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Use of ISSR molecular marker approach to estimate genetic diversity in rice and barley allelopathy

W.X. Lin1,2, H.Q. He1,2, X.X. Chen1, J. Xiong1, B.Q. Song2, Y.Y. Liang2 and K.J. Liang2

1School of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002, Email zjwxlin@pub5.fz.fj.cn or wenxiong181@163.com
2
Key Laboratory of Biopesticide and Chemical Biology, FAFU, Ministry of Education, China, Email zjwxlin@pub5.fz.fj.cn or wenxiong181@163.com

Abstract

The inter-simple sequence repeat (ISSR) approach was used to detect the genetic diversity of allelopathic potential in 57 rice accessions and 65 barley lines introduced from more than 10 countries or regions such as America, Brazil, India, Colombia, Philippines, Mexico, Mainland China, and Taiwan. Seven pairs of ISSR primers and eleven pairs of primers that generated clear, reproducible banding patterns were chosen for the ISSR analysis of Oryza sativa and Hordeum vulgare respectively. For ISSR markers used in collected rice accessions, 34 polymorphic bands were generated, and the percentage of polymorphic bands (PPB) was 53.0%, In collected barley accessions, 137 polymorphic bands were yielded, and the PPB was 88.4%. The result from the clustering analysis by unweighted pair group method arithmetic average (UMGMA) indicated that those accessions (rice or barley) from the same geographical location could be clustered into one group. It was also found that some accessions with higher allelopathic potential could be grouped together, implying that the genes conferring allelopathy in those accessions of rice or barley might be isolocus. However, some accessions of rice and barley with significantly different allelopathic potential clustered into the same group performed lower level of genetic polymorphism. This was believed to be attributed to oriented selection for high- yielding traits in breeding.

Media summary

Seven pairs of ISSR primers and eleven pairs of primers that generated clear, reproducible banding patterns were chosen for the ISSR analysis of Oryza sativa and Hordeum vulgare respectively

Key words

Allelopathy, Oryza sativa ,Hordeum vulgare, rice, barley, genetic diversity, ISSR

Introduction

Weeds are the major biological constraint in crop production. This problem has traditionally been solved by hand-weeding. Presently, access to herbicides is helping in decreasing the weed problem. However, increasing farm labour costs and environmental concerns about pesticide usage make it increasingly important to find alternative and sustainable weed management methods. One ecological strategy of weed control, allelopathy, has drawn increased attention. Many weed scientists have attempted to explore allelopathy directly as a weed management strategy through screening for allelopathic traits in germplasm of crops. Furthermore, the application of crop allelopathy in integrated weed control will enhance the competitive ability of the crop and thereby reduce or delay the need for applying herbicides (Lin et al. 2000; Lin et al. 2003) Allelopathy is defined as “direct or indirect (harmful or beneficial) effects of a plant (donor)on another plant (receiver) through the release of compounds into the environment”(Rice 1984).To date, much progress had been made in crop allelopathy , such as screening for allelopathic rice accessions (Navarez et al. 1996; Dilday 1998;Fujii 1999), identifying allelochemicals (Chou et al. 1998; Mattice et al. 1998; Rimando et al. 2001), and identifying QTLs for allelopathy (Louise et al. 2000,Ebana et al. 2001; ). When a significant level of intra-accession variability in allelopathic expression became evident, the assessment of genetic diversity became necessary (Motiul et al. 2001). However, information on the use of molecular markers for the characterization of genetic diversity in allelopathic germplasm of crops is limited. The purpose of the present study was to assess the genetic diversity in a collection of rice and barley cultivars, landraces and introduced accessions by using molecular markers of inter-simple sequence repeats (ISSR), evaluate their relationships at the species level per se, and establish their potential usefulness as genetic resources in breeding for allelopathic cultivars resistant to weeds.

Materials and Methods

Plant material

Fifty-seven rice accessions (Oryza sativa L).and sixty-five barley accessions (Hordeum vulgare L) introduced from more than ten countries or regions in the world, were screened for allelopathic potential. Barnyardgrass (Echinochloa crus-galli L.) and lettuce (Lactuca sativa L.) were used as receiver plants in bioassay to assess genetic diversity of allelopathic potential in rice and barley respectively. The analysis was based on ISSR markers, following the procedure as described by Navarez and Olofsdotter (1996).

Screening for allelopathic potential.

