Measuring Allelolapathy in Plants - Research Paper Example

Measuring Allelolapathy in Plants Abstract With a view to evaluate the possible effects of allelopathy of tree of heaven (Ailanthus altissima) on a radish seed, as well as examine the possible effects of the acid rain upon and the effectiveness of the allelopathic chemicals that are secreted by the tree of heaven, samples of leaves to be used in this lab were gathered from trees on the Piedmont field station at the Environmental Studies. There were a series of lab sessions involving the use of different PH levels. For sections 202, 203, and 201 used PH of 7.0, sections 204, 205 and 206 used a PH of 5.0 with sections 207, 208, and 209 using a PH of 3.0. Using a 50 petry dishes with a layer of paper, 10 radish seeds were placed in each of the Petry dishes. 25 grams of Ailanthus altissima were placed in a blender combined with 250 ml of water and blended for a period of five minutes followed by filtering the solution that resulted through various layers of cheesecloth. 6 ml of the solution was added to 10 of the petry dishes that contains the raddish seeds. Following a series of procedures the number of seeds in each of the dishes having germinated was counted. The length of each root was measured to the nearest tenth of a cm using a ruler. After germination of the seed, the root length was counted as zero. Results indicated that the extract of A. altissima significantly inhibits germination of test species, as well as inhibit root growth. Moreover, results indicate that the pH values of the aqueous extracts affect germination rates and root growth. By and large the strength of inhibition is closely related to the concentration of the extracts and/or the pH. In conclusion, altissima significantly inhibits germination of test species, as well as inhibit root growth. It is also clear that the pH values of the aqueous extracts affect germination rates and root growth. Introduction The term allelopathy is used to refer to chemical inhibition of one species by another species (Duke et al. 2001). The inhibitory chemical is often released to the environment causing a negative effect on the growth and development of the neighboring plants (Gaudet, 2006). Allelopathic chemical can be found in parts of the plants (Feeny, 2002). The parts are flowers, leaves, stems or fruits, as well as in the soils that surround the plant (Garrity, 2003). Neighboring species may be affected by the toxins in a variety of ways. Also, the toxic chemicals can inhibit the root or shoot growth in root prevent nutrient uptake (Christensen, 2001). Hydrochemicals may also attack a symbiotic relationship hence destroy the way plants uptake their source of nutrients (Movillon, 2002). Research indicated that environmental stresses can induce allelopathic substances (Dilday, 2000). This indicates that through root exudation, volatilization, leaching and decomposition of the residues of plants, plants can release compounds into the environment. Allelopathic substances can be used economically and ecologically. For instance, in weed management, herbicides are used in controlling the growth of weeds (Garrity, 2003). Research has indicated that it is a great challenge to demonstrate how allelopathy occurs. This is attributed to the complexity in the interference of plant (Courtois, 2005). Tree of heaven is a species introduced from Asia that is commonly found growing in almost pure stands in disturbed habitats such as roadsides and urban areas. These stands often have a halo or plant free zone around them (Mallik, 2007). It has been shown that A. altissima leaves, stems and roots contain a variety of chemicals, several of which were demonstrated to be potential allelopathic compounds (Liang, 2002). In particular, the chemical