Evaluation of allelopathic activity of 68 medicinal and wild plant species of Iran by Sandwich method

Document Type: Research paper

Authors

1 Department of Horticultural Science, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran

2 Department of Horticultural Science, Ferdowsi University of Mashhad, Mashhad, Iran

3 Research Center of Plant Science, Ferdowsi University of Mashhad, Mashhad, Iran

4 Department of Horticultural Science, College of Agriculture, University of Birjand, Birjand, Iran

Abstract

This experiment was conducted in Ferdowsi University of Mashhad, in 2011 to investigate the allelopathic potential of 68 medicinal and wild plant species belong to 19 plant families grown in Iran. Results showed that among examined plants, stigma and style of Crocus sativus,leaves of Artemisia kopetdaghensis, Mentha piperita, Zhumeria majdae, Frulago subvelutina, flowers bud of Eugenia caryophyllata, flower of Perovskia abrotanoides, fruits of Melia azedarach and Ruta graveolenhad the strongest inhibitory effects on lettuce seedling growth. Interestingly by using of very low amount of plant samples (10 mg)growth inhibitory effects of these plants were observed by more than 70%. Additionally, the leaf of Atriplex canescens and the flower of Achillea millefolium had the strongest inhibitory effect on radicle growth (more than 75%) compare to the growth of hypocotyl (less than 20%). Here we can suggest that plants  with inhibitory effects on growth and development of other plants have the potential to be applied as biological herbicides; this finding can be highlighted as new sustainable herbicides for biological control of weeds.

Keywords


Introduction

Allelopathy is a process by which chemical substances are released from plants by mechanisms including root exudation, leaching dew and rain from the plant surface, volatile compounds secretion or as consequence of decaying plant litters (Rice, 1984). For many years, it was thought that the allelochemicals are useless for practical weed managements but nowadays the protective potential of these compounds against biotic stresses such as pathogens, insects, and pests has been approved (Khanh et al., 2005). Therefore, plants with capacity to produce allelochemicals can positively influence agricultural systems (Macias et al., 2007). Numerous growth inhibitors with allelopathic properties have been identified from allelopathic plants (Xuan et al., 2005). These compounds vary in their chemical compositions and concentrations (Haddadchi and Massoodi Khorasani, 2006). The current research is aim to investigate allelopathic activity of some plant materials to solve ecological and agricultural problems with an emphasis on the use of allelochemicals as an alternative candidate for management of weeds. This will help to reduce the using of synthetic herbicides and avoid their environmental hazards (Khanh et al., 2005).

In the agricultural system, application of chemical herbicides is one of the effective approaches in plants weed control (Batish et al., 2006). However, excessive uses of chemical herbicides in recent decades have caused serious concerns such as environmental and health problems due to long-term and large-scale herbicide application (Gao-Feng et al., 2010). Moreover, induction of herbicide-resistant mechanisms in weeds (Quader et al., 2001) has raised needs for introduction of new herbicides (Xuan et al., 2005). Therefore, recent studies have mainly focussed on finding novel natural plant products to develop bio-herbicides (Khanh et al., 2005). In comparison with chemical herbicides, natural plant products exhibit important advantages including biodegradable property, structural diversity and complexity and low amount of halogenated atoms (Dayan et al., 1999; Duke et al., 2000). Besides, they can act on unexploited target sites (Duke et al., 1997).

In general allelopathic plants are used to introduce selective weed management strategies (Khanh et al., 2005). In order to identify plants containing natural compounds with biological activity, allelopathic plants selection strategy is a general and an acceptable approach (Duke et al., 2000). However, researches belong to allelopathic studies meet some difficulties. As an example, insufficient description of methodology may cause a serious concern due to the use of unnatural growth medium in laboratory condition which makes it rather difficult to explore the actual effects of allelopathy in artificial condition (Inderjit and Nilsen, 2003). This can be due the fact that in natural conditions plants generally are capable of adapting to the toxic compounds (Harper, 1977), and raise the question whether this capacity is lost in laboratory condition? (Weibhuhn and Parti, 2009). In addition, allelopathy bioassays are influenced by soil property as a complex biological system which causes different complexities during experiments (Inderjit, 2006).

