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Sergio quantitative resistance
Sergio quantitative resistance
Sergio quantitative resistance
Sergio quantitative resistance
Sergio quantitative resistance
Sergio quantitative resistance
Sergio quantitative resistance
Sergio quantitative resistance
Sergio quantitative resistance
Sergio quantitative resistance
Sergio quantitative resistance
Sergio quantitative resistance
Sergio quantitative resistance
Sergio quantitative resistance
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Sergio quantitative resistance

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  • 1. Abstract Sixteen barley cultivars with a suscep-tible infection type (IT = 7–8) in the seedling stageto an isolate of race 24 of Puccinia striiformis f. sp.hordei were planted at two locations in Me´xico.Disease severity (DS) parameters were assessedfor the flag leaf and for the upper three leaves. Thecultivars represented at least five levels of quanti-tative resistance ranging from very susceptible toquite resistant. ‘‘Granado’’, ‘‘Gloria/Copal’’ and‘‘Calicuchima-92’’ represented the most resistantgroup and had an IT of 7 or 8. The culti-var · environment interaction variance, althoughsignificant, was very small compared with thecultivar variance. The disease severity parameterswere highly correlated. The monocyclic parameterDSm, measured when the most susceptible cultivarhad reached its maximum DS, was very highlycorrelated with the area under the disease progresscurve (AUDPC), r being 0.98.Components of quantitative resistance wereevaluated in two plant stages. In the seedling stagesmall cultivar effects for the latency period wereobserved, which were not correlated with thequantitative resistance measured in the field. In theadult plant stage the latency period (LP), infectionfrequency (IF) and colonization rate (CR) weremeasured in the upper two leaves. The LP wasmuch longer than in the seedling stage and differedstrongly between cultivars. The differences in IFwere too large, those in CR varied much less. Thecomponents showed association with one another.The LP and IF were well correlated with the AU-DPC (r = 0.7–0.8).Keywords Barley Æ Disease severity Æ Durableresistance Æ Colonization rate Æ Infectionfrequency Æ Latency period Æ Puccinia striiformisf. sp. hordei Æ Quantitative resistance ÆResistance components Æ Yellow rust DeceasedJ. S. Sandoval-Islas Æ G. Mora-Aguilera ÆS. Osada-KawasoeInstituto de Fitosanidad, Colegio de Postgraduados,56230 Montecillo, Texcoco, Me´xicoL. H. M. Broers Æ H. E. VivarCentro Internacional de Mejoramiento de Maı´z yTrigo (CIMMYT), Lisboa 27, Apdo Postal 6-641,Col. Jua´rez, Deleg. Cuauhtemoc, 06600 Me´xico,D. F. Me´xicoPresent Address:L. H. M. BroersNunhems Zaden BV, P.O. Box 4005,6080 AA Haelen, The NetherlandsJ. E. Parlevliet (&)Dept. Plant Sci., Lab. Plant Breeding, P.O. Box 386,6700 AJ, Wageningen, The Netherlandse-mail: jan.parlevliet@wur.nlEuphyticaDOI 10.1007/s10681-006-9236-y123Quantitative resistance and its components in 16 barleycultivars to yellow rust, Puccinia striiformis f. sp. hordeiJ. S. Sandoval-Islas Æ L. H. M. Broers ÆG. Mora-Aguilera Æ J. E. Parlevliet ÆS. Osada-Kawasoe  ÆÆ H. E. VivarReceived: 21 April 2005 / Accepted: 11 July 2006Ó Springer Science+Business Media B.V. 2006
  • 2. IntroductionYellow rust (P. striiformis f. sp. hordei) in barley(Hordeum vulgare) occurs worldwide and is a majordisease in various parts of South, Central and NorthAmerica (Dubin and Stubbs 1986; Chen et al. 1994;Roelfs and Huerta-Espino 1994; Sandoval-Islaset al. 1998). There are different strategies for con-trolling the disease, but genetic resistance is themore economically and environmentally appropri-ate option (Broers and Jacobs 1989). The economicvalue of genetic resistance depends on both its leveland durability (Denissen 1993).As in other cereal–rust pathosystems, in thebarley–yellow rust pathosystem two types ofresistance can be discerned, the hypersensitivityreaction and the quantitative resistance (Osman-Ghani and Manners 1985; Sandoval-Islas et al.1998). The former type is usually inherited in amajor genic way, is typically race-specific andnon-durable. The latter tends to be of a polygenicor oligogenic nature and is often highly durable(Parlevliet 1993). The durability of quantitativeresistance has been demonstrated in variousother cereal–rust pathosystems (Parlevliet 1979;Van Ginkel and Rajaram 1993; Broers et al.1996). Also some barley cultivars with highlevels of quantitative resistance, such as ‘‘UNA-80’’, ‘‘IBTA-80’’, ‘‘Kolla’’, ‘‘Tera´n-78’’ and‘‘Calicuchima-92’’, that were released in SouthAmerica by national programs in the late 1970sand early 1980s, are still resistant to yellow rust.Many barley cultivars with hypersensitiveresistance to yellow rust have been released(Bakshi and Luthra 1971; Roane 1972; Parlevliet1976; Stubbs 1985), but with this kind of resis-tance, the fungal population is able to adaptgenetically, resulting in a loss of effectiveness ofthe resistance (Broers and Jacobs 1989).In both spring and winter barley it has beenfound that some cultivars have high infectiontypes in the seedling stage associated with highlevels of quantitative resistance in the adultplant stage (Osman-Ghani and Manners 1985;Sandoval-Islas et al. 1998).Although quantitative resistance has beenstudied in detail in other cereal–rust pathosys-tems, little information is available for the barley–yellow rust pathosystem. Quantitative resistanceto P. hordei in barley (Parlevliet and VanOmmeren 