Evaluation of Allelopathic Activity Interactions of Some Medicinal Plants Using Fractional Inhibitory Concentration and Isobologram

Abstract

Allelopathy is a physiological process with an ecological concept and application. Allelopathy is the result of the production of biologically active molecules by growing plants or their remains, which may have a direct effect on the growth and development of individuals of the same species or other species after changing their shape and entering the environment. As regards, the use of natural compounds in the control of weeds and pests is a priority. In this research, the allelopathic activity of 123 specimens of medicinal and aromatic plants were investigated individually by the dish-pack method using lettuce seeds as a model. Then, the strongest inhibitory ones were selected and their allelopathic interaction effects were investigated for the first time by interacting them together. Two methods were used to evaluate allelopathic interaction effects: calculating Fractional Inhibitory Concentration (FIC) and drawing Isobologram diagrams. Lettuce hypocotyl length, root length, germination percentage, and germination rate were investigated. Pelargonium graveolens (leaf) had the greatest inhibitory effect on lettuce radicle growth (EC₅₀ = 5.31 mg/well) and Echinophora platyloba (stem) had the greatest effect on hypocotyl growth inhibition (EC₅₀ = 7.91 mg/well). Also, the lowest lettuce germination percentages were observed in the treatments Lavandula officinalis (flower) and Nepeta binaloudensis (leaf), respectively (23.61, 22.85%). The highest inhibitory effect by considering lettuce germination rate was detected in Salvia ceratophylla (leaf), (12.86 seed/day) and the lowest belonged to Nepeta binaloudensis (leaf) and Lavandula officinalis (flower), respectively (3.60, 3.32 seed/day). According to FIC calculations and isobolograms, two types of interaction, including synergist (Nepeta binaloudensis (leaf) with Trachyspermum ammi (fruit) and Nepeta binaloudensis (leaf) with Lavandula officinalis (flower) and antagonist (Pelargonium graveolens (leaf) with Lavandula officinalis (flower)), were observed significantly among the plants tested in this research. These interactions can be used to prepare more effective natural herbicides and decrease the use of herbicides.

1. Introduction

Weeds and crops have growth interactions and cause high expenses for agricultural systems [1]. This played a significant role during the domestication of crops, so weed control measures are required [2]. In most integrated weed management systems, herbicides are widely used [3,4]. Over the last 40 to 50 years, with the commercial production of more than 200 chemical compounds, significant changes in weed control have begun to develop [5].

Medicinal, aromatic, and spice plants and mushrooms produce a wide range of secondary metabolites and the uses of these metabolites as agrochemicals for the control of pests, diseases, and weeds have been well investigated [6,7,8]. Secondary metabolites are a plentiful source of the natural compounds that are produced in the special structure in medicinal and aromatic plants and their content and composition are affected by plant species, climate, cultural practices, and harvest time [9,10,11]. Some of the secondary metabolites have a good potential use in the development of natural herbicides [12]. They are more environmentally friendly than chemical pesticides and are economically viable and can be easily produced in small industries by farmers [13].

The allelopathic compounds are chemicals produced by some plants (especially medicinal and aromatic plants) that can affect the ecosystem in association with other compounds in collaboration with microorganisms [14,15,16]. In 1999, the International Allelopathy Society offered a precise definition of the allelopathy concept: allelopathy is a science that studies the production of secondary metabolites in plants, algae, bacteria, and fungi and examines their impact on growth in biological and agricultural systems [17].

At the beginning of recognition of plants with allelopathic compounds, due to the lack of rapid methods and knowledge of chemical constituents, it was difficult to describe this important phenomenon [18]. However, in recent years some methods, such as the dish pack method, have be used to detect the allelopathic properties very easily and quickly. In this method, many plant materials can be tested anywhere and in a short period [19].

Although many studies have been conducted on the interaction type (synergistic, antagonistic, and additive potentials) between antimicrobial compounds [20,21,22,23], research on the interaction of allelopathic plants or allelochemicals is very rare [6]. The synergistic interaction is a promising combination which could be used to overcome the resistance to herbicides, insecticides, and microbes. It also could decrease the used herbicide volume and increase the herbicidal efficiency and sustainability.

This research aims to evaluate the allelopathic interaction effects of some medicinal plants by the dish pack method by using seed germination and seedling growth of lettuce as a model plant for allelopathic activity.

2. Materials and Methods

2.1. Plant Materials

Different parts (leaves, flowers, stems, fruits, roots, flowering branches, and seeds) of 123 specimens belonging to 31 families of volatile and medicinal species were collected from the Research Center for Plant Sciences of Ferdowsi University of Mashhad and Botanical Garden of Mashhad. The plant parts were dried in the oven at 45 °C for 2 days to keep the volatile compounds. After the appropriate drying, the parts were kept in a plastic bag until use.

The effect of the tested plants on radicle and hypocotyl growth of lettuce seeds in comparison with control in different plant families was investigated separately. In each plant family, a comparison was made at two probability levels (p ≤ 0.05; p ≤ 0.01).

