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Physiological traits associated with drought tolerancein bread wheat (Triticum aestivum L.) under tropicalconditionsP.K. Kimurto a , J.B.O. Ogola b , M.G. Kinyua c , J.M. Macharia d & P.N. Njau ea Department of Crop and Soil Sciences , Egerton University , P.O. Box 536 , Njoro ,Kenyab Department of Plant Production , The University of Venda, Private Bag X5050 ,Thohoyandou , 0950 , South Africac Department of Crop Science and Biotechnology , Moi University , P.O. Box 39000 ,Eldoret , Kenyad Department of Botany , Egerton University , P.O. Box 536 , Njoro , Kenyae National Plant Breeding Research Centre, Private Bag , Njoro , KenyaPublished online: 07 Mar 2013.

To cite this article: P.K. Kimurto , J.B.O. Ogola , M.G. Kinyua , J.M. Macharia & P.N. Njau (2009) Physiological traitsassociated with drought tolerance in bread wheat (Triticum aestivum L.) under tropical conditions, South African Journalof Plant and Soil, 26:2, 80-90, DOI: 10.1080/02571862.2009.10639938

To link to this article: http://dx.doi.org/10.1080/02571862.2009.10639938

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80 S. Afr. J. Plant Soil 2009, 26(2)

Physiological traits associated with drought tolerance in bread wheat (Triticum aestivum L.) under tropical conditions

P.K. Kimurto1, J.B.O. Ogola2*, M.G. Kinyua3, J.M. Macharia4 and P.N. Njau51 Department of Crop and Soil Sciences, Egerton University, P.O. Box 536, Njoro, Kenya.

2 Department of Plant Production, The University of Venda, Private Bag X5050, Thohoyandou 0950, South Africa.3 Department of Crop Science and Biotechnology, Moi University, P.O. Box 39000, Eldoret, Kenya.

4 Department of Botany, Egerton University, P.O. Box 536, Njoro, Kenya.5 National Plant Breeding Research Centre, Private Bag, Njoro, Kenya.

27 February 2009

Although it is generally accepted that drought tolerance is a critical agronomic trait, efficient and predictableimprovement in drought tolerance in bread wheat (Triticum aestivum L.), in varying drought stress conditions,has not been fully achieved. This study aimed at assessing the responses of bread wheat to drought, usingphysiological traits associated with drought tolerance. Two experiments were undertaken in 2001 and 2002. InExperiment I, 17 wheat genotypes were planted in the field in Katumani, Kenya, using a randomised completeblock design. Experiment II was conducted under rain shelter (by simulating early season drought at seedlingstage) at National Plant Breeding Research Centre, Njoro, Kenya. Treatments were imposed in a split-plotdesign with water regime (low, medium and high) as main plots and 12 wheat genotypes as sub-plots. Evapo-transpiration (ET) was determined by monitoring soil moisture content at 7 d intervals using a neutron probe,stomatal conductance (g) and instantaneous transpiration (T) rates were measured on the uppermost fullyexpanded leaves at booting stage using a steady-state porometer, net leaf CO2 exchange rates (CER) wasmeasured on selected leaves using a portable Infrared Gas Analyser, fitted with Parkinson Leaf chamber, andcrop biomass, grain yield and harvest index (HI) determined at harvest maturity. Water use efficiency (q), HI,stomatal conductance, and CER were identified as key control points in determining the drought resistance oftolerant genotypes. Therefore it is important to determine the heritability of these traits in order to ascertain theirpotential usefulness in a wheat breeding program.

Key words: Carbon dioxide exchange rates, genotype, rain shelter, stomatal conductance, water use effi-ciency.

*To whom correspondence should be addressed. (E-mail: ochanda@univen.ac.za)

IntroductionWater scarcity is increasingly becoming a major limitation toagricultural production and food security in sub-SaharanAfrica (Turner, 2001; FAO, 2006; UNEP, 2008). For exam-ple, in Kenya the major constraint limiting wheat and maizeproduction in marginal rainfall areas (81% of total land area)is inadequate and erratic rainfall (Jaetzold & Schmidt, 1983;Mugo et al., 1998; Kinyua et al., 2000). Development ofwheat cultivars with improved adaptation to drought has thusbeen a major goal in most of the National Wheat BreedingProgrammes in Kenya (KARI, 2006) and other regions (CIM-MYT, 1996; Reynolds et al., 1999). Plant breeders have tra-ditionally applied methods where grain yield comparison isused as the main selection criterion for drought tolerance.This approach has often succeeded in the absence of in-depthknowledge of physiological bases for superior performanceof existing germplasm. However, the effectiveness of selec-tion for grain yield per se is low. This could be due to thelarge number of genes involved (and hence low heritabilities)(Acevedo, 1993), and large genotype × year, genotype × loca-tion and genotype × year × location interactions (Calhoun etal., 1994; Van Ginkel et al., 1998). Therefore geneticprogress for drought and heat tolerance is usually extremelylow and new varieties are released, for commercial produc-tion, after long periods (8-10 years).