1975) and to P. triticina in wheat ispartial (Ohm and Shaner 1976; Broers 1989b),and is characterized by a susceptible infectiontype (IT) in both the seedling and the adult plantstages combined with a slow rate of diseasedevelopment. It is therefore partial sensu Par-levliet (Parlevliet and Van Ommeren 1975). Bycontrast, quantitative resistance to wheat yellowrust is not partial sensu Parlevliet since it ischaracterized by a susceptible infection type inthe seedling stage and reduced rate of diseasedevelopment, but the infection type in the adultplant stage is not necessarily a susceptible one(Broers 1993, 1997; Broers et al. 1996; Park andRees 1989).Wheat and barley cultivars with quantitativeresistance to yellow and leaf rust tend to have along latency period, a low infection frequency, adecreased spore production and a short infectiousperiod (Parlevliet 1975; Denissen 1993; Broersand Jacobs 1989; Broers 1997). Latency period isthe most important component of quantitativeresistance in these pathosystems (Parlevliet andVan Ommeren 1975; Neervoort and Parlevliet1978; Broers and Jacobs 1989). The degree ofassociation between these resistance componentsdepends on the pathosystem (Parlevliet 1975;Broers 1989a, 1997; Wilson and Shaner 1989;Habtu and Zadoks 1995).In several cereal–rust pathosystems the quan-titative aspects of cultivar resistance have beendescribed by means of the disease severity (DS)at a certain moment or plant developmentstage, the area under the disease progress curve(AUDPC) or by means of the apparent infectionrate, r, (Parlevliet 1979; Steffenson and Webster1992; Broers et al. 1996; Shaner 1996).This paper studies the quantitative resistanceand its components to yellow rust in a range ofbarley cultivars in three different environmentsto obtain some insight into the range of quan-titative resistance already available in elitematerial and the stability of the expression ofthis character.Euphytica123
  • 3. Materials and methodsField experimentsToluca valleyFifteen barley cultivars from the breeding pro-grams of ICARDA–CIMMYT and INIFAP(Mexico) with different levels of quantitativeresistance to yellow rust, P. striiformis f. sp.hordei, were sown in the summer season in theexperimental fields of CIMMYT in Atizapan nearToluca, Mexico. To create different environmentstwo sowing dates were used, 23 May and 8 June.Both experiments were sown adjacent to eachother in a complete block design with three rep-licates at a rate of 80 kg/ha. A plot consisted oftwo beds each of two rows of 2.0 m length. Thebeds were 0.75 m apart, the rows within beds0.20 m. The distance between plots was 0.75 m.The blocks were separated from each other by apath perpendicular to the direction of the plotrows into which a spreader row of the susceptiblecultivar Cerro Prieto was sown. The yellow rustepidemic was initiated by inoculating a number ofplants in the spreader rows when the plants werein the development stage 20–30 on the scale ofZadoks et al. (1974), about 5½ weeks after sow-ing. The plants were inoculated by injecting themwith 0.5 ml of a spore suspension of P. striiformisf. sp. hordei, isolate Mex-1, of race 24 (Sandoval-Islas et al. 1998). The suspension was obtained bysuspending 2 g of spores per litre of water ontowhich five drops of Tween 20 were added.CelayaThe experiment was sown at the AgriculturalExperiment Station of INIFAP near Celaya at25 November with the same cultivars, except‘‘Arupo’’, which was substituted by ‘‘Apizaco’’.The experiment consisted of a complete blockdesign with four replicates. Each plot had six rowsof 4.0 m length and 0.30 m apart. The plots wereseparated by 0.60 m. The seed rate was 80 kg/ha.As in Toluca, a spreader row with a susceptiblecultivar was planted in the paths separating theblocks. The inoculation, about 3½ weeks aftersowing, was as in Toluca.Field assessmentsThe assessment of the DS started when all culti-vars had developed the flag leaf, developmentstage 39–41 on the scale of Zadoks et al. (1974).Seven assessments (six for Toluca sowing 1), eacha week apart, were taken to be used to calculatethe AUDPC. At each assessment date 12 tillersper plot were taken at random from the twocentral rows and stored in plastic bags in arefrigerated room kept at below 10°C. In the next2 days all samples were assessed. Of each of10 tillers per sample the DS expressed as thepercentage leaf area affected using the modifiedCobb scale (Peterson et al. 1948), the develop-ment stage according to Zadoks et al. (1974) andthe infection type (IT) according to McNeal et al.(1971) were assessed.The DS was assessed on the flag leaves and onthe upper three leaves. It was measured when thehighly susceptible control cultivar reached itsmaximum disease level, DSm (flag leaf) and DSm(upper three leaves), and when the cultivars, whichdiffered in earliness, reached development stage60, DS60 (flag leaf) and DS60 (upper three leaves).Greenhouse and growth room experimentsThe experiments were carried out at CIMMYT,El Bata´n, Mexico with the same 16 cultivars asused in the field experiments. All cultivars had asusceptible infection type in the seedling stageand varied for their DS in the field. Seedlings andadult plants were inoculated with the same isolateas used in the field experiments.Seedling experimentsPer cultivar 20 seeds were sown in rows in plastictrays (40 · 30 · 10 cm) with a mixture of soil,peat moss and sand in a 7:5:5 proportion. Each ofthe two experiments consisted of a randomizedcomplete block design with four replications, eachblock consisting of two trays. Eight cultivars wererandomized within each tray. Eight days oldseedlings, stage 10, were inoculated with auredospore–Soltrol suspension (8 · 105uredosp-ores/ml). Seedlings were incubated for 16 h in amoist chamber at 100% relative humidity, in theEuphytica123