They were subjected to the analysis of their allelopathic effects using the dish pack method (Figure 1) and the lettuce seeds (Great Lakes 366) were used as the test plant because of their good reliability in germination, sensitivity to inhibitory and stimulatory chemicals, and their convenience of purchase [6,7,19,24].

2.2. Assessment of Allelopathic Effect on Lettuce Seed and Germination Traits

2.2.1. Dish Pack Method

One of pathways to screen volatile compound secreted from plants is the dish pack method as described by Fujii et al. (2000) [19]. In this method, multi-dishes with six wells (18 mm × 36 mm) (Nunc Company, Tokyo, Japan) were used. The distances from the center of a plant sample well to the center of other wells were 41, 58, 82, and 92 mm, respectively, (Figure 1). Then, 200 mg of dried plant samples were placed in one well (source well), while in the rest of wells no plant sample was added. These wells contained a piece of filter paper that was soaked with 0.7 mL of distilled water. Thereafter, seven lettuce seeds were placed over the filter paper in each well. Five blank dishes were prepared as a control sample according to the above method except that the source well contained no plant. The dishes were sealed with parafilm tape to prevent volatile compound losses and desiccation. Then, they were wrapped in aluminum foil to prevent light penetration and incubated for 3 days at 25 °C [19].

2.2.2. Germination and Seed Traits

The effects of the strongest inhibitory plants in the screening stage on the percentage and rate of germination were investigated. For this reason, the data were recorded every 12 h for a period of 3 days and calculated using the following formulas.

Germination percentage = (Total germinated seeds by the end of experiment/Total seeds) × 100 [25,26].

Germination Rate = (Number of germinated seeds per day/Number of days after planting) × 100 [27].

2.3. Assessment of Medicinal Plants’ Allelopathic Effects on Lettuce Seedling Growth

At the end of the incubation period (3 days), to evaluate the growth of hypocotyl and radicle of lettuce seeds, they were placed on checkered paper and photographed and measured by Image J (version 1.331, August 2022) and Excel software (Version 2210) (Figure 2a–c).

2.4. Statistical Analysis

The inhibition index of plants on lettuce seed germination factors (Criteria) was defined.

According to the results obtained from the average inhibition activity, the mean and standard deviation were calculated, and based on these, the basis of different groupings for the inhibition percentage of plants were defined in 4 levels: (****) Mean + 3 SD, (***) Mean + 2 SD, (**) Mean + 1 SD, (*) Mean < 1 SD. The highest inhibition percentage is related to the group (****), which indicates 3 times the difference with the standard deviation, (***) which indicates 2 times the difference with the standard deviation, (**) which indicates one times the difference with the standard deviation, and (*) which indicates less than 1 times the difference with the standard deviation.

The inhibition index of the samples was calculated and the means of three replications were analyzed statistically on the basis of RCD in each family. The means comparison was performed using Duncan’s multiple-range test at 0.05 level of probability. Minitab (version 21.01.0), Graphpad Prism (Version 9.4.1), and Excel (Version 2210) were used for the statistical analysis and graphing. In addition, the variance analysis was performed separately for plants of each family.

2.5. Headspace Gas Chromatography-Mass Spectrometry (HS-GC-MS)

Headspace GC-MS was performed to investigate the chemical composition of the samples’ volatiles with the most allelopathic effects. For this purpose, 200 mg of solid plant samples were incubated in 20 mL glass vials and stored at 20 °C for one hour. Then, 1000 μL of air over each sample was removed by a 5 mL SGE 5MDR-HSV syringe and injected into the GC-MS (Shimadzu QP 2010, Tokyo, Japan). GC analysis was run on a (30 m × 250 μm × 0.25 μm) column with helium gas as the carrier gas. The temperature of the injection was as follows: the oven temperature was 50–150 °C, with an increase rate of 3 °C/min, kept in this mode for 10 min, then, reached a temperature of 200 °C at 10 °C/min. The components of volatile compounds were determined by the device library (NIST/NBS). Mass spectra were registered at 70 eV with a mass range of 50 to 400 m/z, in comparison to an internal spectral library (NIST and Wiley). They were then validated by comparing the retention times with the valid standards.

2.6. Allelopathic Interaction Effects

After investigating the allelopathic effects of plants, the strongest inhibitory plants were identified. In order to investigate the allelopathic interaction of these plants, the effective concentration was determined first.

2.6.1. Determination of EC₅₀ and EC₂₅

EC₅₀ is the concentration of the substance that causes 50% of the effect in a process. To evaluate EC₅₀, different concentrations (10, 50, 70, 100, 120, 150, and 200 mg) of each allelopathic plant were examined using the dish pack method. The determination of these values for radical and hypocotyl resistance was performed separately. The results were analyzed by GraphPad Prism 8 software and finally EC₅₀ value was calculated. In addition, the values of EC₂₅ were calculated with Quick Calcs online software.

2.6.2. Plants Combinations

The combined effects of these plants were performed based on the combination of EC₂₅ concentrations. The experiments were conducted to investigate the radicle and hypocotyl growth. Based on the FIC formula and isobologram curves, the mutual behaviors of two plants were investigated.