The procedure was adapted from the relay seedling technique (Navarez et al. 1996). After 0.3% water agar was compared with Perlite, the water agar was used as the growth medium. 30 sterilized rice or barley seeds were sown in two parallel rows (3.0 cm apart,5 seeds in each row ) inside a petri dish with 10 ml 0.3% water agar The seeds were planted into the water agar to restrain arching of the rice or barley roots The petri dishes were placed inside a germination box(50cm×25cm×15cm) and 500 ml of distilled water added to each germination box outside the petri dishes. No nutrient was applied at any time during the experiment. The germination box was covered with a transparent plastic film to prevent the water evaporation. On 7 days, ten sterilized and pregerminated seeds of E.crus-galli or L.sativa were sown in one row in between the two rows of donor plants(rice or barley) on the top of the water agar medium.The control was the no-donor plant check treated in the same way but without rice or barley seedlings. The germination box was placed in growth chamber set at 3000lux light intensities ,in which the photoperiod was 12 hours, and the temperature was kept between 25-30℃ for rice and 15-20℃ for barley respectively.. Thus the relay seeding technique ensured that there was no competition for light, water or nutrients, which was confirmed in our preliminary experiment (data not shown here). On 14 days, the agar was washed off the roots of receiver plants (E.cus-galli and L. sativa) and the root length of barnyardgrass and lettuce was recorded after 14 days in the mixture, which was used as an indicator of allelopathic potential of rice and barley plants in questions by using it to calculate the inhibition rate (IR). The screening experiment was conducted with four replications. All data were subjected to statistical analysis

DNA extraction and ISSR analysis.

Tweenty pre-germinated seeds of each entry were grown in Petri dishes containing 10 ml 0.3% water agar under sterile conditions. Genomic DNA were extracted from triplicate samples of a single seedling by the method of Weining et al.(1994). The polymerase chain reaction (PCR) was performed in a 15μl reaction mixture containing 10ng template DNA, 1.5μl 10×buffer, 200μmol/L deoxyribonucleotide triphosphate (dNTPs), 0.2μl Taq DNA polymerase and 1ng 10-mer primer. Amplification program is: 4 minutes predenatured at 94℃; 30 seconds at 94℃, 30 seconds at 52℃, 90 seconds at 72℃, 40 cycles; 10 minutes at 72℃, then stored at 4℃. Electrophoretic separation of the PCR products was done following the procedure as described in Agnese et al. (2004).

Statistical Analysis.

The root length of barnyardgrass and lettuce was transformed and expressed as inhibition rate (IR), [IR=(1-TR/CK)×100%], where TR represents the treatment and CK refers to the control. Genetic data analysis was performed by using the computer package TFPMG 1.3. The dendrogram was constructed by the unweighted pair group method (UPGMA) (Sneath et al. 1973).

Results

Screening for allelopathic potential.

Of fifty-seven rice accessions, five cultivars (Iguape Cateto, PI312777, Azucena, Taichung Native 1 and IAC25) demonstrated over 50% inhibition of barnyardgrass root growth. IRs of twelve cultivars ranged from 40% to 50%, IRs of twenty-one cultivars were 30%~40%, IRs of thirteen cultivars ranged from 20% to 30%, while IRs of 6 cultivars were less than 20% (Table1). Of sixty-five barley accessions, fifty-one cultivars demonstrated at least 50% inhibition of the model receiver plant (lettuce), such as M24, 82-F165, G10-Nan74-17, IRs of sixteen cultivars were higher than 80% and six accessions exhibited 40% -50% inhibition over control, including 96015-0-6, Yong3646, CM67, H0651, Baoshan80-10, 85-V2, Alarnos and Shishui Huanjing. four cultivars, Yong2158, 81-11, Fang 18 and Pala santo"s") showed lower inhibitory effect on the receiver plant, ranging from 30%-40% inhibition of the control. IRs of 3 accessions, namely M13, 955099 and 331-1, ranged from 20%-30%, and one cultivar, 96-85, had an IR of less than 20% (Table 2). The distribution of allelopathic potential in rice and barley accessions tested in terms of inhibition rate was almost normal.

Genetic diversity in collected accessions of rice and barley.