  • 4. dark at 15°C. After incubation, the seedlings weretransferred to a greenhouse with temperatureranges of 15–20/15–18°C night/day and 14 h oflight. After the first flecks were observed, seed-lings were examined every day to detect thepresence of sporulation. The seedling latencyperiod 1 (SLP1) was defined as the number ofdays between the start of incubation and the firstsporulating infection detected in one of theseedlings of a cultivar. The SLP50 was estimatedas the time at which 50% of the seedlings of eachcultivar were sporulating and was calculated bylinear interpolation as described by Parlevliet(1975) for barley leaf rust. The DS of each seed-ling (SDS) was assessed using a modified Cobbscale, which is a pictorial scale (Peterson et al.1948). The IT was rated according to the scale(0 = immune to 9 = fully susceptible) of McNealet al. (1971).Adult plant experimentsPer cultivar seven seeds were sown in plastic pots(18 cm in diameter) in a greenhouse. Ten dayslater five seedlings per pot were kept. The plantswere fertilized every 14 days with 4 g of a mixtureof triple calcium superphosphate and urea in a 1:2proportion. Sowing was performed at weeklyintervals over a period of 6 weeks to ensure theavailability of sufficient plants of each cultivar atthe same development stage, 47–49. Inoculationswere carried out at this stage, when flag leaveswere young and fully developed.Four experiments were carried out each using arandomized complete block design with fourreplications. Each replication consisted of 16 pots,each pot with five plants of a cultivar and only onetiller per plant was inoculated. In experiments oneto three, the flag leaf (FL) and the leaf below theflag leaf (FL-1) of each randomly selected tillerwere inoculated with fresh uredospores. Theinoculation technique, using inoculated water agarpieces followed the procedures described byBroers and Lo´pez-Atilano (1994). One water agarpiece (1.0 · 2.0 cm) with ca. 1,500 spores/cm2wasput in the central part of the adaxial side of eachFL and FL-1. Incubation was done as withthe seedlings. Subsequently the plants weretransferred to a greenhouse with day/night tem-peratures of 18/16°C and 14 h of light. The fourthexperiment was carried out with a different inoc-ulation technique. The FL and FL-1 were inocu-lated with a mixture of 14 mg of fresh uredosporesand 36 mg of spores of Lycopodium, using apaintbrush (size 5). After inoculation, plants weretreated as in experiments 1–3.The latency period 1 (LP1) was defined as thenumber of days between the start of incubationand the first sporulating uredosorus on any oneinoculated leaf of a cultivar. The latency period50 (LP50) and the infection frequency (IF) wereboth measured in the following way. A leaf wasdivided into several longitudinal areas usinglargeleaf veins as separators (Broers and Lo´pez-Atilano 1994). After the LP1 was registered, thenumber of sporulating stripes in these areas wascounted daily until the number did not vary for3 days. The LP50 was assessed when 50% ofsporulating stripes were present and was calcu-lated by linear interpolation as described by Par-levliet (1975). The IF was equal to the totalnumber of sporulating stripes divided by the widthof the leaf in cm where the water agar piece wasplaced. The lesion length was measured twice at10 and 20 days after the LP50 was reached.Therefore, measurements were taken at differenttimes for each cultivar. In this way a large part ofthe variation due to genotypic differences in la-tency period was removed. To calculate the colo-nization rate (CR), the difference in lesion lengthat the first and second measurement was dividedby 10. In order to calculate the error variance ofthe infection frequency (IF), the spore concen-tration in each experiment was estimated bycounting the spores on greased slides placed in thesettling tower next to the water agar pieces. TheIT was assessed only in experiment 4, 30 days afterinoculation.Statistical analysisField experimentsThe AUDPC was calculated using the formula ofCampbell and Madden (1990) for the flag leafalone and for the three upper leaves together. TheEuphytica123
  • 5. Weibull probability density function and cumula-tive distribution can be successfully used to de-scribe a wide range of disease progress curves(Pennypacker et al. 1980; Mora-Aguilera et al.1996). In this formula b is a scale parameter, whichis inversely related to the rate of disease increase.The value b–1is similar, but not the same as theapparent infection rate r of Vanderplank (1963).The differences between cultivar means of thevarious parameters over the three experiments(environments) were tested with the Duncan’sNew Multiple Range test using the combinedGenotype · Environment and Error variance ascalculated from the analysis of variance. Perexperiment a covariance analysis was carried outbetween the DSm (flag leaf) and DSm (upper threeleaves) and the development stage because of thecultivar differences in earliness. Both the Pearsonlinear correlation coefficients and the Spearmanrank correlation coefficients were calculated be-cause of non-normality of the distributions.Greenhouse and growth room experimentsAll experiments were analysed using a random-ized complete block design with four replications.The least