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Atmospheric Environment 44 () e Contents lists available at ScienceDirect Atmospheric Environment journal homepage: africanamericanchildrenbooks.com Establishing ozone fluxeresponse relationships for winter wheat: Analysis of uncertainties based on data for UK and Polish genotypes Ignacio GonzalezeFernandez a, b,1, Agnieszka Kaminska a, c,1, Mahmadali Dodmani a, Eleni Goumenaki a, d, Steve Quarrie a, Jeremy D. Barnes a, * a Environmental and Molecular Plant Physiology, Institute for Research on the Environment and Sustainability, Devonshire Bldg., Newcastle University, Newcastle NE1 7RU, UK b CIEMAT, Ecotoxicology of Air Pollution, Avda. Complutense, 22, Madrid, Spain c Institute of Plant Physiology, Polish Academy of Sciences, ul. Niezapominajek 21, Cracow, Poland d School of Agricultural Technology, Technological Education Institute of Crete, P.O. Box , Heraklion, Greece a r t i c l e i n f o a b s t r a c t Article history: The work outlined in this paper had three objectives. The first was to explore the effects of ozone Received 28 June pollution on grain yield and quality of commercially-grown winter wheat cultivars. The second was to Received in revised form derive a stomatal ozone flux model for winter wheat and compare with those already developed for 7 November spring wheat. The third was to evaluate exposure- versus fluxeresponse approaches from a risk Accepted 11 November assessment perspective, and explore the implications of genetic variation in modelled ozone flux. Fifteen winter wheat cultivars were grown in open-top chambers where they were exposed to four Keywords: levels of ozone. During fumigation, stomatal conductance measurements were made over the lifespan of Risk assessment Modelling ozone uptake the flag leaf across a range of environmental conditions. Although significant intra-specific variation in Grain yield ‘ozone sensitivity’ (in terms of impacts on yield) was identified, yield was inversely related (R2 ¼ , Quality P < ) to the accumulated hourly averaged ozone exposure above 40 ppb during daylight hours Doseeresponse relationships (AOT40) across the dataset. The adverse effect of ozone on yield was principally due to a decline in seed weight. Algorithms defining the influence of environmental variables on stomatal uptake were subtly different from those currently in use, based on data for spring wheat, to map ozone impacts on pan- European cereal yield. Considerable intra-specific variation in phenological effects was identified. This meant that an ‘average behaviour’ had to be derived which reduced the predictive capability of the derived stomatal flux model (R2 ¼ , P < , 15 cultivars included). Indeed, given the intra-specific variability encountered, the flux model that was derived from the full dataset was no better in predicting O3 impacts on wheat yield than was the AOT40 index. The study highlights the need to use ozone risk assessment tools appropriate to specific vegetation types when modelling and mapping ozone impacts at the regional level. Crown Copyright Ó Published by Elsevier Ltd. All rights reserved. 1. Introduction altered sensitivity to a range of biotic and abiotic stresses in many common agricultural and horticultural crops (Ashmore, ; Feng Although the frequency, intensity and duration of ozone and Kobayashi, ). pollution episodes have been reduced in parts of Europe and North Losses in agricultural production attributable to ozone America over the past decade, ‘background’ levels of this air pollution are valued2 at c. V billion across Europe and North pollutant are expected to continue to rise for the foreseeable future America (Ashmore, ). Given the scale of the losses there if current emission trends persist (Dentener et al., ). This gives would appear to be a clear need for the development of risk cause for concern as the gas is phytotoxic and current levels of the assessment tools to facilitate the modelling of impacts on specific pollutant are known to be high enough to cause visible foliar injury, crops and assist strategic policy development to curb emissions. In reduced growth and yield, accelerated senescence of foliage plus Europe, a ‘Critical Levels’ approach has been adopted for ozone * Corresponding author. Tel.: þ44 ; fax: þ44 2 E-mail address: africanamericanchildrenbooks.com@africanamericanchildrenbooks.com (J. D. Barnes). Based on prices (Europe Rapid Press Releases Reference: IP/07/, 20/ 1 Authors contributing equally to this study. 12/). /$ e see front matter Crown Copyright Ó Published by Elsevier Ltd. All rights reserved. doi/africanamericanchildrenbooks.comnv  I. GonzalezeFernandez et al. / Atmospheric Environment 44 () e risk assessment (Fuhrer and Booker, ; UNECE, ). Initially, targeting parents of partially-mapped double haploid populations an exposure-based approach was employed based on the linear with a view to using the information to probe quantitative trait loci decline in crop yield resulting from cumulative exposure to ozone conferring ozone resistance; (2) derive a stomatal flux model (sensu above a threshold of 40 ppb (AOT40) during the three months of Emberson et al., ) for winter wheat to enable comparison with the growing season that the crop is most active in the field (Fuhrer similar models developed for spring wheat and compare exposure- et al., ). However, this approach was recognised to suffer versus fluxeresponse approaches; and (3) explore the extent of several serious limitations, and the introduction of models genetic variation in modelled ozone flux and highlight the delivering an estimate of ozone uptake over the lifespan of implications for pan-European modelling approaches. the crop (Emberson et al., ; Grünhage et al., ) have facilitated an improved approach where effects can be assessed in 2. Materials and methods relation to ozone uptake (i.e. effective biological dose) rather than exposure (UNECE, ). Robust ozone fluxeresponse relation- Plant cultivation ships are now available for mapping and modelling the risks posed by ozone to spring wheat and potato (Pleijel et al., ), Ten-day-old seedlings of eleven commercially-grown UK culti- and work on other crops is underway e.g. grapevine (Soja et al., vars of winter wheat (Avalon, Claire, Consort, Deben, Hereward, ), lettuce (Goumenaki et al., ), clover (Mills et al., ; Hobbit, Riband, Rialto, Soissons, Spark and Steadfast), and four Gonzalez-Fernandez et al., ), sunflower and tomato (Ember- commercially-grown Polish cultivars of winter wheat (Kamila, son et al., ). Whilst there is a general consensus that the flux Kobra, Korweta and Rywalka), were transferred in November modelling approach constitutes a significant evolution of previous to pots