پیش‌بینی فعالیت آنزیمی خاک در طول یک ترانسکت با استفاده از برخی ویژگی‌های خاک(مطالعه موردی: شهرستان میامی، استان سمنان)

نوع مقاله: مقاله پژوهشی

نویسندگان

1 دانشجویی دکتری شیمی و حاصلخیزی خاک گروه مهندسی علوم خاک دانشکده کشاورزی دانشگاه لرستان، خرم آباد، ایران

2 مدیر گروه مهندسی علوم خاک دانشکده کشاورزی دانشگاه لرستان، خرم آبد، ایران

3 رییس 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


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 Akhyani 1
  • hamid reza Matinfar 2
  • hadi asadi rahmani 3
1 The phd student of soi chimestry and fertility in soil science agricutural faculty of lorestan university, khoram abad, Iran
2 The head of soil science department of agricultural faculty of lorestan university, khoram abad, iran
3 The 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
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