significant difference values (LSD atP £ 0.05) are given except for those of the infec-tion frequencies as these deviated too stronglyfrom a normal distribution. An analysis of vari-ance (ANOVA) was carried out for SLP50 andSDS. For adult plant experiments, the experi-mental unit was the pot mean obtained by aver-aging the data of the five tillers per pot. ANOVAcalculations were performed on the basis ofresistance components, leaves and experiments.Pearson linear correlation coefficients were cal-culated between components across cultivars ex-cept for those where the infection frequencieswere involved. In those cases the Spearman rankcorrelation was calculated. The role of the adultplant resistance components on the observedvariation in the DSm, the AUDPC and the b–1,was tested through multiple regression analyses.All statistical analyses were performed with theSAS software package, version 6.09 (SAS InstituteInc. 1988).ResultsField experimentsThe DS data of the flag leaf and those of theupper three leaves followed the same pattern andwere highly correlated in all three experiments.The mean (over three experiments) Pearson lin-ear correlation coefficients for the DSm and theDS60 between those of the flag leaves and those ofthe upper three leaves were 0.98 and 0.97,respectively. Therefore only the data for the up-per three leaves are presented here.The covariance analysis between the DSm andthe development stage (earliness) showed that thecultivar differences in earliness had no significanteffect on the DSm in any of the experiments. Thevariance analysis over the three experiments,carried out on the 14 cultivars tested in all experi-ments (Table 1) showed highly significant effectsfor environments (experiments), cultivars andcultivar · environment interactions for each of thefour DS parameters. The cultivar · environmentTable 1 Analysis of variance of the disease severity whenthe most susceptible cultivar reached its maximum (DSm),when the cultivars reached development stage 60 (DS60),of the area under the disease progress curve (AUDPC)and of the disease increase rate (b–1) of 14 barley cultivars(CV) in three environments (E) when exposed to yellowrust, Puccinia striiformis f. sp. hordeiSource of variation n DSm DS60 AUDPC b–1MS F* MS F* MS F* MS F*E 2 171 10 582 21 396,397 47 0.001700 134Repl. within E 7 51 3 76 3S70,806 8 0.000018 1NSCV 13 9,815 593 4,361 158 490,0579 583 0.002400 186CV · E 26 259 16 159 6 162,377 19 0.000320 25Error 91 16.5 27.7 8,404 0.000013*All F-values highly significant (P £ 0.01), except two, which were significant at P £ 0.05 (S) or not significant (NS)Euphytica123
  • 6. interaction effects, however, were very smallcompared with the cultivar effects.The first infections in the plots in the threeexperiments appeared when all cultivars haddeveloped their flag leaves. After that the epi-demics developed very well. There were consid-erable differences in the rate of disease increasebetween cultivars resulting in large differences inthe DS measured as DSm, DS60 or AUDPC(Tables 2, 3). The cultivar Apizaco appeared verysusceptibe, followed by a group of quite suscep-tible cultivars like Trompillo, Guanajuato, CerroPrieto, Arupo and Puebla. ‘‘Esperanza’’ and‘‘Esmeralda’’ can be considered moderately sus-ceptible, while cultivars such as Calicuchima-92,Gloria/Copal and Aleli appeared quite resistant.Of the 16 cultivars 13 had a basically susceptibleIT (7 or 8) and only three, ‘‘Esmeralda’’, ‘‘Maris/Mink’’ and ‘‘Aleli’’ had a lower IT (Table 3).The four parameters are strongly correlatedwith each other (Table 4). The DS60 is theparameter which is the least correlated with theother three. The DSm and the AUDPC are veryhighly correlated with a correlation coefficient ofat least 0.98.Although the cultivar · environment interac-tion variance was significant it was very smallcompared with the cultivar variance (Table 1).This is born out by the high correlation coeffi-cients between the three environments for all fourepidemiological parameters of the cultivars. ThePearson and Spearman correlation coefficientsbetween the two sowings in Toluca were onaverage 0.97 and 0.93, respectively, while thecorresponding r values between the Tolucasowings and the Celaya sowing were 0.91 and0.87. This indicates that the greater part of thecultivar · environment interaction variance camefrom the sowing in Celaya (Table 5). A consid-erable part of this small G · E interactionvariance comes from ‘‘Centinella’’. This culti-var seemed more susceptible in Toluca than inCelaya.Greenhouse and growth room experimentsSeedling experimentsSeedling latency period 1 (SLP1) did not varyamong cultivars. SLP50, on the other hand,Table 2 Mean disease severity (DS) when the mostsusceptible cultivar reached its maximum DS (DSm),mean DS when the cultivars were at plant stage 60(DS60), mean area under the disease progress curve(AUDPC) and mean disease increase rate (b–1) · 100 inthree experiments of the upper three leaves of 16 barleycultivars when exposed to yellow rust, Puccinia striiformisf. sp. hordeiCultivar Toluca-1 Toluca-2 CelayaDSm DS60 AUDPC b–1DSm DS60 AUDPC b–1DSm DS60 AUDPC b–1Apizaco* 98 37.3 2,854 6.2 99 39.4 2,387 4.8 100 56.6 2,386 3.8Guanajuato 96 61.3 2,160 6.8 83 53.8 1,662 4.4 92 65.9 1,804 3.0Centinela 90 7.4 1,917 5.6 86 30.6 1,720 4.5 50 2.3 790 1.9Arupo* 82 5.6 1,841 4.9 67 16.6 1,430 3.1 76 32.3 1,484 2.7Cerro Prieto 87 29.0 2,047 6.1 75 33.8 1,499 3.8 83 51.4 1,434 2.6Trompillo 83 49.1 2,205 7.2 81 49.3 1,818 4.7 92 67.4 1,870 3.1Puebla 87 21.9 1,810 5.1 71 21.3 1,328 3.2 82 25.6 1,460 2.6Klages 71 47.1 1,388 3.6 66 35.3 1,329 2.6 68 63.5 1,185 2.3Esperanza 39 8.8 770 1.5 29 5.8 509 1.2 55 12.5 933 2.0Esmeralda 39 5.8 702 1.6 36 6.3 535 1.8 53 10.8 811 1.9Ase/3CM** 26 11.5 337 1.4 24 8.4 373 1.3 25 14.7 318 1.4Granado 16 7.8 261 0.9 23 4.6 280 1.4 25 10.7 320 1.4Gloria/Copal 11 2.0 147 1.0 13 3.7 204 0.9 13 6.0 186 1.0Calicuchima-92 9 2.1 110 0.9 11 2.3 127 1.1 9 3.7 133 0.9Maris/Mink** 6 0.8 89 0.6 16 2.2 198 1.2 13 1.6 188 1.1Aleli 6 0.5 100 0.4 15 2.7 166 1.1 20 4.0 309 1.2* The data in italics are missing values estimated from the real data but corrected for the experiment effects** Advanced lines derived from complex crosses; Maris/Mink/Esc.II.72.83.3E.7E.5E.1E//Shyri and Ase/3CM//RO/3/Smai/4/Ruda‘‘S’’/5/Agave‘‘S’’Euphytica123