To overcome these challenging problems, accurate laboratory experiments have been designed in the past few years. These experimental designs are used to distinguish the effect of individual elements such as light, water, and nutrients (Tang and Young, 1981). Sandwich method, is a new approach to specify bioassay test for assessing allelopathy by using of leaf litter plants in a nutrient free agar medium (Fujii et al., 2003); therefore this method exclude the mentioned difficulties. Furthermore, it is relatively fast and allows researchers to conduct numerous experiments in a short timeframe. In our experiment, to select the strongest allelopathic species, dried leaves of 239 plant species were assayed by the Sandwich method, using Lactuca sativa (lettuce) as the test plant (Fujii et al., 2003). Furthermore, allelopathic properties of 37 plant species were determined with this method (Ibrar Shinwari et al., 2013). Recently, 251 plant species collected from the Sino-Japanese Floristic Region were screened for allelopathic activity by sandwich method (Appiah et al., 2015)., Although many studies have been done by using this method, less information is available regarding the allelopathic activity of plant species from Iran, particularly this method is not regularly applied in former studies. Therefore such information is of considerable importance for any attempts to evaluate the allelopathic capacity of native plants ifrom Iran by using of newly advanced approaches like sandwich method.

 

Material and Methods

Plants material, preparation, and procedures

This study was conducted in Department of Horticultural Science, Ferdowsi University of Mashhad, Iran and Tokyo University of Agriculture and Technology. In our research, for evaluating allelopathic activity, the majority of test-plants were selected from medicinal and weed plants, due to the high content of secondary metabolites in the medicinal plants and high aggressive power of the weeds which indicate proper identity to choose candidate plants for allopathic assessment (Table 1). Most of the plant materials collected from different regions of Khorasan Province, Northeast part of Iran. After authenticating samples in the Ferdowsi University of Mashhad Herbarium (FUMH) voucher samples were deposited in the herbarium for further studies. The samples were oven dried at 60 ˚C for less than 24 h and were approximately left for two days in a general drying chamber. Dried samples were placed in plastic bags and kept in an air-tight box until use.

 

Table 1. Screening of 68 medicinal and wild plant species using the sandwich method

No.

Family

Scientific name

Part used

Plant samples amount in each well

Criteria

10 mg

50 mg

Radicle

Hypocotyl

Radicle

Hypocotyl

1

Berberidaceae

Berberis vulgaris L.

Leaf

32.3

2.6

79.3

67.3

 

Fruit

67.6

38.0

97.3

93.0

 

2

Boraginaceae

Borago officinalis L.

Leaf

49.6

23.6

81.3

66.6

 

Caccinia macranthera (Barks & Soland.) Brand var. Crassifolia (Vent.) Brand

Leaf

46.6

-7.3

84.6

63.0

 

Echium italicum L.

Leaf

40.0

-19.0

73.6

19.3

 

3

Chenopodiaceae

Atriplex canescens James

Leaf

81.3

21.0

95.0

89.0

R*

Chenopodium botrys L.

Leaf

64.0

24.0

94.3

82.3

 

Halimocnemis mollissima Bge.

Leaf

58.0

25.0

95.3

91.0

 

Krascheninnikovia ceratoides (L.) Gueldenst.

Leaf

51.6

-12.3

85.3

63.0

 

Krascheninnikovia ceratoides (L.) Gueldenst.

Seed

54.6

9.3

74.0

39.3

 

4

Cistaceae

Helianthemum ledifolium (L.) Miller

Leaf

33.6

-21.6

61.0

-6.0

 

5

Compositae (Asteraceae)

Achillea  biebersteinii Afan.

Leaf

56.3

2.0

87.3

71.3

 

Flower

71.6

30.6

93.3

80.6

 

Achillea  millefolium L. subsp. Elbursensis Hub.Mor.