To improve genetic gains and realise productionincreases, more efficient screening and selection methodolo-gies and tools need to be developed (Pfeiffer et al., 2000;

Reynolds et al., 2001). Ludlow and Muchow (1990) notedthat grain yield (under drought) is dependent upon many phe-nological, morphological and physiological characters. Thusthe use of physiological traits as an indirect selection criterionmay be important in augmenting yield-based selection proce-dures (Acevedo, 1993). The use of physiological traitswould, perhaps, result in more precise targeting of factorslimiting yield and hence lead to faster rates of yield improve-ment and broadening of genetic base (Richards et al., 2002).This is because physiological traits are faster to measure thangrain yield; they can be observed gradually at seedling stagebefore flowering, and hence provide an estimate of yieldpotential more easily before final harvest (Edmeades et al.,1996). The breeder can thus eliminate less drought tolerantlines from crossing nursery and shorten time to completeselection cycle.

The objective of this study was to evaluate the responsesof physiological traits, which control grain yield in breadwheat, to water stress. The hypothesis tested was that grainyield of bread wheat produced under drought stress conditionis controlled by several physiological traits, which may beused as indirect selection criterion for drought tolerance inwheat breeding programmes.

Material and methods

Experimental site Two experiments were undertaken in 2001/2002 and 2002/

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2003. Experiment I was carried out in 2001/2002 under fieldconditions at National Dryland Research Centre, Katumani,Machakos, Kenya (1o 33´S, 37o 14´E and 1560 m.a.s.l).Katumani lies in the semi-arid, low potential area withinAgro-Ecozone UM 4 in the Eastern Province of Kenya. Theaverage annual rainfall is about 716 mm, and mean minimumand maximum temperatures are 13.9oC and 24.7oC, respec-tively. Water loss through evaporation is about 1800 mm peryear, creating an annual water deficit of about 1048 mm(ICRAF, 1988). The soils are Ferral Chromic Luvisols,which are well-drained, deep sandy loam to clay loam (Jaet-zold & Schmidt, 1983).

Experiment II was conducted in 2002/2003 under a rain

shelter (by simulating early season drought at seedling stage)at National Plant Breeding Research Centre, Njoro, Kenya(0o 20’S, 35o 56’E and 2160 m.a.s.l). Njoro receives averageannual rainfall of 931 mm and is characterised by mean max-imum and minimum temperatures of 22.7oC and 7.9oC,respectively. The soils are well drained Mollic Andosols withsandy loam (Jaetzold & Schmidt, 1983). The shelter wassimilar to that described by Jefferies (1993), and was 15.5 mlong and 7.5 m wide. Translucent sheets (which allow up to90% of photosynthetic active radiation to pass through) cov-ered the roof. Plots were shielded from rainfall by coveringwith the rain shelter at all rainy times and at night.

Wheat genotypesSeventeen bread wheat genotypes were evaluated in Experi-ment I (Table 1). Out of these, only 12 genotypes (R917,R960, R962, R963, R965, R966, R970, 94b01, KM20, Chozi,Duma and Heroe) were evaluated in Experiment II. Amongstthe 17 genotypes, seven originated from Kenya, including 2drought tolerant checks (Duma and Chozi), and one suscepti-ble commercial check (Heroe). The other 10 were introduc-tions from CIMMYT, and a preliminary evaluation showedthat the genotypes had differences in drought responses,drought susceptibility index, phenotypic traits, maturity peri-ods and yield potential. These genotypes could therefore beloosely classified as drought tolerant (Chozi, Duma, KM14,R960, R963, R965), medium drought tolerant (R920, R840,R966, 94B01, R970) and moderately susceptible (R962,KM15, KM20, R917, R913) (Table 1).

Experimental designExperiment I was conducted during the short rains (SR) sea-son of 2001 (season I) and 2002 (season II). Season I wassown on 26 October 2001 while season II was sown on 22October 2002. In both seasons, 17 wheat genotypes wereplanted in 4 rows, each 6 m long, spaced 0.2 m apart (at aseed rate of 125 kg ha-1) in a randomised complete block

design, replicated three times.Experiment II was a split-plot design sown on 15 Septem-

ber 2002 (season I) and 5 January 2003 (season II) with 3watering regimes as main plots (12 m x 6 m) replicated 3times and 12 wheat genotypes as sub-plots (1 m x 6 m). The3 watering regimes were: high (withholding water supply fora period of 2 weeks; from 7 days after emergence to 21DAE); medium (withholding water supply for a period of 4weeks; from 7 DAE to 35 DAE); and low (withholding watersupply for a period of 6 weeks; from 7 DAE to 49 DAE). Toensure good germination and crop establishment, all experi-mental plots were uniformly watered at planting to 30-32%moisture content (near field capacity). All plots also received30 mm of water at emergence, at 7 DAE and after relieving ofdrought stress. In total the low watering regime received 210mm of moisture, medium watering regime received 240 mm,and high water regime received 270 mm during the growingseason. The amount and frequency of water application sim-ulates the amount and nature of rainfall pattern usuallyreceived in most marginal rainfall areas during cropping sea-son (Jaetzold & Schmidt, 1983; Mugo et al., 1998). Drip irri-gation was used to water the plots (Watermatics, 1999).

In both experiments 70 kg P205 ha-1 and 37 kg N ha-1 wasapplied as Diammonium phosphate (46-18-0) at sowing.

