Transpiration-use efficiency of barley

Agricultural and Forest Meteorology 130 (2005) 1–11 www.elsevier.com/locate/agrformet Transpiration-use efficiency of barley Armen R. Kemanian a,*, Claudio O. Stöckle a, David R. Huggins b,1 a Biological Systems Engineering Department, Washington State University, Pullman, WA 99164-6120, USA b USDA-ARS, Washington State University, Pullman, WA 99164-6421, USA Received 2 March 2004; accepted 6 January 2005 Abstract Transpiration-use efficiency, the ratio of biomass (Y) produced per unit of water transpired (T) by a crop, depends on crop characteristics and on the environment in which crops develop. Transpiration-use efficiency has been described as Y/T = kc/Da, where kc is a crop dependent constant and Da is the daytime air vapor pressure deficit. Our objectives were to determine Y/T and kc of barley grown in Pullman, WA, and to analyze the variation in Y/T and kc of barley (Hordeum vulgare L.) and wheat (Triticum aestivum L.) reported in the literature. Transpiration and biomass accumulation of barley crops were measured in the years 2000 and 2001. The coefficient kc was estimated as the slope of the regression between cumulative values of biomass and T/Da. It ranged from 6.6
0.4 to 6.9
0.2 Pa. These figures are greater than 5.8 Pa obtained by applying equations developed by Tanner and Sinclair [Tanner, C.B., Sinclair, T.R., 1983. Efficient water use in crop production: research or re-search. In: Taylor, H.M., et al. (Eds.), Limitations to Efficient Water Use in Crop Production. ASA, Madison, WI, pp. 1–27]. Data on kc reported in the literature, although scarce, ranged from 3.0 to 5.9 Pa for barley, and from 2.8 to 6.7 Pa for wheat, with the lower values occurring at low Da (<1 kPa). This variability seems to associate with the response of the internal (leaf) to external (bulk air) CO2 concentration ratio (ci/ca) to changes of the leaf-to-air vapor pressure deficit (Dl), suggesting that kc rather than a constant could be a function of Dl. The evaluation of more field data on kc, the field validation of the response of ci/ca to Dl, and testing this approach for different species and cultivars is needed to improve the understanding of the Y/T determination at the canopy level. # 2005 Elsevier B.V. All rights reserved. Keywords: Transpiration-use efficiency; Barley; Wheat; ci/ca; Air vapor pressure deficit 1. Introduction Transpiration-use efficiency is the ratio of biomass produced per unit of water transpired by a crop. * Corresponding author. Tel.: +1 509 335 1578; fax: +1 509 335 2722. E-mail addresses: armen@wsunix.wsu.edu (A.R. Kemanian), stockle@wsu.edu (C.O. Stöckle), dhuggins@wsu.edu (D.R. Huggins). 1 Tel.: +1 509 335 3379; fax: +1 509 335 3842. Bierhuizen and Slatyer (1965) proposed that, at the leaf level, transpiration-use efficiency is represented by: A kl ¼ ; E Dl (1) where A is the CO2 assimilation rate per unit of leaf area, E is the rate of evaporation per unit leaf area, kl is a constant for leaves of a given crop, and Dl is the leafto-air vapor pressure deficit. Bierhuizen and Slatyer 0168-1923/$ – see front matter # 2005 Elsevier B.V. All rights reserved. doi:10.1016/j.agrformet.2005.01.003 2 A.R. Kemanian et al. / Agricultural and Forest Meteorology 130 (2005) 1–11 (1965) argued that kl could be scaled up to the entire canopy (kc), since the leaf temperature appears to be within
2–3 8C of air temperature, and as first approximation the vapor pressure deficit of the air (Da) could be a surrogate of Dl; hence: Y kc ¼ ; T Da (2) where Y is crop biomass production, T is crop transpiration, and kc is a canopy level constant for a given crop. Tanner (1981) presented a rich discussion on the scaling of leaf (A/E) to canopy (Y/T) transpiration-use efficiency. He pointed out that kc should be a conservative parameter (at least within a location), considering that the ratio between the internal (leaf) and the external (bulk air) concentration of CO2 (ci/ca) is reasonably constant, an idea previously expressed by Bierhuizen and Slatyer (1965). Figures for this ratio reported by Wong et al. (1979) were around 0.7 for C3 crops and 0.3 for C4 crops. Tanner (1981) also indicated that kc should be lower than kl for two reasons. First, there is a loss of CO2 due to maintenance and growth respiration. Second, if the effectively photosynthesizing leaf area of a canopy is less than the effectively transpiring leaf area, kc is further decreased below kl. Tanner and Sinclair (1983) expanded the analysis of Tanner (1981). They developed equations to represent biomass production and transpiration of a canopy from which kc can be explicitly calculated. Since we will use these equations throughout our analysis, they are summarized in this section. Scaling up from leaf to canopy, they concluded that biomass production could be represented by the following expression (their Eq. 11): Y¼ abcca PAId ; 1:5rd (3) where a is the ratio of molecular weights of