Flower

70.6

9.0

86.0

65.3

R*

Achillea nobilis L. subsp. Neilreichii (Kerner) Formanek

Leaf

71.0

-18.3

90.3

70.3

R* H+

Flower

48.3

-9.0

88.0

75.0

 

Achillea pachycephala Rech. F

Leaf

72.0

48.3

95.6

86.0

 

Artemisia kopetdaghensis Krasch., M. Pop. & Lincz. Ex poljak

Leaf

90.0

84.0

99.3

98.3

*

Echinacea purpurea (L) Moench

Leaf

52.3

-22.3

68.6

20.0

 

Heteropappus altaicus (Willd.) Novopoker

Leaf

64.0

52.3

88.3

86.3

 

Lactuca serriola L.

Leaf

53.3

33.0

84.6

59.6

 

Pulicaria gnaphalodes (Vent.) Boiss.

Seed

61.0

25.3

77.6

63.3

 

6

Cupressaceae

Juniperus excelsa M.B.

Leaf

-27.3

-16.0

9.3

7.3

R+H+

Fruit

13.6

-10.0

57.0

25.0

 

7

Euphorbiaceae

Euphorbia aellenii Rech. F.

Leaf

61.3

47.0

77.0

59.0

 

8

Iridaceae

Crocus sativus L.

Style

79.3

68.6

96.3

90.0

*

Leaf

67.6

51.3

77.0

63.0

 

Stigma

79.0

68.6

97.3

92.3

*

9

Labiatae (Lamiaceae)

Hyssopus angustifolius M.B.

Leaf

61.6

43.3

86.3

78.3

 

Flower

31.0

-2.3

58.6

28.6

 

Lavandula vera D.C.

Syn: L. angustifolia Miller

Flower

76.0

48.6

99.6

99.3

 

Leaf

38.6

14.0

98.0

94.6

 

Melissa officinalis L.

Leaf

50.0

21.0

86.0

75.6

 

Mentha piperita L.

Leaf

90.6

86.6

99.3

99.3

*

Origanum vulgar L.

Leaf

41.0

27.6

75.3

64.0

 

Perovskia abrotanoides Karel.

Flower

72.3

66.3

97.3

93.0

*

Phlomis cancellata Bunge.

Leaf

69.6

37.3

89.0

67.6

 

Rosmarinus officinalis L.

Leaf

22.6

3.6

61.0

54.6

 

Salvia nemorosa L.

Leaf

57.6

32.0

92.0

83.3

 

Satureja hortensis L.

Leaf

0.0

13.6

76.0

59.6

 

Stachys lavandulifolia Vahl.

Leaf

50.0

14.0

85.6

70.6

 

Stachys turcomanica Trautv.

Leaf

67.6

49.6

89.3

77.0

 

Teucrium polium L.

Leaf

50.6

25.6

86.6

71.6

 

Thymus vulgaris L.

Leaf

29.6

13.0

93.0

90.0

 

Zataria multiflora Boiss.

Leaf

-2.3

27.6

62.6

60.0

 

Zhumeria majdae Rech.

Leaf

86.3

73.0

100

100.0

*

Ziziphora clinopodioides Lam.

Leaf

78.0

50.0

94.0

78.6

 

10

Meliaceae

Azadirachta indica Adr. Ju

Fruit

39.3

14.0

68.3

41.6

 

11

Myrtaceae

Eugenia caryophyllata Thunb.

Flower

73.6

60.6

96.3

91.3

*

12

Oleaceae

Melia azedarach L.

Fruit

76.3

72.6

95.3

91.3

*

Melia azedarach L.

Flower

64.6

56.0

66.6

69.6

 

13

Ranunculaceae

Ranunculus cicutarius Schlectend.

Leaf

61.3

24.6

80.6

57.3

 

Rosaceae

Cotoneaster nummularia Fisch. & C.A. Mey

Leaf

72.3

42.3

88.3

65.3

 

14

Rutaceae

Ruta graveolens L.

Fruit

60.3

67.3

84.0

82.0

*

Leaf

55.3

49.3

76.6

73.0

 

15

Scrophulariaceae

Verbascum speciosumSchrad.

Leaf

41.0

3.0

83.3

56.6

 

16

Solanaceae

Hyoscyamus turcomanicus Pojark.

Leaf

81.3

46.6

96.0

89.6

 

Lycium depressum Stocks

Leaf

55.6

38.6

93.0

85.6

 

Withania coagulans (Stocks) Dun.