• Fractional inhibitory concentration (FIC) was calculated using the following equation:

FIC = obtained inhibitory effect in combining two plants expected inhibitory effect in combining two plants

The obtained inhibitory effect of combining two plants indicating the inhibition percentage that was obtained as a result of the combination two plants at a concentration of EC₂₅ in the test.

The expected inhibitory effect of combining two plants indicating the inhibition value of 25% in the concentration of EC₂₅ for each plant, which is naturally expected to be 50% in combination [28].

• Isobologram curves

To draw the isobologram curves, the inhibitory effect of two plants was considered as base, then the concentrations of each plant A and B that lead to similar inhibition were calculated separately using Quick Calcs software. Therefore, three concentrations (A alone, B alone, and A + B in combination) were used to draw graphs showing the same inhibition percentage in all three modes. This curve can be describe in three different situations: (1) without a curve indicating an additive effect; (2) with an upward curve, meaning an antagonistic effect; and (3) with a downward curve, meaning a synergistic effect (Figure 3) [6].

3. Results

3.1. Allelopathic Effects of Medicinal Plants on Lettuce Seed Growth and Germination Specifications

The results of allelopathic effects of 123 samples selected from 31 plant families are shown in

Table 1. The results of investigating the inhibitory power of medicinal plants on the growth of lettuce seeds.