Table 1 The origin, pedigree and drought tolerance level for 17 wheat genotypes evaluated in Experiment I & II.Genotype Origin Pedigree Drought tolerance responseChozi Kenya F12.71/COC//GEN Tolerant Duma Kenya SW 53 = BUCK BUCK ‘S’ Tolerant checkKenya Heroe Kenya MBUNI/SRPC 64//YRPC1 Susceptible checkR913 CIMMYT Mexico KMN/BOW/OPATA Moderately susceptibleR917 CIMMYT Mexico URES/BOW/OPATA Moderately susceptibleR920 CIMMYT Mexico PJN/BOW//OPATA Moderately tolerantR960 CIMMYT Mexico PASTOR TolerantR962 CIMMYT Mexico KLEIN CHAMACO Moderately susceptibleR963 CIMMYT Mexico BOW//URES//KEA/1 TolerantR965 CIMMYT Mexico BOW//BUC/BUL/3/KAUZ TolerantR966 CIMMYT Mexico FILIN Moderately tolerantR970 CIMMYT Mexico PIPED/5PATIO/ALD//PAT/72300/3PUN/4/BOW//46BAW 898 Moderately tolerantR840 CIMMYT Mexico PIPED/5PATIO/ALD//4PAT 72300/3PUN Moderately tolerantKM14 Kenya PASA MUTANT(BUC “S”/CHAT “S” TolerantKM15 Kenya PASA MUTANT Moderately susceptibleKM20 Kenya PASA MUTANT Moderately susceptible94b01 Kenya PUN// BOW/BAW Moderately tolerant

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Aphids were controlled by application of Metasystox at therate of 1 L ha-1. The experimental plots were kept weed-free

throughout the growing season by manual weeding and thecrop was protected from bird damage manually.

Measurement of weather variablesAn automatic weather station located 100 m from the site ofExperiment I recorded rainfall (mm), maximum and mini-mum air temperatures (oC), solar radiation (MJ m-2 d-1) andrelative humidity (RH, %) each day during the experiment(Table 2). Also, instantaneous weather variables like atmos-pheric temperature, RH (%) and photosynthetically activeradiation (PAR) were recorded in Experiment I (Table 3)

using a steady-state porometer (LI-1600Lico Inc. Lincoln,NE, USA).

Measurement of water useTotal crop water use was determined in Experiment II bymonitoring changes in volumetric moisture content through-out the season. Soil moisture content was measured at 7 dintervals using a neutron probe (Troxler Model 4300, New

Table 2 Summary of Weather Data at Katumani, Kenya, during the 2001 and 2002 growing seasons. Monthly totals or means ofdaily values are given (Experiment I).

MeanRainfall(mm)

TotalEpot. (mm)

MaximumDailyTemp (0C)

MinimumDailyTemp (0C)

Mean* Temperature(oC)

SolarRadiation(MJ m-2 d-1)

RelativeHumidity(%)

2001January 244.5 115.4 24.5 14.0 19.3 609.1 71.0February trace 161 26.4 14.3 20.4 694.4 60.0March 113 158 26.7 14.3 21.5 658.1 60.0April 88.9 115.4 24.9 15.1 20.0 549.2 68.5May 15.3 123.8 25.0 14.0 19.5 533.9 63.5June 4.3 79.4 23.6 11.9 17.8 498.2 65.0July 4.3 100.3 21.2 10.9 16.2 490.7 66.0August 2.5 134.5 24.5 11.0 17.8 527.5 59.0September trace 169.5 26.7 12.5 19.6 611.2 54.5October 73 180.3 27.1 13.6 20.4 630.0 51.5November 169 126.1 24.0 14.6 19.3 573.9 69.0December 43.6 127.6 24.2 14.4 19.3 552.7 72.5Mean/Total 758.4 1591.3 24.9 13.1 19.2 577.4 63.42002 January 79.5 148.2 25.9 14.1 20.0 624.4 65.5February 7.5 179.0 27.1 13.9 20.0 676.4 53.0March 98.9 141.6 26.3 15.3 21.3 634.1 65.5April 120.4 151.9 25.8 15.8 20.3 572.4 67.0May 125.6 111.3 24.4 14.2 19.3 475.5 70.0June 94.9 94.9 23.4 12.1 17.8 447.8 66.5July trace 101.3 23.9 13.2 18.6 445.6 65.0August 0.2 120.3 24.1 12.0 18.1 435.6 64.5Mean/Total 527.0 1048.5 25.1 13.8 19.4 539.0 64.6* The mean of daily maximum and minimum temperature

Table 3 Diurnal variation in mean temperature, relative humidity (RH) and photosynthetically active radiation(PAR) at 61 days after emergence, DAE (season I) and 65 DAE (season II) at Katmunai, Kenya (Experiment I).Time Of day (hours) Atmospheric Temperature (0C) RH (%) PAR (μE m-2s-1)

0800 23.0 52.1 780.81000 28.1 39.8 1369.71200 31.3 37.1 1866.81300 34.0 36.7 1941.3

Mean 29.1 41.4 1489.7

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York). Measurements were taken between 7 and 91 DAE(season I) and 7 and 98 DAE (season II). On each occasion,neutron probe readings were taken at 0.1 m depth intervals inthe upper 0.4 m soil profile and at 0.2 m further down the pro-file to a depth of 1.2 m. Volumetric water content at eachdepth was calculated using calibration equations for this site(Ooro, 2004).

