دوماه نامه

نوع مقاله : مقالات پژوهشی

نویسندگان

دانشگاه ارومیه

چکیده

یکی از ویژگی‌های مهم در ارزیابی جمعیت فعال میکروبی خاک تنفس ناشی از بستره (SIR) می‌باشد. این مطالعه با هدف بررسی تأثیر منبع کربن (گلوکز)، دما و دوره خواباندن در تنفس ناشی از بستره در دو خاک جنگلی و کشاورزی با استفاده از روش سطح پاسخ و بر مبنای طرح مرکب مرکزی انجام شد. بدین منظور دامنه‌های متفاوتی از این سه متغیر شامل مقدار گلوکز (10-5/0 میلی‌گرم در گرم)، زمان خواباندن (10-1 ساعت) و دما (30-15 درجه سلسیوس) در نظر گرفته شده و طرح مرکب مرکزی با 40 آزمایش برای دو خاک و بر اساس مقادیر کدبندی شده متغیرهای مستقل طراحی شد. نتایج نشان داد که میانگین مقدار SIR خاک جنگلی به دلیل دارا بودن ماده آلی بیشتر و جمعیت فعال میکروبی بالاتر تقریباً دو برابر خاک کشاورزی است. نتایج بیانگر کارآمدی مدل طراحی شده برای پیش‌بینی مقدار تنفس ناشی از بستره در دو خاک کشاورزی (919/0 =R2) و جنگلی ( 823/0 =R2) بود. از بین سه متغیر مورد بررسی در مدل طرح مرکب مرکزی، تاثیر خطی دما بر تنفس ناشی از بستره در هر دو خاک معنی‌دار بود. با این حال در خاک جنگلی مقدار بستره (گلوکز) تأثیر بسیار معنی‌دار و به مراتب بیشتری در مقایسه با خاک زراعی داشت که می‌تواند به دلیل بیشتر بودن مواد آلی قابل تجزیه در این خاک باشد.

کلیدواژه‌ها

عنوان مقاله [English]

Mathematical Modeling and Comparison of the Substrate Induced on Forest and Agricultural Soils

نویسندگان [English]

  • mohsen barin
  • Ehsan Ehsan-Malahat
  • Farrokh Asadzadeh

urmia university

چکیده [English]

Introduction: Soil is a complex and dynamic biological system, and it still is difficult to determine the composition of microbial communities in soil. Most soil microorganisms are dormant, so their rate of respiration is low. However, their respiration can be stimulated by adding an easily decomposable substrate. Also, by adding a simple organic matter, respiration may rapidly increase to a maximum and remains at a constant rate for more than 4 h. Glucose is commonly used as a substrate because most soil microorganisms can readily utilize it as a carbon source. The substrate-induced respiration (SIR) method was modified and adapted to measure fungal, bacterial and total microbial contributions to glucose-induced respiration and the potentially active microbial biomass on decaying plant residues of different composition. Decomposing residues from natural and agricultural ecosystems were chopped and sieved to include the >1 mm fraction for routine SIR analyses on a continuous flow-through respiration system. Substrate induced respiration is a main factor for the assessment of the soil microbial activity. This technique is already used widely in soil microbial studies. Different factors such as the source of carbon, temperature and incubation may play a significant role in the amount of SIR. Therefore, optimizing the test conditions is one of the important criteria for SIR determination. For this purpose, statistical methods such as central composite design (CCD) and response surface method can be used as a useful tool for determining optimal conditions. This study was carried out to model and compare the effect of carbon source (glucose), temperature and incubation time on the SIR of forest and agricultural soils.
Materials and Methods: In this research, 40 experiments were conducted for two soil types including agricultural soil (with relatively low organic matter content) and forest soil (with relatively high organic matter content). Soil samples were collected from the topsoil (0-20 cm) layer. In the laboratory, all visible roots were removed and the soil samples were divided into two parts. One part was kept in plastic bottles at 4°C for SIR analysis. And the rest was air dried in the shade at laboratory temperature for chemical and physical analysis. Electrical conductivity (EC) and pH were determined in saturated soil extract and organic carbon persent (%OC) was determined by di-chromate oxidation. Soil texture was determined using a Bouyoucos hydrometer in a soil suspension. Response surface methodology based on the central composite design was applied in modeling procedure. Different ranges of the independent variables including glucose (0.5-10 mg g-1), incubation time (1-10 hr), and temperature (15-30˚C) were used in central composite design experiments. Totally, 40 experiments based on the coded values of the independent variables were conducted for two soils.
Results and Discussion: Experimental results indicated that the SIR in forest soil is two times greater than the agricultural soil, which may be related to the higher organic matter content and more microbial activity in this soil. Results also revealed the efficiency of the central composite design in predicting the SIR of forest (R2= 0.823) and agricultural (R2=0.919) soils. Among the three independent variables, the linear effect of temperature on the SIR were significant for both soils. However, the substrate (glucose) content has more significant effect in forest soil in comparison with agricultural soil which may be associated with the higher decomposable organic matter content of the forest soil. Glucose enhancement didn’t have significant effect on SIR alteration rate which can be attributed to low organic matter content in agricultural soil. Totally, with increasing time and temperature, the amount of SIR was significantly increased, however with increasing glucose, SIR amount was not significantly increased especially in the agricultural soil. In the forest soil, the process of SIR changes is clearly distinct in response to independent variables compared to agricultural soil. Maximum levels of the SIR in forest soil is clearly associated to the highest time and glucose levels. This indicates that increasing glucose and sufficient time in the forest soil, which contains high amounts of digestible organic matter, can stimulate microorganisms to decompose more organic matter and it outcome is increasing SIR.
Conclusion: This study indicated the high efficiency of response surface methodology in SIR modeling for both forest and agricultural soils. However, the quantitative amounts of SIR were very different in two soils. The amounts of SIR in the forest soil were almost twice relative to agricultural soil. In the forest soil, the amounts of glucose and temperature were as the main variables in increasing SIR, while the temperature and time variables were more determinant in agricultural soil on it.