containing 15 dm3 of potting compost (Levington John Innes pan-European ozone risk assessment approaches (Ashmore, No. 2, compost:peat:sand []; incorporating John Innes Base ), there is recognition that current models could be improved fertilizer [ NPK] plus lime). Plants were transferred to even further by the inclusion of (1) an ozone detoxification unprotected cold frames adjacent to a glasshouse and thinned to 16 algorithm rather than the employment of an empirically-derived seedlings per pot. On 1st May , three pots per cultivar were flux threshold (Musselman et al., ), (2) consideration of randomly assigned to each of twelve open-top chambers (three effects on crop quality as well as yield (see Gonzalez-Fernandez OTC replicates per ozone treatment) situated at Newcastle Uni- et al., ) and (3) potential regionalisation of modelling versity's Close House Field Station at Heddon-on-the-Wall, North- approaches to account for local edaphic and plant-specific umberland, in Northern England (latitude 54 N, longitude variances (Fuhrer and Booker, ; Fiscus et al., ). 1 W, elevation 30 m.a.s.l.). The site is upwind of major Because of the importance of wheat production to the European conurbations and background levels of SO2 and NOx are known to economy much attention has focused on assessing the risks posed to be intrinsically low at this rural locality (see Wilbourn et al., ). this crop by ozone pollution. Across the EU, wheat occupies the The m2 of floor space in each OTC was divided into three, and greatest area (around 25 million ha are grown each year), exhibits one pot of each cultivar randomised within each division. All OTCs the largest production (c. million tonnes of grain in ) and were ventilated with non-filtered air (NFA). On 7th May, ozone was delivers the greatest economic value (worth c. V billion based injected in to the ductwork ventilating nine of the twelve chambers on end escalated prices due to rising fuel costs, increasing (with ozone treatments randomly assigned to chambers) to achieve demand for agricultural products and changing production four targeted daytime (7 h d 1 (e) treatments: NFA, strategies). It is thus surprising, given the overwhelming commer- NFA þ 25 ppb O3, NFA þ 50 ppb O3 and NFA þ 75 ppb O3) delivering cial importance of winter wheat across the EU, as well as in other a seasonal (6 May to 5 August) accumulated hourly mean ozone parts of the world, that the vast majority of ozone-related research exposure above 40 ppb (AOT40) of , , 13 and on wheat has focused on spring-sown genotypes (see meta-analysis 18 ppb h, respectively. Each OTC was ventilated (day and night) by Feng et al., ). This extensive body of work reveals modern via a perforated annulus positioned m above ground-level via hexaploid wheat (Triticum aestivum L.) to be one of the most ozone- a fan supplying sufficient particulate-filtered air (non-filtered air: sensitive crops identified to date (Mills et al., ). Exposure to NFA) to achieve two air changes min 1 in each chamber. Ozone was a 7-h seasonal mean [O3] of 72 ppb reduces wheat grain yield by generated from oxygen by electric discharge (Model SGC22, Pacific c. 30% (Feng et al., ). However, considerable, heritable, variation Ozone Technology, Benicia, California USA) and supplied to in sensitivity (especially impacts on grain yield) is known to exist O3 chambers following dilution in a stream of clean compressed between cultivars (Barnes et al., , ; Velissariou et al., ; air. Ozone levels were logged and controlled using a feedback Biswas et al., ) and the genetic basis for this variation remains to regulation system based around a motorized voltage regulator, be dissected and understood (see Quarrie et al., ). rather than mass flow controllers. Further details of the OTC facility There has been considerable investment in quantifying ozone and ozone control systems are provided in Gonzalez-Fernandez effects on agricultural production, but little attention has been paid et al. (). to integrating effects on crop quality or organoleptic characteristics Plants were watered as required throughout the experiment to into current risk assessment approaches despite known effects of ensure a soil moisture content sufficient to support uninterrupted pollutants such as ozone on nutritional aspects (Fuhrer and Booker, growth, and were sprayed with a combination of pesticides (‘Radar’ ) and important quality-related attributes of crops such as and ‘Malathion 60’). Plants were fertilised at fortnightly intervals grapes (Soja et al., ), cotton (Heagle et al., ), oilseed rape using liquid fertilizer ‘Nitro-Top’: % N. (Bosac et al., ), soybean (Heagle et al., ), bean (Tingey et al., ) and potato (Vorne et al., ). Previous studies on bread Measurement campaign wheat, for example, reveal ozone-related increases in grain protein content (GPC), Zéleny value and Hagberg Falling Number; variables Environmental variables providing an indication of the bread-making quality of flour (Pleijel Ozone concentrations were monitored at canopy height in the et al., ; Piikki et al., ). centre of each OTC via a solenoid-based time-share system using The purpose of the present study was to (1) explore the extent of a photometric analyser (Dasibi Environmental Corporation (Dasibi) genetic variation in the effects of O3 on grain yield and quality- Model Ultraviolet (UV) Photometric Ozone Analyzer, Series related characteristics in commercially-grown winter wheat, PC; Dasibi Environmental Corporation, W. Colorado St.,  I. GonzalezeFernandez et al. / Atmospheric Environment 44 () e Glendale, California ), serviced weekly and cross- a boundary line approach to a data cloud containing checked against a similar unit calibrated against NPL standards. measurements of gH2 O made on flag leaves borne on the primary Photosynthetically-active radiation (PAR), air temperature and shoot over a range of conditions over the leaf lifespan (sensu relative humidity were recorded with cross-referenced sensors Emberson et al., ). This technique assumes the line connecting using a combination of loggers (Sentry Intelisys Ltd, Manchester, data points at the outer margin of the data cloud depicts UK and Delta-T Devices Ltd, Cambridge, UK), and all environmental the maximum possible gH2 O for a given value and thus the func- measurements were made at the position occupied by the flag leaf tional dependency between the plotted variables (Jarvis, ; (in one OTC). Emberson et al., ). A minimum stomatal conductance (fmin) was considered in the model based on gH2 O measurements Stomatal conductance taken over-night during the course of the experiment. Adaxial stomatal conductance to water vapour ðgH2 O Þ was Factors considered to modify gmax were: photosynthetically- measured in the mid-region of the flag leaf at regular intervals over active radiation (light), air temperature (temp), vapour pressure it's lifespan across a range of monitored environmental conditions. deficit (VPD), phenology (phen) and accumulated stomatal ozone Measurements were made with cross-referenced AP4 Porometers flux (AFst0) (Pleijel et al., ). Soil water potential (SWP) was not (Delta-T Devices, Ltd, Cambridge, UK). Data were expressed on considered, as plants were kept well-watered throughout. The a projected leaf area basis, accounting for the total:adaxial surface influence of VPD on stomatal conductance in the afternoon was also conductance ratio () exhibited by the flag leaf of wheat considered using the VPD function (sensu Pleijel et al., ). A P (Amundson et al., ; Araus et al., ). phenological weighting factor, used to describe the reduction Web resources were used to identify all peer-reviewed literature in gH2 O as leaves age and senesce, was determined using reporting stomatal conductance measurements for wheat raised in a temperature sum (tt). For this purpose, the mean value between the field. Following the quality criteria outlined in Pleijel et al. maximum and minimum daily temperature was used, employing () 17 field studies (spanning Europe, America and Asia, and a basal temperature of 0  C (sensu McMaster and Wilhelm, ). covering 27 cultivars of spring and winter wheat) were identified Circadian influences on stomatal conductance resulting in partial from which maximum stomatal conductance values were obtained stomatal closure during the afternoon were also taken into account (see Appendix 2) normalised on a projected leaf area basis. Of those by deriving ftime from boundary line analysis of diel gH2 O (sensu identified, 3 of the studies on spring wheat (delivering data for 5 Danielsson et al., ). The fphen function includes a plateau of cultivars) contributed to the wheat flux model derivation in the maximum activity around anthesis before decreasing towards the UNECE Mapping Manual (UNECE, ). Stomatal conductances to end of the experiment. The fAFst function takes into account the O3 CO2 were transformed to account for the difference in diffusivity cumulated flux effect. The flight, ftemp and fVPD functions account for between CO2 and H2O in air; DCO2 =H2 O ¼ (Larcher, ). short-term effects of photosynthetically-active radiation, air Stomatal conductance to O3 ðgO3 Þ were calculated based on the temperature and VPD on gmax. The time window selected for the difference in diffusivity between O3 and H2O in air; flag leaf accumulation of O3 flux was set from 10 May to 14 July DO3 =H2 O ¼ (Nobel, ). , from tt ¼  C day (about three weeks before the average date of anthesis) to  C day after anthesis (about four weeks after Stomatal conductance model and estimation average date of anthesis), by which time the flag leaf of most of the of ozone flux (AFstY) genotypes was displaying visible signs of senescence. Measurements of gH2 O and meteorological parameters were Calculations of O3 uptake per unit leaf projected area (Fst) were used to parameterise a Jarvis-style (Jarvis, ) model where gH2 O based on the guidelines provided in the CLRTAP Mapping Manual is estimated from a multiplicative function describing the manner (UNECE, ) (see Appendix 1). Ozone flux estimates were in which gH2 O responds to key species-specific and environmental based on the hourly mean O3 concentration and considered quasi- variables via effects on maximum stomatal conductance (gmax). laminarity plus cuticular resistances. The wind speed used for the Equation (1) shows the model used to derive gH2 O for winter quasi-laminar resistance was m s 1; representing the air flow in wheat: the OTCs employed for the investigation. n o n o Stomatal flux was accumulated on an hourly basis over the gH2 O ¼ gmax $min fphen ; fO3 $min flight ; ftime lifespan of the flag leaf and the effect of different flux thresholds (Y) n on doseeresponse relationships examined. The predictive capacity o of the derived stomatal flux model was compared with the existing  $max fmin ; ftemp $fVPD $fSWP (1) DO3SE model based on data for spring wheat grown in Northern Where, gH2 O represents the stomatal conductance to water vapour and Central Europe (UNECE, ). of the flag leaf expressed per unit projected leaf area (mmol m 2 s 1); gmax represents maximum stomatal conductance; Yield and yield components fphen represents the influence on phenology on gmax; fO3 represents Plants were harvested over a ten-day-period at full maturity the effects of accumulated ozone stomatal flux (AFst0 in mmol m 2) (7e17 August ). The ears from the tallest plant in each pot on gmax (an attempt to simulate effects of ozone on flag leaf were bagged separately from those of the remaining plants, and senescence); flight, ftime, ftemp and fVPD represent the influence of these were employed for subsequent detailed yield component photosynthetically-active radiation, time of day, air temperature analysis. Remaining ears were mechanically threshed, then grain and vapour pressure deficit on gmax, respectively; fmin represents number and weight recorded. minimum stomatal conductance; fSWP represents the influence of Measurements of grain protein content (GPC) and a-amylase soil water potential on gmax. For this well-watered experiment fSWP (AA) activity were restricted to one ‘sensitive’ and one ‘resistant’ was set at 1. cultivar: ‘Rialto’ and ‘Hereward’, respectively. Grain was ground Maximum stomatal conductance was calculated based on the using a pestle and mortar, and the resulting flour sieved ( mm average gH2 O above the 90th percentile (sensu Gonzalez-Fernandez mesh size) prior to analysis. Total nitrogen content was determined et al., ). fmin was calculated as the average of gH2 O values below by combustion using a LECO Model FP C:N analyser, calibrated the 10th percentile for night-time measurements. The relationship with EDTA and data reported on the basis of 14% moisture content. between gH2 O and the climatic variables was analysed by applying Protein content was calculated by multiplying grain nitrogen  I. GonzalezeFernandez et al. / Atmospheric Environment 44 () e content by (Williams et al., ). a-Amylase activity was revealed the relatively low predictive capacity of the model to be determined using a kit (Megazyme, Bray, Ireland) based on an assay due, at least in part, to plant-to-plant variability across the dataset. described by McCleary et al. (). The Falling Number (FN), Maximum stomatal conductance derived from the data cloud sometimes known as the Hagberg Index, a descriptor of the bread- for winter wheat was  21 mmol O3 m 2 s 1 with considerable making quality of wheat flour, is