Total crop evapotranspiration (ET) was estimated usingthe soil water balance equation:

ET = -ΔS + I – D - R. (1)

Where ΔS is the change in storage (the difference in volumet-ric water content of the entire profile between the start and theend of the experiment), I is irrigation, D is drainage and R isrunoff. Drainage and runoff were assumed to be negligible.No water leaching below 1.0 m depth was observed from neu-tron probe measurements during the crop-growing season(Kimurto et al., 2005).

Water use efficiency (q); the ratio of the total aboveground dry matter produced (DM) to the total amount ofwater used by the crop was determined using the equation:

Measurement of gas exchange parametersIn Experiment I, stomatal conductance (g) and instantaneoustranspiration (T) rates were measured on both upper andlower surfaces of selected uppermost fully expanded leaves attwo hour intervals (between 10:00 and 13:00 hrs) on clearsunny days, at booting stage. This was expected to be themost active physiological growth stage. The measurementswere taken using a steady-state porometer (LI-1600Lico Inc.Lincoln, NE, USA). Stomatal resistance (rs) was calculatedas inverse of stomatal conductance. Net leaf CO2 exchangerates (CER) was measured on selected leaves using a portableInfrared Gas Analyzer (LC-3, IRGA Inc. Lincoln, NE, USA),fitted with Parkinson Leaf chamber, on clear sunny days, atbooting stage. The target leaves were tagged earlier for ageidentification and at each measuring episode, measurementswere taken on leaves of similar age.

Measurement of crop biomass and grain yieldTotal aboveground biomass (Experiment II) and grain yield(Experiment I & II) were determined at final harvest (10 Feb-ruary 2002 and 5 February 2003 for season I & II, respec-tively in Experiment I, and 20 February 2003 and 16 April2003 for season I & II, respectively in Experiment II) by cut-ting all the plants from a 2.4 m2 (Experiment I) and 0.8 m2

(Experiment II) quadrat of inner crop rows at ground level.All the harvested plants were threshed manually, and then allthe plant parts except the grains were oven dried at 70oC forat least 24 h and the dry matter content determined. Finalgrain yield (kg ha-1) was obtained by converting grain yieldper plot into yield per hectare at 13.5% moisture content.Harvest index (HI) was obtained by dividing grain yield withtotal aboveground biomass in each plot in Experiment II.

Statistical analysisAnalysis of variance (ANOVA) was performed using thegeneral linear model (GLM) (SAS, 1996). Data for both sea-sons were pooled and treatment means of all variables meas-ured were separated using Fisher’s least significance test(LSD) at P<0.05.

Results

Crop biomass, grain yield and harvest indexThe interaction between watering regimes and genotypesaffected biomass in Experiment II. The increase in crop bio-mass due to high moisture regime was greater for droughtsusceptible (171-367%; mean 263%) compared with droughttolerant (89-153%; mean 116%) genotypes (Table 4). Simi-larly, the increase in biomass due to medium watering wasgreater for drought susceptible (66-212%) compared withmedium susceptible (46-106%) and drought tolerant (39-93%) genotypes (Table 4). Chozi had greatest biomass underall moisture regimes (2064, 3986 and 5228 kg ha-1 at low,medium and high watering regime, respectively). In contrast,R970 had lowest biomass at low (747 kg ha-1), and high(2333 kg ha-1) moisture regimes while R917 gave lowest bio-mass (1439 kg ha-1) at medium watering regime (Table 4).

Genotype affected grain yield in Experiment I. Grainyield ranged from 861 kg ha-1 (KM20) to 1816 kg ha-1

(R965) (Table 5). The mean grain yield was 39% greater and34% lower than the highest and lowest grain yields, respec-tively. On average, drought tolerant genotypes had greatergrain yield (1530 kg ha-1) compared with susceptible (884 kgha-1) and medium tolerant (1295 kg ha-1) genotypes (Table5). Also, drought tolerant genotypes had 17% greater grainyields than the overall mean. In contrast, drought susceptiblegenotypes had lower (by 32%) grain yield than the overallmean. The interaction between moisture regimes and geno-types affected (P<0.05) grain yield in Experiment II. Theincrease in grain yield due to high watering regime wasgreater for susceptible (269%) compared with drought toler-ant (99%) and medium tolerant (143%) genotypes (Table 4).The increase in grain yield due to high water regime rangedfrom 62% (R963) to 365% (Heroe) (Table 4). Drought toler-ant genotypes had greater (by 120% and 65%, respectively)grain yield (843 kg ha-1) compared with susceptible geno-types (382 kg ha-1) and moderately tolerant genotypes (508kg ha-1) under low moisture regime (Table 4). Similarly,under high moisture regime drought tolerant genotypes hadgreater yields (1734 kg ha-1) compared with susceptible(1190 kg ha-1) and moderately tolerant (1245 kg ha-1) geno-types but the magnitude of the yield differences were muchlower (45% and 39%, respectively) than at low moistureregime (Table 4). The increase in grain yield due to mediumwatering regime was greater for drought susceptible (97%-118%) compared with drought tolerant (38%-93%) geno-types. R960 had greatest grain yield (962 and 1502 kg ha-1,respectively) at both low and medium moisture regimes(Table 4). In contrast, Chozi had greatest grain yield (2134kg ha-1) and R970 had lowest grain yield (809 kg ha-1) at highmoisture level (Table 4).

