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Evaluation of Aluminum Tolerance inRiceFabio Almeida de Freitas a , Mauricio Marini Kopp a , Paulo DejalmaZimmer b , Rogério Oliveira de Sousa c , Fernando Irajâ Félix deCarvalho d & Antonio Costa de Oliveira aa Faculdade de Agronomia , Universidade Federal de Pelotas , RioGrande do Sul, Pelotas, Brazilb Departament of Fitotecnia, Faculdade de Agronomia ,Universidade Federal de Pelotas , Rio Grande do Sul, Pelotas, Brazilc Departament of Solos, Faculdade de Agronomia , UniversidadeFederal de Pelotas , Rio Grande do Sul, Pelotas, Brazild Departament of Fitotecnia, Faculdade de Agronomia ,Universidade Federal de PelotasPublished online: 21 Sep 2008.

To cite this article: Fabio Almeida de Freitas , Mauricio Marini Kopp , Paulo Dejalma Zimmer , RogérioOliveira de Sousa , Fernando Irajâ Félix de Carvalho & Antonio Costa de Oliveira (2006) Evaluationof Aluminum Tolerance in Rice, Journal of Crop Improvement, 16:1-2, 141-151, DOI: 10.1300/J411v16n01_10

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Evaluation of Aluminum Tolerancein Rice

Fabio Almeida de FreitasMauricio Marini KoppPaulo Dejalma Zimmer

Rogério Oliveira de SousaFernando Irajá Félix de Carvalho

Antonio Costa de Oliveira

ABSTRACT. The objectives of the present work were to adjust themethod for identifying genetic variability in rice through the use of mini-mal solution in hydroponic culture, and to identify the most importantlevel and character for the study. The experiment consisted of the res-ponse evaluation of 18 rice genotypes to three levels of aluminum treat-ment. Five variables obtained from root and shoot lengths were evaluated.The data were subjected to the clustering methods of Tocher and nearestneighbor to evaluate the dissimilarity and the most adequate aluminum

Fabio Almeida de Freitas and Mauricio Marini Kopp are Graduate Students atFaculdade de Agronomia, Universidade Federal de Pelotas, Pelotas, Rio Grande doSul, Brazil.

Paulo Dejalma Zimmer is Professor, Departament of Fitotecnia, Faculdade deAgronomia, Universidade Federal de Pelotas, Pelotas, Rio Grande do Sul, Brazil.

Rogério Oliveira de Sousa is Professor, Departament of Solos, Faculdade deAgronomia, Universidade Federal de Pelotas, Pelotas, Rio Grande do Sul, Brazil.

Fernando Irajá Félix de Carvalho is Professor, Departament of Fitotecnia,Faculdade de Agronomia, Universidade Federal de Pelotas.

Antonio Costa de Oliveira is affiliated with Faculdade de Agronomia, UniversidadeFederal de Pelotas, Pelotas, Rio Grande do Sul, Brazil.

Address correspondence to: Antonio Costa de Oliveira, Faculdade de Agronomia,Universidade Federal de Pelotas, Caixa Postal-354, CEP: 96001-970, Pelotas, RioGrande do Sul, Brazil (E-mail: acostol@terra.com.br).

The authors are thankful to FAO/IAEA, CNPq, CAPES and FAPERGS for thefinancial support as grants and fellowships.

Journal of Crop Improvement, Vol. 16(1/2) (#31/32) 2006Available online at http://www.haworthpress.com/web/JCRIP

© 2006 by The Haworth Press, Inc. All rights reserved.doi:10.1300/J411v16n01_10 141

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level. The results indicated that the 2 mg L�1 concentration and the dif-ference between first and second measures of root length were the mostuseful for evaluating Al tolerance. Based on the results, it was possibleto identify tolerant and sensitive cultivars to aluminum. [Article copiesavailable for a fee from The Haworth Document Delivery Service: 1-800-HAWORTH. E-mail address: <docdelivery@haworthpress.com> Website:<http://www.HaworthPress.com> 2006 by The Haworth Press, Inc. All rightsreserved.]

KEYWORDS. Oryza sativa, Al toxicity, minimum solution

INTRODUCTION

The need to identify plants adapted to adverse soil conditions has in-creased its importance in the past few decades. This is mostly due tohigher costs in food production and exploration of areas with low fertil-ity (Mazzocato et al., 2002).

