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ارزیابی روش‌های PLSR و bagging-PLSR در برآورد اجزای بافت خاک، کربنات کلسیم و pH خاک با استفاده از داده‌های طیفی | ||
| تحقیقات آب و خاک ایران | ||
| دوره 54، شماره 8، آبان 1402، صفحه 1215-1231 اصل مقاله (2.18 M) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22059/ijswr.2023.362342.669533 | ||
| نویسندگان | ||
| آرام شهابی1؛ مسعود داوری1؛ کمال نبی اللهی* 2؛ روح اله تقی زاده مهرجردی3 | ||
| 1گروه علوم و مهندسی خاک، دانشکده کشاورزی، دانشگاه کردستان، سنندج، ایران | ||
| 2دانشیار گروه علوم و مهندسی خاک دانشگاه کردستان | ||
| 3گروه مدیریت مناطق خشک و بیابانی، دانشکده کشاورزی و منابع طبیعی، دانشگاه اردکان، اردکان، ایران. | ||
| چکیده | ||
| تعیین سریع، دقیق و کم‌هزینه ویژگی‌های خاکی در برنامه‌ریزی و مدیریت اراضی از اهمیت قابل‌توجهی برخوردار است. هدف از این پژوهش ارزیابی بازتاب طیفی نزدیک، به‌عنوان تکنیکی سریع، مقرون به صرفه و غیرمخرب در تخمین برخی ویژگی‌های خاک (شن، سیلت، رس، pH و کربنات کلسیم معادل (CCE)) با استفاده از روش‌های رگرسیون حداقل مربعات جزئی (PLSR) و رگرسیون حداقل مربعات جزئی توأم با بازنمونه‌گیری (bagging-PLSR) بود. بدین منظور، 220 نمونه مرکب خاک از عمق 0 تا 20 سانتی‌متری در شهریور 1398 از دشت قروه استان کردستان جمع آوری شد. سپس ویژگی‌های انتخابی خاک با روش‌های آزمایشگاهی استاندارد اندازه‌گیری شد. بازتاب طیفی نزدیک نمونه‌ی خاک‌ها در محدوده 350 تا 2500 نانومتر (Vis-NIR) با بهره‌گیری از دستگاه اسپکترورادیومتر آزمایشگاهی اندازه گیری شد. پس از ثبت طیف‌ها، انواع مختلف روش‌های پیش‌پردازش مورد ارزیابی قرار گرفت. نتایج نشان داد که روش PLSR مقادیر R2 بین 58/0 تا 76/0 به‌دست می‌دهد، درحالی‌که این مقادیر در bagging-PLSR بین 59/0 تا 74/0 متغیر می‌باشد. مقادیر RMSE معادل با 43/17، 65/7، 83/7، 94/7 و 66/0 در روش PLSR و همچنین مقادیر 66/16، 63/7، 13/8، 71/7 و 45/0 در روش bagging-PLSR به‌ترتیب برای شن، سیلت، رس، CCE و pH خاک به‌دست آمد. بر اساس مقادیر RPD (نسبت برآورد به انحراف)، در برآورد مقدار شن و CCE بهترین عملکرد توسط مدل bagging-PLSR به‌دست آمد؛ این در‌حالی است که در برآورد رس و pH خاک مدل PLSR دقیق‌ترین بود. نتایج پیش‌بینی هر دو مدل برای سیلت یکسان بود (53/1 = RPD). در کل نتایج نشان داد که مدل‌های PLSR و bagging-PLSR در برآورد ویژگی‌های خاکی مورد‌مطالعه از دقت قابل قبولی برخوردار می‌باشند. | ||
| کلیدواژه‌ها | ||
| کربنات کلسیم معادل؛ طیف‌سنجی مرئی &ndash؛ مادون قرمز نزدیک؛ رگرسیون حداقل مربعات جزئی؛ ویژگی‌های خاکی | ||
| عنوان مقاله [English] | ||
| Evaluation of PLSR and bagging-PLSR methods in estimating soil texture, calcium carbonate, and pH using spectral data | ||
| نویسندگان [English] | ||
| Aram Shahabi1؛ Masoud Davari1؛ Kamal Nabiollahi2؛ Rohullah Taghizadeh Mehrjardi3 | ||
| 1Department of Soil Science and Engineering, Faculty of Agriculture, University of Kurdistan, Sanandaj, Iran. | ||
| 2Associate Professor of Soil Science, Department of Soil Science, University of Kurdistan | ||
| 3Department of Arid and Desert Regions Management, Faculty of Agriculture and Natural Resources, Ardakan University, Ardakan, Iran | ||
| چکیده [English] | ||
| The rapid, accurate, and low-cost determination of soil properties has particularly important for land planning and management. The objective of this study was to evaluate the Vis-NIR spectral reflectance of soils, as a rapid, cost-effective, and non-destructive technique, for estimating some soil properties [sand, silt, clay, pH, and calcium carbonate equivalent (CCE)] by partial least-square regression (PLSR) and bagging-PLSR methods. For this purpose, a total of 220 composite soil samples were collected from 0-20 cm depth in Ghorveh Plain, Kurdistan province, in September 2019. The selected soil properties were measured by standard laboratory methods. The proximal spectral reflectance of soil samples was also measured within the 350-2500 nm range (Vis-NIR) using a handheld spectroradiometer. Different pre-processing methods were assessed after recording the spectra. The results indicated that the R2 values for the PLSR method ranged from 0.58 to 0.76, while the bagging-PLSR produced R2 values between 0.59 and 0.74. The RMSE values obtained for sand, silt, clay, CCE, and pH were 17.43, 7.65, 7.83, 7.94, and 0.66, respectively for the PLSR, and 16.66, 7.63, 8.13, 7.71, and 0.45 for the bagging-PLSR. Based on the ratio of prediction to deviation (RPD) values, the bagging-PLSR model achieved the best performance in predicting sand and CCE. However, for clay and pH prediction, the PLSR model was the most accurate. Both the PLSR and bagging-PLSR models yielded identical predictions for silt content, with an RPD value of 1.53. Overall, the results showed that PLSR and bagging-PLSR models have acceptable accuracy for estimating the proposed properties of the soils. | ||
| کلیدواژه‌ها [English] | ||
| CCE, Soil properties, Partial least-squares regression, Visible and near-infrared spectroscopy | ||
| مراجع | ||
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