تعیین نواحی مدیریتی حاصلخیزی خاک‌های شالیزار با استفاده از روش‌های زمین آماری و خوشه‌بندی فازی

نوع مقاله : مقاله پژوهشی

نویسنده

گروه علوم و مهندسی خاک، دانشکده علوم زراعی، دانشگاه علوم کشاورزی و منابع طبیعی ساری، ساری، ایران

چکیده

درحال حاضر کاربرد کودهای شیمیایی بدون در نظر گرفتن تغییرات مکانی عناصر غذایی خاک در شالیزارها انجام می‏شود که مشکلات زیست‌محیطی زیادی را ایجاد می‌کند. در این تحقیق، از ادغام روش‫های زمین ‫آماری، تجزیه مؤلفه‌های اصلی و خوشه ‌بندی فازی برای مرزبندی نواحی مدیریتی 54 هکتار از اراضی شالیزاری استان مازندران استفاده شد. 85 نمونه خاک مرکب برداشته شد و خصوصیات فیزیکی و شیمیایی مهم خاک اندازه‌گیری شدند. انتخاب بهترین روش درون‌یابی برای پهنه‌بندی خصوصیات خاک، با استفاده از آماره‌هایی با بیش‌ترین دقت و همبستگی انجام شد. تحلیل مؤلفه‌های اصلی نشان داد که چهار مؤلفه با مقدار ویژه بالاتر از یک شناسایی شدند. مؤلفه اول با توجیه 78/38 درصد از تغییرات، بیشترین سهم را داشت. مؤلفه‌های دوم (82/17%)، سوم (19/14%) و چهارم (69/8%) به ترتیب در رتبه‌های بعدی قرار گرفتند. در مجموع، این چهار مؤلفه قادر به تبیین 49/79% از کل تغییرپذیری داده‌ها بودند. با استفاده از تحلیل خوشه‌بندی از نوع c-menas فازی، نواحی مدیریتی با در نظر گرفتن دو آماره‌ی شاخص کارآمدی فازی‌شدن (FPI) و شاخص آنتروپی طبقه‏بندی نرمال شده (NCE) انتخاب شدند. FPI و NCE در تعداد سه ناحیه، به‌ترتیب با مقادیر 0683/0 و 0333/0 کم‌ترین مقدار بوده و به‌همین علت تعداد بهینه ناحیه‌ها، سه ناحیه تعیین شد به‌طوری ‫که 34/18 هکتار از اراضی در ناحیه 1، 15/26 هکتار در ناحیه 2 و 12/13 هکتار در ناحیه 3 قرار گرفتند. این رویکرد با شناسایی دقیق نواحی، امکان اعمال مدیریت کودی هدفمند را فراهم کرده و می‌تواند به کاهش مصرف نهاده‌های شیمیایی و آلایندگی محیطی منجر شود. 

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Delineation of soil fertility management zones in paddy fields using geostatistical and fuzzy clustering methods

نویسنده [English]

  • Seyed Mostafa Emadi
Department of Soil Science and Engineering, Faculty of Crop Sciences, Sari Agricultural Sciences and Natural Resources University, Sari, Iran
چکیده [English]

Currently, the application of chemical fertilizer is carried out without taking into account the spatial variabilty of soil nutrients in paddy fields, which creates a lot of environmental problems. In this study, the integration of the geostatistics methods, principal components analysis and the fuzzy clustering were used to support the management area of 54 hectares of the Masandaran province's paddy fields. 85 compound soil samples were removed and the important physical and chemical properties of the soil were measured. The selection of the best Interpolation method for regionalization the properties of the soil was made using the most accurate and consistent statistics. Principal components analysis revealed four components with eigenvalues greater than one. The first component, explaining 38.78% of the variance, had the highest contribution. The second (17.82%), third (14.19%), and fourth (8.69%) components followed in descending order. Collectively, these four components accounted for 79.49% of the total data variability. Using fuzzy c-menas type clustering analysis, management areas were selected by considering two indexs of fuzzy performance index (FPI) and normalized classifcation entropy (NCE). The FPI and NCE were the lowest in the number of three areas, with values of 0/0683 and 0/0333, and thus the optimum number of areas, three areas were determined so that 18/34 hectares of land were placed in area 1, 26/15 hectares in area 2 and 13/12 hectare in area 3. This approach enables precise identification of management zones, facilitating targeted fertilizer management, which can reduce chemical input usage and environmental pollution.