Aluminum (Al3�) toxicity occurs in acid soils and is one of the mostlimiting factors to upland rice production (Vasconcelos et al., 2002a).Aluminum can affect the absorption of water and nutrients by rice rootsbecause it reduces the absorption per unit of root length. Under droughtconditions, plants sensitive to aluminum show striking stress effects incomparison with tolerant genotypes, due to their shallow and less devel-oped root system (IRRI, 1979). The critical stage for aluminum stress isat the initial establishment of seedlings when the first cell division cy-cles are occurring in the root system (Vasconcelos et al., 2002b).

Al3� interferes with the plant metabolism because it has high affinityfor pectins, altering the root cell membrane properties and blocking theprocess of cell wall expansion (Reid et al., 1996). At the plasma mem-brane, aluminum adhesion alters the structural integrity because it acts asa calcium substitute. Calcium plays an important role in many plant cellprocesses, such as signal transduction, cell membrane composition andcytokinesis during mitosis (Huang et al., 1996). There is evidence thatsome plants known to be aluminum tolerant produce some organic acidsin larger quantities than sensitive genotypes, forming stable compoundswith aluminum, decreasing its deleterious effects on the membranes(Zheng et al., 1998; Larsen et al., 1998).

Many methods based on the use of hydroponic solution have been de-veloped for the evaluation of plants for aluminum tolerance (Hai et al.,1993; Paliwal and Sivaguru, 1994; Desouza et al., 1995; Ferreira et al.,

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1995; Foy, 1997; Foy and Murray, 1998; Silva et al., 2004; Minella andSorrells, 2002). In general, these methods allow the comparison of greatnumber of species and/or varieties in small areas, besides providing afast and efficient way of analyzing results (Giaveno and Miranda,2000). The use of minimal solutions, characterized only by aluminum,calcium and distilled water, has been reported as a way to discriminateamong genotypes for aluminum tolerance (Mazzocato et al., 2002).This technique, besides representing a fast and easy way of collectingdata, is not as costly as normal complete solutions. The present workhad as objective to test the minimal solution method to identify rice ge-notypes tolerant to aluminum, to determine the correct Al level and themost important trait for evaluating rice genotypes for tolerance toaluminum stress.

MATERIALS AND METHODS

Eighteen rice genotypes were tested at three aluminum levels (0, 2and 6 mg L�1) in minimal solution as proposed by Mazzocato et al.(2002). Sampling of the two major cultivation systems was done bychoosing 10 upland and 8 irrigated genotypes. The experiment wasconducted in the hydroponics lab at the Plants Genomics Center (CGF),Eliseu Maciel Agronomy School (FAEM), Federal University of Pelotas,Brazil, between March and April 2003. The genotypes used belong tothe germplasm collection of CGF. Seeds were germinated in rolled ger-mination paper kept vertically in chamber at 25 1�C temperature for72 h. After germination, the initial main root length was measured (cm) torepresent the first reading (FR), and subsequently plantlets were trans-ferred to a plastic net placed on a plastic pot containing treatment solution(5.5 liters). The pots were subjected to water bath at 25 1�C with arti-ficial light; a split plot randomized block design with three replicationswas used. Plots consisted of 5 plants each. The treatment solution wascomposed of distilled water, calcium and aluminum, the latter being inthe form of Al2(SO4)3 ·18H2O, in concentrations varying with treat-ment. Calcium was supplied as CaCl2 ·2H2O at a concentration of 40 mgL�1 (Mazzocato et al., 2002). The pH of all solutions was daily verifiedand adjusted to a range of 4.2-4.6 with NaOH or H2SO4.

After 120 hours in treatment solution, all the solutions were changedto distilled water and calcium. After over 48 h, the second reading (SR)(final) on root length was made. The shoot length was also measured (SL)(cm). The difference between the variables (SR-FR) was represented as

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difference (DIF) and this value was divided by FR (DIF/FR), resulting inrelative difference (RDIF).

To identify the optimal level for the study, a clustering method de-scribed by Tocher (Rao, 1952), based on the generalized distance ofMahalanobis, was used. The most indicated level would be the one thatprovides greatest genotype discrimination. With the goal of identifyingthe most sensitive variable, the method indicated by Vicente et al. (1998)was used, aiming to transform the mean values of each variable to rela-tive reduction (RR%) values. These values were calculated as the ratiobetween the value of the variable at a given Al3� level and the value of thevariable at zero Al3� level.