ailanthone, secreted by A. altissima, inhibits germination in many plant species (Lawrence et al. 2006). Black walnut has similar effects due to the compound juglone in the leaves, bark and roots (Inderjit, 2000). Other researchers have criticized laboratory assays as unsuitable for allelopathic (Witt, 2008). We will demonstrate the potential that allelopathic plants have for inhibiting growth of other plants, at least in the short term. Acid rain is a complex of pollutants derived mostly from sulfur and nitrogen oxides resulting from the burning of high sulfur coal in electrical power plants and to a lesser extent from automobile exhaust (Gershenzon, 2004). Acid rain first became an issue in the 1970s due to notable damage to trees such as red spruce in the Northeastern United States and Northern Europe. Although somewhat mitigated by Clean Air Act, the pH of fog over Mt. Mansfield, Vermont in the summer of 1998 was 2.1-2.8. On Whiteface Mountain, New York, rain water pH ranges from 3.4 to 3.8 (Jensen, 2000). Acid rain disrupts soil biogeochemistry and causes damage and leaching of nutrients from the leaves of forest trees. Specifically, depletion of calcium from forest soils by as much as 50% over the past 45 years has been demonstrated (Jensen, 2006). Acid rain is a global problem and recent publications have outlined the growing problem of acid rain in China due to the rapid industrialization and heavy dependence on coal for energy. As much as 70% of energy production in China is based on burning coal, much of which is the high sulfur variety (Larssen et al. 2006). The potential interaction between acid rain and allelopathic agents is unknown. In this experiment we will expose radish seeds to extracts of tree of heaven leaves at different concentrations. These aqueous extracts will be created using water of three different pH values in order to examine the potential for pH to influence the effectiveness of the allelopathic chemicals from tree of heaven leaves. There are various studies so far conducted on allelopathic, however, there is limited research conducted with a view to evaluate the allelopathic effects of a plant Ailanthus altissima upon the radish seeds. More evidently, there are limited studies that sought to examine the effects of acid rain on the allelopathic chemicals effectiveness secreted by the tree of heaven. Recent studies have indicated that allelochemicals are often involved in phytoplankton-zoolankton interactions, plant-herbivore, fire ecology in the communities of Califonia annual grasslands, nutrient succession in the terrestrial cycling ecosystem, and failure or success of natural resource management strategies in forestry and agriculture. Although there are notable examples on the way inhibition of plant by another occurs, there relatively limited uncontroversial cases dealing with true allelopathy. This perhaps can be due to the fact that the process of inhibition might be as a result of direct interference competition for sunlight, sunlight or nutrients or might be occurring following other factors such as herbivore. For instance, salvia bushes that grow in the desert are often surrounded by a halo area free from other associated plants. It can be used to demonstrate allolopathy by salvia. However, research has indicated that halo is caused by the rodents that make use of slavia bushes for purposes of protection. This helps them to keep the halo area somewhat free from other plants. The current study evaluated the possible effects of allelopathic effect of tree of the plant Ailanthus altissima on radish seeds. The study also sought to examine the possible effects of the acid rain upon the effectiveness of the allelopathic chemical that are secreted by the tree of heaven. H: The hypothesis is that