کلیدواژه‌ها [English]

  • Site-specific management
  • Rice
  • Soil organic carbon
  • Chemical fertilizer
  • Mapping of Soil properties

Introduction

Optimum application of chemical fertilizers in low-lying alluvial soils of Mazandaran province with high water tables is of great importance in view of its environmental concerns. The site-specific management of soils can be applied when the accurate information of spatial variability of soil properties is identified. Currently, fertilizer management recommendations for rice in paddy fields of Sari Agricultural Sciences and Natural Resources University (SANRU) are being uniformly applied without consideration of spatial heterogeneity of nutrient content in soils. This study tries to integrate the geostatistics, principal component (PCA) and fuzzy c-means clustering methods for possible delineation of soil management zones (SMZs) in paddy fields.

Methodolog:

In this study, paddy fields of 54 ha were selected as the study site in SANRU and 85 soil composite samples were taken from the topsoil (0–30 cm), on an 80-m grid. Soil samples were analyzed for pH, EC, texture, organic carbon, total nitrogen (N), N-nitrate, available nutrients (P, K, Fe, Mn, Zn, and Cu) and cation-exchange capacity. The raw data passed the Kolmogorov-Smirnov normality test and their spatial variability was analyzed and spatial distribution maps were constructed using interpolation techniques. The PCA and fuzzy c-means clustering algorithm were then performed to delineate MZs, and eigenvalues were used to select the principal components (PCs) for cluster analysis. Fuzzy performance index (FPI) and normalized classification entropy (NCE) were used to determine the optimum cluster number.

Results and discussion

Mean contents of organic carbon and total nitrogen were 2.03 and 0.193 %, respectively, and had the 21.31 and 26.40 % of coefficient of variation. The coefficient of variation of N-nitrate (41%) was more than total nitrogen due to its inherent mobile characteristics. The best fitted semivariogram models for pH, EC, N-nitrate, CEC, clay, P and Mn was exponential but for OC, total N and Fe the spherical model was best fitted. The semivariogram models for Zn and Cu was Gaussian due to the high correlation and minimum RSS. The selection of best interpolation method within kriging, inverse distance within and conditional simulations techniques was conducted by consideration of mean absolute error, root mean square error, and concordance correlation coefficient. The results of PCA indicated that PCs 1, 2, 3 and 4 were considered significant (eigenvalues greater than 1.0); these together accounted for 79.49 % of total variance. The optimum number of MZs for the study area was three and analysis of variance indicated that the MZs were reasonable for the area. The MZs differed significantly with respect to studied soil properties. EC, N-nitrate, P, K and Zn were significantly higher in MZ 3 in comparison with MZs of 1 and 2. OC and total N content in MZs of 2 and 3 were significantly higher than those in MZ 1. Overall, the different management of paddy fields in the study area for three delineated zones can potentially increase the productivity of rice production and in turn, can decrease economically the fertilizers (N, P, K) application. The better nutrient contents of MZ 3 also reflected in more harvested yields compared with MZ 1 and 2.

Conclusions

Thus, the study emphasized that the methodology for delineating MZs could be helpful for site-specific soil nutrient management within the fields in low-lying flat landscape with apparent uniform soil characteristics in Mazandaran province and even in Iran. Therefore, based on the study, the following suggestions seem important in conducting future research:

  • For the regionalization of soil properties, proximal soil sensor should be used so that there is both cost and the possibility of identifying annual changes.
  • Use the integration of geostatistical methods with other fuzzy clustering algorithms such as k-means and ect.
  • Other characteristics of the land, such as the state of drainage, slope, etc., should also be used in the separation of management areas.

Author Contributions

Writing—original draft preparation, methodology, software, Conceptualization, funding acquisition, resources, S.M.E.

Data Availability Statement

All data and results are presented in the text of the article.

 

Acknowledgements

This article is derived from a research project (Code: 04-1394-01), approved by the Research and Technology Council of Sari Agricultural Sciences and Natural Resources University. I sincerely thank the university’s Vice Chancellor for Research and all individuals who contributed to this study.

Ethical considerations

The author avoided data fabrication, falsification, plagiarism, and misconduct.

Conflict of interest

The author declares that there is no conflict of interest.

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تحقیقات آب و خاک ایران
دوره 56، شماره 7
مهر 1404
صفحه 1761-1779

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