To evaluate the genetic dissimilarity among genotypes, the nearestneighbor method was employed (Cruz and Regazzi, 1997), which en-abled a graphical view of distances between genotypes through dendro-grams based on the generalized distances of Mahalanobis. The datawere also subjected to an analysis of comparison of means via the Scott-Knott test, aiming to evaluate the performance of genotypes subjectedto aluminum stress. To perform the analyses, the software programGENES was used (Cruz, 2001).

RESULTS AND DISCUSSION

The analysis of variance (Table 1) showed significant differencesamong genotypes for all variables. The aluminum levels and the geno-type � aluminum interaction were not significant for the variables FRand SL. The variables SR, DIF and RDIF presented significant differ-ences either for the main effects of factors or for the genotype � alumi-num interaction. The results agree with those obtained by Mazzocatoet al. (2002), who worked with aluminum tolerant maize. The absenceof significant interaction demonstrates a homogeneous or similar geno-type response to an increase in aluminum concentration.

The correlations among the variables FR, SR, DIF, RDIF and SL areshown in Table 2. The variable SL demonstrated significant variationsaccording to the increase in aluminum level (Table 1). The variable SRis a good candidate for the screening of aluminum tolerant rice plantssince it is not associated to FR, and represents a good sensitivity to Alstress (Table 2). The variable SR also expressed a higher correlation co-efficient with the variable DIF (Table 2), which was the most sensitive,suggesting that this variable could be used in the selection of aluminumtolerant rice genotypes in hydroponic systems.

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Reduction of growth in the root system is one of the main symptomsin sensitive plants (Foy, 1974). A reduction in SL was detected as theleast affected character (Vicente et al., 1998) under aluminum stress.

The Tocher’s clustering method (Table 3), based on the generalizeddistances of Mahalanobis, demonstrated that the levels 0 and 2 discri-minated among the genotypes but formed a larger number of groups.Taking into account that this work aimed to evaluate the performance ofgenotypes under the effect of Al3�, the Al level 2 mg L�1 was the mostappropriate for studies related to aluminum tolerance in rice, allowingthe detection of a higher genetic variability than 6 mg L�1. It can also bepointed out that, as a selection criterion, one can use a simultaneous eval-uation at both 2 mg L�1 and 6 mg L�1 to achieve a higher selection effi-ciency.

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TABLE 1. Analyses of variance for the variables first reading (FR), secondreading (SR), difference between first and second readings (DIF), relativedifference (RDIF) and shoot length (SL) (UFPel, Pelotas–RS, 2003)

Mean Squares

DF FR SR DIF RDIF SL

Genotype 17 0.83* 7.57* 9.49* 26.14* 2.23*

Aluminum 2 0.07 490.27* 495.58* 351.88* 4.05

Gen. Al. 34 0.2 1.99* 2.33* 9.68* 0.60

CV (%) 34.90 18.40 25.14 49.74 12.50

* Significant at 1% error probability by the F test.

TABLE 2. Phenotypic correlation coefficient between the variables first reading(FR), second reading (SR), difference between first and second readings(DIF), relative difference (RDIF) and shoot length (SL) (UFPel, Pelotas–RS,2003)

Variables n FR SR DIF RDIF SL

FR 162 1 –0.03 –0.20* –0.55* –0.01

SR 162 1 0.98* 0.74* 0.34*

DIF 162 1 0.82* 0.34*

RDIF 162 1 0.22*

SL 162 1

* Significant at 5% probability level.

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Means were compared via the Scott-Knott test (Table 4). This test al-lows one to identify the best treatments, avoiding ambiguous interpreta-tion of data (Ferreira et al., 1999). This technique showed efficiency inthe identification of bean (Benin et al., 2002), rice (Zimmer et al., 2003)and ryegrass (Freitas et al., 2003) genotypes. Among the genotypes eval-uated, none showed superiority in all variables and levels studied. How-ever, the genotypes Jaguari, IAC 1246, 2/52/4 and Toukyo Hirayamarevealed higher stability, expressing satisfactory results in response to thestress applied; this should be useful to breeding programs.