carbohydrates to CO2 (0.68), b is a conversion coefficient from hexose to biomass and varies from near 0.8 for crops with high accumulation of sugar or starch (e.g. sugarcane and potato) to near 0.45 during the seed growth of crops with high accumulation of oil (e.g. sunflower), c = (1  ci/ca), PAId is the sunlit plant area index, ca is the CO2 atmospheric concentration (g m3), and rd is the sum of boundary layer and stomatal resistance to water vapor flux for sunlit leaves. The fundamental assumptions to develop Eq. (3) were: (1) c is reasonably constant (Wong et al., 1979) and (2) the photosynthesis of the shaded leaves is roughly equivalent to the maintenance respiration of the whole canopy. Separating canopy foliage as sunlit and shaded leaves, Tanner and Sinclair (1983) expressed transpiration as (their Eq. 12b): T¼ reDa ½PAId Dl =Da þ ðPAI  PAId Þrd =rs  ; Prd (4) where r is the density of the air, e is the vapor to air molecular weight ratio, P is the atmospheric pressure, and rs is the sum of boundary layer and stomatal resistance to water vapor flux for shaded leaves. As indicated by Tanner and Sinclair (1983), the term in brackets is the effective transpiring leaf area (PAIt). Assuming that the ratio rd/rs is approximately 0.3 for PAI = 4, they calculated that PAIt would be around 2.2
0.2 for PAI > 3, unless the ratio Dl/Da departs appreciably from unity. The fundamental assumption to develop Eq. (4) was that the shaded leaves are at air temperature. The quotient between the equations for biomass and transpiration is Y/T; then kc is: kc ¼ abcCa P PAId : ð1:5reÞ PAIt (5) The merit of the Tanner and Sinclair (1983) analysis is widely recognized; after its publication almost every paper dealing with transpiration-use efficiency refers to it. Several simulation models estimate daily growth (Stockle et al., 1994; Sinclair and Seligman, 1995) and transpiration (Keating et al., 1999) based on kc and Eq. (2). Sinclair (1994) argued that, since the c values that Tanner and Sinclair (1983) used are probably in the upper limit for C3 and C4, kc estimated with their equations should be close to the maximum attainable. Barley and wheat kc can be evaluated by taking b = 0.74 (as used for corn by Tanner and Sinclair, 1983), PAId = 1.4, PAIt = 2.2, the current ca at sea level (0.67 g m3), and the atmospheric pressure at sea level, giving kc of 5.8 Pa g biomass g1 water (hereafter we express kc in Pa). Sinclair and Seligman (1995) used this value in a wheat growth model. A.R. Kemanian et al. / Agricultural and Forest Meteorology 130 (2005) 1–11 However, field-measured kc values for barley are scarce and the available data shows great variability. In Table 1 we summarized data of Y/T and kc of barley and wheat reported or calculated from the literature, assuming that they would be similar for both crops. Different techniques were employed by different authors to obtain kc. Tanner (1981) indicated that kc should be calculated as the slope of the linear regression between biomass and the daily integration of the quotient between transpiration and daytime Da, and that was the method employed by Condon et al. (1993) and Marcos (2000). The other estimates in Table 1 are the product of Y/T times a seasonal average of daytime Da, which can give slightly different values than the daily integration method. Hubick and Farqhuar, 1989 presented data for several cultivars obtained in glasshouse experiments. We only show data for the cultivar with the highest kc (Table 1); other cultivars had kc 20% lower. For the water stressed treatment kc was 5.9 Pa, almost identical to the theoretical value obtained above; however, for the irrigated treatment kc was 4.7 Pa. Higher Y/T in water stressed than in unstressed crops was reported in field grown potatoes (Vos and Groenwold, 1989), and in pearl millet (Pennisetum glaucum [L.] R. Br.) in pot experiments (Brück et al., 2000), suggesting that kc of water stressed crops could be higher than that of unstressed crops. Gregory et al. (1992) and Siddique et al. (1990) estimated kc for barley from field experiments (Table 1). Gregory et al. (1992) estimated kc as the product of Y/T times Da. However, they indicated that Da varied from around 0.51 kPa at the beginning of the season to 1.4 kPa in the last 4 weeks of growth. Siddique et al. (1990) reported the ratio Y/T at crop maturity but did not report Da. We estimated Da from a paper reporting the meteorological conditions for the same experiment (Siddique et al., 1989); it varied from around 0.8 to 1.2 kPa. The kc reported for Gregory et al. (1992) range from 3.16 to 3.58 Pa and the kc calculated from Siddique et al. (1990) is 5.14 Pa. For wheat, reported kc ranges from 2.80 Pa (Gregory et al., 1992) to 6.7 Pa (Angus and van Herwaarden, 2001). This variability cannot be attributed entirely to genotypic variation; for the wheat cultivar Gutha kc ranged from 2.80 to 4.74 Pa, and for Timgalen ranged from 3.83 to 5.18 Pa (Table 