inversely proportional to variation in gmax between cultivars; values ranged between and a-amylase activity (Olered, ). mmol O3 m 2 s 1 across the 15 cultivars used in the study (Table 2). Furthermore, the gmax recorded was not significantly different from the value (  52 mmol O3 m 2 s 1) derived Statistical analyses previously for spring wheat from field studies (see Table 1). A review (Table 2) of the peer-reviewed literature lends support to Effects were tested by ANOVA, using SPSS v (SPSS Inc., our observations, revealing considerable variation in gmax between Chicago, USA), with a confidence level of 95%. Normality and vari- cultivars, but no significant difference in gmax between spring and ance homogeneity were examined prior to every analysis. When winter genotypes, although winter wheat appears to consistently necessary, KruskaleWallis or U ManneWitney tests were used, exhibit lower gmax (bar a single study). gmax measured in the otherwise statistical significance was determined using the least present pot-based study ( mmol O3 m 2 s 1) was higher significant difference (LSD) calculated at the 5% level. First, (P < ), rather than lower, than equivalent measurements positional and chamber effects were tested by ANOVA. No signifi- reported from previous field studies ( mmol O3 m 2 s 1). cant influences were detected, so data were analysed on the assumption that plants in replicate chambers were as likely to be as similar to, or as different from, plants within an individual chamber. Impacts of ozone on yield and yield components Linear regressions were performed to examine exposure- and doseeresponse relationships (based on relative effects) using the Exposure to ozone significantly (P < ) reduced the weight of principles described in Fuhrer () where linear regressions are grain recovered per plant. The loss in yield was predominantly due performed for each individual genotype and then each response to a reduction in thousand grain weight (TGW) and the number of value is divided by the intercept of its regression equation so that seed produced per plant (principally a consequence of a decline in zero O3 exposure or dose is always associated with no effect (%). grain number per ear) (Table 3). There was no significant change in Analysis of exposure- and doseeresponse relationships considered the number of ears produced per plant. Not unexpectedly, there all genotypes together, plus ‘sensitive’ and ‘resistant’ cultivar was significant (O3*Group P < ) variation between cultivars in groups separately. Graphs were drawn e using SigmaPlot the extent of the yield depression induced by ozone, and a group of (Systat Software, Inc.). six ‘sensitive’ cultivars was statistically discernible (P < ) from a group containing six ‘resistant’ cultivars (Table 3). The ‘sensitive’ group comprised Claire, Consort, Deben, Korweta, Rialto and 3. Results Steadfast, which exhibited an average depression in grain yield of 32% in the NFA þ 75 treatment. In contrast, the ‘resistant’ group, Stomatal conductance model comprising Hereward, Kamila, Kobra, Riband, Soissons and Spark, exhibited only a 17 % depression in grain yield in the NFAþ75 Table 1 shows boundary line functions derived for winter wheat treatment. No significant differences (P ¼ ) were found in the and provides a direct comparison with those derived from data for impacts of ozone on the yield of UK and Polish genotypes. Strong spring wheat, and currently in use for pan-European UNECE risk linear ozone exposure [AOT40]eresponse relationships were assessment. Our winter wheat model explained 49% (P < ) of evident for key yield determinants (Fig. 2). Several AFstY the variation in measured stomatal conductance and up to 55% indices were tested (Table 4). The strongest ozone fluxeresponse (P < ) of the hourly averaged gH2 O (employed for estimating relationships (for relative yield) employed a threshold of ozone flux). Fig. 1 illustrates the derived model tended to over- 14 nmol O3 m 2 s 1 (R2 ¼ , P < ), but there was little estimate stomatal conductance, and analysis of hourly average gH2 O difference in the goodness of fit between thresholds ranging from 8 Table 1 Parameterizations of stomatal conductance ðgH2 O Þ model. gmax maximum stomatal conductance; fmin minimum stomatal conductance; fphen phenological weighting factor; tt temperature sum ( C day); fO3 accumulated ozone stomatal flux (AFst0 in mmol m 2) effect on flag leaf senescence; light, photosynthetic active radiation; time, time of day (calculated as hour/24); temp, temperature ( C); VPD, vapour pressure deficit (kPa). Parameter Winter wheat (this study) Spring wheat (UNECE, ) Time window Start:  C day (three weeks before anthesis) Start:  C day (two weeks before anthesis) End:  C day (four weeks days after anthesis) End:  C day (40 days after anthesis) gmax mmol O3 m 2 s 1 mmol O3 m 2 s 1 fmin fphen If tt   C day; y ¼ 1/(1 þ $ 10 3 $ exp( $ tt)) If tt < 0  C day; y ¼ 1 (/) $ ( tt) If tt >  C day; y ¼ 1/(1 þ $ 10 4 $ exp( $ tt)) If tt  0  C day; y ¼ 1 (/) $ tt fO3 y ¼ 1/(1 þ exp( $ (AFst0 ))) y ¼ 1/(1 þ (AFst0/)10) flight y ¼ 1 exp( $ PAR) y ¼ 1 exp( $ PAR) ftime If time < ; y ¼ 1/(1 þ 19 $ exp( 30 $ time)) Not applicable If time  ; y ¼ 1/(1 þ $ 10 9 $ exp( $ time)) ftemp If  C  T   C; If 12  C  T  40  C; y ¼ [((T )/) $ (( T)/)] y ¼ [((T 12)/14) $ ((40 T)/12)]1 y ¼ y ¼ fVPD If VPD < kPa; y ¼ 1 If VPD < kPa; y ¼ 1 If kPa  VPD  3 kPa; If kPa  VPD  kPa; y ¼ (( e $ VPD)/) þ y ¼ (( e $ VPD)/2) þ If VPD > 3 kPa; y ¼ If VPD > kPa; y ¼  I. GonzalezeFernandez et al. / Atmospheric Environment 44 () e a b c Fig. 1. Linear regressions (solid lines) of modelled versus measured stomatal conductance ðgH2 O Þ: a) instantaneous gH2 O ; b) Hourly averaged gH2 O , bars depict standard error. Dashed lines represent the reference line; c) Mean diurnal variation of measured (closed circles) and modelled gH2 O (open circles and dashed line). Bars depict the standard deviation of measured values. to 14 nmol O3 m 2 s 1 (R2 ¼ e). Ozone fluxeresponse exposure (Fig. 4) but ‘sensitive’ and ‘resistant’ genotypes appeared relationships (for relative yield) were, however, significantly to respond similarly. (P < ) improved through the use of a cut-off threshold above AOT40 and AFstY indices appeared roughly equivalent in terms 4 nmol O3 m 2 s 1. Employing AFst14 to the ‘sensitive’ genotypes of explaining the variance in ozone impacts on yield and yield improved the R2 for the ozone fluxeresponse relationship (for components (Fig. 2). One contributor to this finding is the con- relative yield) to (P < ). The loss in yield induced by ozone founding influence of the variation between cultivars in measured appeared to be partially offset by an increase in GPC (Fig. 3). gmax (Table 