No	Family	Plant Scientific Name	Part Used	Inhibition Activity (%)				Criteria
				Average (41 mm)		Average (Whole Wells)
				Radicle	Hypocotyl	Radicle	Hypocotyl
1	Amaranthaceae	Amaranthus blitoides	Flower	30.12	36.08	30.70	40.00	**
2		Amaranthus hypochondriacus	Leaf	79.03	85.62	62.52	63.52	***
3		Atriplex halimus	Leaf	36.98	16.34	29.50	20.42	**
4		Kochia prostrata	Leaf	24.60	15.02	28.27	15.92	*
5	Amaryllidaceae	Allium sativum	Leaf	30.03	18.04	25.27	18.25	*
6		Ungernia trisphaera	Leaf	9.72	−6.32	−21.64	−39.28	+
7	Apiaceae	Conium maculatum	Leaf	82.57	85.93	66.70	73.57	***
8		Echinophora platyloba	Stem	100.00	100.00	84.62	82.85	****
9		Ferula szowitsiana	Leaf	26.94	29.22	5.57	−6.90	*
10		Ferula xylorhachis	Leaf	11.85	17.78	−2.08	0.77	+
11		Foeniculum vulgare	Fruit	87.03	85.23	79.91	76.73	***
12		Seseli transcaucasicum	Flower	12.47	35.98	−8.70	−6.82	+
13		Seseli transcaucasicum	Leaf	37.94	38.03	1.61	−22.83	*
14		Seseli transcaucasicum	Stem	33.63	29.21	−8.06	−55.43	+
15		Seseli transcaucasicum	Root	28.04	31.69	13.91	1.52	*
16		Trachyspermum ammi	Fruit	99.41	100.00	80.20	82.73	****
17	Apocynaceae	Vinca minor	Leaf	77.62	80.55	52.23	51.49	**
18	Asparagaceae	Asparagus officinalis	Leaf	78.25	86.54	66.35	72.66	***
19	Asteraceae	Achillea nobilis	Flower	94.56	97.10	82.39	79.58	***
20		Achillea filipendula	Leaf	55.23	66.35	50.82	60.69	**
21		Achillea biebersteinii	Leaf	90.05	88.37	85.72	83.40	***
22		Achillea wilhelmsii	Flower	87.98	91.68	62.13	62.93	***
23		Achillea millefolium	Flower	27.90	18.02	25.82	16.74	*
24		Achillea pachycephala	Leaf	70.17	65.36	60.49	53.56	***
25		Artemisia absinthium	Leaf	39.75	37.50	40.47	50.54	**
26		Artemisia scoparia	Leaf	40.81	35.56	35.16	27.38	**
27		Artemisia tournefortiana	Leaf	11.36	16.12	−3.64	−13.16	+
28		Calandula officinalis	Leaf	50.54	46.87	58.12	59.35	**
29		Centaurea behen	Leaf	82.11	83.86	71.31	70.17	***
30		Cousinia raddeana	Flower	26.61	27.43	34.69	37.11	**
31		Codonocephalum peacockianum	Leaf	36.40	20.91	30.27	30.48	**
32		Grindelia robusta	Leaf	31.90	31.46	48.49	44.94	**
33		Helichrysum italicum	Leaf	51.91	59.15	44.62	45.42	**
34		Lactuca persica	Leaf	20.45	03.04	−12.73	−9.21	+
35		Matricaria chamomilla	Flower	64.70	68.19	46.51	52.23	**
36		Pseudohandelia umbellifera	Leaf	55.14	59.79	44.50	40.47	**
37		Pulicaria gnaphalodes	Leaf	28.55	30.69	16.11	13.50	*
38		Pulicaria gnaphalodes	Seed	91.07	89.72	84.68	86.79	***
39		Santolina chamaecyparissus	Leaf	85.02	92.05	66.25	69.57	***
40		Tanacetum balsamita	Leaf	45.24	43.94	23.17	28.87	*
41	Berberidaceae	Berberis integerrima	Root	59.00	33.91	46.26	34.12	**
42		Berberis vulgaris	Leaf	59.07	48.68	40.30	31.62	**
43	Boraginaceae	Trichodesma incanum	Leaf	58.96	59.97	57.33	61.59	**
44	Cannabaceae	Cannabis sativa	Leaf	32.14	−4.59	−18.57	−33.67	+
45	Capparaceae	Capparis spinosa	Leaf	87.86	92.02	57.69	68.82	**
46	Cleomaceae	Cleome chorassanica	Leaf	8.63	27.69	4.59	18.94	*
47	Ephedraceae	Ephedra major	Leaf	−0.86	−29.55	−14.81	−54.96	+
48	Euphorbiaceae	Chrozophora tinctoria	Leaf	60.62	61.59	49.55	55.67	**
49		Ricinus communis	Fruit	56.67	49.65	20.26	27.47	*
50		Euphorbia petiolata	Leaf	7.95	4.61	−10.30	−18.42	+
51		Euphorbia serpens	Leaf	82.74	88.23	75.23	75.29	***
52		Euphorbia aellenii	Leaf	26.96	10.15	20.26	12.25	*
53		Euphorbia granulata	Leaf	82.47	88.39	60.35	63.68	***
54	Fabaceae	Genista tinctoria	Leaf	41.69	37.77	34.12	22.73	**
55	Frankeniaceae	Frankenia spp	Leaf	33.52	4.76	27.63	31.92	*
56	Geraniaceae	Pelargonium graveolens	Leaf	100.00	100.00	83.35	88.23	****
57	Hypericaceae	Hypericum helianthemoides	Root	51.68	59.62	37.52	48.88	**
58		Hypericum perforatum	Leaf	71.81	63.71	49.21	52.58	**
59		Hypericum scabrum	Leaf	34.91	35.45	−11.50	−36.67	+
60	Lamiaceae	Acinos graveolens	Leaf	63.97	79.21	37.26	52.02	**
61		Ballota nigra	Leaf	44.93	61.84	26.13	25.00	*
62		Hyssopus angustifolius	Leaf	18.48	3.63	9.82	−7.34	*
63		Hyssopus angustifolius	Flower	39.83	28.13	30.44	28.13	**
64		Lavandula officinalis	Flower	100.00	100.00	80.29	82.49	****
65		Lavandula officinalis	Leaf	84.56	92.14	82.24	88.39	***
66		Melissa officinalis	Leaf	−12.36	−1.22	23.64	22.37	*
67		Melissa officinalis	Root	−12.37	−1.23	−13.39	−1.50	+
68		Mentha piperita	Leaf	−10.03	10.44	0.62	18.36	*
69		Mentha spicata	Leaf	18.06	29.40	9.12	7.31	*
70		Mentha longifolia	Leaf	90.03	88.55	67.20	77.57	***
71		Nepeta binaloudensis	Leaf	100.00	100.00	96.37	98.28	****
72		Nepeta sintenisii	Leaf	29.52	18.82	14.06	16.37	*
73		Origanum major	Leaf	57.07	75.54	16.16	17.39	*
74		Origanum vulgare	Leaf	64.12	92.96	−26.70	−26.53	+
75		Perovskia abrotanoides	Leaf	95.32	89.65	81.81	77.13	***
76		Perovskia abrotanoides	Seed	31.21	20.94	20.81	16.78	*
77		Rosmarinus officinalis	Leaf	90.67	91.63	80.86	85.41	***
78		Salvia aethiopis	Leaf	94.62	92.56	55.38	36.90	**
79		Salvia tebesana	Leaf	12.50	−22.64	−1.00	−31.13	+
80		Salvia nemorosa	Leaf	71.68	71.45	63.16	65.95	***
81		Salvia leriifolia	Root	86.21	78.93	55.88	54.49	**
82		Salvia leriifolia	Leaf	67.54	65.89	85.06	83.94	***
83		Salvia chloroleuca	Leaf	67.16	59.85	29.36	26.37	**
84		Salvia ceratophylla	Leaf	100.00	100.00	83.87	81.54	****
85		Salvia macrosiphon	Leaf	71.56	70.51	57.79	51.84	**
86		Salvia officinalis	Leaf	17.86	6.49	11.43	−8.16	*
87		Salvia virgata	Leaf	32.99	35.00	40.17	41.90	**
88		Salvia sahendica	Leaf	17.85	26.07	24.52	18.59	*
89		Salvia sclarea	Leaf	62.24	73.54	60.19	68.31	***
90		Stachys byzantina	Leaf	43.43	47.05	40.05	45.20	**
91		Stachys lavandulifolia	Flowering branch	100.00	100.00	89.52	88.65	****
92		Thuspeinanta brahuica	Leaf	18.18	−0.32	−10.61	−12.72	+
93		Teucrium chamaedrys	Leaf	21.36	7.84	17.57	13.74	*
94	Malvaceae	Althaea officinalis	Leaf	21.94	51.12	21.61	40.32	*
95		Malva sylvestris	Flower	76.13	82.20	76.75	78.11	***
96		Malva sylvestris	Leaf	49.41	54.58	16.28	10.13	*
97	Myrtaceae	Peganum harmala	Leaf	46.20	49.02	36.22	44.65	**
98		Eucalyptus globulus	Leaf	100.00	100.00	80.29	82.49	***
99	Nitrariaceae	Eucalyptus globulus	Seed	−12.99	−59.00	2.01	−14.22	*
100	Onagraceae	Epilobium hirsutum	Leaf	30.02	38.02	27.22	32.99	*
101		Oenothera biennis	Leaf	63.00	61.01	47.50	52.41	**
102	Papaveraceae	Corydalis aitchisonii	Leaf	34.43	34.83	19.27	18.55	*
103		Glaucium flavum	Leaf	14.69	10.18	14.85	−8.59	*
104	Plantaginaceae	Plantago major	Leaf	29.96	28.87	14.94	17.75	*
105	Polygonaceae	Polygonum aviculare	Leaf	68.71	59.09	45.12	47.84	**
106		Polygonum patulum	Leaf	53.91	60.01	48.00	54.02	**
107	Rosaceae	Filipendula ulmaria	Leaf	16.07	2.08	18.18	20.58	*
108		Rosa foetida	Leaf	58.44	61.15	60.81	57.81	***
109	Rutaceae	Haplophyllum furfuraceum	Leaf	76.91	76.12	37.13	27.99	**
110		Ruta graveolens	Leaf	33.52	41.44	24.40	30.36	*
111	Solanaceae	Datura innoxia	Leaf	37.72	40.01	39.16	33.78	**
112		Datura stramonium	Leaf	12.33	12.88	−3.40	2.00	+
113		Lycium depressum	Leaf	52.60	47.90	45.99	48.99	**
114		Lycium ruthenicum	Leaf	55.37	55.35	59.24	61.67	***
115		Solanum nigrum	Leaf	38.83	36.60	32.42	28.80	**
116	Urticaceae	Urtica dioica	Leaf	77.65	70.97	68.39	71.68	***
117		Urtica dioica	Root	−45.30	21.10	−30.00	20.01	+
118	Verbenaceae	Lippia citriodora	Leaf	91.35	87.32	33.02	22.83	**
119		Vitex pseudo-negundo	Leaf	53.90	45.75	23.99	20.33	*
120		Vitex pseudo-negundo	Seed	20.22	38.54	15.22	12.02	*
121		Lantana montevidensis	Leaf	19.67	15.33	29.50	36.49	**
122	Zygophyllaceae	Tribulus terrestris	Leaf	56.88	67.94	46.14	41.68	**
123		Zygophyllum fabago	Leaf	12.94	11.27	20.22	16.21	*