1). Although the data is insufficient to compare barley and wheat, the range of 3 variation of kc for both species is similar. Condon et al. (1993) found a correlation between genotypic variation in kc and 13C discrimination in wheat, strongly suggesting that the genotypic variation in kc is explained by variation in c (Condon et al., 2002). Interestingly, Angus and van Herwaarden (2001) reported a higher kc postanthesis compared to preanthesis. In that study, Da was also higher postanthesis compared with preanthesis (Table 1), suggesting that the environment could affect kc. To the best of our knowledge, there has been no previous attempt to explain this variability in kc. Our objectives were to: (1) estimate kc of barley from field measurements of biomass accumulation and transpiration and (2) analyze the variability in barley and wheat kc reported in the literature in terms of the assumptions used by Tanner and Sinclair (1983) to develop their theoretical estimate of kc. 2. Materials and methods Measurements of crop growth and biomass accumulation were obtained from a larger field experiment designed to study radiation interception and radiation-use efficiency of barley. Briefly, field experiments were conducted in 2000 and 2001 at the Palouse Conservation Field Station (lat 46.88N, long 117.28W, elevation 756 m), located 5 km NW of Pullman, WA, on a Palouse silt loam (Fine-silty, mixed, mesic Pachic Ultic Haploxerolls). Treatments consisted of a factorial combination of two cultivars of spring barley (Baronesse, a two-row barley and Steptoe, a six-row barley), two seeding densities and two seeding dates, arranged in a complete randomized block design with four replications in 2000 and three replications in 2001. Each plot (2.2 m 12 m) was seeded with a no-till drill rows 20 cm apart. At seeding, each crop received 157 kg ha1 of nitrogen and 51 kg ha1 of phosphorus. The sowing dates were 27 April and 6 June in 2000, and 26 April and 13 June in 2001. Target densities were 100 and 250 plants m2. Plots were irrigated with sprinklers. Weeds were controlled by hand. Diseases and insect damage were prevented or controlled with insecticides and fungicides. In 2000, we monitored water use and crop growth in Baronesse seeded at the highest density in two 4 A.R. Kemanian et al. / Agricultural and Forest Meteorology 130 (2005) 1–11 Table 1 Barley and wheat transpiration-use efficiency (Y/T) and kc as reported or calculated from data obtained in the literature (the average daytime vapor pressure deficit (Da) during the period of biomass growth and transpiration measurement is also reported) Sourcea Site Species and cultivar Y/T (g kg1) Da (kPa) kc (Pa) Observationsb (1) Pullman, WA Barley, cv. Baronesse 4.99 3.20 4.12 4.29 1.39 1.93 1.63 1.63 6.89 6.67 6.72 7.00 2000, 2000, 2001, 2001, cv. Steptoe normal seeding date late seeding date normal seeding date normal seeding date (2) Australia (glasshouse) Barley, cv. Proctor 3.37 4.22 1.4 1.4 4.72 5.91 Irrigated, shoot + roots Water stressed, shoot + roots (3)c Merredin, Australia Barley, cv. O’Connor Wheat, cv. Gutha 5.35 4.93 0.96 0.96 5.14 4.74 1987 (4) East Beverley, Australia Barley, cv. Beecher cv. O’Connor cv. Syrian Wheat, cv. Gutha 5.43 5.69 5.01 4.45 0.63 0.63 0.63 0.63 3.42 3.58 3.16 2.80 1988, shoot + roots Wheat, cv. Timgalen 5.75 4.30 5.64 3.90 4.14 3.10 4.83 4.10 3.91 3.40 0.82 1.19 0.92 1.23 1.07 1.35 0.91 1.17 0.98 1.39 4.69 5.10 5.18 4.80 4.45 4.20 4.38 4.80 3.83 4.73 1973, 1973, 1973, 1973, 1973, 1973, 1975, 1975, 1975, 1975, Wheat, cv. Bank 7.06 8.06 7.75 9.21 0.70 0.64 0.68 0.61 5.07 5.16 5.28 5.63 1984 1985 1984 1985 (5)c (6)c Werribee, Australia cv. Quarrion D1, D1, D2, D2, D3, D3, D1, D1, D2, D2, preanthesis postanthesis preanthesis postanthesis preanthesis postanthesis preanthesis postanthesis preanthesis postanthesis (7) Moombooldool, Australia Wheat, cv. Gutha cv. Quarrion 8.16 6.75 0.54 0.71 4.37 5.51 1985, preanthesis (8)c Toowoomba, Australia Wheat, cv. Hartog 4.2 1.18 4.9 1993 (9) Pucawan, Australia Wheat, average of cv. Comet, Janz and Kulin 7.13 5.98 4.3 3.9 0.51 0.51 1.54 1.54 3.95 3.10 6.7 6.0 Preanthesis, low N Preanthesis, high N Postanthesis, low N Postanthesis, high N (10)c Nottinghamshire, UK Wheat, cv. Soissons 5.66 6.17 6.63 6.66 0.60 0.63 0.60 0.63 3.68 4.01 4.31 4.32 1994 1995 1994 1995 4.59 1.13 5.90 Pooling 1998/1999 data cv. Maris Huntsman (11) a Pullman, WA Wheat, cv. WB926R (1) This study; (2) Hubick and Farqhuar, 1989; (3) Siddique et al. (1990), Da from Siddique et al. (1989); (4) Gregory et al. (1992); (5) Doyle and Fischer (1979) showed data from year 1974 too, but these were excluded because of occurrence of heavy frosts; Da was estimated as 2/3 of the maximum saturation deficit, that is approximated as the difference in vapor saturation between maximum and minimum temperature, both obtained from the average monthly temperature reported and a daily thermal amplitude of 12 8C; (6) Connor et