Eighty pairs of primers purchased from Shengong Inc. were first screened for PCR. Seven pairs of ISSR primers and eleven pairs of primers that generated clear, reproducible banding patterns were chosen for the ISSR analysis of Oryza sativa and Hordeum vulgare respectively. A total of 34 bands were scored corresponding to an average of 4.9 bands per primer on the basis of the presence (1) or absence (0) in the bands. The size of the amplified fragments ranged from 200 to 1300 bp. Among the thirty four loci, eighteen were polymorphic (53%) at the species level of Oryza sativa. Eleven pairs of ISSR primers yielded a total of 155 scorable bands (average ca 14/primer), of which 137 were polymorphic (88.4%) in sixty-five barley genotyes examined. The size of the bands ranged from 240-2000 bp (Table3).

Clustering.

Genetic similarities were calculated using the Nei-Li similarity co-efficient. The resulting similarity matrix was subjected to the UPGMA clustering method for dendrogram construction and cultivar differentiation. Fifty-seven rice accessions were grouped into six main groups based on GS=0.79 (Figure 1). The first group was composed of thirty-one cultivars, of which thirteen were from Mainland China, nine from the Philippines, five from Brazil, two from America and the other from Guinea and Ivory Coast. In this group, four cultivars showed over 40% inhibition of barnyardgrass roots. There were 18 accessions in the second group including 6 lines from China, five from Philippines, three from Brazil, two from India and the others from Bangladesh and Colombia, of which eleven accessions showed more than 40% inhibition. There were only three accessions clustered into the third group. Iguape Cateto from Brazil and PI312777 from America resulted in 58.4% and 56.8% inhibition respectively, and Arroz de campos from Cuba had a lower IR value (30.7%). There were also three cultivars in the fourth group, two from the Philippines and the other from China, all having lower IRs. IR73394 from the Philippines and Dourado Pecoce from Brazil were clustered into the fifth and sixth groups respectively. IRs of these two accessions were low (27.7%-31.8%) as shown in Table 1 and Figure 3. The sixty five barley cultivars, landraces and introduced lines were clustered into 7 groups based on GS= 0.75 (Figure 4), of which 55 accessions were in the first group corresponding to an average of 63.1% inhibition of the target weed. The second group included four accessions, 96015-0-6-85-V2, Alarnos, Moora and Pala santo“s”, with an average IR value of 45.6%. There were only two cultivars in the third group, M7 and M24 introduced from Mexico, showing higher allelopathic potential in the suppression on the receiver plant (average IR ca 78 %). The other four landraces, Dingli13, Yong 2160, Beijin barley and Putian barley No.4 were independently clustered into the fourth, fifth, sixth and seventh groups respectively. IRs of the four accessions were 72.8%,52.1%,85.9% and 73.2% respectively.

Table 1. Influence ofI of rice accessions on Echinochloa crus-galli root growth as described by inhibition rates (IRs )

No

Rice accession

Origin

IR(%)

No

Rice accession

Origin

IR(%)

