BIOTIC AND ABIOTIC FACTORS ASSOCIATED WITH … · Soil suppressiveness to Rhizoctonia solani 153 ... BIOTIC AND ABIOTIC FACTORS ASSOCIATED WITH SOIL SUPPRESSIVENESS TO Rhizoctonia

Soil suppressiveness to Rhizoctonia solani 153

Sci. Agric. (Piracicaba, Braz.), v.63, n.2, p.153-160, Mar./Apr. 2006

BIOTIC AND ABIOTIC FACTORS ASSOCIATED WITHSOIL SUPPRESSIVENESS TO Rhizoctonia solani

Raquel Ghini*; Marcelo Augusto Boechat Morandi

Embrapa Meio Ambiente, C.P. 69 - 13820-000 - Jaguariúna, SP - Brasil.*Corresponding author <[email protected]>

ABSTRACT: Crop management may modify soil characteristics, and as a consequence, alter incidence ofdiseases caused by soilborne pathogens. This study evaluated the suppressiveness to R. solani in 59 soilsamples from a microbasin. Soil sampling areas included undisturbed forest, pasture and fallow groundareas, annual crops, perennial crops, and ploughed soil. The soil samples were characterized according toabiotic variables (pH; electrical conductivity; organic matter content; N total; P; K; Ca; Mg; Al; H; S; Na;Fe; Mn; Cu; Zn; B; cation exchange capacity; sum of bases and base saturation) and biotic variables (totalmicrobial activity evaluated by the CO2 evolution and fluorescein diacetate hydrolysis; culturable bacterial,fungal, actinomycetes, protozoa, fluorescent Pseudomonas and Fusarium spp. communities). Thecontribution and relationships of these variables to suppression to R. solani were assessed by path analysis.When all samples were analyzed together, only abiotic variables correlated with suppression of R. solani,but the entire set of variables explained only 51% of the total variation. However, when samples weregrouped and analyzed by vegetation cover, the set of evaluated variables in all cases accounted for morethan 90% of the variation in suppression of the pathogen. In highly suppressive soils of forest and pasture/fallow ground areas, several abiotic variables and fluorescein diacetate hydrolysis correlated withsuppression of R. solani and the set of variables explained more than 98% of suppressiveness.Key words: soilborne pathogen, soil microorganisms, biological control, path analysis, suppressive soil

FATORES BIÓTICOS E ABIÓTICOS ASSOCIADOS ÀSUPRESSIVIDADE DE SOLOS A Rhizoctonia solani

RESUMO: As atividades agrícolas podem modificar as características do solo e, como conseqüência,alterar a incidência de patógenos veiculados pelo solo. Este trabalho avaliou a supressividade a R. solaniem 59 amostras de solos de uma microbacia. As áreas amostradas foram selecionadas quanto à vegetação,incluindo mata, pasto/pousio, culturas anuais, culturas perenes e solo arado. As amostras de solo foramcaracterizadas quanto às propriedades abióticas (pH, condutividade elétrica, teor de matéria orgânica, Ntotal, P, K, Ca, Mg, Al, H, S, Na, Fe, Mn, Cu, Zn, B, capacidade de troca catiônica, soma de bases esaturação de bases) e bióticas (atividade microbiana do solo, avaliada pelo desprendimento de CO2 ehidrólise de diacetato de fluoresceína; comunidades de bactérias, fungos, actinomicetos, protozoários,Pseudomonas fluorescentes e Fusarium spp.). A contribuição e relação dessas variáveis para asupressividade a R. solani foram quantificadas por análise de coeficientes de trilha. Quando se avaliaramtodas as amostras em conjunto, somente variáveis abióticas apresentaram correlação com a supressão a R.solani, mas o conjunto das variáveis explicou somente 51% da variação total. Entretanto, quando as amostrasforam agrupadas e analisadas considerando o tipo de cobertura vegetal, o conjunto de variáveis explicoumais de 90% da variação da supressividade. Para as áreas de floresta e pasto/pousio, as quais foramclassificadas como as mais supressivas, algumas variáveis abióticas e a hidrólise de diacetato de fluoresceínaapresentaram correlação com a supressão de R. solani e o conjunto de variáveis explicou mais de 98% dasupressividade nesses solos.Palavras-chave: patógeno de solo, microrganismos do solo, controle biológico, análise de trilha, solosupressivo

INTRODUCTION

In suppressive soils (Baker & Cook, 1974), thedevelopment of diseases is suppressed even whenpathogens are present and hosts are susceptible. Soilsuppressiveness could result from biotic and abioticfactors, in a diverse and complex set of mechanisms.