q DMET---------=

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Table 4 Response of biomass, grain yield, and harvest index (HI) to genotype and water regimes (Experiment II)Genotype/ Biomass Grain yield HIWater regime (kg ha-1) (kg ha-1)Low MoistureChozi 2063.6 867.5 0.42Duma 1719.8 854.8 0.50R960 1884.8 962.2 0.51Heroe 1100.5 341.9 0.31KM20 967.4 269.6 0.28R917 865.2 264.6 0.3194B01 1097.1 491.8 0.45R962 914.4 388.2 0.42R963 1424.7 824.4 0.57R965 1771.8 712.9 0.40R966 1628.3 623.7 0.38R970 746.7 410.7 0.55Mean 1348.1 584.8 0.43

Medium MoistureChozi 3986.4 1417.9 0.36Duma 2385.4 1354.5 0.57R960 2796.6 1502.4 0.54Heroe 2934.8 717.3 0.27KM20 1922.1 531.7 0.29R917 1439.2 465.6 0.3294B01 2260.6 867.3 0.38R962 2857.2 846.8 0.30R963 2084.2 1203.8 0.59R965 3066.5 971.9 0.32R966 3206.1 782.7 0.24R970 1887.7 617.5 0.33Mean 2574.1 940.7 0.36

High moistureChozi 5228.1 2131.8 0.42Duma 3261.4 1769.7 0.54R960 3565.6 1886.7 0.53Heroe 5141.3 1591.7 0.31KM20 2621.4 876.5 0.33R917 2589.5 824.7 0.3294B01 3863.5 1521.1 0.39R962 3816.7 1469.3 0.38R963 3008.3 1574.8 0.52R965 4203.5 1314.6 0.32R966 4567.8 1405.6 0.31R970 2333 808.8 0.35Mean 3680.6 1403.9 0.39

Grmn 2584.5 984.17 0.38CV% 19.75 11.2 7.90

S.E.D 351.0 72.5 0.003Lsd 458.9 107.21 0.03Variety P<0.001 P<0.001 P<0.01Water P<0.005 P<0.001 P<0.01W x G P<0.05 P<0.05 nsW x G = water regime x genotype interaction, ns, not significant

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Harvest index was not affected by the interaction betweenwater regimes and genotypes in Experiment II (Table 4).However, the main effects of genotype and watering regimeon HI were significant (P<0.01) (Table 4). High moistureregime decreased HI by 9% (from 0.43 to 0.39) and mediummoisture regime decreased HI by 16% (from 0.43 to 0.36)(Table 4). Averaged over the moisture regimes, HI variedfrom 0.30 (KM20) to 0.56 (R963) (Table 4). Drought tolerantgenotypes had 76% greater HI (0.51) compared with suscepti-ble genotypes (0.29) (Table 4).

Crop water use (ET)The interaction between water regimes and genotypesaffected (P<0.05) total crop ET in Experiment II. Theincrease in crop ET due to medium watering regime wasgreater for susceptible (26%-64%; average of 32%) comparedwith drought tolerant (16%-34%; average of 23%) genotypes(Table 6). Similarly, the increase in crop ET due to highmoisture was greater for drought susceptible (60%-101%;average of 77%) compared with drought tolerant (27%-68%;average of 55%) genotypes (Table 6). Genotype R965 hadgreatest ET (102.0 mm) under low moisture and Chozi hadgreatest crop ET under both medium (132.0 mm) and high(164.8 mm) moisture regimes (Table 6). In contrast, KM20had lowest ET under both low (70.9 mm) and medium (91.5mm) moisture regimes and R970 recorded lowest crop ET(117.4 mm) at high moisture regime (Table 6).

Water use efficiencyThe interaction between moisture regimes and genotypesaffected (P<0.05) water use efficiency of biomass production(qd, Howell et al., 1998). The increase in qd due to mediummoisture regime ranged from 13% (Duma) to 91% (R970).Also, the increase in qd due to medium moisture regime wasgreater for medium tolerant (65%) compared with susceptible(50%) and drought tolerant (28%) genotypes (Table 6). Incontrast, the increase in qd due to high moisture regime wasgreater for drought susceptible (104%) compared withmedium tolerant (88%) and drought tolerant (41%) genotypes(Table 6). Also, the increase in qd due to high moistureregime varied from 22% to 133% for R960 and Heroe,respectively (Table 6). Greatest qd was recorded in Chozi(21.1 kg ha-1 mm-1), R966 (31.1 kg ha-1 mm-1) and Heroe(32.7 kg ha-1 mm-1) at low, medium and high moistureregimes, respectively (Table 6). In contrast, R970 gave thelowest qd (10.2 kg ha-1 mm-1) at low moisture level and R917gave the lowest qd at both medium (15.2 kg ha-1 mm-1) andhigh (19.5 kg ha-1 mm-1) moisture regimes (Table 6).

The interaction between watering regime and genotypedid not affect water use efficiency of grain production (qg,Howell et al., 1998). However, the effect of genotype on qgwas significant (P<0.001); qg ranged from 4.9 kg ha-1mm-1

(R917) to 12.1 kg ha-1mm-1 (R960). Drought tolerant geno-types had greater qg (11.2 kg ha-1mm-1) compared withmedium tolerant (7.5 kg ha-1mm-1) and susceptible (5.9 kgha-1mm-1) genotypes (Table 6). Medium and high moistureregimes increased qg by 26% (from 6.8 to 8.6 kg ha-1mm-1)and 54% (from 6.8 to 10.5 kg ha-1mm-1), respectively (Table6).