al. (1992) showed data for four sowing dates per year but we excluded the last sowing date for Quarrion because it showed irregular phenological development; Da was estimated as in (5) with the reported maximum and minimum temperatures; (8) Meinke et al. (1997); (7) Condon et al. (1993); (9) Angus and van Herwaarden (2001); (10) Foulkes et al. (2001) they had irrigated treatments but indicated that the irrigation added uncertainty to the transpiration estimates; we only show data for non-irrigated crops; (11) Marcos (2000). b Shoot + roots indicates that roots were sampled and included in the computation of biomass; to make a rough accounting of root biomass when it was not measured, Y/T and the resulting kc were multiplied by 1.15 (sources 5 and 7) and by 1.07 (see text) for the preanthesis and the entire crop cycle data, respectively. No apportioning of biomass to roots was made for postanthesis data. c Indicates that kc was estimated as the product of Y/T times Da. A.R. Kemanian et al. / Agricultural and Forest Meteorology 130 (2005) 1–11 replications at both sowing dates. In 2001, we monitored water use and crop growth between booting and the beginning of grain filling (June 28 to July 13) for Baronesse and Steptoe seeded at the highest density in the first seeding date. The techniques employed to estimate water use in each year differed. In 2000, soil water content was measured from emergence to physiological maturity with water reflectometer probes (model CS615-L, Campbell Scientific Inc., Logan, UT). In each plot, five probes were installed to a depth of 1.5 m at 0.3 m interval. An additional sensor was installed in the first layer at angle of 208 from the soil surface to monitor water content in the first 0.1 m of the soil profile. Each probe was connected to a datalogger (CR10x, Campbell Scientific Inc., Logan, UT), and the signal recorded at midnight. Each probe was calibrated against measured volumetric water content. Gravimetric water content was measured four times during the growing season to a depth of 1.8 m at 0.3 m interval. The samples were taken at crop emergence, beginning of stem elongation, heading and harvest. Volumetric water content was estimated as the product of the gravimetric water content and the bulk density of the layer. Bulk density was measured to a depth of 1.8 m at 0.3 m intervals by taking three soil cores of 2 cm in diameter and 20 cm long in spring. A weather station located in the border of the experimental area recorded hourly precipitation, temperature, relative humidity, and wind speed. Radiation interception was measured using one tube solarimeter (70 cm) per plot (Marcos, 2000). After the plants reached the two- to three-leaf stage, the solarimeters were placed below the canopy in areas representative of the plot. Each solarimeter was connected to a datalogger, and the signal recorded every 20 min. Simultaneously, solar radiation was measured at a height of 2.5 m with a pyranometer (LI200X, Licor Inc., Lincoln, NE, USA). The pyranometer and the solarimeter outputs were integrated to obtain daily solar irradiance and daily solar radiation transmitted through the canopy, and the values used to calculate daily fractional radiation interception ( f i). The seasonal variation in f i was reported in Kemanian et al. (2004). The replicates of each treatment for f i showed very low variability (data not shown), consistent with the observations that the crop stand was homogenous and that the plants tillered 5 aggressively, compensating minor unevenness in the plants distribution. Daily evapotranspiration (ET) was calculated from a water balance for the soil profile: ET ¼ PP þ I  DP  R  DS; (6) where, PP is precipitation, I is irrigation, DP is deep percolation, R is runoff, and DS is the change in storage to a depth of 1.8 m. Runoff did not occur during the course of the experiment. Deep percolation was only evident at the beginning of the measurement period in the first sowing date, when the sensors at 1.2 and 1.5 m of depth showed a slight decrease in water content, but thereafter the signal stabilized until the crops started to uptake water from that layer towards the end of the crop growth cycle. Daily ET was partitioned into soil evaporation and crop transpiration on a daily basis. Soil evaporation was taken as the minimum of the change in storage at the first 0.1 m soil and the product (1  f i)ET. The remaining fraction of ET was apportioned to transpiration. Aboveground biomass was estimated from samples of two adjacent 0.5 m length rows (0.2 m2) per plot, at intervals of 6–10 days until physiological maturity. Samples were dried at 60 8C for 72 h and the dry weight recorded. In the year 2001, measurements were taken between flowering and beginning of grain filling (June 28 to July 13). We selected this period because it shows the highest growth and water depletion rate of the crop cycle, the crops fully cover the ground ( f i 0.9) minimizing soil