increasing Ailanthus altissima would reduce the germination of the radish seeds and the growth of roots. H1: The second hypothesis is that increase in PH Concentration of acidic rain causes an increases in the germination of radish seeds and decrease in the PH concentration of the acidic rain causes a reduction in the germination of radish seeds. Methods Samples of leaves to be used in this lab were gathered from trees on the Piedmont field station at the Environmental Studies. These leaves were obtained from the branches and then stored in storage bags in a freezer at the George Mason University. After which, there were a series of lab sessions involving the use of different PH levels. The sections 202, 203, and 201 used a PH of 7.0, sections 204, 205 and 206 used a PH of 5.0 with sections 207, 208, and 209 using a PH of 3.0. Using a 50 petry dishes with a layer of paper, 10 radish seeds were placed in each of the Petry dishes. 25 grams of Ailanthus altissima were placed in a blender combined with 250 ml of water and blended for a period of five minutes followed by filtering the solution that resulted through various layers of cheesecloth. 6 ml of the solution was added to 10 of the petry dishes that contains the raddish seeds. Approximately 60 ml of water of certain pH was added onto a 60 ml in the blended solution followed by 6 ml of the solution in the 10 petry dishes. 60 ml water with a certain pH level were added into the 60 ml of the 50 solution followed adding 6 ml of this given solution into the 10 petry dishes. Then 60 ml with an appropriate PH added onto 60 ml of the 25 percent solution. This constituted about 12.5% solution and about 6 ml of this solution added into the 10 Petry dishes as described above. The remaining 10 petry dishes were moistened using 6 ml of water as a control. The edges of each dishes were sealed using Parafilm™ with a view to prevent dying followed by incubating the dishes at a room temperature for a period of one week. Following this, the number of seeds in each of the dishes having germinated was counted. The length of each root was measured to the nearest tenth of a cm using a ruler. After germination of the seed, the root length was counted as zero. Results The mean number of Ailanthus altissima seeds germinated (n= 5) was least for the 100% concentration treatment at 6.4 seeds and (s.d.=2.86 seeds) after one week of incubation (Table 1). The 100% treatment yielded the shortest average length of Ailanthus altissima seeds (n=5) root growth of 1.7 cm (s.d.= 2.7755 cm) after one week, as shown in Table 1. It is also displayed Figure 1, the regression analysis indicated a significant (p=0.041) negative relationship between the concentration and Ailanthus altissima root length (t= 3.29, R2= 0.85) for treatment with pH 7. Figure 2, the regression analysis indicated a significant (p=0.01) negative relationship between the concentration and Ailanthus altissima germinated seeds (t= 5.38, R2=0.93) for treatment with pH 7. Table 1: Means and Standard Deviation for the Root length and Germinated seeds at different concentration. Root Length in mm 0% 12.50% 25% 50% 100% pH MEAN 1 3.48 4.69 2.79 2.6 0.92 7 MEAN 2 3.68 6.04 5.96 2.06 1.01 7 MEAN 3 7.31 6.04 4.41 2.15 1.19 7 MEAN 4 3.08 4.57 3.43 1.75 0.93 7 MEAN 5 3.07 4.44 3.96 2.1 0.6 7 MEAN 6 2.93 5.65 2.5 1.56 0.71 7 MEAN 7 3.9 6.3 4.97 1.56 1.07 7 MEAN 8 7.6 4.68 4.25 2.83 0.765 7 MEAN 9 4.35 5.12 4.76 2.75 1.61 7 MEAN 10 2.71 4.52 3.93 1.97 0.82 7 MEAN 11 6.175 5.84 5.63 1.82 0.6 7 MEAN 12 4.575 5.69 6.16 1.94 0.4 7 MEAN 13 3.3 7.51 4.16 1.74 0.98 7 MEAN 14 3.85 5.7 7.6 2.66 0.91 7 MEAN 15 7.06 6.07 5.75 2.28 0.72 7 MEAN 16 7.37 9.85 8.6 1.78 1.24 7 MEAN 17 8.003 4.8 6.98 1.51 0.99 7 MEAN 18 4.55 5.2 5.96 0.91 0.52 7 MEAN 19 6.392 7.65 6.09 3.2 0.54 7 MEAN 