A holistic approach is generally needed to study sup-pressiveness, since the contributing factors normallywork interactively (Schneider, 1982). Once a soil be-comes suppressive to a target pathogen, the determi-nation of its main physical, chemical and biologicalattributes can be useful for understanding the mecha-nisms of suppressiveness, and to exploit the informa-

Ghini & Morandi154


tion in other areas where the same pathogen is a prob-lem (Rodríguez-Kábana & Calvet, 1994).

Rhizoctonia solani has great importance amongsoilborne plant pathogens, and damages a wide rangeof hosts worldwide. Ghini & Zaroni (2001) evaluatedand grouped statistically by Ward´s method (Everitt,1981), soils inside a microbasin in categories of sup-pressiveness against R. solani. The authors defined themicrobasin as the physiographic unit for the workbased on its climatic homogeneity, convergent waterdrainage and diversity of vegetation. In general, thepasture and fallow ground areas, followed by undis-turbed forest covered areas, were correlated with sup-pressiveness, while ploughed soils and cultivated soilswith annual (corn) or perennial (sugar cane and cof-fee) crops were most correlated with conducivity.

However, other factors besides vegetation wereinvolved in the suppressiveness to R. solani. The lit-erature describes several factors that could influencethe suppressiveness of soils to the pathogen, includ-ing soil microbiota (Kobayashi & Ko, 1985), the Tri-choderma community (Chet & Baker, 1980; Henis etal., 1979; Liu & Baker, 1980) and pH, moisture andtype of soil (Henis et al., 1979; Liu & Baker, 1980).

The objective of the present work was toevaluate the contribution and relationships of abiotic(chemical properties) and biotic (microorganisms) fac-tors to the suppressiveness of soils from the CórregoTaquara Branca microbasin to R. solani.

MATERIAL AND METHODS

Soil samplingSampling included 59 areas within the Córrego

Taquara Branca microbasin (22º50’ to 22º55’S;47º15’00" to 47º18’45"W), São Paulo state, Brazil. Ar-eas were selected based on vegetation cover, and in-cluded undisturbed forest (10), pasture and fallowground areas (11), annual crops (18), perennial crops(16), and ploughed soil (4). From each area, seven soilsub-samples (80 × 80 × 80 mm) were taken randomly,homogenized and sieved (4 mm). Soil for microbiologi-cal analysis was processed within 24 h after sampling.

Biotic soil characteristicsThe following biotic variables were evaluated

on each soil sample: total microbial activity; culturablebacterial, fungal, actinomycetes and protozoa commu-nities; and, populations of Fusarium spp. and fluores-cent Pseudomonas spp. The total microbial activity ofthe soil was evaluated by measuring the respiratory ac-tivity (determination of CO2 evolution) and overall en-zymatic activity (hydrolysis of fluorescein diacetate,FDA). To evaluate the CO2 evolution, 200-g soil

samples (n = 3) were placed in plastic, hermetic flasks(2.5 L) containing 10 mL of KOH 0.5 N, and incubatedat 25ºC in the dark. After seven, 14 and 21 days, theKOH solution was titrated with HCl (Grisi, 1978), foranalysis of the total amount of CO2 (μg CO2 g

-1 dry soil).For FDA hydrolysis, the method of Chen et al.

(1988) was used. Soil samples (5 g; n = 5) were placedin 250 mL Erlenmeyer flasks and mixed with 20 mLof potassium phosphate buffer (60 mM; pH 7.6). Thehydrolysis reaction was triggered by the addition of 0.2mL of FDA stock solution (2 mg FDA mL-1 acetone)and the flasks were incubated on a rotary shaker (200rpm) at 25ºC for 20 min. The reaction was halted bythe addition of 20 mL of acetone per flask, and the con-tent of each flask was filtered on Whatman nº 1 filterpaper. The absorbance (490 nm) of the filtrate was de-termined spectrophotometrically. To determine the con-centration of the hydrolyzed fluorescein (μg hydro-lyzed FDA g-1 of dry soil), the absorbance of thesamples were compared against a standard curve, ob-tained by following the same methodology, except thata known concentration of FDA was added to the po-tassium phosphate buffer and the flasks were kept at100ºC for 60 min to hydrolyze the FDA, before it wasmixed with the soil samples.

