پیوندهای مفید
اخبار و اعلانات
آمار
| تعداد نشریات | 158 |
| تعداد شماره‌ها | 6,230 |
| تعداد مقالات | 67,757 |
| تعداد مشاهده مقاله | 115,114,704 |
| تعداد دریافت فایل اصل مقاله | 89,881,164 |
پیش‌بینی فعالیت آنزیمی خاک در طول یک ترانسکت با استفاده از برخی ویژگیهای خاک(مطالعه موردی: شهرستان میامی، استان سمنان) | ||
| تحقیقات آب و خاک ایران | ||
| مقاله 8، دوره 50، شماره 10، اسفند 1398، صفحه 2487-2497 اصل مقاله (684.4 K) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22059/ijswr.2019.272348.668082 | ||
| نویسندگان | ||
| احمد اخیانی1؛ حمید رضا متین فر* 2؛ هادی اسدی رحمانی3 | ||
| 1دانشجویی دکتری شیمی و حاصلخیزی خاک گروه مهندسی علوم خاک دانشکده کشاورزی دانشگاه لرستان، خرم آباد، ایران | ||
| 2مدیر گروه مهندسی علوم خاک دانشکده کشاورزی دانشگاه لرستان، خرم آبد، ایران | ||
| 3رییس بخش بیولوژی موسسه تحقیقات خاک و آب، کرج، ایران | ||
| چکیده | ||
| کیفیت خاک بیانگر توانایی خاک در ارائه خدمات زیستی، اکولوژیکی و قابلیت تولید است. تعیین شاخص‌های کیفیت خاک و بیان کیفیت خاک نیازمند اندازه‌گیری تعداد زیادی از خصوصیات خاک است. امروزه فعالیت‌های آنزیمی خاک به عنوان یک شاخص مناسب جهت ارزیابی اثرات عوامل محیطی و مدیریتی بر کیفیت خاک شناخته شدهاند. هدف از این تحقیق توسعه مدلهای رگرسیونی بین فعالیت‌های آنزیمی و ویژگیهای خاک در طول یک ترانسکت از جهت شمال به جنوب میباشد. برای این منظور از سه منطقه شهرستان میامی استان سمنان، 120 نمونه خاک با روش تصادفی طبقه‌بندی‌شده انتخاب شد. خصوصیات خاک و مقادیر آنزیمها طبق روش‌های استاندارد تعیین شد. روابط موجود بین ویژگیهای خاک و فعالیت سه آنزیم بتاگلوکوزیداز، فسفاتاز قلیایی و اورهآز با استفاده از روش رگرسیون خطی ((OLS مدلسازی شد. نتایج نشان داد، به‌طورکلی فعالیت‌های آنزیمی از جنوب به شمال شهرستان افزایش یافته و آنزیم بتاگلوکوزیداز دارای بیشترین ضریبتغییرات (68%) بوده است. مدلهای رگرسیونی ارائه‌شده با دقتی (R2adj) در دامنه 7/50% تا 4/70% توانستند فعالیت آنزیمی خاک را پیش‌بینی کنند. مهمترین ویژگیهای خاک مؤثر بر فعالیت آنزیمی در مناطق شمالی به ترتیب اولویت کربن آلی، بافت، ظرفیت تبادل کاتیونی، فسفر و پتاسیم و در مناطق جنوبی کربن آلی، هدایت الکتریکی و pHبودند. بررسیهای اعتبارسنجی مدلها هم در مرحله صحتسنجی(RMSE, R2adj) نشان داد درجه تخمین مدلها از اعتبار کافی برخوردار است. نتایج این تحقیق در بهبود برنامهریزیهای مدیریتی جهت مدیریت پایدار خاک کاربرد دارد. | ||
| کلیدواژه‌ها | ||
| آنزیم؛ ویژگیهای خاک؛ ترانسکت؛ مدل پیش بینی | ||
| عنوان مقاله [English] | ||
| Prediction of Soil Enzyme Activity Along the Transect Using Some Soil Characteristics (Case Study: Miami County in Semnan Province) | ||
| نویسندگان [English] | ||
| Ahmad Akhyani1؛ hamid reza Matinfar2؛ hadi asadi rahmani3 | ||
| 1The phd student of soi chimestry and fertility in soil science agricutural faculty of lorestan university, khoram abad, Iran | ||
| 2The head of soil science department of agricultural faculty of lorestan university, khoram abad, iran | ||
| 3The head of soil biology department og soil and water research institute, Karaj, Iran | ||
| چکیده [English] | ||
| Soil quality indicates soil ability to provide biological, ecological and production services. Determination of soil quality indices requires a large number of soil characteristics measurements. Soil enzyme activities have been recognized as suitable indicators in assessing the effect of management and environmental factors on soil quality. This study has been implemented to develop a regression model between soil enzyme activities and soil characteristics along the north-south transection in Miamicounting. For this purpose, 120 soil sampleswereselected from the top layer (30 cm) at three different sites using the standardized classification method. Soil properties and activity of enzymes were determined according to standard methods and also, applying linear regression method of ordinary least square, the relationship between soil properties and three soil enzymes included