evaporation and then errors in the estimation of transpiration, and the probability of occurrence of precipitation are low. No irrigation was applied during that time interval. In each plot at high density (three replications), two sections of about 1 m2 were flagged. The sections were visually identical. We carefully avoided borders, areas with uneven plants distribution or populations unusually high or low. Aboveground biomass samples of two adjacent rows 1 m long were taken at the beginning and at the end of the selected period; one of the flagged areas was sampled at each time. Samples were dried at 60 8C for 72 h and the dry weight recorded. Concurrently, gravimetric water content was measured to a depth of 1.5 m at 0.3 m interval. An additional sample was taken in the first 5 cm. Each sample was a composite of two cores 30 cm long 6 A.R. Kemanian et al. / Agricultural and Forest Meteorology 130 (2005) 1–11 (5 cm in the top layer) and a diameter of 2 cm. There was a rain of 3.3 mm during that period but there was no runoff and we assumed deep percolation to be negligible. Therefore, ET was approximated as the change in storage plus the precipitation during the period June 28 to July 13. The change in storage of the first 5 cm was attributed to soil evaporation and the remaining fraction of ET apportioned to transpiration. In 2000, the transpiration efficiency (Y/T) was estimated as slope of the linear regression between cumulative Y against cumulative T, and the coefficient kc was estimated as the slope of the linear regression between Y and daily cumulative T/Da. We considered that the estimations of T for Y > 100 g m2 ( f i of approximately 0.35) were more accurate than the estimations of T for Y < 100 g m2. Therefore, although in theory the regression should pass through the origin, we prioritize honoring the actual data and did not set the intercept to zero. In 2001, Y/T was calculated as the biomass gained in the period divided by the estimated transpiration, and kc was calculated as the product of Da times Y/T, where Da was averaged for the period considered. 3. Results and discussion In the year 2000, crop water uptake was restricted to a depth of 1.5 m; no change in the water content between 1.5 and 1.8 m was detected between heading and maturity (data not shown). Biomass accumulation was linearly related to both cumulative transpiration (slopes of 4.7
0.4 and 3.0
0.6 g biomass kg1 water for the first and the second sowing date) and cumulative transpiration normalized by Da (Fig. 1). As observed by Tanner (1981) in potatoes, the normalization of T by Da decreased the scatter of the data; the slopes of the first and second sowing dates were indistinguishable giving a common kc of 6.2
0.4 Pa (cv. Baronesse). If an accounting for roots is made assuming that on average over the entire crop cycle about 7% of the biomass is allocated belowground, then kc = 6.6
0.4 Pa. The 7% figure comes from the following calculation. Gregory et al. (1978) indicated that roots represent about 15% of the total biomass at anthesis and that root growth stops thereafter. In this area, spring cereals duplicate the aboveground biomass from beginning of anthesis to maturity. Therefore, if root biomass is kept constant, it amounts to about 7% of total biomass at harvest. Another calculation that gives a similar estimate is converting root density measurements to root biomass based on a root length density of 240 m g1 (Gregory et al., 1978). With a maximum root density at the surface of 4 cm cm3 (see the review table by de Willigen and van Noordwijk, 1987, p.88) and a exponential decrease in root density (Dwyer et al., 1998) to a depth of 1.5 m, root biomass would represent slightly less than 7% of the total biomass for a crop with 10 Mg ha1 of aboveground biomass. In the year Fig. 1. Biomass as a function of cumulative transpiration (panel A) and cumulative transpiration normalized by the air vapor pressure deficit (Da) (panel B), of spring barley cv. Baronesse grown at Pullman, WA, year 2000. A.R. Kemanian et al. / Agricultural and Forest Meteorology 130 (2005) 1–11 2001, the average ET for the period considered was 115
7 mm, the average T was 106
7 mm, and the average crop growth rate was 29.4
1.2 g m2 d1. The average kc estimated was 6.9