All other variables, except protozoa communities,were assessed by counting colonies forming units (CFUs)on selective agar media, as follows: Martin’s medium forfungi; agar-nutrients plus nistatine 42 mg L-1 for bacte-ria; alkalinized water-agar medium (pH 10.5) for actino-mycetes; King’s medium B for fluorescent Pseudomonasspp.; and a selective medium for Fusarium spp. (Nash &Snyder, 1962). For each soil sample, aliquots of 100 μLfrom two dilutions (10-1 and 10-2 for general fungi andFusarium spp.; 10-2 and 10-3 for fluorescent Pseudomo-nas spp.; and 10-3 and 10-4 for bacteria and actinomycetes)were applied to Petri dishes (n = 3) containing the spe-cific medium, and incubated upside down at 25ºC untilcolonies were visible (after one day for bacteria; two daysfor general fungi, Fusarium spp. and fluorescentPseudomonas; and five days for actinomycetes). Proto-zoan communities were assessed using the method de-scribed by Stotzky et al. (1993).

Abiotic soil characteristicsThe following abiotic variables were esti-

mated, for each soil sample: pH; electrical conductiv-ity (EC); organic matter content; N total; P; K; Ca; Mg;Al; H; S; Na; Fe; Mn; Cu; Zn; B; cation exchange ca-pacity (CEC); sum of bases (S value, sum of Ca, Mg,K, and Na); and base saturation (V%) (Silva, 1999).

Suppression of R. solani growthThe suppression of mycelial growth of R.

solani AG 4 HG-I, isolated from symptomatic plants



of common bean (Phaseolus vulgaris L.), was evalu-ated on 15-cm Petri dishes containing the soil samples(50 g of soil per dish) (Ko & Ho, 1983). Moisture ofsoil samples was adjusted to 70% of field capacity.Samples were then placed in the dishes and coveredwith a thin layer of water agar medium. One disk(7 mm of diameter) of R. solani mycelium grownon PDA was transferred to the center of each dish(n = 3). The dishes were kept at 25ºC in the darkand perpendicular diameter of the R. solani colonieswere measured daily using a stereomicroscope(12x). The Area Under Growth Curve (AUGC) of R.solani from the first to the fourth day of incubationfor each soil sample was calculated and used foranalysis.

Data analysisThe relative importance of individual biotic

and abiotic factors on R. solani growth suppression andtheir interactions were assessed by path coefficientanalysis (Wright, 1921). Correlations between vari-ables were divided over direct and indirect influencesalong different paths in a system. The direct influences,or path coefficients, of a set of variables (causes) upona certain variable (effect) indicate the degree to whichvariation of that effect is determined in each particu-lar cause. The assumption of path analysis is that re-lationships between variables can be causally struc-

tured (van Bruggen & Arneson, 1986). If variables arenot completely explained by other variables in the sys-tem, an extra variable that contains residual influencesand experimental error can be added. A general rela-tional diagram showing all the possible relationshipsbetween biotic and abiotic, explicative variables mea-sured and the R. solani growth suppression (dependentvariable) is given (Figure 1).

Correlation matrices between data for growthsuppression of R. solani and the biotic and abiotic vari-ables (independent variables) were generated for eachsampled soil, grouped by plant cover (forest, pasture,annual crops, perennial crops, and ploughed soil). An-other matrix correlating R. solani growth suppressionwith all samples, independently of the soil coverage,was also generated. The path coefficient analysis wasperformed using Software ‘GENES’ (Quantitative Ge-netics and Experimental Statistics Analysis, vs. 0.1.0,http://www.ufv.br/dbg/home.htm) (Cruz, 2001), and thestudied variables were grouped in a causal diagram in-corporating possible pathways of influence on R. solanigrowth suppression.

The results of the path analysis were inter-preted according to directives proposed by Singh &Chaudary (1979): 1. If the correlation coefficient (r)between the causal factor and the effect is almost thesame as its direct effect, the correlation can explain theactual relation between them and a direct selection

Figure 1 - General diagram showing the possible relationships between the biotic and abiotic variables (causal or explicative variables)measured on soil samples and the suppressiveness to Rhizoctonia solani growth (dependent variable). Dashed arrows showthe direct effects of the explicative variables on dependent variable (Pij). Solid arrows show the indirect effects (rij x Pij),where rij represents the correlation coefficients among explicative variables and Pij represents the path coefficients. The totaleffects of a given explicative variable on the dependent variable is calculated by Rtotali = Pij+Σ(rij x Pij). The correlation andpath coefficients values for the most significant relationships on each soil are shown on Tables 3 to 5. The following abioticvariables were evaluated: pH, electrical conductivity, organic matter content, total N, P, K, Ca, Mg, Al, H, S, Na, Fe, Mn,Cu, Zn, B, CEC, S value e V(%). The biotic variables evaluated were: culturable bacterial, fungi, actinomycetes, protozoa,fluorescent Pseudomonas and Fusarium communities, total microbial activity on soil (FDA hydrolysis and CO2 evolution).On diagram, n represents variables not shown.