کلیدواژه‌ها [English]

  • Microbial community
  • Response surface
  • Soil quality
  • Soil respiration
1- Aghaeinejad-Meybodi A., Ebadi A., Shafiei S., Khataee A., and Rostampour M. 2015. Degradation of antidepressant drug fluoxetine in aqueous media by ozone/H2O2 system: process optimization using central composite design. Environmental technology, 36(12):1477-88.
2- Anderson T.H., and Domsch K.H. 1990. Application of eco-physiological quotients (qCO 2 and qD) on microbial biomasses from soils of different cropping histories. Soil Biology and Biochemistry, 22(2):251-255.
3- Beare M.H., Neely C.L., Coleman D.C., and Hargrove W.L. 1990. A substrate-induced respiration (SIR) method for measurement of fungal and bacterial biomass on plant residues. Soil Biology and Biochemistry. 22: 585-594.
4- Beheshti A., Raiesi F., and Golchin A. 2011. The Effects of Land Use Conversion from Pasturelands to Croplands on Soil Microbiological and Biochemical Indicators. Journal of Water and Soil, 25(3): 548-562. (In Persian with English abstract)
5- Bossio D.A., Scow K.M., Gunapala N., and Graham K.J. 1998. Determinants of soil microbial communities: effects of agricultural management, season, and soil type on phospholipids fatty acid profiles. Microbial Ecology, 36(1):1-12.
6- Bradford M.A., Davies C.A., Frey S.D., Maddox T.R., Melillo J.M., Mohan J.E., Reynolds J.F., Treseder K.K., and Wallenstein M.D. 2008. Thermal adaptation of soil microbial respiration to elevated temperature. Ecology Letters, (12):1316-1327.
7- Campbell C.A., Lafond G.P., Biederbeck V.O., Wen G., Schoenau J., and Hahn D. 1999. Seasonal trends in soil biochemical attributes: effects of crop management on a Black Chernozem. Canadian Journal of Soil Science, 79(1):85-97.
8- Carter M.R., and Gregorich E.G. 2008. Soil Sampling and Methods of Analysis (2nd ed). CRC Press. Boca Raton, FL. P.1204.
9- Cooper V.S., Bennett A.F., and Lenski R.E. 2001. Evolution of thermal dependence of growth rate of Escherichia coli populations during 20,000 generations in a constant environment. Evolution, 55(5):889-896.
10- Dick R.P. 1994. Soil enzyme activities as indicators of soil quality. Defining soil quality for a sustainable environment. PP:107-124.
11- Doran J.W., and Parkin T.B. 1994. Defining and assessing soil quality, In: Defining soil quality for a sustainable Environment, edited by Doran, j W., DC. Coleman, DF. Bezdicek, and B.A. Stewart, soil sci, soc. Am. Special publication, NO.35, Madison, Wisconsin, USA. Pp: 3-21.
12- Doran J.W., Coleman D.C., Bezdicek, D.F., and Stewart B.A. 1994. Defining Soil Quality for a Sustainable Environment. SSSA Special Publication No. 35, Soil Science Society of America, Inc. and the American Society of Agronomy, Inc. Madison, WI
13- Ebrahimzad S.A., Aliasgharzad N., and Najafi N. 2013. Impressionability of Some Soil Ecophysilogical Indices by land Use Changes in Suldoz Plain (Naqadeh, West Azarbaijan). Agricultural science and sustainable production, 23:41-56. (In Persian with English abstract)
14- Gee G.W., and Bauder J.W. 1986. Particle-size analysis. Methods of soil analysis: Part 1—Physical and mineralogical methods. PP: 383-411.
15- Haynes R.J. 2005. Labile organic matter fractions as central components of the quality of agricultural soils: an overview. Advances in agronomy, 85:221-68.
16- Horwath W.R., and Paul E.A. 1994. Microbial Biomass. In: Weaver RW, Angle JS, Bottomley PS (eds) Methods of soil analysis, part 2. Microbiological and biochemical properties. SSSA Book Series No. 5. Soil Science Society of America, Madison, WI, pp 753–773.