1—The intensity of the inhibitory effect on lettuce seed germination was defined by the standard deviation value in four levels: Criteria (****) Mean + 3 SD; (***) Mean + 2 SD; (**) Mean + 1 SD; (*) Mean < 1 SD. 2—Negative numbers indicate stimulating effects on lettuce seed germination.

. In each of the samples, the part with evidence of the presence of the most volatile compounds was selected and analyzed at close distances (41 mm) and the total average (whole wells).

Among these samples, seven species showed a strong inhibitory effect on the germination of lettuce seeds. Some samples also stimulated the germination of lettuce seeds compared to the control.

3.1.1. Radicle Growth (R %)

The most inhibitory effects on radicle growth were observed in the families Lamiaceae (N. binaloudensis leaf); Asteraceae (A. nobilis flower, A. biebersteinii leaf and P. gnaphalodes seed); Apiaceae (E. platyloba stem, C. maculatum leaf, F. vulgare fruit, and T. ammi fruit); Euphorbiaceae (E. serpens leaf, and E. granulata leaf); Solanaceae (L. ruthenicum leaf); Amaranthaceae (A. hypochondriacus leaf); Malvaceae (M. sylvestris leaf) and Hypericaceae (H. perforatum leaf). In the family Verbenaceae, it can be concluded that the individual species had an inhibitory effect on radicle growth (although in some cases small), but no significant difference between them was detected.

3.1.2. Hypocotyl Growth (H %)

The most inhibitory effects on hypocotyl growth were observed in the families Lamiaceae (N. binaloudensis leaf); Asteraceae (P. gnaphalodes seed); Apiaceae (E. platyloba stem, C. maculatum leaf, F. vulgare fruit, and T. ammi fruit); Euphorbiaceae (E. serpens leaf); Solanaceae (L. ruthenicum leaf) and L. depressum leaf); Amaranthaceae (A. hypochondriacus leaf); Malvaceae (M. sylvestris leaf); Verbenaceae (L. montevidensis leaf) and Hypericaceae (H. perforatum leaf and H. helianthemoides root) (Figures S1–S9).