  • 7. showed small but significant differences betweensome cultivars. The seedling disease severity(SDS) too showed small but significant cultivardifferences (Table 6). ‘‘Guanajuato’’ had thelowest SDS (31%) and ‘‘Arupo’’ the highest(55%). The infection type (IT) was high in allcultivars and varied between 7 and 8. The SLP50and the SDS were not correlated.Table 3 Mean disease severity (DS) when the mostsusceptible cultivar reached its maximum DS (DSm),mean DS when the cultivars were at plant stage 60(DS60), mean area under the disease progress curve(AUDPC), mean disease increase rate (b–1) · 100, andmean infection type (IT) averaged over three experimentsof the upper three leaves of 16 barley cultivars whenexposed to yellow rust, Puccinia striiformis f. sp. hordeiCultivar DSm DS60 AUDPC b–1ITApizaco** 98.8 a* 44.4 bc* 2,542 a* 4.9 a* 8Guanajuato 90.3 a 60.3 a 1,875 bc 4.7 a 7Centinela 75.3 a 13.4 def 1,476 d 4.0 ab 8Arupo*** 75.0 a 18.2 de 1,585 bcd 3.6 ab 7Cerro Prieto 81.7 a 38.1 c 1,660 bcd 4.2 ab 8Trompillo 85.3 a 55.3 ab 1,964 b 5.0 a 8Puebla 80.0 a 22.9 d 1,533 cd 3.6 ab 8Klages 68.3 a 48.6 abc 1,301 d 2.8 bc 7Esperanza 41.0 b 9.0 ef 737 e 1.6 cd 8Esmeralda 42.7 b 7.6 ef 683 ef 1.8 cd 5Ase/3CM**** 25.0 bc 11.5 def 343 efg 1.4 d 8Granado 21.3 bc 7.1 ef 287 g 1.2 d 8Gloria/Copal 12.3 c 3.9 f 179 g 1.0 d 7Calicuchima-92 9.7 c 2.7 f 123 g 1.0 d 7Maris/Mink**** 11.7 c 1.5 f 158 g 1.0 d 5Aleli 13.7 c 2.4 f 192 g 0.9 d 5* Significantly different according to Duncan’s New Multiple Range Test at P = 0.05 if letters are different; ** was presentin only one environment; *** was present in two environments**** See Table 2Table 4 Pearson linear correlation coefficients and Spearman rank correlation coefficients between four epidemiologicalparameters measured in the upper three leaves of barley cultivars affected by yellow rustParameter Pearson SpearmanDSm DS60 AUDPC DSm DS60 AUDPCDS60 0.81 0.93AUDPC 0.99 0.83 0.98 0.88b–10.97 0.83 0.98 0.97 0.92 0.96All values highly significant, P £ 0.001Table 5 Pearson linear correlation coefficients and Spearman rank correlation coefficients between environments for fourepidemiological parameters of barley cultivars affected by yellow rustEnvironments Pearson SpearmanDSm DS60 AUDPC b–1DSm DS60 AUDPC b–1Tol1/Tol2 0.99 0.99 0.92 0.98 0.95 0.97 0.88 0.91Tol1/Cel. 0.93 0.93 0.97 0.91 0.85 0.91 0.92 0.88Tol2/Cel. 0.90 0.89 0.89 0.85 0.86 0.87 0.83 0.85All values highly significant, P £ 0.001Euphytica123
  • 8. Adult plant experimentsLatency period 1 (LP1) and latency period 50(LP50) in the adult plant stage varied widely be-tween cultivars (Table 7) and large, significantdifferences were observed on both the flag leaf(FL) and the leaf below the flag leaf (FL-1). Onthe FL, the LP1 in ‘‘Calicuchima-92’’ was, onaverage, 11.7 days (93%) longer than the LP1 in‘‘Apizaco’’ and on FL-1 it was 8.9 days (60%)longer than the LP1 in ‘‘Apizaco’’. On average,the LP1 on FL-1 was 1.1 days longer than LP1assessed on FL (Table 7). There was a highlysignificant correlation between the values of LP1for the FL and the FL-1 (r = 0.95).On FL’s, the LP50 was on average 55% longeron ‘‘Calicuchima-92’’ than on ‘‘Apizaco’’; a sim-ilar result was found for the FLs-1 (Table 7). Onaverage, LP50 on FL-1 was 0.7 days longer thanLP50 assessed on FL. The correlation coefficientbetween the LP50 for FL and for FL-1 was highand positive (r = 0.94).Infection frequencyThe spore counts on the greased slides in thesettling tower next to the water agar pieces re-vealed very small differences between appliedspore densities. The number of spores per cm2was 1,518, 1,522 and 1,519 for experiment 1, 2 and3, respectively. The IF varied greatly betweencultivars and significant cultivar differences wereobserved in both the FL and FL-1 (Table 8). Inboth the FL and the FL-1 three groups of culti-vars could be discerned. ‘‘Apizaco’’ formed group1 with a very high IF, 23.1 infections per cm in deFL and 14.3 in the FL-1. ‘‘Trompillo’’, ‘‘Guan-ajuato’’, ‘‘Cerro Prieto’’, ‘‘Arupo’’ and ‘‘Ase/3CM’’, with a clearly lower IF (15.1–8.5 for theFL and 7.1–3.4 for the FL-1), formed the secondgroup. The remaining cultivars formed the thirdgroup with an IF ranging from 3.6 to 0.0 on the FLand from 2.5 to 0.0 on the FL-1. The IF on theFL-1 was on all cultivars lower than on the FL,except for ‘‘Esmeralda’’, with no infections at allon both leaves. The Spearman rank correlationcoefficient between the IF’s of the FL and thoseof the FL-1 was high and positive (r = 0.96).Colonization rateThe CR varied significantly between cultivars forboth the FL and FL-1 (Table 8), but the differ-ences between cultivars were considerably smal-ler than for the IF. Remarkable was the high CRof ‘‘Granado’’, which had a very low IF. Severalother cultivars