20 6.98 7.95 7.55 3.17 0.47 7 MEAN 21 4.7 4.1 3.8 2.9 1.4 7.0 MEAN 22 2.8 5.0 3.3 3.2 1.5 7.0 MEAN 23 2.9 6.2 2.5 3.3 0.6 7.0 MEAN 24 5.11 6.1 2.4 2.57 1.08 7 MEAN 25 4.42 3.75 4.12 2.15 1.78 7 MEAN 25 3.2 7.1 4.0 4.7 0.4 7.0 MEAN 27 4.7 3.7 3.1 2.8 2.1 7.0 MEAN 28 3.56 5.39 4.48 3 1.42 7 MEAN 29 2.7 4.6 3.2 2.4 0.4 7.0 MEAN 30 3.0 3.6 4.4 2.6 0.5 7.0 MEAN 31 3.1 2.3 2.7 1.5 1.8 5.0 MEAN 32 5.8 3.0 1.2 1.7 1.3 5.0 MEAN 33 5.2 3.3 2.3 2.4 1.8 5.0 MEAN 34 5.7 2.7 1.1 1.5 1.4 5.0 MEAN 35 5.6 3.1 2.3 1.6 1.6 5.0 MEAN 35 5.4 2.8 1.7 1.2 2.1 5.0 MEAN 37 4.8 2.8 2.4 1.5 1.0 5.0 MEAN 38 5.0 2.7 2.2 1.3 0.9 5.0 MEAN 39 5.3 2.1 1.8 1.8 1.7 5.0 MEAN 40 6.5 3.0 2.5 1.1 1.4 5.0 MEAN 41 11.4 2.0 8.8 11.6 8.4 5.0 MEAN 42 10.25 2.95 7.33 6.99 4.81 5 MEAN 43 10.71 2.42 7.33 8.81 5.86 5 MEAN 44 12.26 2.98 8.87 6.29 8.59 5 MEAN 45 13.15 3.99 9.83 8.37 3.13 5 MEAN 46 8.01 2.66 10.78 8.53 5.78 5 MEAN 47 15.75 2.56 8.83 9.25 4.24 5 MEAN 48 11.44 2.21 9.11 10.37 5.94 5 MEAN 49 12.2 2.47 6.82 9.86 6.9 5 MEAN 50 12.44 3.22 7.31 11.02 7.79 5 MEAN 51 2.99 3.82 9.16 6 0.2 5 MEAN 52 3.21 4.52 10.43 6.4 0.43 5 MEAN 53 4.21 3.8777778 9.97 4 0.36 5 MEAN 54 2.24 3.61 7.68 4.2 0.03 5 MEAN 55 2.97 2.45 8.42 5.1 0 5 MEAN 56 3.28 4.16 9.51 7.16 0.15 5 MEAN 57 4.14 1.92 7.7 7.6 0.2 5 MEAN 58 3.16 3.42 7.42 7.89 0.17 5 MEAN 59 2.89 3.99 9.24 6.4 0.29 5 MEAN 60 5.07 3.75 7.82 10.95 0.22 5 MEAN 61 7.2 4.3 2.9 0.9 0.2 3.0 MEAN 62 1.3 1.1 2.4 1.4 0.0 3.0 MEAN 63 1.9 1.1 2.5 2.8 0.0 3.0 MEAN 64 7.3 8.0 3.6 1.6 0.0 3.0 MEAN 65 1.2 1.0 3.0 1.7 0.0 3.0 MEAN 66 2.9 1.9 3.2 1.3 0.0 3.0 MEAN 67 2.0 2.7 2.8 1.4 0.0 3.0 MEAN 68 1.1 1.2 1.5 1.3 0.0 3.0 MEAN 69 2.7 1.0 6.4 3.7 0.0 3.0 MEAN 70 1.7 7.5 3.0 1.1 0.0 3.0 MEAN 71 6.0 4.8 3.9 7.1 0.7 3.0 MEAN 72 3.2 5.0 11.6 6.8 0.6 3.0 MEAN 73 3.7 5.0 10.8 6.0 2.6 3.0 MEAN 74 4.0 5.8 2.2 9.3 1.8 3.0 MEAN 75 4.0 5.4 9.6 3.5 0.3 3.0 MEAN 76 4.8 11.9 6.9 3.9 1.6 3.0 MEAN 77 5.1 3.7 3.7 5.8 3.9 3.0 MEAN 78 3.4 5.4 7.5 7.3 4.8 3.0 MEAN 79 5.7 9.0 3.0 6.3 2.1 3.0 MEAN 80 4.6 3.5 1.7 8.8 0.0 3.0 MEAN 81 2.8 0.8 10.1 6.8 5.0 3.0 MEAN 82 10.9 10.2 14.6 8.0 7.8 3.0 MEAN 83 8.7 10.1 8.4 6.6 6.1 3.0 MEAN 84 5.7 12.2 9.5 9.5 3.2 3.0 MEAN 85 6.9 10.3 12.2 7.4 0.6 3.0 MEAN 86 9.0 9.9 8.7 7.0 0.6 3.0 MEAN 5.5 4.9 5.9 4.4 1.7 5.0 Standard Deviation 4.5868143 3.9783233 4.6670514 4.479525 2.775502 1.632144 Means and standard Deviation for the Germinated seeds in different concentration. Number Germinated 0% 12.50% 25% 50% 100% pH Mean 1 10 9 10 10 7 7 Mean 2 9 8 9 10 8 7 Mean 3 7 9 10 8 6 7 Mean 4 9 8 9 8 8 5 Mean 5 9 8 8 10 10 5 Mean 6 10 8 9 10 7 5 Mean 7 9 7 9 6 2 3 Mean 8 10 10 6 8 5 3 Mean 8.955556 9.133333 8.833333 8.344444 6.422222 5 Standard Deviation 1.460423 0.914306 1.309001 1.342152 2.863869 1.642142 Figure 1. Figure 2 . Table 2. SUMMARY OUTPUT Regression Statistics Multiple R 0.952025 R Square 0.906351 Adjusted R Square -1.66667 Standard Error 0.576304 Observations 1 ANOVA   df SS MS F Significance F Regression 5 9.643085 1.928617 29.03441 #NUM! Residual 3 0.996378 0.332126 Total 8 10.63946         Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 65535 65535 X Variable 1 -2E-298 2.4E-298 X Variable 2 65535 65535 X Variable 3 1.8E-298 5.7E-298 X Variable 4 -7.18701 2.1795 -3.29755 0.045818 -14.1232 -0.25087 -14.1232 -0.25087 X Variable 5 1.398638 0.259567 5.388359 0.012523 0.572581 2.224694 0.572581 2.224694 y Variable 0 0.125 0.25 0.5 1 Discussion From the regression analysis, it is clear that growth length of the root of the raddish seeds and the concentration of the toxins from the altissima are strongly negatively correlated. It is clear that the growth in root length is significantly affected by the concentration of toxins from the altissima (R2=0.93), P= p=0.001). As the concentration of the toxins produced by altissima increases, the rate