3.1.3. Germination Percentage (G %)

The comparison of the average germination percentage of lettuce seeds in the vicinity of strong inhibitory plants in the period of 3 days of the experiment is shown in Figure 4. In the treatment of S. ceratophylla (leaf), most germinated seeds were observed compared to other treatments, about 72.76%. The highest degree of reduction in lettuce seed germination percentages were observed in the treatment L. officinalis (flower) and N. binaloudensis (leaf), respectively, (23.61, 22.85%).

3.1.4. Germination Rate

As it can be seen in Figure 5, S. ceratophylla (leaf), in comparison to other treatments showed the least effect on reducing the germination rate of lettuce seeds (12.86), while the highest effects belong to N. binaloudensis (leaf) and L. officinalis (flower), respectively, (3.60 and 3.32). The results showed that there is a significant difference between the plants at the probability level of 5%.

3.2. Headspace Gas Chromatography-Mass Spectrometry (HS-GC-MS)

In order to identify the compounds causing allelopathy in the most inhibitory plants (seven specimens), the headspace analysis was performed. The results showed that some phenolic compounds, such as Thymol, Carvacrol, P-Cymene and 1,8-Cineole, were the most common important components in these plants (

Table 2. The main components of the most inhibitory plants based on Headspace Gas Chromatography-Mass Spectrometry (HS-GC-MS) analysis.

Sample	Part of Use	Main Identified Components	RT	%Area
Stachys lavandulifolia	Flowering branch	Thymol	20.13	7.96
Salvia ceratophylla	Leaf	Carvacrol	17.9	1.42
		trans-Caryophyllene	18.14	0.7
		Thymol acetate	20.13	11.82
		Chavicol	25.13	0.98
Echinophora platyloba	Stem	Thymol acetate	20.11	5.31
Trachyspermum ammi	Fruit	P-Cymene	8.82	0.82
		β-Pinene	10.10	0.69
		Borneol	14.46	0.53
		Carvacrol Methyl Ether	17.9	0.77
		α-Ionone	18.12	0.35
		Thymol	20.12	40.02
		Carvacrol	20.48	0.92
		trans-Caryophyllene	25.13	0.62
		Propene	33.98	0.56
		α-terpinolene	35.29	1.18
		4-Cumylphenol	35.49	1.02
		s-Indacene	37.42	0.95
Lavandula officinalis	Flower	1,8-Cineole	9.1	14.3
		Camphor	13.55	2.46
		1-Borneol	14.47	1.04
		Carvacrol Methyl Ether	17.9	0.42
		Thymol	20.11	35.71
		Linalool	20.49	0.71
		Chromolaenin	35.28	1.3
		α-Amorphene	35.49	1.12
		Bornyl acetate	37.4	0.7
Nepeta binaloudensis	Leaf	p-Cymene	8.84	0.57
		1,8-Cineole	9.11	8.47
		α-Pinene	10.15	0.34
		Carvacrol Methyl Ether	17.92	0.21
		Verbenone	19.2	0.14
		Thymol	20.11	28.44
		α-iso-methyl ionone	20.5	0.71
		4-Cumylphenol	35.27	0.86
		β-Caryophyllene	35.49	0.92
		α-Terpinene	37.4	0.79
Pelargonium graveolens	Leaf	β-pinene	7.17	1.22
		1,8-Cineole	9.14	1.13
		α-Pinene	10.13	0.7
		Thymol	20.12	13.93
		Carvacrol	20.49	0.85
		4-Cumylphenol	35.28	0.74
		Isomenthone	35.49	0.56

RT: Retention time (min).

).

3.3. The Specification of Effective Concentrations of the Most Inhibitory Plants

The determination of the effective concentration of plants on germination inhibition (EC₅₀ and EC₂₅) was performed on seven plants, including S. lavandulifolia (flowering branch), S. ceratophylla (leaf), E. platyloba (stem), T. ammi (fruit), L. officinalis (flower), N. binaloudensis (leaf), and P. graveolens (leaf). For all these plants, EC₅₀ and EC₂₅, based on the radicle and hypocotyl inhibition, were calculated (

Table 3. The effective concentration of the most inhibitory plants on lettuce radicle and hypocotyl by dish pack method.

Plant Scientific Name	Part of Use	Radicle Inhibition		Hypocotyl Inhibition
		EC25	EC50	EC25	EC50
		mg/well
Stachys lavandulifolia	Flowering branch	20.57	72.80	58.97	107.8
Salvia ceratophylla	Leaf	36.96	83.70	92.87	130.5
Echinophora platyloba	Stem	2.44	8.99	1.97	7.915
Trachyspermum ammi	Fruit	9.81	25.48	29.72	52.19
Lavandula officinalis	Flower	7.01	9.86	8.65	11.21
Nepeta binaloudensis	Leaf	6.76	7.85	2.64	7.923
Pelargonium graveolens	Leaf	0.53	5.31	2.72	13.71

).