Fruit

29.3

11.3

60.3

42.0

 

Withania somnifera (L.) Dun.

Leaf

31.0

8.0

81.0

45.6

 

17

Umbellifera (Apiaceae)

Bunium persicum (Boiss.) B.

Straw

40.0

9.6

84.6

63.0

 

Dorema ammoniacum D. Don.

Flower

58.6

26.0

91.3

67.6

 

Leaf-2

65.0

37.6

94.3

79.6

 

leaf-1

44.6

21.0

80.6

49.6

 

Stem

43.6

4.0

43.6

25.6

 

Frulago subvelutina Rech.F

leaf

91.6

76.3

96.0

90.0

*

18

Verbinaceae

Vitex pseudo-negundo (Hausskn.)

leaf

37.0

5.6

54.0

38.0

 

19

Zygophyllaceae

Zygophyllum fabago L.

leaf

39.3

21.6

69.0

53.0

 

*(seventh cluster): highest growth inhibitory on radicle and hypocotyl.

R* (second cluster): inhibitory effects on radicle growth

R* H+ (fourth cluster): inhibitory effects on radicle growth and stimulatory on hypocotyl.

R+ H+ (ninth cluster): stimulatory effects on radicle and hypocotyl growth.

 

Evaluation of allelopathic activity

To assess the allelopathic activity of the selected plants, multi-dishes plates with 3.5 cm diameter including 6 holes (wells) (Nunc Company) were used (Fujii et al., 2003). Ten mg of dried samples were placed in all three wells in the upper row and 50 mg was placed in rest of the three lower wells.

For the preparation of the growth medium, commercially available agar was used (gelling temperature 30-31 °C, Nacalai Tesque, Kyoto, Japan). The medium was prepared as 0.5% (w/v) and autoclaved at 115 °C for 20 min. The autoclaved agar was cooled down to 45 °C in a water bath. Thereafter, five ml autoclaved agar was added to each well of the multi-dish plastic plate include plant samples (Fig. 1a). After gelatinizing the agar within 30-60 min at room temperature (25 °C), another five ml agar was added to all wells as the second layer and left at room temperature. This made a sandwich of dried leaves by two layers of agar (Fig. 1b). For the bioassay experiment, lettuce seeds (Lactuca sativa L. var. Great Lakes 366) were used as a test plant because lettuce is reliable plant to investigate the inhibitory and stimulatory allelochemicals at low concentrations (Fujii et al., 1990). Five seeds of lettuce were planted on the agar surface of the wells and all treatments replicated four times. Each side of the prepared multi-dishes was then sealed with parafilm and wrapped by aluminum foil to prevent light penetration and was placed in incubator (25 °C) (Fig. 1c). After three days, germination rate and seedling growth (radicle and hypocotyl length) of the lettuce seeds were recorded and were compared with control samples (Fig. 1d). Agar medium without plant samples was used as control (Fig. 1e).

Fig. 1. Steps of the sandwich method; (a) five ml autoclaved agar was added to each well of the multi-dish plastic plate include plant samples; (b) five ml agar was added to all wells as the second layer and left at room temperature. Five seeds of lettuce were planted on the agar surface of the wells; (c) Each side of the prepared multi-dishes were sealed with parafilm and wrapped by aluminium foil to inhibit light penetration and placed in incubator (25 °C); (d) After 3 days, germination rate and seedling growth (radicle and hypocotyl length) of the lettuce seeds recorded and compared with control samples; and (e) Agar medium without plant samples was used as control

 

Statistical analysis

For initial statistical analysis, growth inhibition percentage was calculated. In this experiment, 68 plants including radicle and hypocotyl growth percentage in two concentrations of 10 and 50 mg plant samples were compared. Visual clustering was not conducted due to the large numbers of variables. For more convenient comparisons between plants Minitab software (version 16) was used. Clustering was performed by centroid method. Similarity level between plants, in each cluster, was 90%.