2). To highlight the potential significance of cultivar However, protein yield per plant was not significantly affected by variation in gmax, Fig. 5 shows cumulative modelled O3 uptake over ozone. a-Amylase activity was also positively related with O3 the course of the season employing extremes in gmax recorded in the present study for UK winter wheat cultivars as well as for the extremes taken from the peer-reviewed literature. This approach reveals potential variation in estimated O3 uptake in the order 32% Table 2 between UK cultivars, rising to 79% if extremes reported in the Literature review of maximum stomatal conductance (gmax) to ozone (normalised literature are employed for O3 flux estimation. on a projected leaf area basis) for wheat flag leaves. Reference gmax Country No. (mmol O3 m 2 s 1 ) Genotypes 4. Discussion Winter wheat dataset (this study)a e UK 15 Winter wheat Stomatal flux model for winter wheat EU Müller et al., Germany 1 Table 1 illustrates the close agreement in the boundary lines for Tuba et al., a Hungary 1 PAR, T and VPD between the current gH2 O model derived from data World for spring wheat (UNECE, ) and measurements made on Bunce, a USA 1 Jiang et al., e China 5 winter wheat in the present study. However, substantial differences Shen et al., China 1 were evident in fO3 functions; with winter wheat appearing less Xue et al., e USA 4 responsive to increases in AFst0 values than spring wheat. This Yu et al., China 1 conclusion is generally consistent with the reported differences in Mean value stomatal response to ozone between spring and winter wheat (see Median review by Feng et al., ). There were also marked differences Spring wheat between spring and winter wheat in the fphen function. State-of the- EU art spring-wheat models incorporate a ‘plateau’ to simulate the Ali et al., Denmark 1 high gH2 O values recorded after anthesis (Uddling and Pleijel, ), Araus et al., e Spain 3 but this clouds genotypic variability in the timing of anthesis. The Araus and Tapia, Spain 1 Danielsson et al., a Sweden 1 new fphen relationship for winter wheat yields a maximum shift Del Pozo et al., Spain 1 Mulholland et al., a UK 1 Pleijel et al., ,b Sweden 1 Table 3 ANOVA illustrating ozone impacts on yield and quality parameters for ‘sensitive’ and World ‘resistant’ genotype groups. García et al., USA 1 Sato et al., Syria 5 ANOVA Seed Seed Thousand Grain protein a-Amylase Wall et al., USA 1 weight number grain weight contenta activitya Mean value O3 < < < < < Median Group < < < a O3  group Experiments employing OTCs. b a Conference proceedings (not peer-reviewed). Data for Rialto and Hereward.  I. GonzalezeFernandez et al. x y 10 x y 10 x R P R P R P 20 Sensitive : Sensitive : Sensitive : 20 y x y 10 x y 10 x R P R P R P 0 0 0 0 0 AOT40 (ppb.h) AOT40 (ppb.h) AOT40 (ppb.4x 40 y x y x R P R 0,38 P 0, R P 20 Sensitive : Sensitive : Sensitive : 20 y x y x y x R P R P R P 0 0 AFst14 (mmol m-2) AFst14 (mmol m-2) AFst14 (mmol m-2) Fig. 2. Ozone exposure and dose effects on yield components of winter wheat. Ozone exposure was expressed as AOT40 (ppb h), accumulated ozone exposure over a threshold of 40 ppb. Ozone dose was expressed as accumulated stomatal flux of ozone above a threshold of 14 nmol m 2 s 1 (AFst14 (mmol m 2)). Filled circles fitted by the dashed line represent ‘sensitive’ genotypes (Claire, Consort, Deben, Korweta, Rialto, Steadfast); open circles and solid line represent ‘resistant’ genotypes (Hereward, Kamila, Kobra, Riband, Soissons, Spark). Dotted lines represent 95% confidence intervals. of 12% in modelled gH2 O compared to fphen for spring wheat. In and (Danielsson et al., ; Büker et al., ). Over- addition, a function representing the influence of time of day on estimation of low conductance values measured during the after- relative gH2 O ðftime Þ was included in our winter wheat model to noon maybe explained by the reduced sensitivity of stomata to VPD simulate circadian changes in gH2 O (sensu Danielsson et al., ). during the late afternoon (Elvira et al., ), suggesting that some This approach was adopted in preference to the VPD function diurnal changes in stomatal function may reflect circadian shifts in P used in the DO3SE model (Pleijel et al., ) as adoption of the metabolism (Chaves et al., ) or plant water potential over the VPD function was found to reduce the R2 of predicted versus course of the day (Pleijel et al., ). In the present study, over- P measured gH2 O . This possibly reflects the fact that non-limiting VPD estimation of afternoon conductance was tempered by means of values ( kPa on average) were maintained throughout the the ftime function. In the present study, 55% of the hourly variability experiment (plants were kept well-watered). of gH2 O was explained by the derived model, and up to 93% of the Our model tended to overestimate gH2 O (see Fig. 1) a frequently mean diurnal variation in gH2 O . One confounding factor maybe the encountered situation employing a multiplicative approach to high variability in gH2 O measurements e a factor at least partly the derivation of such stomatal flux models e with different attributable to genetic variation in gmax (Table 2). Using genotype- parameterizations yielding R2 values typically ranging between specific gmax in the multiplicative model for winter wheat reduced Table 4 Coefficients of determination (R2) and linear regressions of relative yield versus AOT40 or AFstY employing a range of flux thresholds (Y, nmol m 2 s 1). Analyses based on entire dataset (all 15 cultivars); ‘Sensitive’ cultivars: Claire, Consort, Deben, Korweta, Rialto and Steadfast. ‘Resistant’ cultivars: Hereward, Kamila, Kobra, Riband, Soissons and Spark. All regressions were significant at the % level. AOT accumulated hourly mean ozone exposure over a threshold of 40 ppb during daylight hours (>50 W m 2). AOT40 AFst0 AFst4 AFst6 AFst8 AFst10 AFst12 AFst14 AFst16 All y¼ x þ y ¼ x þ y¼ x þ y ¼ x þ y ¼ x þ y ¼ x þ y ¼ x þ y ¼ x þ y¼ x þ R2 ¼ R2 ¼ R2 ¼ R2 ¼ R2 ¼ R2 ¼ R2 ¼ R2 ¼ R2 ¼ Sensitive y ¼ x þ y ¼ x þ y¼ x þ y ¼ x þ y ¼ x þ y ¼ x þ y ¼ x þ y ¼ x þ y¼ x þ R2 ¼ R2 ¼ R2 ¼ 2 R ¼ 2 R ¼ 2 R ¼ 2 R ¼ R2 ¼ R2 ¼ Resistant y ¼ x þ y ¼ x þ y¼ x þ y ¼ x þ y ¼ x þ y ¼ x þ y ¼ x þ y ¼ x þ y¼ x þ R2 ¼ R2 ¼ R2 ¼ R2 ¼ R2 ¼ R2 ¼ R2 ¼ R2 ¼ R2 ¼  I. GonzalezeFernandez et al. / Atmospheric Environment 44 () e Crude protein concentration Resistant : Relative effect (%) y x Relative effect (%) R P Sensitive : y x 80 R P 0 .1 60 Protein yield Resistant : y 10 x 40 R , ns. Sensitive : 20 y 10 x R , ns. 0 0 0 AOT40 (ppb.h) AOT40 (ppb.h) Crude protein concentration Resistant : Relative effect (%) y x Relative effect (%) R P Sensitive : y x 80 R P 60 Protein yield Resistant : y x 40 R , ns. 20 Sensitive : y x