Ghini & Morandi156


based on this factor will be efficient; and, 2. If the cor-relation is positive (or negative) but the direct effectis negative, positive or can be ignored, the indirect ef-fects seem to be the cause of the correlation. In suchsituations, the indirect causal factors should be evalu-ated simultaneously. To select the major variable(s) andits/their influence on R. solani suppressiveness, the fol-lowing criteria were used: a) statistical significance oncorrelation at α = 0.05 by t test; and b) the fulfillmentof the directives of Singh & Chaudary (1979).

RESULTS AND DISCUSSION

Ghini & Zaroni (2001) had previously groupedthe same areas of the microbasin in categories of sup-

pressiveness, based on vegetation cover. The pasture,fallow ground and forest covered areas were classifiedas suppressive soils, while ploughed soils and culti-vated soils, with annual or perennial crops, as condu-cive soils. However, in that work it was not possibleto determine the factors that contributed to the gradi-ent of suppressiveness of the soils to R. solani.

In this study, biotic and abiotic characteristicsof the soils were assessed (Table 1), and the contribu-tion of each variable to the suppression of R. solanigrowth was determined by path coefficient analysis.This analysis has rarely been used in plant pathology,but van Bruggen & Arneson (1986) indicate the po-tential use of this technique, such as to assess the rela-tive importance of certain factors contributing to patho-

Table 1 - Mean values of abiotic and biotic variables from soils of the Córrego Taquara Branca microbasin and the AreaUnder Growth Curve (AUGC) of Rhizoctonia solani mycelial growth on Petri dishes containing soil samplestaken from different vegetation areas inside the microbasin.

elbairaV tinUnoitategeV

/erutsaPdnuorgwollaf

tseroFlaunnAporc

lainnerePporc

dehguolPlios

H(Hp 2 )O 78.5 73.5 89.5 39.5 02.6lacirtcelE ytivitcudnoc μ mcS 1- 70.45 95.59 10.271 81.97 33.721

rettamcinagrO gkg 1- 54.62 05.83 44.91 60.91 05.02)latot(N % 31.0 91.0 01.0 01.0 11.0

P mdgm 3- 76.94 64.21 67.77 65.38 34.89K lomm c md 3- 89.5 47.3 40.5 43.6 81.7aC lomm c md 3- 46.13 02.91 82.05 57.33 52.04gM lomm c md 3- 00.8 02.5 60.01 13.8 05.01lA lomm c md 3- 46.0 02.6 82.1 65.1 00.0H lomm c md 3- 72.52 03.63 49.32 96.32 05.71S mdgm 3- 74.11 29.41 88.24 51.41 56.02aN mdgm 3- 55.72 08.44 22.44 31.82 00.84eF mdgm 3- 30.123 42.47 94.331 59.921 87.911nM mdgm 3- 76.501 92.231 40.95 21.95 07.47uC mdgm 3- 44.4 81.1 42.8 97.01 84.31nZ mdgm 3- 48.6 99.6 26.01 49.6 37.6B mdgm 3- 52.0 23.0 02.0 02.0 52.0CEC a lomm c md 3- 54.17 06.07 00.19 65.37 57.57

Vb % 34.95 41.04 67.66 34.26 03.67eulavS c lomm c md. 3- 5.54 1.82 3.56 3.84 3.85airetcaB liosyrdfogUFCgol 1- 51.6 67.5 81.6 61.6 14.6

ignuF liosyrdfogUFCgol 1- 46.4 26.4 18.4 76.4 67.4setecymonitcA liosyrdfogUFCgol 1- 06.5 81.5 17.5 26.5 51.6

tnecseroulF sanomoduesP liosyrdfogUFCgol 1- 22.4 30.4 10.4 76.3 06.4muirasuF .pps liosyrdfogUFCgol 1- 22.4 91.4 94.4 81.4 74.4aozotorP liosyrdfogllecgol 1- 34.4 12.3 48.3 55.4 68.3

ADF μ liosyrdfogADFdesylordyhg 1- 00.14 60.57 52.81 22.32 13.63OClatoT 2 noitulove μ OCg 2 liosyrdfog 1- 82.437 25.098 69.733 33.382 70.454nalos.R id yadmc 1- 4.2±5.81 1.1±5.02 0.1±0.52 2.1±6.42 5.0±2.72

aCation exchange capacity. bSum of Ca, Mg, K, and Na. cBase saturation. dArea under growth curve (AUGC) of Rhizoctonia solanimycelial growth on Petri dishes containing soil samples taken from different vegetation areas inside a microbasin.



gen growth and disease development. Path analysis isnot just a multiple linear regression analysis, becauseit allows several diagrams to be drawn and the estab-lishment by the researcher of a cause-effect model ac-cording to one’s hypothesis. Furthermore, path analy-sis can generate more information than multiple regres-sion, and such is the case in this study.

