between treatments. This suggests that residual transpiration also included a stomatal component, with cuticular water loss possibly not differing between treatments. An alternative explanation would be that there is no direct, positive relationship between cuticle wax load and permeance. Larsson and Svenningsson (1986) and Svenningsson (1988), studying several barley cultivars, did not find correlations between cuticular transpiration and the amount or composition of cuticular lipids in response to treatments causing water stress. In contrast, González and Ayerbe (2010) observed a negative correlation between epicuticular wax load and residual transpiration, which was not significant, in a range of barley genotypes exposed to terminal drought. However, there are reports on species other than barley which point to a decrease in leaf cuticular water loss in response to salt and drought stress (Cameron et al., 2006; Kosma et al., 2009; for a review, see Shepherd and Wynne, 2006) and where negative (cor)relations were observed between cuticular wax load and residual transpiration of detached leaves (Jordan et al., 1984; Premachandra et al., 1992; Hasanuzzaman et al., 2017). We do not know whether these differences between barley and other plant species reflect a species-specific response or result from differences in the developmental stage or experimental setup (treatments, growth conditions, analyses) between studies. Boyer (2015) demonstrated that cuticular conductance for water vapour and CO2 decreased with large decreases in leaf turgor, due to a wrinkling of the epidermal surface and tightening of the cuticle. Barley plants which are exposed to high salt concentrations retain a significant amount of turgor (0.7 MPa and more) in leaf epidermal cells (Fricke and Peters, 2002). This makes it unlikely that leaf wrinkling caused decreases in cuticular permeance in response to salt stress in intact plants, in addition to any decreases in cuticular permeance as suggested by data on residual transpiration for detached leaves. CONCLUSIONS The rates of night- and daytime transpiration in salt-stressed barley are highly correlated with each other. The present data can best be explained through stomata playing a key role in adjusting the two rates. Furthermore, the data suggest that the evolutionary driver for the occurrence of night-time transpiration in plants is not so much the facilitation of water vapour exchange and delivery of xylem-borne nutrients to the leaf, but the facilitation of sufficiently high export rates of respiratory CO2 from leaves to sustain night-time cellular metabolic activity and leaf growth. Plants such as barley not only face a water-use efficiency (WUE) but also a CO2-release efficiency (CORE) challenge. Whether a similar reasoning applies to the uptake of respiratory O2 into leaves during the night needs to be tested. SUPPLEMENTARY DATA Supplementary data are available online at https://academic.oup.com/aob and consist of the following. Figure S1: Time course of exudation rates. ACKNOWLEDGEMENTS Part of this work was carried out during internship visits by M.E. (Ecole d’Ingénieurs de PURPAN, France) and M.S (Université de Toulousse III Paul Sabatier, France) to University College Dublin, funded in part through the ERASMUS+ Mobility Traineeship Scheme. D.M. was funded through a joint CSC (Chinese Scholarship Council)/UCD PhD fellowship. Financial support by the Deutsche Forschungsgemeinschaft (GRK 2064) to L.S. and T.K. is highly appreciated. W.F. would like to thank Eugene Sherry (UCD) for help with the setup for continuous transpiration analyses and Charilaos (‘Harry’) Yiotis for help with Li-Cor analyses. W.F. would also like to thank two anonymous reviewers for some very helpful and constructive comments, and Gerhard Kerstiens for some very helpful discussions. LITERATURE CITED Boyer JS. 2015. Turgor and the transport of CO2 and water across the cuticle (epidermis) of leaves. Journal of Experimental Botany  66: 2625– 2633. Google Scholar CrossRef Search ADS PubMed  Boyer JS, Wong SC, Farquhar GD. 1997. 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Annals of BotanyOxford University Press

Published: May 30, 2018

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