Table 5 Grain yield of 17 wheat genotypes at Katumani, Kenya (Experiment I)Cultivar Grain yield (Kg ha-1)

Chozi 1535.5Duma 1643.1KM14 1586.7R960 1615.8R965 1815.8R963 1604.3R920 1385.5R840 1312.8R966 1455.894B01 1027.7R962 1032.2R970 1294.2Heroe 927.4KM15 866.5KM20 860.6R917 970.1R913 1066.7Mean 1294.9

P(F-ratios) P<0.05CV% 13.7 SED 76.8Lsd 16.4

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Table 6 Response of evapotranspiration (ET), water use efficiency of biomass production (qd) and grain yield (qg) to genotypeand water regimes (Experiment II)Genotype/ ET qd qg Water regime (mm) (kg ha-1mm-1) (kg ha-1mm-1)Low MoistureChozi 97.9 21.1 8.9Duma 90.1 19.1 9.5R960 92.1 20.5 10.4Heroe 78.5 14.0 4.4KM20 70.9 13.6 3.8R917 73.6 11.8 3.694B01 78.3 14.0 6.3R962 86.1 10.6 4.5R963 91.7 15.5 9.0R965 102 17.4 7.0R966 86.6 18.8 7.2R970 73.3 10.2 5.6Mean 85.2 15.8 6.8

Medium moistureChozi 132 30.2 10.7Duma 117.3 20.3 11.5R960 117.2 23.9 12.8Heroe 116.3 25.2 6.2KM20 91.5 21.0 5.8R917 94.8 15.2 4.994B01 113.4 19.9 7.6R962 109 26.2 7.8R963 109.6 19.0 11.0R965 118.8 25.8 8.2R966 102.5 31.3 7.6R970 96.7 19.5 6.4Mean 110.7 23.9 8.6

High moistureChozi 164.8 31.7 12.9Duma 143.8 22.7 12.3R960 143.5 24.8 13.1Heroe 157.1 32.7 10.1KM20 120.4 21.8 7.3R917 132.9 19.5 6.294B01 145.8 26.5 10.4R962 137.7 27.7 10.7R963 130.2 23.1 9.2R965 144 29.2 9.1R966 149.8 30.5 9.4R970 117.4 19.9 6.9Mean 137.1 26.6 10.5

Grmn 112.3 22.8 8.8

CV% 16.7 9.3 7.6S.E.D 46.1 0.93 11.5Lsd 48.19 1.78 2.67Variety P<0.001 P<0.005 P<0.001Water P<0.001 P<0.05 P<0.001W x G P<0.05 P<0.05 nsW x G = water regime x genotype interaction, ns, not significant

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Gas exchange parametersGenotypes affected (P<0.05) leaf temperature in experimentI; leaf temperature varied from 22.1oC (Chozi) to 27.1oC(R913) (Table 7). Leaf temperature was lower in drought tol-erant (23.8oC) compared with medium tolerant (24.3oC) andsusceptible (25.1 C) genotypes (Table 7).

Leaf temperature depression was affected (P<0.05) bygenotype. Leaf temperature depression varied from 0.8oC(R840) to -1.2oC (Chozi) (Table 7). Leaf temperature depres-sion was greater in drought tolerant (-0.7oC) compared withmedium tolerant (-0.3oC) and susceptible (0.5oC) genotypes

(Table 7).The effect of genotype on stomatal conductance (g) and

stomatal resistance (rs) was significant (P<0.001 and P<0.05,respectively). Stomatal conductance varied from 0.59 μmolcm-2 s-1 (KM20) to 2.11 μmol cm-2 s-1 (Chozi) and stomatalresistance varied from 0.47 s cm-1 (Chozi) to 1.69 s cm-1

(KM20) (Table 7). Drought tolerant genotypes had greater(by 158%) g (1.91 μmol cm-2 s-1) compared with susceptible(0.74 μmol cm-2 s-1) genotypes (Table 7). Conversely,drought tolerant genotypes had 60% lower rs (0.51 s cm-1)than susceptible (1.3 s cm-1) genotypes (Table 7).

Instantaneous transpiration was affected (P<0.001) by geno-type; T varied from 9.32 mmol m-2 s-1 (R970) to 18.98 mmolm-2 s-1 (Chozi) (Table 7). Also, T was greater (by 21% and44%, respectively) for drought tolerant compared withmedium tolerant and susceptible genotypes (Table 7).

There was genotypic variation in CER (from 7.2 to 15.7μmol m-2 s-1, respectively for R970 and KM14) in Experi-ment I (Table 7). Drought tolerant genotypes had greaterCER (14.5 μmol m-2 s-1) compared with medium tolerant(10.5 μmol m-2 s-1) and drought susceptible (8.4 μmol m-2 s-1) genotypes (Table 7).

Genotype affected (P<0.05) instantaneous transpirationefficiencies (TE) (ratio of CER to T) in Experiment I. TEvaried from 0.46 (Heroe) to 1.14 μmol C02 mmol H20-1

(KM14 and R965) (Table 7). Duma, KM14, R960, R965, andR840 had TE ratio greater than 1 μmol C02 mmol H20-1,

while TE of the rest genotypes was less than 1 μmol C02mmol H20-1 (Table 7). The average TE of drought tolerantgenotypes was greater than 1 μmol C02 mmol H20-1whilesusceptible and moderately tolerant genotypes had TE valuesof less than 1 μmol C02 mmol H20-1 (Table 7).