When all samples were analyzed together, in-dependently of the soil type and vegetation, only abi-otic variables (P, K, Ca, Mg, Na, Cu, CEC and S value)were correlated (α ≤ 0.05) with R. solani growth sup-pression, and the entire set of variables explained only51% of the total variation (R2 = 0.51; residual variable,Rv = 0.69) (Table 2), which is not useful in predictingsoil suppressiveness or the mechanism of suppression.However, when samples were grouped and analyzed

by vegetation cover, the set of evaluated variables inall instances explained more than 90% of the variationin growth suppression of R. solani. In highly suppres-sive forest soils and pasture/fallow ground areas, sev-eral abiotic variables and FDA hydrolysis correlatedwith growth suppression of R. solani and the set ofvariables explained more than 98% of suppressiveness(Tables 3 and 4, respectively). For less suppressivesoils, no correlations of suppressiveness with the bi-otic variables were found. Several abiotic variableswere correlated with suppressiveness of soils from an-nual crops (Table 5), but no correlations were foundfor ploughed soils and perennial crops. These findingsstress the importance of the vegetation cover and soilmanagement on soil supressiveness. To understand thenature of soil suppressiveness, the ecological context

elbairaV tneiciffeocnoitalerroC α%

H(Hp 2 )O 71.0 69.81)EC(ytivitcudnoclacirtcelE 52.0 74.5

)MO(rettamcinagrO 40.0- 32.47)N(negortiN 50.0- 04.37)P(surohpsohP 13.0 *16.1)K(muissatoP 13.0 *96.1)aC(muiclaC 62.0 *08.4

)gM(muisengaM 62.0 *22.4)lA(munimulA 82.0 86.81)H(negordyH 02.0- 38.11

)S(rufluS 41.0 79.72)aN(muidoS 33.0 *89.0

)eF(norI 11.0 75.65)gM(esenagnaM 51.0 62.72

)uC(reppuC 53.0 *47.0)nZ(cniZ 42.0 38.6)B(eroB 00.0 67.79

CEC a 72.0 *34.3%V b 52.0 86.5

eulavS c 82.0 *10.3airetcaB 02.0 44.21

ignuF 92.0 *52.2setecymonitcA 22.0 83.9

tnecseroulf sanomoduesP 50.0- 42.27muirasuF .pps 11.0 92.95aozotorP 50.0 82.27

ADF 20.0 82.09OClatoT 2 50.0- 36.37

R(noitanimretedfotneiciffeoC 2) 15.0elbairavlaudiseR 96.0

Table 2 - Correlation coefficients between the biotic and abiotic variables measured on soil samples and the suppressivenessto Rhizoctonia solani.

*t test, α = 0.05. aCation exchange capacity. bBase saturation. cSum of Ca, Mg, K, and Na

Ghini & Morandi158


within which the major players act must be considered,since the interactions among soil microorganism com-munities as well as the abiotic variables may influenceboth the structure and activities of populations, includ-ing those of pathogens and their antagonists (Welleret al., 2002).

Suppressive soils are common in ecologicallybalanced environments with ecosystems in climax,where the physico-chemical and microbiological con-

stituents of the soil are stabilized (Schneider, 1982).In theory, the greater the complexity of the biologicalcommunity of the soil, the greater is the stability ofthe soil and, consequently, the level of natural biologi-cal control. Many soils possess similarities with regardto microorganisms involved in disease suppression,while other attributes are unique to specific pathogen-suppressive soil systems. The manipulation of micro-bial communities to induce a disease-suppressive soil

elbairaVtceffetceriD

no inalos.R:aivtceffetceridnI latoT

noitalerrocHp P aC gM H %V a eulavS b ADFHp 25.4- 64.0 90.0- 71.0 42.2 75.1 17.0 12.1- 86.0-P 68.0 04.2- 80.0- 11.0 92.1 99.0 65.0 25.0- 86.0-aC 01.0- 41.4- 76.0 71.0 31.2 45.1 57.0 21.1- 38.0-gM 71.0 44.4- 55.0 01.0- 12.2 85.1 47.0 22.1- 57.0-