R , ns. 0 AFst14 (mmol m-2) AFst14 (mmol m-2) Fig. 3. Ozone exposure and dose effects on grain protein of winter wheat. Ozone exposure expressed as AOT40 (ppb h), accumulated ozone exposure over a threshold of 40 ppb. Ozone dose expressed as accumulated stomatal flux of ozone above a threshold of 14 nmol m 2 s 1 (AFst14 (mmol m 2). Filled circles fitted by the dashed line represent the ‘sensitive’ genotype Rialto; open circles and solid line represent the ‘resistant’ genotype Hereward. the root mean square error by nearly 30%, from mmol m 2 s 1 approaches for the prediction of gH2 O (Emberson et al., ; (using a fixed gmax) to mmol m 2 s 1 (using genotype-specific Tuovinen et al., ). A critical review of the available literature gmax), though there was little effect on R2 (R2 was improved from (Table 2) revealed no difference in gmax between spring and winter to employing a fixed versus variable gmax). gmax consti- wheat. x y x R P R P Sensitive : Sensitive : y x y x R P R P 0 AOT40 (ppb.h) AFst14 (mmol m-2) Fig. 4. Ozone exposure and ozone dose effects on a-amylase activity of winter wheat. Ozone exposure expressed as AOT40 (ppb h), accumulated ozone exposure over a threshold of 40 ppb. Ozone dose expressed as accumulated stomatal flux of ozone above a threshold of 14 nmol m 2 s 1 (AFst14 (mmol m 2). Filled circles fitted by the dashed line represent the sensitive genotype Rialto; open circles and solid line represent the resistant genotype Hereward.  I. GonzalezeFernandez et al. / Atmospheric Environment 44 () e 20 (Quarrie et al., ). Whilst several studies have focused on the impacts of ozone pollution on wheat yield, far less attention has been paid to effects on grain quality, and no Critical Levels or 15 Critical Fluxes currently consider effects on crop quality alongside AFst 0 (mmol m -2 ) productivity (see Gonzalez-Fernandez et al., ). In wheat 79% trading, GPC and a-amylase activity are frequently considered as 10 quality grading factors, determining the end use and price of the 32% grain (Lawlor and Mitchell, ). Yet, scant attention has been paid to O3 effects on grain quality aspects (Piikki et al., ). In this 5 study, O3 exposure increased GPC and a-amylase activity (Figs. 3 and 4) and although intra-specific variability in responses to the 0 pollutant was evident, the improvement in grain quality in elevated ozone would partially offset the negative effects on yield in terms of revenue generation. This conclusion is generally consistent with other reports in the literature (Piikki et al., ). 10/05 24/05 07/06 21/06 05/07 A meta-analysis of the impacts of elevated O3 on wheat has Date revealed greater effects on photosynthetic characteristics of plants Fig. 5. Accumulated stomatal ozone flux (AFst0) (mmol m 2) calculated using the raised in the field versus those grown in small pots (<5 dm3), while range of gmax values found. The bold solid and dashed-dotted lines represent the AFst0 effects on aboveground biomass show the corollary (Feng et al., using a gmax of  31 and  18 mmol O3 m 2 s 1 respectively. Dotted lines ). Although ozone effects presented in this work are within the represent the variation in AFst0 calculated using gmax values reported in the literature (e mmol O3 m 2 s 1). range reported in previous studies, it is possible that our findings along with those of previous authors, have been influenced by the use of OTC and the adoption of potted plants. This will only be determinable when the results of field studies using free-air studies where data for multiple genotypes is reported e.g. 58% fumigation systems are available. variation was reported across Chinese varieties (Jiang et al., ) AOT and the AFst (derived using a threshold of and 21% across US varieties (Xue et al., ). The variability in 14 nmol m 2 s 1) performed equally well, yielding similar R2 for all gmax would be considerably greater (c. 79%) were the same multi- relationships (Figs. 2e4 and Table 4). In the present study, AOT40 plicative models to be adopted globally. and AFst14 were strongly correlated (r ¼ ) one likely reason for Model overestimations of conductance were common around this is the lack of climatic variability which would also help explain anthesis over a range of climatic conditions, suggestive of intra- the lack of difference in the performance of flux-based and expo- specific differences in phenological development. A specific sure-based O3 indices. Previous studies on spring wheat suggest regional derivation of fphen for the genotypes common in a local that flux-based indices generally out-perform AOT40 across area would improve the estimation of gH2 O , in contrast to the experiments performed over a range of climatic conditions, across current ‘one size fits all’ approach. Whilst the implications of using years and sites (Pleijel et al., ). But this has not always proven a fixed fphen compared with a genotype-specific fphen have not been to be the case. For example, Karlsson et al. () combined data analysed in the present study, genotypes growing in the same OTC for tree species and found AOT40 to perform slightly better than showed variation in the order of 15 days in the timing of anthesis cumulative flux in predicting effects. This possibly reflects (data not shown). Thus, a source of uncertainty maybe the uncertainties in the parameterization of the underlying model of genotypic variability in phenology. stomatal conductance (Ashmore, ). gmax and flux threshold The reduced predictive capabilities of stomatal flux models have a strong influence on the modelled AFstY values (Fig. 5) used resulting from genetic/regional variation in gmax and fphen highlight to derive doseeresponse relationships. Moreover, the best- a need to consider the development of regional model performing flux index used a higher cut-off threshold than that parameterizations to improve local ozone risk assessment proce- usually employed in the derivation of fluxeresponse relationships dures through better estimation of gH2 O . for spring wheat (Danielsson et al., ; Pleijel et al., ). This disparity between models could be the result of differences in Genotypic variability of O3 effects on grain yield gmax values and/or a higher intrinsic defence capability in winter and quality-related characteristics versus spring wheat e a view supported by the difference in fO3 function for spring (Pleijel et al., ) and winter (Table 1) wheat. The threshold AOT40 at which the first statistically significant adverse effects on yield were encountered in winter wheat was Implications for pan-European modelling approaches ppb h, which compares favourably with the threshold for effects derived from spring wheat ( ppb h). The highest ozone Despite the uncertainties described elsewhere (Musselman exposure employed in the present study (NFA þ 75, 18 ppb h) et al., ), the advantages of the flux-based approach to risk resulted in an average loss in wheat yield of 25%. This compares assessment are clear. It constitutes a physiologically-relevant favourably with the available literature which suggests a 7 h day 1 representation of the phenology of the crop (Pleijel et al., ), seasonal average O3 exposure of 42 ppb results in a loss in spring- takes account of the year-to-year variation in environmental wheat yield of 10e20% (Feng et al., ). Genotypes showed conditions that may affect the period of maximum O3 sensitivity considerable variation in their response to the same ozone expo- (Pleijel et al., ) and considers environmental variation sure (i.e. there was evidence of considerable intra-specific variation between sites. However, current models are derived from data for in ‘O3 sensitivity’); losses in yield in the ‘resistant’ and ‘sensitive’ spring wheat. The data presented in this paper indicate a need to groups varying between 17 and 32% respectively in response to an consider differences between spring and winter wheat in the AOT40 of 18 ppb h. The genetic basis for this variation is poorly understood, but such findings suggest there maybe scope for breeders to select genotypes with enhanced ozone tolerance 3 Considered in EU O3 pollution regulations (Directive /50/EC).  I. GonzalezeFernandez et al. / Atmospheric Environment 44 () e sensitivity of gH2 O to AFst0, the fphen function and flux thresholds, Xh AFst Y mmol m 2 ¼ 2 1     Fst Y nmol m s in order to better qualify the impacts of ozone on wheat at a pan- i European level. Moreover, the genetic variation observed in gmax, $ s h 1 $10 6   ð2AÞ phenological development and O3 sensitivity in the present study highlights uncertainties for the development of ozone risk Where Y represents the flux threshold. assessment exercises at the European and worldwide scale, and illustrates a need for the development of regionalized risk Appendix 2. References used in review of wheat gmax assessment approaches applicable to local crops and conditions. Ali, M., Jensen, C.R., Mogensen, V.O., Andersen, M.N., Hensen, I.E., Root sig- nalling and osmotic adjustment during intermittent soil drying sustain grain yield of field grown wheat. Field Crops Research 62, 35e 5. Conclusions Araus, J.L., Tapia, L., Photosynthetic gas exchange characteristics of wheat flag leaf blades and sheaths during grain filling. Plant Physiology 85, e Widely-grown winter wheat exhibited O3-induced yield Araus, J.L., Tapia, L., Alegre, L., The effect of changing sowing date on leaf structure and gas exchange characteristics of wheat flag leaves grown under reductions equivalent to those displayed by spring wheat, and Mediterranean climate conditions. Journal of Experimental Botany 40, these relationships currently provide the cornerstone data to assess e the impacts of ozone pollution on cereal yield across Europe. Bunce, J.A., Responses of stomatal conductance to light, humidity and temperature in winter wheat and barley grown at three concentrations of However, the data presented in this manuscript indicate a need to carbon dioxide in the field. Global Change Biology 6, e consider differences between spring and winter wheat in the Danielsson, H., Karlsson, G.P., Karlsson, P.E., Pleijel, H., Ozone uptake sensitivity of gH2 O to AFst0, the fphen function and flux thresholds, in modelling and fluxeresponse relationships e an assessment of ozone-induced yield loss in spring wheat. Atmospheric Environment 37, e order to better qualify the impacts of ozone on wheat at a pan- Del Pozo, A., Perez, P., Gutierrez, D., Alonso, A., Morcuende, R., Martinez Carrasco, R., European level using the latest flux-based approaches. The present Gas exchange acclimatation to elevated CO2 in upper-sunlit and lower study also highlights uncertainties in the development of ozone shaded canopy leaves in relation to nitrogen acquisition and partitioning in wheat grown in field chambers. Environmental and Experimental Botany 59, risk assessment models at the European and worldwide scale. The e genetic variation observed in gmax, phenological development and Garcia, R.L., Long, S.P., Wall, G.W., Osborne, C.P., Kimball, B.A., Nie, G.Y., Pinter, P.J., O3 sensitivity illustrates a need for the development of regionalized Lamorte, R.L., Wechsung, F., Photosynthesis and conductance of spring- wheat leaves: field response to continuous free-air atmospheric CO2 enrich- risk assessment approaches applicable to local crops and ment. Plant, Cell and Environment 21, e conditions. Although flux-based approaches are recognised to be Jiang, G.M., Hao, N.B., Bal, K.Z., Zhang, Q.D., Sun, J.Z., Guo, R.J., Ge, Q.Y., Kuang, T.Y., an appropriate metric to determine O3 effects, the AOT40 index Chain correlation between variables of gas exchange and yield potential performed equally well in this study. in different winter wheat cultivars. Photosynthetica 38, e Mullholland, B.J., Craigon, J., Black, C.R., Colls, J.J., Atherton, J., Landon, G., Impact of elevated atmospheric CO2 and O3 on gas exchange and chlorophyll content in spring wheat (Triticum aestivum L.). Journal of Experimental Botany 48, e Acknowledgements Müller, J., Wernecke, P., Diepenbrock, W., LEAFC3-N: a nitrogen-sensitive extension of the CO2 and H2O gas exchange model LEAFC3 parameterised and The authors thank Robert Hodgson and Alan Craig for tested for winter wheat (Triticum aestivum L.). Ecological Modelling , e their technical assistance (Newcastle University), plus Benjamín Pleijel, H., Danielsson, H., Emberson, L., Simpson, D., Application of flux-based S. Gimeno (CIEMAT, Spain), Andrzej Skoczowski (Polish Academy of methods on a local and a regional scale. In: Wieser, G. et al. (Eds.), Critical Levels Science, Poland), John Snape (John Innes Institute, UK) and Paul of Ozone: Further Applying and Developing the Flux-based Concept. Proceed- ings UNECE Workshop, 15e19 November , BFW, Vienna, pp 49e Bilsborrow (Newcastle University, UK) for their respective inputs. Sato, T., Abdalla, O.S., Oweis, T.Y., Sakuratani, T., Effect of supplemental irri- The study was funded through a combination of an EU Framework gation on leaf stomatal conductance of field grown wheat in northern Syria. 