0.2 Pa (n = 6); the estimates for Baronesse and Steptoe, although not statistically different, are shown separately in Table 1. No accounting for root biomass was made in the year 2001 as root growth stops around anthesis (Gregory et al., 1978). Comparing the values that we obtained for barley with the values summarized in Table 1, Y/T values are within the range reported in the literature, while kc values of 6.6 and 6.9 Pa are in the upper limit reported in the literature for both barley and wheat, and so are the Da values. Furthermore, while some kc presented in Table 1 are similar to the 5.8 Pa obtained by applying Eq. (5), others are noticeable lower. We graphed Y/T of Table 1 against the daytime Da (Fig. 2) and found that, as suggested by Bierhuizen and Slatyer (1965), Y/T seems to be an inverse function of Da, that is well represented by the model Y/T = 4.9Da0.59 (r2 = 0.97, n = 38, P < 0.001). The upper envelope of the data departs from the Y/T predicted by Eq. (2) using kc = 5.8 Pa, particularly at Da < 1 kPa, where predicted Y/T is much higher than the observed Y/T, Fig. 2. Transpiration-use efficiency (Y/T, g biomass kg1 H2O) as a function of the vapor pressure deficit of the air. The points are the Y/T reported in the literature for wheat and barley (Table 1); the dotted line is for Y/T = 5.8/Da; the solid line is for Y/T calculated using c = 1  (0.85  0.05Dl) (Eq. (7), see text) and (Eqs. (2), (5), (8) and (9)); the dashed line is for Y/T calculated using c = 1  (0.85  0.12Dl); see text for explanations. The solid line is well approximated by Y/T = 3.8/Da3/4 and the dashed line by Y/ T = 5.2/Da3/5. 7 except the highest Y/T reported by Connor et al. (1992) (Fig. 2). We suspect that Connor et al. (1992) underestimated T. The information presented in their paper allows calculating Y/T for different phenological stages, and we found that in the third seeding date of 1984, the cultivar Quarrion Y/T was 17 g biomass kg1 H2O in the period between floral initiation and anthesis. This value is unusually high, even for a C4 plant, and may be indicative of an underestimation of transpiration and consequently an overestimation of Y/T. There is also considerable scattering in the data of Fig. 2, and although part of this scattering could be genetic variation, it is probably better explained by uncertainties in measuring transpiration and growth. However, the upper and lower envelopes of the data are almost parallel, suggesting that they are truly depicting the trend of Y/T as a function of Da (Fig. 2). The significant conclusion here is that, to make the reported Y/T compatible with Eq. (2), kc cannot be a constant but rather decrease with decreasing Da, which is in fact the trend observed in Table 1. One of the fundamental assumptions of Bierhuizen and Slatyer (1965) and Tanner and Sinclair (1983), was that the ratio ci/ca, and hence c, is fairly constant. However, there is evidence that c varies in response to physiological and environmental factors. Among these factors, it is well documented that ci/ca decreases as water stress increases in field-grown potatoes (Vos and Groenwold, 1989), wheat (Whitfield, 1990), and sorghum (Williams et al., 2001). Indirect evidence of that response to water deficit and the associated decrease in stomatal conductance is the decrease in the 13 C discrimination in water stressed plants (e.g. Hubick and Farqhuar, 1989; Condon et al., 1992). Interestingly, there is also evidence that the ratio ci/ca decreases with increasing Dl (Table 2), and effect suggested in the analysis by Condon et al. (1992). Farquhar et al. (1982) concluded that when assimilation rate is reduced by a decrease in the stomatal conductance, ci should decrease. Then, the response of ci/ca to Dl could be explained by a reduction in stomatal conductance at increasing transpiration rates (Mott and Parkhurst, 1991), caused in turn by increasing Dl. The magnitude of the response of ci/ca to Dl seems to be associated to the photosynthetic metabolism. While the extrapolated ci/ca at Dl = 0 is approximately 8 A.R. Kemanian et al. / Agricultural and Forest Meteorology 130 (2005) 1–11 Table 2 Relation between the ratio leaf-to-ambient CO2 concentration (ci/ca) and the leaf-to-air vapor pressure deficit (Dl) for several species (the Dl at which the plants were exposed during the measurements is reported) Sourcea Species Intercept Slope (kPa1) r2 n Dl range (kPa) C3 plants (1) Nicotiana glauca 0.81 0.051 0.63 10 0.5–3.0 (2) Gossypium hirsutum 0.83 0.120 0.99 5 1.5–3.4 (3) Phalaris aquatica Oryza sativa 0.95 0.91 0.093 0.120 0.97 0.97 4 4 0.4–2.0 0.4–2.0 (4) Phaseolus vulgaris 0.84 0.065 0.97 6 0.8–3.0 (5) Ricinus communis 0.90 0.83 0.070 0.126 0.97 0.81 6 4 0.2–2.0 0.2–2.0 (6) Encelia farinosa 0.89 0.027 0.85 28 1.0–4.0 (7) Solanum tuberosum 0.93 0.070 0.55 32 0.9–3.0 Average C3 0.88 0.082 Zea mayz Paspalum plicatulum 0.85 0.93 0.203 0.179 0.99 0.98 4 4 0.4–2.0 0.4–2.0 (6) Pleuraphis rigida 0.80 0.101 0.88 21 1.0–4.0 (7) Sorghum bicolor 1.00 0.246 0.79 22 1.0–2.5 Average C4 0.90 0.182 C4 plants (3) (1) Farquhar et al. (1980), their Fig. 4, plants grew in growth chamber, ca 330 mmol mol1, photosynthetic photon flux density (PPFD) 480 mmol m2 s1; (2) Sharkey et al. (1982), their Fig. 2, plants grew at ca 1900 mmol mol1, measurements were at ca 350 mmol mol1; (3) Morison and Gifford (1983), their Fig. 8, plants grew in growth chamber at Da 0.95 kPa, ca 340 mmol mol1, 1, and PPFD 670 mmol m2 s1; (4) Commstock and Ehleringer, 1993, their Fig. 2, plants grew in glasshouse with Da 2.5 kPa, ca 350 mmol mol1, and maximum PPFD 1600 mmol m2 s1; (5) Dai et al. (1992) plants