1

Iguape Cateto

Brazil

58.4±1.6*

30

Chaoerzhan

China

33.3±6.3

2

PI312777

America

56.8±2..3

31

Sanyizhaozhan

China

32.7±6.7

3

Azucena

The Philippines

53.9±1.4

32

Wab56-125

Ivory Coast

32.5±4.1

4

Taichung Native 1

Taiwan

50.2±8.9

33

Polha Murcha

Brazil

32.0±6.6

5

IAC25

Brazil

50.0±4.7

34

Qisanzhan

China

31.8±7.5

6

AU257

Bangladesh

48.4±0.6

35

Dourado Pecoce

Brazil

31.8±3.5

7

Red Rice5

China

48.2±6.8

36

Bala

India

31.6±6.7

8

Batatais

Brazil

47.5±5.2

37

Arroz de campos

Cuba

30.7±7.9

9

IAC120

Brazil

46.7±7.4

38

Shuangzhan 2

China

30.4±7.5

10

Co39

India

45.2±2.6

39

Fengaizhan

China

29.1±5.8

11

IAC47

Brazil

45.1±7.5

40

IR721413

The Philippines

28.9±4.7

12

IR72417-3R-8-2

The Philippines

44.5±13.2

41

Qidaizhan

China

28.9±8.8

13

Yehuazhan

China

43.6±5.9

42

IR73384

ThePhilippines

27.7±9.4

14

IR70617

The Philippines

43.2±6.7

43

IR64

The Philippines

27.7±5.3

15

Jingyouzhan

China

41.1±8.6

44

Xinsimiao

China

27.3±1.3

16

IAC164

Brazil

41.1±6.9

45

Daishuzhan

China

27.0±4.3

17

Mafeng 1

China

40.9±10.1

46

Qingxiangzhan

China

26.8±6.1

18

Taizhong 189

China

39.3±8.6

47

IR62266-42-6-2

The Philippines

25.9±4.0

19

Dinorado

The Philippines

39.3±2.2

48

IR65907-116-1-B

The Philippines

24.1±9.1

20

Vandana

Colombia

38.2±5.6

49

Moroberekan

Guinea

23.2±6.6

21

IAC165

Brazil

37.5±1.1

50

IR60080-46A

The Philippines

21.4±4.1

22

IR56

The Philippines

36.6±4.7

51

IR72412

The Philippines

20.2±7.8

23

Shuangmeizhan

China

36.4±6.4

52

Zhengyou 1

China

19.5±1.9

24

IR70651

The Philippines

35.7±2.4

53

IR55423-01

The Philippines

18.4±2.5

25

IR36

The Philippines

34.5±4.3

54

Pratao Precoce

Brazil

18.2±2.6

26

Dee Geo Woo Gen

Taiwan

34.3±3.8

55

Aisanruzhan

China

17.7±4.6

27

Muxiang 25

China

34.1±3.1

56

Dular

America

14.1±2.1

28

IR73382

The Philippines

33.9±2.8

57

Lemont

America

10.9±3.2

29

IR71331

The Philippines

33.3±9.4

       

*the average of inhibition rate (IR)±standard deviation(SD)

Table 2. Influence of barley accessions on Lactuca sativa root growth described by inhibition rates (IRs ).

No

Barley accession

Origin

IR(%)

No

Barley accession

Origin

IR(%)

No

Barley accession

Origin

IR(%)

1

96015-0-6

China

45.8±3.2*

23

92-18

China

65.5±1.2

45

Zhou 6121

China

81.3±1.1

2

H0689

Japan

78.2±1.1

24

Ji19

China

58.2±0.8

46

89-268

China

51.7±6.3

3

Shisuijinhuang

China

48.9±3.9

25

Ensi 293

China

64.0±5.1

47

G10Nan74-17

China

86.7±6.4

4

85-V2 Alarnos

China

43.5±2.7

26

Lidingmushisan

China

72.8±2.2

48

82-F165

China

88.1±1.8

5

Moora

Mexico

57.8±4.8

27

S-2

China

80.8±2.0

49

791

China

82.0±2.6

6

96-85

China

6.8±2.4

28

88-2

China

73.0±3.4

50

M1

Mexico

82.6±2.3

7

Pu 829019

China

70.4±8.2

29

72537-1

China

66.9±0.8

51

M9

Mexico

79.1±1.9

8

H0686

Japan

82.6±6.0

30

Kepin 5 Hao

China

61.0±0.7

52

M10

Mexico

68.2±5.5

9

85-Y1TVpino

China

58.1±13.4

31

85-143

China

60.8±7.8

53

M13

Mexico

20.2±5.3

10

H0687

Japan

86.4±2.4

32

Baoshan80-10

China

48.3±3.4

54

M3

Mexico

73.1±3.0

11

Aodaliya 1

Australia

56.7±5.9

33

CM67 H0651

China

45.1±3.1

55

M7

Mexico

64.8±3.0

12

suyin 21

Japan

69.5±0.8

34

87-32

China

66.8±5.0

56

M24

Mexico

91.5±2.7

13

Tongjian 43

China

58.6±6.6

35

331-1

China

24.7±3.2

57

Yong 2148

China

83.0±10.4

14

HDE84194-622-1

China

84.8±3.4

36

954073

China

67.4±4.0

58

Yong 2149

China

58.1±1.5

15

Pala santo"s"

Mexico

35.3±4.8

37

799006

China

74.9±0.9

59

Yong 2158

China

32.1±1.0

16

Zhe 88-23

China

51.1±1.3

38

808042

China

51.1±4.3

60

Yong 2160

China

52.1±1.3

17

Dan 2

China

80.6±3.4

39

Pu damai 2

China

80.7±6.4

61

Yong 2176

China

81.9±3.5

18

98-565

China

62.1±0.5

40

Pu damai 4

China

73.2±1.7

62

Yong 2177

China

77.1±4.1

19

89-179

China

63.7±9.9

41

955099

China

23.0±4.1

63

Yong 2181

China

65.3±1.5

20

Fang 18

China

30.0±9.6

42

Pu damai 6

China

62.0±3.9

64

Beijing Mimai

China

85.9±1.0

21

24631

China

66.6±6.3

43

Xingsheng

China

83.7±6.9

65

Heitumi

China

66.1±3.1

22

81-11

China

33.7±5.2

44

Yong 3646

China

47.9±4.1

       