5 Marie Curie ‘Training Site’ award (HPMT-CT) and Agricultural Water Management 85, e a grant from the Spanish Ministerio de Medio Ambiente, Medio Shen, Y., Kondoh, A., Tang, C., Zhang, Y., Chen, J., Li, W., Sakura, Y., Liu, C., Tanaka, T., Shimada, J., Measurement and analysis of evapotranspiration and surface Rural y Marino, “Critical Loads and Levels” (administered via conductance of a wheat canopy. Hydrological Processes 16, e CIEMAT). Tuba, Z., Szente, K., Koch, J., Response of photosynthesis, stomatal conduc- tance, water use efficiency and production to long-term elevated CO2 in winter wheat. Journal of Plant Physiology , e Wall, G.W., Adam, N.R., Brooks, T.J. Kimball, B.A., Pinter, P.J., Lamorte, R.L., Adamsen, Appendix 1. Calculation of accumulated ozone stomatal F.J., Hunsaker, D.J., Wechsung, G., Wechsung, F., Grossman-Clarcke, S., Leavitt, S. W., Matthias, A.D., Webber, A.N., Acclimatation response of spring wheat fluxes (AFstY) in a free-air CO2 enrichment (FACE) atmosphere with variable nitrogen regimes. 2. Net assimilation and stomatal conductance of leaves. Photosynthesis Calculations of O3 uptake per unit leaf projected area (Fst) were Research 66, 79e Xue, Q., Soundarajan, M., Weiss, A., Arkebauer, T.J., Baenziger, P.S., Genotypic based on the guidelines provided in the CLRTAP Mapping Manual variation of gas exchange and carbon isotope discrimination in winter wheat. (UNECE, ) Eq. (1A). Journal of Plant Physiology , e Yu, Q., Zhang, Y., Liu, Y., Shi, P., Simulation of the stomatal conductance of  2 1   3  1  rc winter wheat in response to light, temperature and CO2 changes. Annals of Fst Y nmol m s ¼ CO3 nmol m $gO3 m s $ botany 93, e rb þ rc (1A) where, rc ¼ 1=ðgO3 þ gext ); rb ¼ s m ; gext ¼ m s 1; 1 References cO3 is the hourly O3 concentration; rc is the leaf surface resistance; rb is the quasi-laminar resistance and gext is the leaf cuticular Amundson, R.G., Kohut, R.J., Schoettle, A.W., Raba, R.M., Reich, P.B., Correlative reductions in whole-plant photosynthesis and yield of winter wheat caused by conductance. gH2 O values were transformed into stomatal ozone. Phytopathology 77, 75e conductance to O3 ðgO3 Þ based on the difference in diffusivity Araus, J.L., Tapia, L., Alegre, L., The effect of changing sowing date on leaf between O3 and water vapour in air; DO3 =H2 O ¼ (Nobel, structure and gas exchange characteristics of wheat flag leaves grown under ). Mediterranean climate conditions. Journal of Experimental Botany 40, e Stomatal flux was accumulated on an hourly basis over the Ashmore, M.R., Assessing the future global impacts of ozone on vegetation. lifespan of the flag leaf following Eq. (2A). Plant, Cell and Environment 28, e  I. GonzalezeFernandez et al. / Atmospheric Environment 44 () e Barnes, J.D., Velissariou, D., Davison, A.W., Holevas, C.D., Comparative ozone Karlsson, P.E., Uddling, J., Skarby, L., Wallin, G., Sellden, G., New critical levels sensitivity of old and modern Greek cultivars of spring wheat. New Phytologist for ozone effects on young trees based on AOT40 and simulated cumulative leaf , e uptake of ozone. Atmospheric Environment 38, e Barnes, J.D., Bender, J., Lyons, T., Borland, A., Natural and man-made Larcher, W., Physiological Plant Ecology. Ecophysiology and Stress Physiology selection for air pollution resistance. Journal of Experimental Botany 50, of Functional Groups. Springer, Berlin. e Lawlor, D.W., Mitchell, R.A.C., Crop ecosystems responses to climate change: Biswas, D.K., Xu, H., Li, Y.G., Sun, J.Z., Wang, X.Z., Han, X.G., Jiang, G.M., wheat. In: Reddy, K.R., et al. (Eds.), Climate Change and Global Crop Produc- Genotypic differences in leaf biochemical, physiological and growth responses tivity. CABI Publishing, Wallingford, pp. 57e to ozone in 20 winter wheat cultivars released over the past 60 years. Global McCleary, B.V., McNally, M., Monaghan, D., Measurement of alpha amylase Change Biology 14, 46e activity in white wheat flour, milled malt, and microbial enzyme preparations. Bosac, C., Black, V.J., Roberts, J.A., Black, C.R., Impact of ozone on seed yield and Using the ceralpha assay: collaborative study. Journal AOAC International 85, quality and seedling vigour in oilseed rape (Brassica napus L.). Journal of Plant e Physiology , e McMaster, G.S., Wilhelm, W.W., Growing degree days: one equation, two Büker, P., Emberson, L.D., Ashmore, M.R., Cambridge, H.M., Jacobs, C.M.J., interpretations. Agriculture and Forest Meteorology 87, e Massman, W.J., Müller, J., Nikolov, N., Novak, K., Oksanen, E., Schaub, M., de la Mills, G., Buse, A., Gimeno, B., Bermejo, V., Holland, M., Emberson, L., Pleijel, H., Torre, D., Comparison of different stomatal conductance algorithms for A synthesis of AOTbased response functions and critical levels of ozone flux modelling. Environmental Pollution , e ozone for agricultural and horticultural crops. Atmospheric Environment 41, Chaves, M.M., Pereira, J.S., Maroco, J., Rodrigues, M.L., Ricardo, C.P.P., Osório, M.L., e Carvalho, I., Faria, T., Pinheiro, C., How plants cope with water stress in Mills, G., Büker, P., Hayes, F., Emberson, L., Werner, W., Gimeno, B., Fumagalli, I., the field. Photosynthesis and growth. 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Environmental Pollution , assessment for agricultural crops in Europe: further development of stomatal e flux and fluxeresponse relationships for European wheat and potato. Atmo- Emberson, L.D., Massman, W.J., Buker, P., Soja, G., Van der Sand, I., Mills, G., spheric Environment 41, e Jacobs, C., The development, evaluation and application of O3 flux and Pleijel, H., Danielsson, H., Gelang, J., Sild, E., Selldén, G., Growth stage fluxeresponse models for additional agricultural crops. In: Wieser, G., et al. dependence of the grain yield response to ozone in spring wheat (Triticum (Eds.), Critical Levels of Ozone: Further Applying and Developing the Flux-based aestivum L.). Agriculture, Ecosystems and Environment 70, 61e Concept. Proceedings UNECE Workshop, 15e19 November , BFW, Vienna, Pleijel, H., Mortensen, L., Fuhrer, J., Ojamperä, K., Danielsson, H., Grain protein pp. e accumulation in relation to grain yield of spring wheat (Triticum aestivum L.) Feng, Z., Kobayashi, K., Assessing the impacts of current and future concen- grown in open-top chambers with different concentrations of ozone, carbon trations of surface ozone on crop yield with meta-analysis. Atmospheric Envi- dioxide and water availability. Agriculture, Ecosystems and Environment 72, ronment 43, e e Feng, Z., Kobayashi, K., Ainsworth, E.A., Impact of elevated ozone concen- Quarrie, S.A., Pekic-Quarrie, S., Radosevic, R., Rancic, D., Kaminska, A., Barnes, J.D., tration on growth, physiology, and yield of wheat (Triticum aestivum L.): a meta- Leverington, M., Ceoloni, C., Dodig, D., Dissecting a wheat QTL for yield analysis. Global Change Biology 14, e expressed in a range of environments: from the QTL to candidate genes. Journal Fiscus, E.L., Booker, F.L., Burkey, K.O., Crop responses to ozone: uptake, modes of Experimental Botany 57, e of action, carbon assimilation and partitioning. 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