3.4. Allelopathic Interaction of the Most Inhibitory Plants

The interaction effect of the strongest inhibitory plants was evaluated separately on radicle and hypocotyl growth based on the screening test results.

3.4.1. Interaction Result

The results showed a different combination of synergistic, additive, and antagonistic effects. As shown in

Table 4. Fractional Inhibitory Concentration (FIC) of combinations among the strongest inhibitory plants using EC₂₅ of lettuce radicle and hypocotyl.

Plant Interactions		FIC
		Radicle	Hypocotyl
Echinophora platyloba ×	Stachys lavandulifolia	0.52 An	1.46 S
	Salvia ceratophylla	0.15 An	1.17 Ad
	Pelargonium graveolens	−0.09 St	1.11 Ad
	Trachyspermum ammi	0.33 An	1.61 S
	Nepeta binaloudensis	0.56 An	1.30 S
	Lavandula officinalis	−0.12 St	1.49 S
Stachys lavandulifolia ×	Salvia ceratophylla	0.27 An	1.37 S
	Pelargonium graveolens	0.73 Ad	1.46 S
	Trachyspermum ammi	0.72 Ad	1.28 S
	Nepeta binaloudensis	−0.53 St	1.56 S
	Lavandula officinalis	0.18 An	1.85 S
Salvia ceratophylla ×	Pelargonium graveolens	0.58 An	1.05 Ad
	Trachyspermum ammi	0.52 An	1.24 S
	Nepeta binaloudensis	0.97 Ad	1.22 S
	Lavandula officinalis	−0.50 St	1.36 S
Pelargonium graveolens ×	Trachyspermum ammi	1.03 Ad	1.97 S
	Nepeta binaloudensis	−0.38 St	1.46 S
	Lavandula officinalis	−0.56 St	0.54 An
Trachyspermum ammi ×	Nepeta binaloudensis	1.60 S	2.00 S
	Lavandula officinalis	−0.20 St	1.47 S
Nepeta binaloudensis ×	Lavandula officinalis	1.50 S	2.00 S

FIC values ≤ 0 indicate stimulant effects (^St), between 0 and 0.7 indicate antagonistic effects (^An), values between 0.7 and 1.2 indicate additive effects (^Ad) and values greater than 1.2 indicate synergistic effects (^S).

, 42 results were obtained from 21 combinations, which were investigated on radicle and hypocotyl growth separately. In the investigation of these interactions on radicle inhibition, 15 combinations showed antagonistic interactions, 4 combinations showed additive interactions, and 2 combinations showed synergistic interactions. The combination of P. graveolens (leaf) and L. officinalis (flower) had the most antagonistic interaction (28.13%). The most synergistic interaction (80.00%) was observed in the combination of the T. amm (fruit) and N. binaloudensis (leaf).

For hypocotyl inhibition among 21 combinations, 1 combination showed antagonistic effects, 3 combinations showed additive effects, and most combinations (17 combinations) showed synergistic effects. The combination of P. graveolens (leaf) and L. officinalis (flower) was the only combination to show an antagonistic effect (26.91%). Also, the most synergistic effects (100.00%) were observed in two combinations of N. binaloudensis (leaf) with T. ammi (fruit) or L. officinalis (flower).

3.4.2. Isobologram Curves

Different types of allelopathic effects were shown in the isobologram curves (Figure 6 and Figure 7). In the isobologram curves of root growth inhibition (Figure 3), 11 curves showed antagonistic effects between strong inhibitory plants, 3 curves showed synergistic effects, and 7 combinations showed growth stimulating effects. The highest number of antagonistic effects related to S. ceratophylla (leaf) (with five antagonistic effects) and P. graveolens (leaf) had the highest number of synergistic effects (two synergistic effects) with other plants. The additive effects were not observed in these compounds. In the isobolograms showing hypocotyl inhibition (Figure 4), one combination showed antagonistic effects (L. officinalis (flower) with P. graveolens (leaf)), two curves showed synergistic status between plants, and 18 other curves showed synergistic effects. N. binaloudensis (leaf) and T. ammi (fruit) showed the highest number of synergistic curves.

3.4.3. Comparison of Evaluation Methods of Allelopathic Interactions

In order to compare two evaluation methods (FIC and Isobologram curves), the results are summarized in

Table 5. Fractional Inhibitory Concentration (FIC) of combinations of the strongest inhibitory plants using EC₂₅ of lettuce radicle and hypocotyl.