*the average of inhibition rate (IR)±standard deviation(SD)

Table 3. The primer sequences and their SSR band data

Barley

Rice

primer

Sequences
(5’~3’)

Total Bands

Polymorphic bands

PPB(%)

primer

Sequences
(5’~3’)

Total Bands

Polymorphic bands

PPB(%)

7

(AG)8T

14

12

85.7

7

(AG)8T

7

3

42.9

11

(AG)8TC

14

12

85.7

9

(AG)8G

4

4

100.0

25

(AC)8T

14

14

100.0

25

(AC)8T

6

4

66.7

27

(AC)8G

13

12

92.3

34

(AG)8CTT

4

1

25.0

35

(AG)8CTC

17

15

88.2

43

(CT)4AGA

4

2

50.0

40

(GA)8CTT

12

11

91.7

50

(GT)8CTC

4

1

5.0

41

(GA)8CTC

13

10

76.9

73

(GACA)4

5

3

60.0

44

(CT)8AGC

15

12

80.0

         

48

(CA)8AGG

14

13

92.8

         

55

(AC)8CTT

15

13

86.7

         

73

(GACA)4

14

13

92.8

         

Figure1 DNA fragment of rice amplified by ISSR 73 primer

Figure 2 DNA fragment of barley amplified by ISSR 11 primer

Discussion and Conclusion

In the screening for allelopathic potential, five rice accessions, Iguape Cateto, PI312777, Azucena, Taichung Native 1 and IAC25, demonstrated over 50% inhibition of barnyardgrass root growth. Barley accessions showed higher allelopathic potential in the suppression on receiver model plant (lettuce), showing that IRs of 16 accessions such as H0686, H0687, HDE84194-622-1, Dan2, S-2,82-F165 and G10Nan74-17 were higher than 80%. These differences might result, in part, from the different receiver plants with different sensitivity to allelochemicals. However, they were still thought to be potentially useful for the research on plant allelopathy and the breeding program for allelopathic crops. But the result also indicated that several accessions, of both rice and barley, showed less than 20% inhibition of target plant growth. This research has clearly demonstrated that genetic variability of the allelopathic trait is widespread within rice and barley species. To address this issue, it was essential to investigate the underlying genetic diversity of the accessions being examined.In the present study, the genetic polymorphism of allelopathic rice and barley accessions detected by ISSR approach indicated that those accessions from the same geographical location could be clustered into one group. It was found that some rice and barley accessions with higher allelopathic potential also could be grouped together, implying that the genes conferring allelopathy in those accessions might be isolocus, such as rice accessions IAC25(5), IAC47(11) and IAC120(9). Also, PI312777(2) and Taichung Native 1(4),from America and Taiwan respectively, were clustered together and all possessed high allelopathic potential as shown in Figure 3. This could be certificated by the fact that PI312777 was hybrid progeny from Taichung Native 1 and Taichung 65 (Dilday et al., 1998). However, some accessions with differentallelopathic abilities were clustered in the same group. Iguape Cateto (1), Dourado Pecoce (35) and Pratao Precoce (54) as shown in Figure 3, exhibited lower levels of genetic polymorphism. The same tendency was also found in the examined barley lines, which might be attributed to oriented selection for other desirable traits in breeding program. It has been postulated that wild types of existing crops might once have possessed high allelopathic activity and that this character inadvertently attenuated through continuous selection of crop plants for other desirable characteristics (Putnam and Duke, 1974)

In conclusion, ISSR is a powerful tool to assess the genetic diversity and cultivar differentiation in terms of allelopathic potential. Accordingly, we were able to search for the different genes involved in rice and barley allelopathy from the different groups. This offers us a genetic pool for the selection of crop cultivars with high allelopathic ability (Wu et al, 1999). Further research is also required to confirm the close relationship between allelopathic traits and specific molecular marks, then attempt the cloning and the transfer of allelopathy genes from the selected accessions into cultivated crops based on the approaches of molecular biology and bioinformatics.

Acknowledgement

This work was supported by grants (30471028, 30200170, 2003F012) from National Natural Science Foundation of China, and The Key Scientific Technological Program of Fujian Province, China.