grew in growth chamber Da 1.3 kPa, ca 345 mmol mol1, and PPFD 600 mmol m2 s1, measurements at 20 8C and at PPFD of 1000 and 1800 mmol m2 s1 shown here; (6) Zhang and Nobel (1996), field and growth chamber study, ca 380 mmol mol1, maximum PPFD 1600 mmol m2 s1, measurements made several times over daytime; (7) Bunce (personal communication, 2003), field study, Da varied day-to-day, measurements were on plants grown at ca of 350 and 700 mmol mol1, the regressions were identical for both CO2 levels and were pooled, PPFD > 1500 mmol m2 s1; for potatoes, the regression was not significant for instantaneous Da variation. a 0.90 for both C3 and C4 plants, the slope of the response is on average 0.08 kPa1 for C3 and 0.18 kPa1 for C4 plants (Table 2). Choudhury (1986) calculated ci for field grown cotton based on measured net photosynthesis and other biophysical considerations; we estimated that the slope of ci/ca versus Dl was 0.07 kPa1 (Choudhury, 1986, Fig. 5), very similar to the average of 0.08 kPa1 for C3 crops shown in Table 2. Hence, the empirical relation between ci/ca and Dl appears robust and could be included in an analysis of Y/T. Zhang and Nobel (1996) developed a simple model to explain the response of A/E to Dl, explicitly considering the linear response of ci/ca to Dl. However, there is no report integrating this response to the canopy level Y/T. We calculated Y/T (and kc) using Eq. (5) but allowing c to vary linearly with Dl: ci (7) c ¼ 1  ¼ 1  ðd0 þ d1 Dl Þ; ca where d0 and d1 are the intercept and slope, respectively, of the regression of ci/ca versus Dl (Table 2). Since there is no report of the response of ci/ca for barley and wheat, we can only assume that the response would be somewhere within the range indicated by the data gathered in Table 2. We calculated Y/ T using the average of the three steepest slopes (d1 = 0.12 kPa1) and the average of the three less steep slopes (d1 = 0.05 kPa1) for the C3 species summarized in Table 2. In both cases the average d0 was 0.85. The Y/T obtained with the steepest d1 would A.R. Kemanian et al. / Agricultural and Forest Meteorology 130 (2005) 1–11 approximate an upper boundary for C3, while the Y/T obtained with the less steep d1 would represent a lower boundary. With d1 = 0.12 kPa1, the value of c of 0.3 used by Tanner and Sinclair (1983) is achieved at Dl = 1.25 kPa. Vos and Groenwold (1989) reported ci/ ca 0.77 (c = 0.23) at Da 1.4 kPa for the potato cv. Saturna; assuming that Dl is approximated by Da, Eq. (7) predicts c = 0.22 (d1 = 0.05 kPa1) and c = 0.32 (d1 = 0.12 kPa1). Two more responses to change in the vapor pressure deficit should be considered for completeness in applying Eq. (5): (1) the response of the stomatal resistance and thus the ratio rd/rs, and (2) the canopy evaporative cooling and thus the ratio Dl/Da. Choudhury and Monteith (1986) summarized information showing that the stomatal resistance increases with increasing Dl. Due to the exposure of sunlit leaves, we can expect that the increase in resistance with rising Dl be more acute in the sunlit leaves, increasing the ratio rd/rs. Since we did not find experimental information, we assumed that a linear function could approximate this effect: rd Dl ¼ 0:2 þ 0:8 : rs 7 (8) This function assumes that when Dl = 0 kPa the ratio of resistances is 0.2, and increases until a maximum of 1 for Dl = 7 kPa. The limit of 7 kPa was taken from Choudhury and Monteith (1986), who assumed by extrapolation of published data that stomata of arable crops close at Dl of approximately 7 kPa. We did not perform any calculation above 5 kPa, which is a reasonable upper limit for the Dl experienced by field crops. Although field measurements of resistance of both sunlit and shaded leaves should be performed to test the validity of this approximation, the use of an intercept of 0.2 seems to be consistent with some available measurements. For example, this equation predicts that the ratio rd/rs equals 0.3 at a Dl of 0.9 kPa, the ratio assumed by Tanner and Sinclair (1983) for their computations of kc. Kjelgaard (1993) reported the stomatal resistance for both sunlit and shaded leaves of irrigated corn (average PAI = 3.7, range 2.0–4.5). From this data, we calculated that the ratio rd/rs averaged 0.4 for an average Da of 1.7 kPa, while Eq. (8) yields 0.39. The leaf-to-air vapor pressure deficit depends on the canopy temperature and the air vapor pressure. 9 Although the canopy temperature depends on the energy balance of the foliage, Idso (1982) showed that for well-watered crops the difference between canopy and air temperature (DT) is a linear function of Da. Even more, Idso et al. (1987) showed that this relationship is weakly affected by doubling ca from 330 to 660 mmol mol1. For barley Idso (1982) reported that: DT ¼ 2:01  2:25Da : (9) For potato and sunflower the slopes reported by Idso are also near 2.0 C kPa1. We used this equation to calculate the ratio Dl/Da assuming that it gives the sunlit leaves temperature and that the shaded leaves are at the air temperature. It is of interest to analyze the behavior of PAIt as a function of Da after the introduction of these changes. Increasing Da causes PAId to be cooler than the air and consequently a decreasing ratio Dl/Da than under the isothermal condition (Dl/Da = 1), and an increasing ratio rd/rs. Hence, on the computation of PAIt the weight of the sunlit leaf area decreases while the weight of the shaded leaf area increases, keeping the value reasonably bounded. For instance, for a dew point temperature of 10 8C, air temperatures varying from 15 to 30 8C, d1 = 0.12 kPa1, a PAI of 4 and a PAId of 1.4, PAIt is 2.1