H 33.2- 43.4 84.0- 90.0 61.0- 65.1- 17.0- 43.1 67.0%V 06.1 44.4- 45.0 01.0- 71.0 72.2 47.0 42.1- 67.0-

eulavS 67.0 52.4- 46.0 01.0- 71.0 71.2 75.1 61.1- 28.0-ADF 48.1 69.2 52.0- 60.0 11.0- 96.1- 80.1- 84.0- 27.0


Table 3 - Path coefficient analysis of the relations between the suppressiveness to Rhizoctonia solani and the biotic andabiotic correlated variables (α = 0.05) measured in soil samples from a forest-covered area.

aBase saturation. bSum of Ca, Mg, K, and Na.

elbairaVtceriDnotceffeinalos.R

:aivtceffetceridnI latoTnoitalerrocCE MO N K aN eF nM uC nZ CEC eulavS ADF OC 2

CE 42.0- 82.0- 07.0- 44.0 61.0- 97.0 71.0 91.0 06.0- 91.0- 17.0 04.0- 67.0 07.0

MO 35.0- 31.0- 72.1- 04.0 24.0- 45.0 91.0 72.0 25.0- 41.0- 66.0 76.0- 35.1 08.0

N 82.1- 31.0- 35.0- 93.0 24.0- 45.0 91.0 72.0 25.0- 41.0- 86.0 76.0- 65.1 18.0

K 75.0 91.0- 63.0- 88.0- 83.0- 30.1 32.0 72.0 77.0- 42.0- 50.1 96.0- 29.0 87.0

aN 06.0- 60.0- 73.0- 88.0- 63.0 06.0 22.0 82.0 25.0- 61.0- 67.0 89.0- 16.1 07.0

eF 11.1 71.0- 52.0- 26.0- 35.0 33.0- 42.0 72.0 67.0- 72.0- 51.1 37.0- 58.0 17.0

nM 72.0 51.0- 73.0- 98.0- 94.0 94.0- 79.0 23.0 37.0- 62.0- 71.1 99.0- 75.1 18.0

uC 43.0 31.0- 14.0- 00.1- 54.0 94.0- 58.0 52.0 76.0- 72.0- 61.1 30.1- 57.1 68.0

nZ 97.0- 81.0- 53.0- 58.0- 55.0 04.0- 70.1 52.0 92.0 62.0- 31.1 97.0- 70.1 08.0

CEC a 23.0- 41.0- 32.0- 65.0- 34.0 13.0- 39.0 22.0 92.0 56.0- 62.1 29.0- 21.1 26.0

eulavS b 33.1 31.0- 62.0- 56.0- 54.0 53.0- 69.0 42.0 03.0 76.0- 03.0- 39.0- 02.1 26.0

ADF 41.1- 90.0- 13.0- 57.0- 53.0 25.0- 17.0 42.0 13.0 55.0- 62.0- 90.1 67.1 66.0

OC 2 70.2 90.0- 93.0- 69.0- 52.0 74.0- 64.0 12.0 92.0 14.0- 71.0- 77.0 79.0- 67.0


Table 4 - Path coefficient analysis of the relations between the suppressiveness to Rhizoctonia solani and the biotic andabiotic correlated variables (α = 0.05) measured in soil samples from pasture and fallow ground areas.

aCation exchange capacity. bSum of Ca, Mg, K, and Na.



environment is a potential tool in the management ofsoil borne plant diseases (Mazzola, 2002).

Colony counts of bacterial, fungal and actino-mycete communities on the selective media and the to-tal number of protozoan cells were not correlated withsoil supressiveness to R. solani. Considering that thereis no universal culture media, and that only a small per-centage (0.9 to 22%) of total microbial communitiescan be cultivated on available media (Herbert, 1990),the number of CFU obtained per group of microorgan-isms evaluated was not enough to detect differencesamong the analyzed soils. The potential of other or-ganisms, such as protozoa, to contribute to the suppres-siveness to plant pathogens in soils are poorly ex-plored. One of the few works on this topic was doneby Homma & Ishii (1984), who observed perforationon R. solani hyphae by Arachnula impatiens (amoe-bae). Once the predominantly protozoan groups werenot identified, it was not possible to determine theircontribution to pathogen suppressiveness.

However, the total microbial activity, inferredby the amount of hydrolyzed FDA, was positively andhighly correlated with the pathogen suppression at thepasture/fallow ground and forested areas. The suppres-siveness to R. solani was mainly related to biotic soilcharacteristics, represented by the total microbial ac-tivity of the soil (FDA hydrolysis), since this variablewas correlated for the most suppressive soils (pasture/fallow ground and forest areas). These results reinforceearly reports that the pasture, fallow ground and for-est covered areas, which were classified as suppressivesoils, became conducive after fumigation (Ghini &Zaroni, 2001). Positive relationships of total microbialactivity and suppressiveness of soils to soilbornepathogens are well documented in the literature (Welleret al., 2002).