with a low IF had a relatively highCR. Also remarkable was the clearly higher CRin the FL-1 compared with that in the FL, which isa reversal compared with that for the IF. Therewas a high correlation between the CR assessedon FL and the CR assessed on FL-1 (r = 0.85).Infection typeIn the seedling stage ITs among the cultivarsranged from 7 to 8, which is considered to be asusceptible reaction (Table 6). In the adult plantstage the IT ranged from 5 to 8. The cultivarsTable 6 Seedling latency period 50 (SLP50) in days andrelative to that of cv. Apizaco, set at 100% (Rel), meanseedling disease severity (SDS) and relative SDS to that ofApicazo set at 100% (Rel) and infection type (IT) causedby P. striiformis f. sp. hordei race 24 on 16 spring barleycultivars. Means of two experiments. Cultivars are rankedaccording to their latency period (LP1) on the flag leaf(Table 7)Cultivar SLP50aSDS ITDays Rel Mean RelApicazo 9.0 100 48 100 8Trompillo 8.8 98 36 74 8Guanajuato 9.5 106 31 64 7Cerro Prieto 8.7 97 43 89 8Arupo 8.7 97 55 115 7Ase/3CM* 8.6 96 45 94 8Puebla 9.2 102 43 90 8Klages 9.2 102 43 89 7Centinela 9.5 106 47 98 8Granado 9.4 104 47 98 8Maris/Mink* 9.2 102 34 70 7Esperanza 9.5 106 40 82 7Alelı´ 9.1 101 47 97 7Esmeralda 9.4 104 46 95 7Gloria/Copal 9.1 101 45 94 7Calicuchima-92 9.3 103 47 98 7LSD 5%b0.2 2 2 4* See Table 2aPeriod between the start of incubation and sporulation in50% of the seedlingsbLeast significant difference at P < 0.05Euphytica123
  • 9. Maris/Mink, Alelı´ and Esmeralda had an IT of 5;for the other cultivars the IT did not change rel-ative to the IT observed in the seedling stage(Table 7). On all cultivars the IT on FL was thesame as on FL-1.Associations between componentsThe correlation between the SLP50 and the adultplant resistance components LP1, LP50 and IFwere significant but not high, r being 0.5(Table 9). With the CR the correlation wasinsignificant. The Seedling LP and DS showed noassociation with the quantitative resistance in thefield as measured by the AUDPC and the DSm.The LP and the IF in the adult plant stage werevery well correlated. The correlation of the CRwith the LP and IF was inconsistent. The LP andthe IF in the adult plant stage both had a fairlyhigh correlation with the AUDPC and the DSm,that of the LP being slightly higher than that ofthe IF. The CR did not correlate with the quan-titative resistance in the field (Table 9).To investigate the relative contribution of thethree components for quantitative resistancemultiple regression analyses were carried out.Table 10 shows the proportion of the variance ofthe quantitative resistance as measured by theAUDPC or the DSm as explained by the com-ponents studied. The data indicate that the LP isthe most important component and the CR theleast. The data of the experiment Toluca-2 wereleft out as they gave too little extra information;they followed those of Toluca-1 very closely.DiscussionQuantitative resistance to yellow rust in barleyappears to be common. Sandoval-Islas et al. (1998)reported this for advanced lines in the ICARDA/CIMMYT breeding program. Also amongTable 7 Latency period 1 (LP1) and latency period 50(LP50) in days and relative to that of cv. Apizaco set at100% (Rel), measured on the flag leaf (FL) and leaf belowthe flag leaf (FL-1) of 16 spring barley cultivars, and theirinfection types (IT) after exposure to P. striiformis f. sp.hordei race 24. Cultivars are ranked according to their LP1on the flag leafCultivar LP1, mean of three experiments LP50, mean of four experiments ITFL FL-1 FL FL-1Days Rel Days Rel Days Rel Days RelApicazo 12.6 100 14.8 100 15.7 100 17.5 100 8Trompillo 13.2 105 14.7 99 15.8 101 16.4 94 8Guanajuato 14.3 113 15.7 106 16.2 103 17.7 101 7Cerro Prieto 15.9 126 16.7 113 18.1 115 18.8 107 8Arupo 16.8 133 18.6 126 18.7 119 19.6 112 7Ase/3CM* 17.5 139 18.1 122 18.8 120 19.2 110 8Puebla 18.3 145 18.9 128 20.3 129 19.8 113 8Klages 18.5 147 20.0 135 19.7 125 21.6 123 7Centinela 19.4 154 21.3 144 21.3 136 23.3 133 8Granado 19.6 156 23.4 158 21.8 139 22.8 130 8Maris/Mink* 20.2 160 20.4 138 22.2 141 21.8 125 5Esperanza 21.8 173 23.0 155 22.0 140 –b–b8Alelı´ 22.4 178 21.5 145 23.4 149 21.9 125 5Esmeralda 23.5a187a–b–b–b–b–b–b5Gloria/Copal 23.8 189 24.0 162 22.7 145 23.7 135 7Calicuchima-92 24.3 193 23.7 160 24.4 155 26.0 149 7LSD 5%c3.5 28 3.0 20 4.2 27 3.9 22* See Table 2aWas recorded only in one experimentbInfection frequency was 0cLeast significant difference with P £ 0.05Euphytica123
  • 10. cultivars quantitative resistance it is far from rareas is shown by the research reported here. This is inagreement with the conclusion of Parlevliet (1993)that oligogenic or polygenic quantitative resistanceis present at low to fair levels in most cultivars ofnearly all crops to all important pathogens.Table 8 Number of sporulating stripes per cm leaf width(IF) and the colonization rate in mm per day (CR) of P.striiformis f. sp. hordei race 24, measured on the flag leaf(FL) and the leaf below the flag leaf (FL-1) and the samevalues relative to those of cv. Apizaco set at 100% (Rel) of16 spring barley cultivars. Mean of three experiments.Cultivars are ranked according to their mean LP1 on theflag leaf (Table 7)Cultivar IF CRFL FL-1 FL FL-1Mean Rel Mean Rel Mean Rel Mean RelApicazo 23.1 100 14.3 100 2.81 100 3.26 100Trompillo 15.1 65 7.1 50 2.74 98 3.17 97Guanajuato 10.4 45 5.0 35 2.55 91 2.76 85Cerro Prieto 7.0 30 4.3 30 2.53 90 3.53 108Arupo 11.0 48 3.4 24 1.48 53 2.86 88Ase/3CM* 8.5 37 6.2 43 2.49 89 2.94 90Puebla 2.6 11 1.1 8 2.34 83 3.00 92Klages 2.5 11 1.5 