of root length reduces significantly. It is observed that raddish seeds growth in root length is highest at lowest concentration. However, the highest germination percentages were noted in a condition of distilled water and at low toxin concentration. Toxin concentration significantly caused a significant impact on the rate of growth in root length decreasing with the increasing concentration. At higher concentration, the rate of increase in root length in the raddish seeds was significantly lower relative to lower concentration. It is worth noting that seeds tend to recover, following their transfer from the concentrated environment to the distilled water. Final recovery percentages of germination in higher concentration treatments were found to be significantly higher as compared to the none-concentrated controls. This indicates that the exposure of the seeds to higher concentration tend to permanently inhibit root growth. It is also clear that the pH values of the aqueous extracts affect root growth. It was also observed that there was a strong correlation between concentration of toxins from the altissima and germination. Statistically, it is observed that root growth is significantly affected by the concentration of altissima (R2=0.93), p=0.001). However, the highest rate of germination was noted in a condition of low concentration. Concentration significantly roots growth with the rate of root growth decreasing with the increasing concentration. At higher concentration, the root growth rate was significantly lower relative to lower concentration. Notably, seeds tend to recover well in terms of root growth, following their transfer from the altissima concentrated environment to the distilled water. A final recovery percentage of root growth rates were found to be significantly higher as compared to the none-concentrated controls. It is clear that altissima significantly inhibits germination of test species, as well as inhibit root growth. Moreover, pH values of the aqueous extracts significantly affect germination rates and root growth. These results are in tandem with the findings of Fay and (2005), in which the effect of the allelopathic in plants was tested using the Avena germplasm. Avena germplasm adversely affects the ability of the growth of celery seed and for those seeds that sprouts seem not to do so at a lower rate (Fay, 2005). From this findings Fay concluded that allelopathic effect in plants is significance impact. While conducting a research on the biological control of some paddy weeds using allelopathy, Fujii (2004) found out that certain species of rice varieties pose an allelopathic impact on root growth and, therefore, the overall growth of other varieties of rice species. These findings are in conformity with the findings of this study in which altissima was found to inhibit the rate of growth of root in the raddish plants. Allelopathic crops can be used for purposes of inhibiting germination of certain weeds, and therefore, in controlling weeds (Duke et al. 2001). Another study carried out a study with a view to ascertain the allelopathic effects of plants (Witt, 2008). In this study, Witt sought to investigate the growth of the celery in the absence or presence of the garlic volatiles. Witts findings were that garlic volatiles affect the ability of the seeds of celery to grow. In support of Witt’s findings Inderjit used broccoli along with the celery (Inderjit, 2000). In this study, Inderjit found out that broccoli adversely affects the ability of celery to grow and mature. Clearly, it is undisputed fact the tree of heaven is one of the allelopathic plants, which characteristically produce chemical substances that are harmful to other plants. Evidently, the tree of heaven contains toxins in its leaves and