The two variables used to evaluate the totalmicrobial activity (CO2 evolution and FDA hydroly-

sis) were correlated (r = 0.71) when all samples wereanalyzed together, independently of the soil type andvegetation. However, when samples were grouped andanalyzed by vegetation cover, the two variables werecorrelated (r = 0.85) only on the pasture/fallow groundareas. In these soils, both FDA hydrolysis and CO2evolution were correlated with suppressiveness to R.solani. There was no correlation between the two vari-ables and only the FDA hydrolysis was correlated withsuppressiveness in forested areas. The differences incontribution to suppressiveness between FDA hydroly-sis and CO2 evolution probably reflect different pro-cesses of microbial activity, influenced by differentenvironmental conditions. The FDA is hydrolyzed byseveral enzymes (lipase, protease and esterase) fromlive cells (Inbar et al., 1991), while CO2 evolution de-pends on the total respiratory activity of the livingcells.

Besides the FDA hydrolysis, the suppressive-ness against R. solani of the two most suppressive soils(pasture/fallow ground and forest areas) was correlatedwith different groups of abiotic variables. Althoughonly the significantly correlated variables at 5% areshown, several other variables contributed to suppres-siveness at a low level of significance. These resultsreinforce the current knowledge that soil suppressive-ness against R. solani could result from the biotic andabiotic factors of the soil, in a complex set of interac-tions among the chemical, biological and physicalproperties of the soil (Chet & Baker, 1980; Henis etal., 1979; Kobayashi & Ko, 1985; Liu & Baker, 1980).

Suppressiveness to R. solani was measuredonly by mycelial growth tests, where extension growthwas measured on agar-covered soils. This separates thefungus from the soils and not all of the measured prop-erties are going to influence directly the mycelialgrowth. Sieved soil and physical orientation of the soilparticles placed in Petri dishes also can influence the

Table 5 - Path coefficient analysis of the relations between the suppressiveness to Rhizoctonia solani and the biotic andabiotic correlated variables (α = 0.05) measured in soil samples from annual crops areas.

aBase saturation.

elbairaVtceffetceriD

no inalos.R:aivtceffetceridnI latoT

noitalerrocHp K gM H nM %VHp 51.3- 64.2- 69.2- 70.3 35.2- 50.3- 25.0K 13.0 42.2 42.0 52.0- 92.0 52.0 06.0gM 04.1 23.1 60.1 33.1- 40.1 73.1 35.0

H 23.1- 92.1 60.1 52.1 70.1 03.1 46.0-nM 09.1- 25.1- 67.1- 14.1- 55.1 35.1- 55.0%V a 65.3 44.3 58.2 84.3 05.3- 68.2 85.0


Ghini & Morandi160


growth of R. solani. Despite these methodology limi-tations, it has been used to study soil suppressivenessto several plant pathogens (De Boer et al., 1998; vanElsas et al., 2002). This study evaluated the major fac-tors in the analyzed soil samples that influence thegrowth of the pathogen, which is an important suppres-siveness component but the infection of plants with R.solani was not tested. Suppression of infection mayshow different results, since new variables of the plantgrowth should be included in the analysis. Future in-ground experiments in each vegetation type can evalu-ate more precisely pathogen-suppressive and disease-suppressive soils.

ACKNOWLEDGEMENTS

To Prof. Dr. Paulo Cézar Ceresine fromUNESP/FEIS for the classification of the anastomosisgroup of the R. solani isolates, and to CNPq for re-search grant to first author.

REFERENCES

BAKER, R.; COOK, J. Biological control of plant pathogens. SanFrancisco: W.H. Freeman, 1974. 433p.

CHEN, W.; HOITINK, A.J.; SCHMITTHENNER, A.F.; TUOVINEN,O.H. The role of microbial activity in suppression of damping-offcaused by Pythium ultimum. Phytopathology, v.78, p.314-322, 1988.

CHET, H.; BAKER, R. Induction of suppressiveness to Rhizoctoniasolani in soil. Phytopathology, v.70, p.994-998, 1980.

CRUZ, C.D. Software Genes – Windows version – Computationalsystem on Genetics and Statistics. Viçosa: Editora UFV, 2001.

De BOER, W.; GUNNEWIEK, P.J.A.K.; WOLDENDORP, J.W.Suppression of hyphal growth of soil-borne fungi by dune soils fromvigorous and declining stands of Ammophila arenaria. NewPhytologist, v.138, p.107-116, 1998.