10 1.41 50 1.63 50Centinela 2.8 12 1.3 9 1.84 65 2.83 73Granado 0.2 < 1 0.03 < 1 3.00 107 4.70 144Maris/Mink* 3.6 16 2.5 17 1.56 56 1.21 37Esperanza 0.01 < 1 0.0 0 0.30 11 –a–aAlelı´ 1.4 6 1.0 7 1.49 53 1.70 52Esmeralda 0.0 0 0.0 0 –a–a–a–aGloria/Copal 0.5 2 0.3 2 1.25 44 1.89 58Calicuchima-92 1.1 5 0.5 3 1.44 51 1.90 58LSD 5%b– – – – 1.40 50 1.73 53aInfection frequency was 0bLeast significant difference with P £ 0.05* See Table 2Table 9 Pearson linear correlation and Spearman rankcorrelation coefficients (in italics) between fivecomponents of quantitative resistance to P. striiformis f.sp. hordei measured on the flag leaf (FL) and leaf belowthe flag leaf (FL-1) of 16 barley cultivars, and threeepidemiological parameters measured in the field in threeenvironmentsComponents LP1bLP50cIFdCReAUDPCfDSmgb–1 hSLP50aFL 0.50* 0.48* –0.48* –0.23NS–0.25NS–0.13NS–0.25NSFL-1 0.52* 0.49* –0.42NS–0.13NS–0.24NS–0.24NS–0.28NSLP1bFL 0.98** –0.87** –0.70** –0.75** –0.75** –0.83**FL-1 0.96** –0.87** –0.32NS–0.77** –0.80** –0.82**LP50cFL –0.83** –0.63* –0.77** –0.78** –0.83**FL-1 –0.85** –0.42NS–0.71** –0.74** –0.74**IFdFL 0.54** 0.73** 0.68** 0.66**FL-1 0.43NS0.75** 0.71** 0.74**CReFL 0.30NS0.37NS0.42NSFL-1 0.35NS0.38NS0.41NSaSeedling latency period 50b, c, d, eThe latency period 1, the latency period 50, the infection frequency and the colonization rate observed on the flagleaf and flag leaf minus one, respectivelyf, g, hThe area under the disease progress curve, the disease severity (DS) when the most susceptible cultivar reached itsmaximum DS, and b–1, an estimator of the rate of disease increase according to the Weibull model** P £ 0.01; * P £ 0.05; NS= not significantEuphytica123
  • 11. The cultivars with a susceptible IT in the adultplant stage represented at least five levels ofquantitative resistance ranging from verysusceptible to quite resistant (Table 3) suggestingan oligogenic or polygenic inheritance. Thisagrees with Sandoval-Islas et al. (2002), whoconcluded that the quantitative resistance in‘‘Calicuchima-92’’, ‘‘Gloria/Copal’’ and ‘‘Alelı´’’was incompletely recessive and inherited in anoligogenic way. QTL analysis confirmed that arestricted number of QTLs can give a fairly highlevel of quantitative resistance. QTLs were foundat chromosomes 4, 5 and 7 (Castro et al. 2003a,b). In the present study the quantitative resistancewas expressed very well in all three environments,the cultivar · environment (G · E) interactionvariance being very small compared to the verylarge cultivar variance (Table 1). This stableexpression of quantitative resistance is also re-ported from other cereal–rust pathosystems. Thepartial resistance to wheat leaf rust, P. triticina,came to expression very well in widely differentenvironments such as Mexico, Brazil, and TheNetherlands (Broers and Parlevliet 1989). Thepartial resistance to barley leaf rust, P. hordei, toois very stable, being expressed very well inWestern Europe, Morocco, Israel and Mexico(Parlevliet et al. 1988).The covariance analysis did not indicate a sig-nificant effect of earliness on the DSm. This is notsurprising as the epidemics developed after allcultivars had developed their flag leaves. Thedifferences in ranking between the DSm and theDS60 do, however, suggest some effect of latenesson the DS (Tables 2, 3). Four of the quite resis-tant cultivars are late heading, while several ofthe susceptible cultivars are early heading. Theassociation between later heading and higherlevels of quantitative resistance in barley to yel-low rust also exists to barley leaf rust (Parlevlietand Van Ommeren 1975).To assess the DS accurately and reliably, vari-ous parameters, such as the DSm, the AUDPCand the apparent infection rate have been used byvarious researchers (Parlevliet 1979; Kranz 1983;Steffenson and Webster 1992; Shaner 1996). TheAUDPC is often considered the best parameteras it estimates the DS over the full period ofexposure to the disease. Gaunt (1995) mentionedthat single point models are only useful when theepidemic development is not too variable andoccurs relatively late in the crop development. Inthis study the correlation between the AUDPCwas very high with the DSm and the disease in-crease rate, and fairly high with the DS60. Thishigh correlation is probably due to the rather latedevelopment, from ear emergence onward, of theepidemics in all three experiments. For selectionpurposes the DSm is very suitable as the breederneeds a fast and reliable evaluation method. TheAUDPC on the other hand is more suitable forscientific studies were accuracy is most importantTable 10 Proportion of the variance of the area under thedisease progress curve (AUDPC) and the disease severitymeasured when the most susceptible cultivar reached itsmaximum disease severity (DSm) of P. striiformis f. sp.hordei development on 16 spring barley cultivars in twofield experiments, explained by one, two or threecomponents of quantitative resistance measured on theflag leaf and the flag leaf minus oneEpidemiological parameter Exp. ComponentaLP1 IF CR LP1 + IF LP1 + CR LP1 + IF + CRFlag leafAUDPC Toluca-1 0.56 0.41 0.05 0.56 0.66 0.67DSm Toluca-1 0.53 0.29 0.06 0.55 0.60 0.67AUDPC Celaya 0.61 0.49 0.12 0.61 0.71 0.71DSm Celaya 0.58 0.35 0.11 0.60 0.70 0.72Leaf below flag leafAUDPC Toluca-1 0.55 0.22 0.11 0.72 0.57 0.74DSm Toluca-1 0.51 0.20 0.10 0.69 0.54 0.71AUDPC Celaya 0.73 0.47 0.13 0.73 0.74 0.74DSm Celaya 0.71 0.35 0.15 0.74 0.73 0.76Mean 0.60 0.35 0.11 0.65 0.66 0.72aLP1, IF and CR are, respectively, latency period 1, infection frequency and colonization rateEuphytica123