 

Results

Table 1 shows the growth inhibitory percentage of the radicle and hypocotyl of lettuce seedlings based on the dried samples of 68 plant specimens from 19 different families. Growth percentages of lettuce seedlings are presented according to either induction or inhibition effects. Negative and positive values represented induction and inhibition when compared to the corresponding controls, respectively. The initial results provided in Table 1 showed that among 68 plant samples, 57 plants had inhibitory responses while 11 plants induced seedling growth in lettuce.

A graphical analysis of clusters and associated plants was done with centroid method and presented in Figure 2. According to the results of clustering analysis, after adjustment, the data were strikingly clustered and all plants with their associated variables were categorized in nine clusters. 

Wherever the horizontal line has cut the vertical lines that point is a cluster and the joined plants to each point are in the same cluster

Fig. 2. Graphical depiction of clusters and their associated plants by using of centroid method

 

Clustering summary has been indicated in Table 2. Properties of clusters including growth inhibitory percentage of radicle and hypocotyl in two different amounts of plant samples and also the number of plants in each cluster have been explained in this Table. Results showed that based on allelopathic effects four clusters are more important including inhibitory and stimulatory effects among nine clusters.

Table 2. Clustering summary: similarity level between plants in each cluster is 90%


Cluster

Mean of inhibitory

Number of plants

10 mg

50 mg

Radicle

Hypocotyl

Radicle

Hypocotyl

7

79.97

72.43

96.13

92.77

10

2

76.00

15.00

90.50

77.17

2

4

71.00

-18.67

90.33

70.33

1

6

68.5

45.54

88.06

77.90

16

1

45.57

16.60

79.32

62.08

29

3

45.44

-15.28

76.89

39.06

6

5

13.67

-10.00

57.00

25.00

1

8

-1.17

20.67

69.33

59.83

2

9

-27.33

-16.00

9.33

7.33

1

                       

These four clusters are described as the following:

-          The seventh cluster includes ten plant samples (from nine species) namely viz., stigma and style of Crocus sativus, leaves of Artemisia kopetdaghensis, Mentha piperita, Zhumeria majdae, Frulago subvelutina, flower buds of Eugenia caryophyllata, the flower of Perovskia abrotanoides, fruit of Melia azedarach, Ruta graveolens. Plants in this cluster had the highest growth inhibitory effects among all clusters. The growth inhibitory of these plants was more than 70% in 10 mg plant sample. 

-          The second cluster contains two plant samples including leaves of Atriplex canescens and flowers of Achillea millefolium. These plants had the strong inhibition growth effects on radicle growth. However, inhibitory effects on hypocotyl growth in this cluster were less than 20%. Similar to the seventh cluster, plants in this cluster can be considered for identification of allelopathic active compound or further compounds identification

-          The fourth cluster includes leaves of Achillea nobilis. Allelopathic activity of this plant influenced the growth rate In both positive and negative manner, So that  a significant allelopathic stimulation of hypocotyl and strong inhibition of radical growth was observed. Even though growth induction can be related to the allelopathic compounds, but their inhibitory effects are more noteworthy.

-          The ninth cluster includes the leaf of Juniperus excelsa (Fig. 2). Stimulatory growth effects on radicle and hypocotyl was observer for this plant.

Clustering was done to facilitate the comparison among plants. This experiment was conducted according to 50 mg dried plant samples however, final selection and classification was performed based on 10 mg dried material. This was done due to the fact that most of the plants in 50 mg dried plant sample showed considerable inhibitory effects on lettuce seedlings. One of the possibilities for these strong inhibitory effects could be the high amount of elements or compounds other than allelochemicals which eventually results in seedlings death.

Discussion

The results presented in this paper indicated that among 68 specimens 12 plant samples had allelopathic effects as inhibitory growth on lettuce germination (second, fourth and seventh clusters). So far, there is little information on the allelopathic effects of most tested plants which have been used in this study. However, few reports have shown allelopathic properties of Achillea millefolium, Crocus sativus, Melia azedarach and Ruta graveolens.