DiscussionThe production of biomass was affected by the interactionbetween genotype and moisture regime in Experiment II;although medium and high watering regime increased bio-mass of all genotypes, the increase was greater for droughtsusceptible compared with medium tolerant and drought tol-erant ones. Crop evapotranspiration was subject to a similarinteraction suggesting that biomass production was closelyassociated with crop water use. Similar findings have beenreported in wheat (Kirigwi et al., 2004) and other crops (Sin-

Table 7 Leaf temperature (LT), leaf temperature depression (LTD), and gas exchange parameters of 17 wheat genotypes atKatumani, Kenya (Experiment I)Cultivar LT

(0C)LTD(0C)

TR(mmol m-2 s-1)

g(μmol cm-2 s-1)

rs(s cm-1)

ITE(μmol C02 mmol H20-1)

CER(μmol m-2 s-1)

Chozi 22.1 -1.2 18.98 2.11 0.47 0.78 15.01Duma 24.7 -0.7 13.08 1.92 0.52 1.06 13.92KM14 23.8 -0.2 13.79 2.01 0.50 1.14 15.67R960 23.8 -0.2 14.25 1.81 0.56 1.10 14.95R965 24.0 -0.3 13.90 1.67 0.61 1.14 14.83R963 24.0 -0.3 12.87 1.30 0.77 0.91 12.85R920 24.3 0.6 15.08 1.25 0.80 0.73 11.01R840 25.8 0.8 12.00 1.05 1.00 1.03 12.51R966 23.9 -0.7 17.40 1.27 0.78 0.68 11.0594B01 23.5 -0.6 16.50 1.27 0.79 0.65 10.39R962 24.6 -0.3 15.19 1.03 0.98 0.57 8.77R970 26.2 0.4 9.32 0.62 1.62 0.80 7.20Heroe 24.2 -0.3 15.91 1.05 0.95 0.46 7.95KM15 25.5 0.7 13.62 0.74 1.35 0.57 7.83KM20 25.2 0.5 14.79 0.59 1.69 0.55 7.58R917 25.3 0.6 13.25 0.68 1.47 0.76 10.02R913 27.1 0.7 11.92 0.64 1.56 0.64 7.73Mean 24.6 0.2 14.22 1.25 0.86 0.81 11.17

P(F-ratios) P<0.05 P<0.05 P<0.001 P<0.001 P<0.05 P<0.05 P<0.001CV% 5.93 18.4 13.83 19.6 121.3 28.83 14.2SED 1.46 0.36 1.96 0.24 0.39 0.22 1.57Lsd 1.13 0.36 0.57 0.15 0.52 0.45 3.80Key: g-stomatal conductance, rs-stomatal resistance, TR-Instantaneous transpiration, CER-carbon exchange rates

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clair et al., 1984; Ogola, et al., 2002). Also, drought tolerantgenotypes tended to produce greater biomass under all mois-ture regimes compared with susceptible genotypes. How-ever, the difference in biomass between drought tolerant andsusceptible genotypes was much lower at high (311 kg ha-1;8%) compared with low (811 kg ha-1; 46%) watering regime.High biomass production amongst drought tolerant genotypesmay represent inherent ability of high grain yield potential.This was the case for Chozi (drought tolerant check) andother drought tolerant genotypes, which produced relativelyhigh biomass and grain yield. Indeed, Kimurto (2008) foundhigh correlations (r=0.78*) between grain yield and crop bio-mass of these genotypes. Therefore high biomass productionin water stressed environments could probably be a usefulindicator of high grain yield in such environments and hencecould be used as selection criterion in breeding for superiorperformance in drought environments. This compares wellwith the findings of Fisher (1996), van Ginkel et al. (1998)and Kirigwi et al. (2004) who reported that high biomasspotential is a useful criterion in breeding for superior per-formance in drought environments. In contrast, Ceccarelli(1987) concluded that yield potential in wheat is not a usefulcriterion in breeding for superior performance in droughtenvironments.

Drought tolerant genotypes had greater grain yield com-pared with medium tolerant and susceptible genotypes inExperiment I. The greater grain yield in drought tolerant gen-otypes could be due to greater HI, greater biomass produc-tion, or a combination of greater HI and greater biomassproduction by these genotypes (Kimurto, 2008; Donmez etal., 2001). Although biomass accumulation was not moni-tored in Experiment I, results from Experiment II indicate thatdrought tolerant genotypes had greater biomass at low water-ing regime. Moreover, the average rainfall received (approx-imately 331 mm; 300mm in season I and 362mm in season II)during the crop season in Experiment I was greater than thetotal amount of moisture supplied under high moisture regime(270 mm) in Experiment II. Also, drought tolerant genotypeshad greater HI in Experiment II (HI was not determined inExperiment I). Similar results have been reported elsewhere.For example, Siddique et al. (1990) reported that improvedmechanisms of partition between straw and grain amongstdrought tolerant bread wheat were the main cause ofincreased yield in Mediterranean-type of climate. Morerecently, Richards et al. (2002) noted that drought tolerantgenotypes convert high amounts of biomass into grain thusraising HI and final grain yield.