EVERITT, B. Cluster analysis. 2.ed. New York: Wiley, 1981.GHINI, R.; ZARONI, M.M.H. Relação entre coberturas vegetais e

supressividade de solos a Rhizoctonia solani. FitopatologiaBrasileira, v.26, p.10-15, 2001.

GRISI, B.M. Método químico de medição da respiração edáfica: algunsaspectos técnicos. Ciência e Cultura, v.30, p.82-88, 1978.

HENIS, Y.; GRAFFAR, A.; BAKER, R. Factors affectingsuppressiveness to Rhizoctonia solani in soil. Phytopathology, v.69,p.1164-1169, 1979.

HERBERT, R.A. Methods for enumerating microorganisms anddetermining biomass in natural environments. In: GRIGOROVA, R.;NORRIS, J.R. (Ed.) Techniques in microbial ecology. San Diego:Academic Press, 1990. p.1-39. (Methods in Microbiology, 22).

HOMMA, Y.; ISHII, M. Perforation of hyphae and sclerotia ofRhizoctonia solani Kuhn by mycophagous soil amoebae fromvegetable field soils in Japan. Annals of the PhytopathologicalSociety of Japan, v.50, p.229-240, 1984.

INBAR, Y.; BOEHM, M.J.; HOITINK, H.A.J. Hydrolysis of fluoresceindiacetate in sphagnum peat container media for predictingsuppressiveness to damping-off caused by Pythium ultimum. SoilBiology and Biochemistry, v.23, p.479-483, 1991.

KO, W.; HO, W. Screening soils for suppressiveness to Rhizoctonia solaniand Pythium splendens. Annals of the Phytopathological Societyof Japan, v.49, p.1-9, 1983.

KOBAYASHI, N.; KO, W.H. Nature of suppression of Rhizoctonia solaniin Hawaiian soils. Transactions of the British Mycological Society,v.84, p.691-694, 1985.

LIU, S.; BAKER, R. Mechanism of biological control in soil suppressiveto Rhizoctonia solani. Phytopathology, v.70, p.404-412, 1980.

MAZZOLA, M. Mechanisms of natural soil suppressiveness to soilbornediseases. Antonie van Leeuwenhoek, v.81, p.557-564, 2002.

NASH, S.M.; SNYDER, W.C. Quantitative estimations by plate countsof propagules of the bean root rot Fusarium in field soils.Phytopathology, v.52, p.567-572, 1962.

RODRÍGUEZ-KÁBANA, R.; CALVET, C. Capacidad del suelo paracontrolar enfermidades de origen edafico. Fitopatologia Brasileira,v.19, p.129-138, 1994.

SCHNEIDER, R.W. Suppressive soils and plant disease. St. Paul: APS,1982. 88p.

SILVA, F.C. Manual de análises químicas de solos, plantas efertilizantes. Brasília: Embrapa Comunicação para Transferência deTecnologia, 1999. 370p.

SINGH, R.K.; CHAUDARY, B.D. Biometrical methods in quantitativegenetic analysis. New Delhi: Kalyani Publishers, 1979. 304p.

STOTZKY, G.; BRODER, M.W.; DOYLE, J.D.; JONES, R.A. Selectedmethods for the detection and assessment of ecological effectsresulting from the release of genetically engineeredmicroorganisms to the terrestrial environment. San Diego:Academic Press, 1993. 98p. (Advances in Applied Microbiology,38).

Van BRUGGEN, A.H.C.; ARNESON, P.A. Path coefficient analysis ofeffects of Rhizoctonia solani on growth and development of drybeans. Phytopathology, v.76, p.874-878, 1986.

Van ELSAS, J.D.; GARBEVA, P.; SALLES, J. Effects of agronomicalmeasures on the microbial diversity of soil as related to thesuppression of soil-borne plant pathogens. Biodegradation, v.13,p.29-40, 2002.

WELLER, D.M.; RAAIJMAKERS, J.M.; GARDENER, B.B.M.;THOMASHOW, L.S. Microbial populations responsible for specificsoil suppressiveness to plant pathogens. Annual Review ofPhytopathology, v.40, p.309-348, 2002.

WRIGHT, S. Correlation and causation. Journal of AgriculturalResearch, v.20, p.557-585, 1921.

Received July 22, 2005Accepted March 08, 2006

Documents

BIOTIC AND ABIOTIC FACTORS ASSOCIATED WITH … · Soil suppressiveness to Rhizoctonia solani 153 ... BIOTIC AND ABIOTIC FACTORS ASSOCIATED WITH SOIL SUPPRESSIVENESS TO Rhizoctonia