in b-glucosidase, urease and alkaline phosphatase was modeled. The results showed, overall all soil enzyme activity decreased from north to south and b-glucosidaseenzyme had the highest coefficient of variation (%68). The models provided with accuracy (R2adj) about %50.4 to %70.4 are able to predict the soil enzymes activity. The most important soil properties effective on enzyme activity in the northern region included respectively, total organic carbon, soil texture, cation exchange capacity, Phosphorus and potassium available but in the southern region, total organic carbon, salinity, PH. The results of validation (RMSE, R2adj)ascertained that the predictors were sufficiently accurate. The results of this study used in the improvement of regional planning for sustainable management of soil. | ||
| کلیدواژه‌ها [English] | ||
| Enzyme, Soil properties, Transects, Prediction models | ||
| مراجع | ||
|
Abasian, A., Golchin, A. and Sheklabadi, M. (2014) Influence of soil type and sampling depth on soil biological properties and enzymatic activities. Journal of Soil Biology. 2(2): 11-124. (In Farsi) Bardgett, R. D. and vanderPutten, W. H. (2014) Belowground biodiversity and ecosystem functioning. Nature, 515: 505–511. Blake, G. R. and Hart age, K. H. (1986) Bulk density. In: Klute, A. (Ed.), Methods of Soil Analysis. Part1: physical and Mineralogical Methods, 2nd ed. Agronomy Monograph. 9: 363–382. Creamer, R.E., Hannula, S.E., Leeuwen, J.P.V., Stone, D., Rutgers, M.,Schmelz, R.M. et al. (2016) Ecological network analysis reveals theinter-connection between soil biodiversity and ecosystem function asaffected by land use across Europe. Applied Soil Ecology, 97: 112–124. Hashemi, M., Gholamalizadeh Ahangar, M., Bameri, A., Sarani, F. and Hejazizadeh, A. (2016) Survey and Zoning of Soil Physical and Chemical Properties Using Geostatistical Methods in GIS (Case Study: Miankangi Region in Sistan). Journal of Water and Soil. 30(2):443-458. (In Farsi) Hendriksen, B.N., Creamer, R.E., Stone, D., Winding, A. (2015) Soil exo-enzymeactivities across Europe—the influence of climate, land-use and soil properties. Applied Soil Ecology 97: 44–48. Hoseini, M. A., Haghnia, G.H., Lakzian, A. and Emami, H. (2012) The influence of barley (Hordeum vulgare L.) residue managements on the β-glucosidase activity in soil. Journal of Agroecology.4(1): 74-82. (In Farsi) Jenkinson, D. S., Brookes, P. C. and Powelson, D. S. (2004) Measuring soil microbial biomass. Journal of Soil Biology and Biochemistry. 36: 5-7. Kandeler, E., Eder, G. and Sobotik, M. (1994) Microbial biomass, N mineralization, and the activities of various enzymes in relation to nitrate leaching and root distribution in a slurry-amended grassland. Journal of Biology and Fertility of Soils. 18: 7–12. Kemper, W. D. and Rosenau, R. C. (1986) Aggregate stability and size distribution. In: Klute A (ed). Methods of Soil Analysis. Soil Science Society of America, Madison, WI: 425–442. Li, Q., Liang, J.H., He, Y.Y., Hu, Q.J., Yu, S.(2014) Effect of land use on soil enzyme activities at karst area in Nanchuan, Chongqing, Southwest China. Plant Soil Environ. 1: 15–20. Li, W., Liu, T., Jiang, M., Wu, CY., Chen, M., Ma, X. F. and Li, X. Y. (2017) Changes in soil aggregate- associated enzyme activities and nutrients under long-term chemical fertilizer applications in a phosphorus-limited paddy soil. Soil Use Manage. 33(1):25–33. Liu, X. M., Li, Q., Liang, W. J. and Jiang, Y. (2008) Distribution of soil enzyme activities andmicrobial biomass along a latitudinal gradient in farmlands of Songliao plain,northeast China. Pedosphere Journal. 