The interaction between water regime and genotype didnot affect HI in Experiment II. This may suggest that theeffect of drought stress on HI is similar in both drought toler-ant and drought susceptible genotypes and hence HI may notbe a good indicator of drought tolerance. These results arecomparable to the findings of Edhaie (1995) who showed thatthe mean HI for two wheat bread cultivars were similar inwell-watered and drought conditions and hence HI could noteffectively separate tolerant and susceptible cultivars.

The effect of genotype and moisture regime on water useefficiency of biomass production (qd) was subject to interac-tion such that the increase in qd due to medium and highmoisture regime varied with genotype. For example, the

increase in qd due to high moisture regimes was greater fordrought susceptible compared with medium tolerant anddrought tolerant genotypes. The increase in qd due to highmoisture regime could be attributed to a similar increase intotal crop biomass. Similarly, Ogola et al. (2002) reportedthat an increase in qd in maize due to application of nitrogenfertiliser could, in part, be due to increase in biomass. Also,genotypes that had high qd values tended to produce high bio-mass. For example, drought tolerant genotypes had greater qdand biomass under all moisture regimes. Association of highqd with high biomass has also been reported in maize (Ogola,et al., 2005).

The interaction between genotype and watering regimedid not affect water use efficiency of grain production (qg)but genotype and moisture regime affected qg. Drought toler-ant genotypes had 89% greater qg than drought susceptiblegenotypes and high moisture regime increased qg by 54%.This was similar to the observed effect of genotype on HI.Therefore it is likely that drought tolerant genotypes investedmore photosynthates into grain production, probably by max-imising growth early in the season. Earlier, Kimurto et al.(2005) showed that drought tolerant genotypes, especiallyDuma, R963 and R965, sustained early vigour and biomassaccumulation during cooler part of growing season whenvapour pressure deficits are low and postulated that this couldhave enhanced early-season drought stress survival. Theimportance of qg and early-season dry matter production inearly-drought situations has also been reported in winterwheat (Entz & Fowler, 1990).

Drought tolerant genotypes had greater leaf temperaturedepression, lower leaf temperature, greater stomatal conduct-ance, lower (but non-significant) stomatal resistance, greaterinstantaneous transpiration, and greater CER compared withmedium tolerant and susceptible genotypes. It is likely thatdrought tolerant genotypes created cooler conditions aroundthe leaf and were thus able to continue photosynthesising atmoisture levels that were inhibitory to susceptible geno-types. In support of this, drought tolerant genotypes hadgreater grain yield (Experiment I) and greater biomass andgrain yield at low water regime (Experiment II). Theseresults are in line with the conclusions of Fisher et al. (1998)and El Hafid et al. (1998) that higher stomatal conductance,which enhances greater CO2 assimilation, has been docu-mented as a trait for increasing grain yield under stress. Fromthe foregoing, it is clear that stomatal conductance and tran-spiration rates are traits used by tolerant genotypes to enhanceCER and grain yield in drought stress conditions and hencecan be used as indicators of drought tolerance in wheat breed-ing programmes.

Drought tolerant genotypes had greater TE compared withsusceptible genotypes. This is an indication of the ability ofdrought tolerant genotypes to open stomata and fix more car-bon while losing less water in the process. However, thismay not always be the case under drought stress conditionswhen survival is more important than optimal functioning.For example KM14 had the highest TE, but it was not thehighest yielding genotype in this study; an indication thatdrought tolerance may not necessarily lead to high grainyield. This compares with earlier findings in durum wheatthat some genotypes may have high drought tolerance mecha-

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nism but low potential yield (El Hafid et al., 1998). Thisapparent contradiction may perhaps be due to the fact that thephysiological basis of association of yield with photosyn-thetic rates, leaf temperature depression (LTD) and othertraits are not well understood and may probably be controlledby several metabolic processes including sink strength, vas-cular capacity, photosynthetic rates and hormonal signals(Reynolds et al., 1999). In this study increase in stomatalconductance for tolerant genotypes could probably haveaccounted for most of increased carbon assimilation rate.However, TE still offers great promise for possible use as aselection trait for drought tolerance in wheat.

ConclusionThe hypothesis tested in this study was that grain yield ofbread wheat produced under drought stress condition is con-trolled by several physiological traits, which may be used asindirect selection criterion for drought tolerance in breedingprogrammes. This hypothesis was based on the assumptionthat a drought tolerant ideotype would combine all traits con-trolling grain yield and that once identified, these traits couldbe used to select for yield. The hypothesis has not been dis-proved. Genotypes which had greater qg, HI, crop biomass,and stomatal conductance and concomitant high transpiration,and photosynthetic rates gave greater grain yields underdrought stress both in the field and in the rain shelter (seed-ling stage water stress). These traits were identified as keycontrol points in determining the drought resistance of breadwheat genotypes; they can therefore be used to separatedrought susceptible and tolerant wheat germplasm. However,there is need to determine the heritability of these traits inorder to know their potential usefulness in a breeding pro-gram. Furthermore, this study confirms (based on physiolog-ical parameters and grain yields) preliminary findings thathad classified the test genotypes into three groups: droughttolerant (Chozi, Duma, KM14, R960, R963, R965), mediumdrought tolerant (R920, R840, R966, 94B01, R970) and mod-erately susceptible (R962, KM15, KM20, R917, R913).

AcknowledgementWe thank DAAD for funding this work, KARI and EgertonUniversity for providing materials and logistical support, andMr Kamundia for statistical advice.

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