0.2, reasonably close to the 2.2 used by Tanner and Sinclair (1983). For this set of conditions, c ranges from 0.22 to 0.39. Then, the adjustment of c by Da will cause a greater impact on kc than the adjustment of PAIt by Da. The resulting Y/T calculated with variable kc follows approximately the lower envelope (d1 = 0.05 kPa1, Fig. 2, solid line) and the upper envelope (d1 = 0.12 kPa1, Fig. 2, dashed line) of the data gathered from the literature. The calculated kc decrease with decreasing Da as suggested by the data of Table 1; for instance, using d1 = 0.12 kPa1, Eq. (5) gives kc = 3.9 Pa for Da = 0.5 kPa and kc = 6.8 Pa for Da = 2.0 kPa. The differences in Y/T suggested by the so-called upper and lower boundary could represent both differences among species or cultivars. In comparing two cultivars of potatoes, Vos and Groenwold (1989) found that the cultivar Bintje (high stomatal resistance) had Y/T about 14% higher than the cultivar Saturna (low stomatal resistance). Genetic differences in Y/T were also reported for barley (Hubick and Farqhuar, 1989) and wheat 10 A.R. Kemanian et al. / Agricultural and Forest Meteorology 130 (2005) 1–11 (Condon et al., 1993). Therefore, although the information presented is not conclusive, it strongly suggests that the variability observed in Y/T could be associated to the variation of c as a function of Da, and that kc is not constant. Both a constant or a variable kc imply that the water use efficiency increases with decreasing Da, but the advantage in biomass production at low Da compared with high Da predicted by the variable kc is smaller than that predicted by a constant kc of 5.8 Pa (Fig. 2). Tanner and Sinclair (1983) warned that under low Da the departure of the ratio Dl/Da from unity due to canopy temperature rising above the air temperature could cause deviation from their calculations. The additions presented here to their equations seem to account explicitly for that effect. Testing this approach under high Da would be of major interest. However, due to the season at which barley and wheat are grown, average Da > 2 kPa are rarely obtained for a long period of time. Consequently, we could not find data in the literature reporting Y/T at Da > 2 kPa. The set of equations presented can be used to speculate on the effect of water stress on kc. The temperature of a water stressed canopy can be 2–4 8C above the air temperature. This would cause a rise in both c Eq. (7) and PAIt Eq. (4). We tried several combinations of dew point, air and canopy temperatures, and found only a marginal variation of kc. This is in disagreement with some investigations showing that Y/T tends to increase with increasing water stress (e.g. Vos and Groenwold, 1989). The reason is that in addition to the effect on c through an increase in Dl, water stressed plants close the stomata to prevent dehydration, a response attributed to an abscisic acidmediated root signal (Davies and Zhang, 1991), which causes a further increase in c. This would explain an increase in Y/T of stressed crops, and suggests that kc of Eq. (2) should be calculated independently for stressed and unstressed crops. 4. Conclusions The coefficient kc of barley (cv. Baronesse) measured at Pullman ranged from 6.6
0.4 to 6.9
0.2 Pa. Thus, in this environment and for the cultivars selected, kc is greater than the 5.8 Pa estimate obtained from Tanner and Sinclair (1983) Eq. (5). This difference, as well as the variability reported in Y/T and kc in the literature, seems to be accounted for by allowing the ratio ci/ca to vary as a function of Dl in the Tanner and Sinclair (1983) derivation. However, both the quality and the quantity of available data on kc of barley (and wheat) preclude being conclusive. The evaluation of more field data on kc, the field validation of the response of ci/ca to Dl, and testing this approach for different species and cultivars is needed to improve the understanding of the transpiration-use efficiency determination at the canopy level. Acknowledgment Dr. James Bunce, from USDA-ARS Alternate Crops and Systems, generously provided the information presented in Table 2 for potatoes and sorghum. References Angus, J.F., van Herwaarden, A.F., 2001. 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