18: 431-440. Moscatelli M. C., Lagomarsino, A., De Angelis, O. and Grego, S. (2005) Seasonality of soil biologicalproperties in a poplar plantation growing under elevated atmospheric CO2. Apply Soil Ecology, 30:162–173. Olsen, S. R. and Sommers, L. (1982). Phosophorus. In: AL. Page: Methods of soil analysis, Agron. No. 9, Part2: Chemical and microbiological properties, (ed.) American Society Agronomy, Madison, WI, USA. 403-430. Page, A. L., Miller, R. H and. Keeney, D. R. (1982) Methods of Soil Analysis, part2, chemical and microbiological properties. American Society of Agronomy,Inc. Soil Science Society of America, Madison, WI. Paz-Ferreiro, J., Gascó, G., Gutiérrez, B. and Méndez, A. (2012) Soil biochemical activities and the geometric mean of soil enzyme activities after application of sewage sludge and sewage sludge biochar to soil. Biology and Fertility of Soils. 48: 511–517. Paz-Ferreiro, J., Trasar-Cepeda, C., Leirós, M. C., Seoane, S. and Gil-Sotres, F. (2011) Intra-annual variation in biochemical properties and the biochemical equilibrium of different grassland soils under contrasting management and climate. Biology and Fertility of Soil, 47: 633–645. Paz-Ferreiro. J., Trasar-Cepeda, C., Leirós, M. C., Seoane, S. and Gil-Sotres, F. (2010) Effect of management and climate on biochemical properties of grassland soils from Galicia (NW Spain). European Journal of Soil Biology. 46: 101–108. Philippot, L., Spor, A., Henault, C., Bru, D., Bizouard, F. and Jones, C.M. (2013) Loss in microbial diversity affects nitrogen cycling in soil. ISME Journal. 7: 1609–1619. Reed, H. E. and Martiny, J. B. H. (2007) Testing the functional significance of microbial composition in natural communities. FEMS Microbiology Ecology. 62: 161–170. Rutgers, M., Wouterse, M., Drost, S. M., Breure, A. M., Mulder, C., Stone, D., et al. (2016) Monitoring soil bacteria with community-level physiological profiles using Biolog ECO-plates in the Netherlands and Europe. Appl. Soil Ecol. 97: 23–35. Sarikhani, M. R., Chalabianlu, N. and Alavikia, S. S. (2016) Distribution of Phosphate Solubilizing Bacteria and Soil Phosphatase Activity in Different Land Uses. Journal of Water and Soil . 29(6): 1662-1673. (In Farsi) Sinsabaugh, R. L., Zak, D. R., Gallo, M., Lauber, C. and Amonette, R. (2004) Nitrogendeposition and dissolved organic carbon production in northern temperateforests. Soil Biology and Biochemistry. 36: 1509–1515. Tabatabai, M. A. (1994) Method of Soil analysis. Part2_Microbiological and Biochemical Properties. SSSA Book, Series No.5. Soil Science Society America, Madison, WI: 775-803. Tajik, S., Ayoubi, Sh. and Nourbakhash, F. (2012) Prediction Soil Enzyme Activity by the Use of Soil and Topographic Characteristics in Hilly Region of Semiroum District, Isfahan Province. Journal of Water and Soil. 26(3): 753-761.(In Farsi) Vasconcellos, R.L., Segat, J.C., Bonfim, J. A., Baretta, D. and Cardoso, E.J. (2013) Soilmacrofauna as an indicator of soil quality in an undisturbed riparian forest andrecovering sites of different ages. Eur. J. Soil Biol. 58: 105–112. Waring, B. G.,Weintraub, S. R. and Sinsabaugh, R. L. (2014) Ecoenzymatic stoichiometry of microbial nutrient acquisition in tropical soils. Biogeochemistry. 117: 101-113. Wilding, L. P. (1985) Spatial variability: Its documentation, accommodation, and implication to soil survey. Pp. 166-194. In: Nielsen DR, and Bouma J (eds.). Soil Spatial Variability, Wagenigen, the Netherlands. Xiao-Chang, W. and Qin, L. (2006) Beta-glucosidase activity in paddy soils of the Taihu lake region, China. Pedosphere, 16: 118-124. Xu, Z., Yu, G., Zhang, X., He, N., Wang, Q., Wang, S., Wang, R., zhao, N., Jia, Y. and Wang, C. (2017) Soil enzyme activity and stoichiometry in forest ecosystems along the North-South Transect in eastern China (NSTEC). Soil Biology and Biochemistry, 104: 152–163. | ||
|
آمار تعداد مشاهده مقاله: 380 تعداد دریافت فایل اصل مقاله: 275 |
||