مقایسه روش‌های آماری حداقل مربعات جزیی و رگرسیون مولفه اصلی در برآورد مقادیر گچ، کربنات‌ها و ماده آلی خاک با استفاده از طیف‌سنجی مرئی و مادون قرمز نزدیک

نوع مقاله : علمی - پژوهشی

نویسندگان

1 دانشکده کشاورزی، دانشگاه لرستان و مربی گروه کشاورزی، دانشگاه پیام نور

2 دانشکده کشاورزی، دانشگاه لرستان

3 دانشکده کشاورزی، دانشگاه باهنر

4 دانشکده کشاورزی و منابع طبیعی، دانشگاه اردکان

5 دانشکده کشاورزی،دانشگاه صنعتی اصفهان

چکیده

داده‌های طیفی محدوده مرئی – مادون قرمز که با حداقل هزینه و صرف وقت تهیه می‌شوند، کاربرد وسیعی در برآورد خصوصیات فیزیکی و شیمیایی خاک دارند. مطالعه حاضر، با هدف بررسی توانایی این روش در برآورد مقدار ماده آلی، کربنا‌ت‌ها و درصد گچ سطح خاک صورت پذیرفته است. بر اساس تکنیک ‌هایپرکیوب، محل 115 پروفیل شناسایی  و سپس نمونه‌برداری از افق‌های خاک انجام گرفت و مقدار ماده آلی، درصد گچ و آهک خاک نیز با رو‌ش‌های استاندارد اندازه‌گیری شد. آنالیز طیفی خاک افق‌‌های سطحی مورد نظر با استفاده از دستگاه طیف‌سنج زمینی با دامنه طول موج 400-2500 نانومتر انجام شد(115 نمونه سطحی). پس از ثبت طیف‌ها، انواع روش‌های پیش‌پردازش، مورد ارزیابی قرار گرفت و سپس از رگرسیون حداقل مربعات جزئی (Partial Least Square Regression) و رگرسیون مولفه اصلی((PCR، برای پیش‌بینی پارامترهای مورد نظر استفاده شد. جهت ارزیابی مدل،  80 درصد داده‌ها برای کالیبراسیون مدل و 20 درصد برای صحت‌سنجی مدل، به صورت تصادفی انتخاب شدند. پیش‌پردازش‌های مختلف از جمله مشتق اول و دوم، به همراه فیلتر ساواتزکی و گلای، متغیر نرمال استاندارد و تصحیح پخشیده چندگانه با هم مقایسه شدند. نتایج ‌این بررسی نشان داد بهترین نتایج مدل‌سازی، مربوط به روش PLSR با پیش‌پردازش مشتق اول+فیلتر ساویتزکی و گلای برای برآورد گچ، کربنات و ماده آلی خاک است. با توجه به مقادیر درصد انحراف نسبی(RPD)، پیش‌بینی مدل، برای درصد گچ  و ماده آلی در کلاس خوب و برای کربنات‌ها در کلاس ضعیف است.

کلیدواژه‌ها

عنوان مقاله [English]

Comparing Different Statistical Models and Pre-processing Techniques for Estimation several chemical properties of the soil Using VNIR/SWIR Spectrum

نویسندگان [English]

  • Elham Mehrabi Gohari 1
  • Hamid Reza Matinfar 2
  • Azam Jafari 3
  • Ruhollah Taghizadeh-Mehrjardi 4
  • F khayamim 5
1 College of Agriculture, Lorestan University, Lorestan, Iran and Faculty, Department of Agriculture, Payame Noor University.
2 College of Agriculture, Lorestan University, Lorestan, Iran
3 Agriculture Faculty, Shahid Bahonar University of Kerman, Kerman, , Iran
4 Faculty of Agriculture and Natural Resources, Ardakan University, Yazd, Iran.
5 Faculty of Agriculture, Isfahan university of Technology,Isfahan,Iran
چکیده [English]

Visible and Near-Infrared (VNIR) and Short-Wave Infrared (SWIR) reflectance spectroscopy (400-2450nm), which are at least as costly and time-consuming, are widely used in the estimation of physical and chemical properties of the soil. The purpose of this study was to investigate the ability of this method to estimate the amount of organic matter, carbonates and gypsum content of soil surface. In the present study, 115 profiles were identified based on the Hypercube technique, and the horizons were sampled and the amount of organic matter, carbonates and gypsum content were measured by standard methods. Reflectance spectra of all samples were measured using an ASD field-portable spectrometer in the laboratory. Soil samples were divided into two random groups (80% and 20%) for calibration and validation of models. PLSR and PCR models and different pre-processing methods i.e. First (FD) and Second Derivatives (SD), Multiplicative Scatter Correction (MSC) and Standard Normal Variate (SNV) were applied and compared to estimate texture elements. The highest RPD of calibration and validation were obtained for PLSR with First derivative of reflectance+ Savitzky_Golay filter pre-processing technique which was classified as a good for the amount of organic matter and gypsum and was classified as a poorly for the amount of carbonates.

کلیدواژه‌ها [English]

  • Partial Least Squares Regression (PLSR)
  • Principal Component Regression (PCR)
  • spectroscopy
  • carbonate
  • gypsum
  • organic matter

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