in the event that these leaves fall, the toxins released can leach through the soil, and can end up being absorbed by other plants nearby. This way, they can lead to poor germination, and reduced root growth among other effects. However, one thing to content with is that, the effects of allelopathic plants upon other plants can be explored for economic gains. The effects of allelopathic plants can be used in weed control (Movillon, 2002). Conclusively, from the findings of this study, the growth length of the root of the raddish seeds and the concentration of the toxins from the altissima are strongly negatively correlated. Certainly, the growth in root length is significantly affected by the concentration of toxins from the altissima. Moreover, as observed in this study, there was a strong correlation between concentration of toxins from the altissima and germination and it is can be said with 95 percent confidence that root growth is significantly affected by the concentration of altissima. References Courtois, O. (2005). Incorporating the allelopathy trait in upland rice breeding programs. In Olofsdotter, M. ed. Allelopathy in Rice. Manila, Philippines: Int. Rice Research Institute. 2005. pp. 57-68. Christensen, S. (2001). Weed suppression in cereal varieties. London: john and Sons. Denmark. Dilday, R.H. (2000). Allelopathic activity in rice (Oryza sativa L.) against ducksalad (Heteranthera limosa (sw.) Willd.). In D. Hanson, M.J. Shaffer. D.A. Ball. and C.V. Cole., eds. Symposium Proc. on Sustainable Agriculture for the Great Plains. USDA, ARS-89, pp. 193-201. Dayan, R. (2004). Investigating the mode of action of natural phytotoxins. J. of Chem. Ecol. 2000: 2079-2094. Duke et al. (2001). Strategies for using transgenes to produce allelopathic crops. Weed Tech.2001:15: 826-834. Fay, D. (2005). An assessment of allelopathic potential in Avena germplasm. Weed Sci. 2005; 25: 224-228. Fujii, Y. (2004). The potential biological control of paddy weeds with allelopathy: allelopathic effect of some rice varieties. In Proc. Int. Symposium on Biological Control and Integrated Management of Paddy and Aquatic Weeds in Asia. Tsukuba, Japan. National Agricultural Research Center. pp. 305-320. Garrity, M. (2003). Allelopathic potential of wild rice Oryza perennis. Taiwania: 36 (3) 201-210. Gaudet, K. (2006). Population Biology of Plants. New York: Oxford Publishers. Gershenzon, C. (2004). Identification of an allelopathic compound from Alianthus altissima (Simaroubaceae) and characterization of its herbicidal activity. Amer. J. of Botany.193-200. Inderjit, D. (2001). On laboratory bioassays in allelopathy. Bot. Rev. 29- 44. Inderjit. F. (2004). Plant phenolics in allelopathy. Bot. Rev;186-202. Inderjit, L. (2000). Are laboratory bioassays for allelopathy suitable for prediction of field responses? J. of Chemical Ecology 2000: 2111-2118. Inderjit. K. (2000). Plant phenolics in the allelopathy. Bot. Rev.2000: 186-202 Liang, G. (2002). Allelopathic and herbicidal effects of extracts from tree of heaven (Alianthus altissima). Amer. J. of Botany.77: 662-670. Jensen, C. (2000). Acid rain impacts on calcium nutrition and forest health. Bioscience 2001: 49: 789-800. Larssen et al. (2006). Acid rain in China. Environmental Science and Technology: 40: 418-425. Colwell, S. (2005). The ecological impact of allelopathy in Ailanthus altissima. Amer. J. of Bot.78: 948-58. Movillon, B. (2002). Allelopathy, Koch’s postulates, and the neck riddle. 2002. Pp. 143-162. Mallik, A. (2007). Challenges and opportunities in allelopathy research: brief overview. J. of Chem. Ecol. 26: 2007-2110. Feeny, N. (2002). Allelochemics: chemical interactions between species. Science 171: 757‑770. Witt, J. (2008). Effect of allelopathy in plants. New York: Oxford publishers. Read More