  • 12. and for environments were yellow rust developsearly or irregularly. The parameters ‘‘apparentinfection rate’’ and ‘‘disease increase rate’’ havethe disadvantage of being less accurate than theAUDPC as they tend to harbour a larger error.Although the DS60 could be thought to be thebetter assessment method as it would take intoaccount differences in heading date it has at thesame time the disadvantage that the observationsare taken at different moments, which mayintroduce another error. In this study it was theparameter that correlated less well with the otherthree parameters (Table 4).The LP, IF and CR are important componentsof quantitative resistance (Mehta and Zadoks1970; Parlevliet 1975, 1979; Parlevliet and Kuiper1977; Broers 1989a, b; Habtu and Zadoks 1995;Broers 1997). In the seedling stage the differencesin LP among cultivars were small. Osman-Ghaniand Manners (1985), working with the samepathosystem, found similar results for winterbarley. In the barley–barley leaf rust pathosystemParlevliet (1975) and Parlevliet and Van Omm-eren (1975) also observed small cultivar differ-ences in LP in the seedling stage, while the LP inthe flag leaf showed much larger differences be-tween cultivars. The flag leaf LP was very highlycorrelated with the partial resistance in the field.In the wheat-leaf rust pathosystem the observa-tions were very similar (Broers 1989a, b).Apparently quantitative resistance is expressed toa limited extent in the seedling stage. In this stageresistance is usually not necessary as the diseasenormally develops in later plant stages. In theadult plant stage the LP was much longer andthe cultivar differences much larger than in theseedling stage, similar to the situation in the leafrusts of barley and wheat as mentioned above.The LP is often considered to be a very importantcomponent of quantitative resistance. Zadoks(1971) and Teng et al. (1977) demonstrated thatsmall changes in the LP can have a strong impacton the development of rust epidemics. The IFshowed large differences among cultivars. Similarresults have been found in several other patho-systems (Parlevliet and Kuiper 1977; Ahn andOu 1982; Groth and Urs 1982; Broers 1989a, b).The CR is a more complex component. Thegrowth of rust infections is density dependent. Inbean rust the growth rate of uredosori and sporeproduction were negatively associated withinfection density (Yarwood 1961). In wheat leafrust (Mehta and Zadoks 1970) and barley leaf rustthe same was observed (Baart et al. 1991). Thisdensity depending effect starts as soon as themuch energy asking spore production starts. Inthe initial period of infection, before the sporeproduction starts, there is no effect of the infec-tion density on the growth of the colonies (Baartet al. 1991). The density effect is strong and itprobably played a role here too. The differencesin IF between cultivars was large and as a con-sequence affected the cultivar effects on CRconsiderably, resulting in fairly high CR’s for thecultivars with a very low IF. This also explains itslow correlation with the AUDPC and the DSm.The CR is therefore most likely not an indepen-dent component of resistance. As a consequence,assessing it accurately is very difficult and esti-mating its effect on quantitative resistance seemshardly possible.The component long LP was best expressed inthe flag leaf, the component low IF in the leafbelow it. This reverse effect may be explained bythe difference in age of the two leaves, the flagleaf being younger than the leaf below it.Parlevliet (1975) found that the LP of all barleycultivars decreased with increasing age of theleaves. This was not observed with the IF(Parlevliet and Kuiper 1977).Within many plant–pathogen systems, associa-tion between components of quantitative resistancehave been reported, although the degree ofassociation can vary considerably (Parlevliet1992). The barley–yellow rust pathosystem is noexception. The LP and the IF in the adult plantstage are mutually correlated and correlated wellwith the quantitative resistance as measured bythe DSm and the AUDPC. The quantitative resis-tance in three of the cultivars investigated hereappeared to be controlled by two or three genes(Sandoval et al. 2002). The strong associationbetween the LP and IF is suggestive for a control ofboth components by these two or three genes.Of the three components investigated, thevariance in the LP contributed most, 60%, thevariance in the IF less, 35%, and the variance inthe CR little, 11%, to the quantitative resistanceEuphytica123
  • 13. (Table 10). As mentioned above, the contributionof CR is probably underestimated due to itsnegative association with IF.It can be concluded that quantitative resistancecan be assessed very well in the field. Due to itscommon occurrence selection for higher levels ofquantitative resistance should not be difficult.Acknowledgements This research was partly financed bythe Dutch Minister for Development Cooperation (DGIS/DST/SO), Colegio de Postgraduados and Consejo Nac-ional de Ciencia y Tecnologı´a de Me´xico (CONACYT) asa part of a collaborative project between the InternationalMaize and Wheat Improvement Center (CIMMYT) inMexico and the Department of Plant Breeding of theWageningen Agricultural University (WAU). We thankDiego Gonza´lez de Leon for critical reading and RosaAtilano for technical assistance.ReferencesAhn SW, Ou SH (1982) Epidemiological implications ofthe spectrum of resistance to rice blast. 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