In Table 4 are shown the relative reductions (RR%) in variables SR,DIF and RDIF based on the mean genotype values. Aluminum did notaffect FR and SL significantly; therefore, the values for these variablesare not presented. The maximum relative reduction was observed for thevariables DIF, RDIF and SR, indicating that these variables were themost severely affected by the aluminum stress. However, the variableRDIF showed the highest coefficient of variation (Table 1), indicatinglower precision and reliability. Using the same methods, Mazzocatoet al. (2002) detected DIF as the most important variable to evaluatesensitivity to aluminum, highlighting the importance of measuring rootlength in the beginning of the experiment (FR).

The genotypes Firmeza, BR IRGA 410 and BRS 7 “Taim” were alwaysamong the most sensitive in regard to all variables and conditions ana-lyzed, suggesting that they are not promising genotypes for aluminumtolerance. These results agree with those obtained by Ferreira et al.

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TABLE 3. Clustering of 18 rice genotypes by Tocher’s method, considering thevariables first reading (FR), second reading (SR), difference between first andsecond readings (DIF), relative difference (RDIF) and shoot length (SL) inthree aluminum levels (UFPel, Pelotas–RS, 2003)

Aluminum Levels

Cluster Control 2 mg L 1 6 mg L 1

1 5 7 11 6 3 2 14 17 18 8 12 7 13 5 18 16 4 9 1514 2 6 3 1

2 4 12 1 13 10 8 9 1 2 6 7 5 9 8 4 3 16 10 11

3 16 18 14 10 12 15 17

4 15 13 –

5 17 11 –

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(1995), where the tolerant rice genotypes belonged to the upland and thesensitive ones to the irrigated groups.

The identification of genetic constitutions that provide segregatingpopulations for a breeding program is one of the main decisions that abreeder makes. Multivariate statistics is a technique that enables one toclassify genotypes based on different variables simultaneously. It mea-sures dissimilarity and genetic distance among the analyzed genotypes,providing information on hybridizations expected to have a higher proba-

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TABLE 4. Means for second reading (SR), difference between readings (DIF),relative difference (RDIF) and relative reduction (RR%) of 18 rice genotypes innutritive solution for three aluminum levels (UFPel, Pelotas–RS, 2003)

