پديد آورندگان :
خرمالی فرهاد نويسنده استاد گروه علوم خاك، دانشگاه علوم كشاورزی و منابع طبیعی گرگان khormali farhad , سرمدیان فریدون نويسنده استاد گروه علوم و مهندسی خاك، دانشگاه تهران sarmadian fereydoon , كیانی فرشاد نويسنده دانشیار گروه علوم خاك، دانشگاه علوم كشاورزی و منابع طبیعی گرگان kiani farshad , افتخاری كامران نويسنده استادیار مؤسسه تحقیقات خاك و آب كشور Eftekhari kamran
چكيده لاتين :
Introduction: Assessing the soil quality of agricultural land is essential for the economic success and sustainability of the environment in developing countries. Recently, there are many types of methods for assessing soil quality, each of them uses different criteria. Considering that Qazvin plain is one of the most important regions of agricultural products in Iran as well as Middle East, so the assessment of the soil status using quantitative models of soil quality can be used as an indicator of the status of soils in relation to sustainable agriculture, optimal utilization of resources Natural and better land management. Among the quantitative models of soil quality index, cumulative model integrated quality index (IQI) and Nomero (NQI) index can be mentioned. Therefore, this study intends to evaluate the best quantitative and quality index model by examining and comparing two methods of selecting the appropriate criteria, Total data set (TDS) and Minimum (MDS) and the second order soil quality index, integrated quality index(IQI) and Nomero (NQI) index in Qazvin plain lands.
Material and Methods: The study area with 25220 hectares is located in east of Qazvin Province. The average annual precipitation is 275 mm and the soil moisture and temperature regimes are Thermic, Dry xeric and Weak Aridic, respectively. A total of 76 samples from the depth of 0-20 cm of the soil surface were studied and based on uniformity, soil type and land use. In this study, four types of criteria that affect the quality of soil in terms of their performance, including: upper limit, lower limit, optimal limit and descriptive function were selected. To qualify (normalize), the upper limit, lower limit and peak limit were selected. In the following, the Total Data Set (TDS) and the Minimum Data Set (MDS) set of data were used. In the TDS method, all of the measured characteristics (a total of 19 physicals, chemical and biological properties of the soil) were considered. Then, the degree of soil quality indices was determined based on the combination of TDS and MDS criteria and the final NQI and IQI quality indices.
Result and Dissection: Comparison of soil types in the region showed that the Aridisols had good, moderate and poor quality (19.35% of soil with good quality, 67.76% with moderate quality and 12.94% with poor quality), Entisols have good and medium quality (53.21% of the soil with good quality and 46.79% with moderate quality) and Inceptisols have very good, good, moderate and poor quality (96.9% Soils with very good quality, 66.73% with good quality, 15.85% with moderate quality and 13.44% with poor quality).
According to the TDS standard and the NQI model, the soils with qualities I, II and III were 30.67%, 66.86%, 47.2% of the total soils of the area (lands with poor quality soil quality were not observed in TDSNQI method). Therefore, according to this method, Aridisols has a very good, good and medium quality (13.26% of the soil with a very good quality rating, 73.88% with a good quality and 12.84% with a moderate quality grade), Entisols with The good quality (100% of the soil with good quality degree) and Inceptisols have a very good and good quality (28.11% of the soil with a very good quality grade, 71.88% with a good quality grade). The results of quantitative soil quality by using the MDS standard method and IQI model were showed, soils with very good, good, moderate and poor degree are 2.45, 16.45, 48.93 and 46.3 percent of total land area respectively.
The results of the combination of the MDS and the NQI model also showed that the soils with a very good, good and average grade are 30.67%, 66.86% and 47.2% of the total land, respectively. Also, the results of the combination of the MDS and NQI model showed that the soils with very good, good and average quality are 30.67%, 66.86% and 47.2% of the total land area respectively. The results of the evaluation based on 4 indicators showed that good quality (II) was prevalent in the studied soils and accounted for about 47% of the total area studied in Qazvin plain lands. The map of distribution of soil quality degrees, the distribution of soil degrees is relatively similar to all of four combination methods, the choice of criteria and model. By examining the linear relationship between the indices obtained from TDS and MDS criteria and the IQI and NQI indexes, it is observed that the correlation coefficient is more and more reliable than the NQI model when used in the IQI model (R2 = 0.77). So the highest correlation coefficient we observed two methods for selecting the TDS and MDS criteria when using the IQI model. In general, the results of this study indicate a better performance of the MDS criteria than TDS.
Conclusions: Therefore, the main results of this study suggest using the IQI model with the MDS selection method as the starting point in the global standard path for future studies. Special attention should be paid to the criteria chosen by the MDS. In addition, conducting a series of research into the future in order to modify the MDSIQI model can make it more relevant to international standards.