Plant Interactions		FIC		Isobologram
		Radicle	Hypocotyl	Radicle	Hypocotyl
Echinophora platyloba ×	Stachys lavandulifolia	An	S	An	S
	Salvia ceratophylla	An	Ad	An	S
	Pelargonium graveolens	St	Ad	St	S
	Trachyspermum ammi	An	S	An	S
	Nepeta binaloudensis	An	S	An	S
	Lavandula officinalis	St	S	St	S
Stachys lavandulifolia ×	Salvia ceratophylla	An	S	An	S
	Pelargonium graveolens	Ad	S	S	S
	Trachyspermum ammi	Ad	S	An	S
	Nepeta binaloudensis	St	S	St	S
	Lavandula officinalis	An	S	An	S
Salvia ceratophylla ×	Pelargonium graveolens	An	Ad	An	S
	Trachyspermum ammi	An	S	An	S
	Nepeta binaloudensis	Ad	S	An	S
	Lavandula officinalis	St	S	St	Ad
Pelargonium graveolens ×	Trachyspermum ammi	Ad	S	S	S
	Nepeta binaloudensis	St	S	St	S
	Lavandula officinalis	St	An	St	An
Trachyspermum ammi ×	Nepeta binaloudensis	S	S	S	S
	Lavandula officinalis	St	S	St	S
Nepeta binaloudensis ×	Lavandula officinalis	S	S	An	S

(St): stimulant effects, (An): antagonistic effects, (Ad): additive effects, and (S): synergistic effects.

.

As you can see in Table 5, the analysis of two methods in more than one case provides similar results. Since in the FIC method, the comparison is based on numbers, it seems that it is more accurate, but more research is needed to ensure this claim.

4. Discussion

The results obtained from this research, in many items, confirm the allelopathic effects of the medicinal plants and their volatile compounds seen in other research. In the lamiaceae family, L. officinalis, S. ceratophylla, S. lavandulifolia, and N. binaloudensis were reported as strong inhibitory plants. In several field observations, Nepeta species prevent the germination of other plant species in their surroundings [29]. In another report on the allelopathic effect of N. binaloudensis, the germination and growth of sunflower seeds had been inhibited by the aqueous extract of its roots and leaves. The inhibitory effect of L. officinalis on the germination of lettuce seeds was observed by the plant box method [30]. Also, a high suppression (83–95%) of radicle elongation was observed in the flowers of Lavandula vera [16]. A study conducted on the allelopathic effects of volatile compounds of different medicinal plants, N. binaloudensis, L. angustifolia, P. graveolens, T. ammi, and salvia species, on factors such as germination percentage, average germination time, radicle and hypocotyl length, vigor index, and dormancy incubation, observed similar results in lettuce seeds [6].

In another report on investigating plant growth inhibitory activities, Salvia officinalis had 100% inhibition of lettuce radicle and hypocotyl growth [7]. In addition, investigating the activity of the essential oil and methanolic extract of E. platyloba showed very strong activity against bacteria [31]. In a study to investigate the antioxidant activity of aqueous and ethanolic extracts of S. lavandulifolia, both types of extracts showed good potential with high phenolic content [32].

The use of plants as phytochemicals has been widely seen in recent years due to the presence of chemicals and the development of cross-resistance to the lack of use of synthetic insecticides [33]. The formulations obtained from different species of the genus Nepeta with a large amount of essential oil and flavonoids showed high antimicrobial, antifungal, and insecticidal properties [34,35]. In another study on the essential oil Nepeta cataria against Spodoptera littoralis larvae, a high insecticidal activity of this plant was seen (LC₅₀) value ≤ 10.0 mL/m³) [36]. In a previously conducted study, the effect of P. graveolens has been investigated as an insecticidal property in killing larvae and preventing egg laying [37,38]. In our study, the leaf of this plant showed many inhibitory effects.

Forasmuch as Thymol, Carvacrol, P-Cymene, and 1,8-Cineole were very high in our headspace experiments, they are probably the main factor responsible for the inhibitory effects. In the report, it was shown that monoterpenes such as 1,8 cineole, thymol, geraniol, menthol, and camphor strongly inhibit the radicle growth of Z. mays L. seedlings [39]. In another study, the effects of insecticides and insect repellants of 1,8 cineole were confirmed [40,41].

Another important point in this experiment was the combination of the most inhibitory plants to check the allelopathic properties that were observed as synergistic, additive, and antagonistic effects. Before this, the synergistic effects in antibacterial and antioxidant activity of the combination of Coriandrum sativum with Cuminum cyminum essential oils was reported [42]. Also, the synergistic antimicrobial effects of volatile compounds, such as eugenol with menthol and linalool and carvacrol with thymol, have been reported [43]. In another study, the synergistic antifungal effects were shown between the essential oils of Mentha spicata with Melaleuca alternifolia and Thymus vulgaris with Cinnamomum verum and Origanum majorana [24].

5. Conclusions

Medicinal plants, especially aromatic ones, have been used in traditional medicine in Iran and have potential allelopathic activity. They are good candidates for finding new allelochemicals to be used in agriculture as bio-herbicides. Among the investigated plants, those with high inhibitory effects were introduced and could be used to control, and even destroy, weeds. In this research, the combination of the N. binaloudensis (leaf) with T. ammi (fruit) and N. binaloudensis (leaf) with L. officinalis (flower) had great synergistic effects. For more accurate investigations in the future, the interaction of the main compounds of these plants can be performed in vitro as well as in field conditions. Also, their interaction effects can provide a new field for the bioherbicide research and such effects can play a significant role in determining the effective dose of each compound. Therefore, applying these compounds in agriculture will help us to reduce the use of chemical pesticides, and ultimately contribute to the health of our community.