Achillea millefolium is a medicinal plant that its therapeutic applications have been frequently reported in Europe and in Asia (Vitalini et al., 2011). Scientists have been indicated that high antioxidant capacity (Giorgi et al., 2009) and antispasmodic effects in Achillea genus (Saeidnia et al., 2011) are due to the high amount of phenolic and flavonoids contents. Phenolic and flavonoid compounds are classified in allelochemical groups (Lattanzio et al., 2006). Quercetin is a typical phenolic allelochemical (Lattanzio et al., 2006) that commonly found in Achillea genus (Saeidnia et al., 2011). Rutin is one of the main flavonoid compounds that have also been identified in flowers of Achillea millefolium (Benetis et al., 2008). Allelopathic properties of rutin in Citrus unshiu have been reported by Nishida (2005). Interestingly, fluorescent allelochemical such as austricine and azulenes have been identified in Achillea millefolium. These fluorescent compounds may be applied to the study of allelopathic functional mechanisms (Roshchina et al., 2012). Some flavonoids such as apigenin and luteolin are the major bioactive constituents of the A. millefolium bioactive compounds (Vitalini et al., 2011). Allelopathic effects of apigenin (Basile et al., 2000) and luteolin (Beninger and Christopher Hall, 2005) have been confirmed in former studies. These compounds possibly are effective in triggering of allelopathic responses in A. millefolium.

In our study, saffron showed also strong allelopathic effects (Crocus sativus) in stigma and style organs. Iran is considered as one of the main countries in saffron production. This autumn-flowering perennial plant grows mainly in the East and Southeast of Iran (Sariri et al., 2011). For a long time, Saffron is used for its taste, odor, and colour (Hori et al., 1988). The therapeutic effects of Saffron have been used in traditional and modern medicine (Hadizadeh et al., 2003; Hori et al., 1988; Magdalini et al., 2006). Antioxidant properties in stigma and remaining flowers of saffron are related to flavonoids and phenolic components (Magdalini et al., 2006; Sariri et al., 2011). Allelopathic effects of saffron stigma in this research could be related to the presence of phenolic compounds. These compounds have been previously introduced as allelochemical materials (Almeida Barbosa et al., 2007; Scognamiglio et al., 2012). Allelopathic effects have been also reported in the extract of saffron leaves and corm (Rashed et al., 2008). These allelopathic effects have been identified by dish pack method (Amini et al., 2014), and introduced with the name of safranal as a bioactive compound (Mardani et al., 2015) Melia azedarach L. is another plant species that in this experiment suppressed seed germination and inhibited seedling growth in lettuce. Consistent with our finding, phytotoxic effects of M. azedarach L. on germination and growth of Lactuca sativa L. was reported by Lungu et al. (2011). Analysing M. Azedarach allelochemicals on Raphanus sativus germination and growth showed that Melia allelochemicals caused an imbalance in oxidative status of cells and influenced peroxidation of membrane lipid and electrolytes leakage in radish seedlings (Akacha et al., 2013). Chemical analysis of the Melia azedarach fruit resulted in determination of 14 compounds with insecticidal effects. Although, three compounds including catechin and two kaempherols have been reported in previous studies (Italo Chiffelle et al., 2009), the majority of these compounds are unknown. In addition, further studies showed that the secretion of catechin from roots of noxious weed is negatively influenced the plant-plant interactions (Bais and Kaushik, 2010). Catechin is also exists in Melia azedarach fruit and plays an important role in its allelopathic effect.

In the current experiment, Ruta graveoloans (Rutaceae) showed allelopathic effects on growth. This well-known medical plant is used in ancient civilizations for treating many diseases (Ahmadi Jalali Moghadam et al., 2012). The possible allelopathic activity of R. graveolens essential oil and some of its isolated constituents have been previously reported (De Feo et al., 2002).

Rutin isolated from leaves, stems, and fruits of R. graveolens (Mancuso et al., 2015) is introduced as an allelochemical (Cheng and Cheng, 2015).

The results obtained from current study revealed that the sandwich method is a very useful tool for screening different plants based on their allelopathic activities. In current research, an introductory screening was done on 68 plants to recognise their allelopathic activities. However, further studies are also needed on these plants to identify their effects on the weed plants.

 

Acknowledgment

The research was supported by JSPS (Japanese Society for the Promotion of Science), Ferdowsi University of Mashhad and Tokyo University of Agriculture and Technology.

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