17- Kirschbaum M.U. 2004. Soil respiration under prolonged soil warming: are rate reductions caused by acclimation or substrate loss?. Global Change Biology, 10(11):1870-1877.
18- Lamoochi R., and Safahieh A. 2014. Effect of environmental factors of temperature, salinity and level of heavy metal lead on growth of lead resistant bacterium isolated from Persian Gulf sediments. Journal of Aquatic Ecology. 2014; 3 (4):60-51. (In Persian with English abstract)
19- McLean, E.O. 1982. Soil pH and lime requirement. In: Methods of soil analysis, edited by Page, A. L., Part 2. Chemical and microbiological properties, Madison, Wisconsin, USA. 199-224.
20- Melillo J.M., Steudler P.A., Aber J.D., Newkirk K., Lux H., Bowles F.P., Catricala C., Magill A., Ahrens T., and Morrisseau S. 2002. Soil warming and carbon-cycle feedbacks to the climate system. Science, 298(5601):2173-2176.
21- Mousavi S.M., Niaei A., Salari D., Panahi P.N., and Samandari M. 2013. Modelling and optimization of Mn/activate carbon nanocatalysts for NO reduction: comparison of RSM and ANN techniques. Environmental Technology, 34(11):1377-1384.
22- Myers R.H., and Montgomery D.C. 2002. Response Surface Methodology: Process and Product Optimization using Designed Experiments, (2end ed.), John Wiley and Sons, UK.
23- Nannipieri P., Ascher J., Ceccherini M., Landi L., Pietramellara G., and Renella G. 2003. Microbial diversity and soil functions. European Journal of Soil Science, 54(4):655-670.
24- Nelson D.W., and Sommers L. 1982. Total carbon, organic carbon, and organic matter. Methods of soil analysis. Part 2. Chemical and microbiological properties, Pp:539-579.
25- Padmavathi T. 2015. Optimization of phosphate solubilization by Aspergillus niger using plackett-burman and response surface methodology. Journal of Soil Science and Plant Nutrition, 15(3):781-93.
26- Pratt P.F., and Chapman H.D. 1961. Methods of Analysis for Soils, Plants and Water. Univerisity of California.
27- Raiesi F., and Asadi E. 2006. Soil microbial activity and litter turnover in native grazed and ungrazed rangelands in a semiarid ecosystem. Biology and Fertility of Soils, 43(1):76-82.
28- Rajendran A., Meikandhan T., and Viruthagiri T. 2007. Statistical evaluation of medium components by Plackett- Burman experimental design and kinetic modeling of lipase production by Pseudomonas fluorescens. Indian Journal of Biotechnology, 6: 469- 478.
29- Rasouli-Sadaghiani M.H., Karimi S., Khodaverdiloo H., Barin M., and Banj-Shafiei A. 2016. Impact of forest ecosystem land use on soil physico-chemical and biological indices. Iranian Journal of Forest, 8(2): 167-178. (In Persian with English abstract)
30- Sharifi Z., and Safari Sinegani A.A. 2015. Interactions between Soil Organisms and Global Climate Change and Application of Meta-Analysis in its Interpretation: A Systematic Review, Journal of Human and Environment. 13(3): 43-66. (In Persian with English abstract)
31- Sheklabadi M., Khademi H., Karimian Eghbal M., and Nourbaksh F. 2007. Effects of Climate and Long-Term Grazing Exclusion on Selected Soil Biological Quality Indicators in Rangelands of Central Zagros. Journal of Science and Technology of Agriculture and Natural Resources, 11(41):103-116. (In Persian with English abstract)
32- Swetha S., Varma A., and Padmavathi T. 2014. Statistical evaluation of the medium components for the production of high biomass, a-amylase and protease enzymes by Piriformospora indica using Plackett–Burman experimental design. Biotechnology, 4: 439–445.
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