Genotypes System Aluminum Levels

Control 2 mg L 1 6 mg L 1

SR DIF RDIF SR DIF RDIF SR DIF RDIF

1. Firmeza I* 8.0b** 6.2b 3.5b 3.3c 1.5d 0.9c 2.0c 0.7b 0.6c

2. BR IRGA 410 I 7.3b 5.8b 5.1b 2.8c 1.2d 0.7c 2.2c 0.6b 0.4c

3. BR IRGA 417 I 8.3b 7.0b 5.4b 3.3c 2.0d 1.5c 2.7c 1.5a 1.4c

4. BRS-7 “Taim” I 7.3b 6.0b 5.2b 2.4c 1.0d 0.8c 2.7c 1.0b 0.7c

5. BRS-6 “Chui” I 7.6b 6.2b 5.0b 3.4c 1.9d 1.2c 3.3b 1.7a 1.0c

6. Supremo 1 I 7.1b 5.7b 4.6b 3.1c 1.4d 0.8c 3.0b 0.8b 0.3c

7. L 144 I 7.3b 5.8b 4.1b 3.0c 1.1d 0.6c 2.6c 1.6a 1.6c

8. Epagri 111 I 8.4b 7.2b 6.4b 3.7c 2.2c 1.8c 2.5c 1.5a 1.5c

9. Zabú Branco U 10.0a 8.6a 6.6b 3.6c 2.4c 3.0b 2.6c 1.7a 2.0c

10. Bacaba U 6.5b 5.5b 6.2b 3.7c 2.8c 3.5b 2.6c 2.3a 7.9a

11. Jaguarí U 9.5a 8.2a 6.5b 6.1a 5.3a 7.1a 2.7c 2.2a 5.2b

12. Primavera U 6.6b 5.3b 4.0b 4.3c 3.1c 2.7b 2.5c 1.2b 1.0c

13. Bonança U 9.0b 7.2b 4.5b 5.2b 3.7b 3.4b 2.7c 0.9b 0.6c

14. IAC 1246 U 9.8a 8.8a 9.7b 6.3a 5.1a 4.5b 3.2b 1.7a 2.3c

15. Felune U 9.3a 8.6a 13.5a 4.4c 3.4b 4.2b 3.4b 2.2a 1.9c

16. Matsuyama U 10.8a 9.8 11.3a 3.8c 2.7c 4.0b 2.9c 1.7a 1.6c

17. 2/52/4 U 11.0a 9.3 5.7b 6.4a 5.0a 4.1b 4.2a 2.3a 1.2c

18. ToukyoHirayama

U 10.6a 9.8a 11.7a 5.0b 3.8b 3.4b 3.1b 1.9a 1.7c

RR (%) 100 100 100 47.7 38.4 40.9 33.7 20.5 28.8

* I = Irrigated, U = Upland.** Genotypes followed by the same column do not differ significantly by the Scott-Knott test, at 5% errorprobability.

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bility of generating superior recombinant genotypes in segregating gener-ations (Cruz and Regazzi, 1997). The nearest neighbor joining method(Figure 1) based on five variables showed similar results to those ob-tained with Tocher’s method that detected higher variability at levels 0(control) and 2. At level 6, perhaps because it was the most stressfulcondition, the genotypes showed similar behavior and formed threeclusters, comprising 15, 2, and 1 genotypes each. As the aluminum levelincreased, the genotype Jaguari was separated forming a unique cluster.This result suggests that this genotype can be important for hybridiza-tions aiming to obtain a segregating population adapted to acid soils,since it presented a good performance under Al stress. Also based on thehierarchical method, the most distant genotypes for level 2 were IAC1246 and Jaguari; and for level 6, Firmeza and Bacaba. However, thecross between these two is not advisable because despite the presence of

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I

L/U

U

U

U

U

U

I/U

I/U

UU

UU

0 10 20 30 40 50 60 70 80 90 100

0 10 20 30 40 50 60 70 80 90 100

0 10 20 30 40 50 60 70 80 90 100

Control

2 mg L-1 of Aluminum

6 mg L-1 of Aluminum

EpagriChui

L 144Prima.BR 410

BR 417Taim 9Sup 1

BacabaFirm

Zebu B.Jaguari2/52/4Matsuy.Toukyo

IAC 1246Felune

Bonanca

EpagriChui

L 144

Prima.

BR 410BR 417Taim 9

Sup 1

Bacaba

Firm.

Zebu B.

Jaguari

2/52/4

Matsuy.

Tcukyo

IAC 1246

Felune

Bonanca

Epagri

Chui

L 144

Prima.

BR 410

BR 417

Taim 9

Sup 1

Bacaba

Firm.

Zebu B.

Jaguari2/52/4

Matsuy.Toukyo

IAC 1246

Felune

Bonanca

FIGURE 1. Dendrogram created via the nearest-neighbor method based onthe generalized distance of Mahalanobis of five traits analyzed for three alu-minium levels used in the experiment (U = upland, I = irrigated rice). UFPel,Pelotas–RS, 2003.

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genetic variability, the genotypes must also show high mean for the char-acter to be improved, to be able to generate a promising segregatingpopulation.

Based only on level 2 dendrogram, regarded as the best for infer-ences, it can be suggested that crosses Jaguari � IAC 1246; Jaguari � 2/52/4; Jaguari � Tukyo Hirayama; IAC 1246 � Tukyo Hirayama and 2/52/4 � Tukyo Hirayama would generate promising segregating popula-tions, since all genotypes had good performance under Al3� stress andbelonged to distinct clusters. The cross between IAC 1246 and 2/52/4due to their close distance is not recommended.

The most stable genotypes for aluminum tolerance were Jaguari, 2/52/4 and IAC 1246. BRS 7 “Taim” was the most sensitive genotype to alu-minum stress.

CONCLUSIONS

It is possible to select genotypes with higher stability under alumi-num stress using minimal solutions in hydroponic culture. The alumi-num level of 2 mg L�1 and the variable root length were the mostsuitable parameters for studies related to aluminum tolerance in rice.

The genotypes Jaguari, IAC 1246, 2/52/12 and Tukyo Hirayamawere the most tolerant, whereas genotypes Firmeza, BR IRGA 410 andBRS 7 Taim were the most sensitive to aluminum.

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