References

Agnese K.B., Roland V.B and Christophe D. (2004) Inter simple sequence repeat analysis of genetic diversity and relationship in cultivated barley of Nordic and Baltic origin Hereditas 141:186-192

Boutsalis P.and Powles, S.B.(1995) Resistance of dicot weeds to acetolactate synthase (ALS)-inhibiting herbicides in Australian. Theoretical and .Applied.Geneiics. 35:149-155.

Chou C H. (1998). Adaptive autointoxication mechanisms in rice. In : Olofsdotter M (eds), Allelopathy in Rice. IRRI, Manila,Philippines. 99-116

Dilday R.H., Yan W.G., Moldenhauer K.A.. and Gravois K.A (1998) Allelopathic activity in rice for controlling major aquatic weeds. In ‘Proceedings of workshop on Allelopathy in Rice’.(Ed M.Olofsdotter) pp7–26 (International Rice Research Institute, Manila, Philippines).

Ebana Kaworu, Yan Wengui, Dilday Robert H., Namai Hyoji and Okuno Kazutoshi. (2001) Analysis of QTL associated with the allelopatrhic effect of rice using water-soluble extracts. Breeding Science. 51:47-51

Fujii Y. Shibuya and T.Yasuda. (1990) Method for screening allelopathic activities by using the logistic function (Richards’ function) fitted to lettuce seed germination and growth curves. Weed Research, Japanese, 35:353-361

Lin W.X. and He H.Q. (2003) The performance of allelopathic heterosis in rice (Oryza sativa L.). Allelopathy Journal 12 :179-188

Lin W.X. Kim K.U. and He H.Q. (2000) Rice allelopathic potential and its modes of action on barnyardgrass (Echinochloa crus-galli L) Allelopathy Joural 7:215-224

Louise Bach Jensen, Maria Olofsdotter and Brigitte Courtois. (2000) Genetic Control of Allelopathy in Rice (Oryza sativa L). In. ‘Proceedings of workshop on Rice Allelopathy’.(Eds K.U Kim.and D.H Shin.) pp: 27-40 (Chan-Suk Park publishing Korea.).

Lovett J.V.and Hoult A.H.C. (1995) Allelopathy and self-defence in barley.In ‘Allelopathy, Organisms, Processes, and Application’. (Eds. Inderjit, K M.M Dakshini and F.A Einhellig). pp.170-183 (American Chemical society, Washing, DC).

Mattice J. Lavy T. Skulman B. and Dilday R.H.(1998) Searching for allelochemicals in rice that control ducksalad. In ‘Proceedings of workshop on Allelopathy in Rice’.(Ed M.Olofsdotter) pp:39-44 (International Rice Research Institute, Manila, Philippines).

Motiul.Q., Grant.D., Russell B., Steven W.and Mark W.S. (2001) Allelopathy, DIMBOA and genetic variability in accessions of Triticum Speltoides. Journal of Chemical Ecology.27 :747-760

Navarez D and Olofsdotter M. (1996) Relay seedling procedure as screening method in allelopathy research. In ‘Proceeding of the 2nd International weed control Conference’, (Eds B.H. Cussans,GW Devine and SO Duke et al) pp: 1285-1290 (Department of Weed Control and Pesticide Ecology, Slagelse, Denmark)

Olofsdotter M. (1998) Allelopathy in Rice. In ‘Proceedings of workshop on Allelopathy in Rice’. (Ed M.Olofsdotter) pp1-5 (International Rice Research Institute, Manila, Philippines).

Olofsdotter M. (2001) Rice - A step toward use of allelopathy. Agronomy Joural. 93: 3-8

Punam AR , Duke WB. (1978) Allelopathy in agroecosystem. Annual Review of phytopathology. 16:431-451.

Rice E.L. (1984) Allelopathy,2nd ed. New York.Academic Press Inc.pp:130-188.

Rimando A.M. Olofsdotter M. Duke S.O. (2001) Searching for rice allelochemicals.An example of bioassays-guided isolation.Agronomy.Journal., 93:16-20.

Weining S, Ko L. Henry R.J. (1994) Polymorphisms in the α–amy1 gene of wild and cultivated barley revealed by the polymerase chain reaction. Theoretical and.Applied.Geneticist. 89: 509-513.

Wu H, Pratley J, Lemerle D and Haig T. (1999) Crop Cultivars with Allelopathy Capability. Weed Research. 39:171-180.

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