Developing scoring functions for soil quality to assess land suitability for irrigated wheat in Southern Algeria

2021 ◽  
Author(s):  
Adil Mihoub ◽  
Naima Koull ◽  
Samia Helimi ◽  
Mohammed Elhafed Kherraze ◽  
Sakher Mokhtari ◽  
...  
Keyword(s):  
Soil Quality ◽  
Land Suitability ◽  
Scoring Functions ◽  
Irrigated Wheat

CROPPING SYSTEM EFFECTS ON SOIL QUALITY FOR THREE AGRO-ECOSYSTEMS IN INDIA

2013 ◽  
Vol 50 (3) ◽  
pp. 321-342 ◽  
Author(s):  
NISHANT K. SINHA ◽  
USHA KIRAN CHOPRA ◽  
ANIL KUMAR SINGH
Keyword(s):  
Soil Quality ◽  
Crop Production ◽  
Cropping Systems ◽  
Soil Layer ◽  
Cropping System ◽  
Scoring Functions ◽  
Soil Quality Index ◽  
Data Set ◽  
Non Linear ◽  
Semi Arid

SUMMARYSoil quality integrates the effects of soil physical, chemical and biological attributes. Some of them are dynamic in nature and behave differentially in various agro-ecosystems (AESs) and are quantified in terms of a soil quality index (SQI). An attempt has been made in this paper to develop an SQI based on a minimum data set (MDS), which could be used to evaluate the sustainability of the crop production in three varying AESs in India, namely sub-humid, semi-arid and arid. Thirteen indicators were utilized to develop the SQI from the properties measured from the surface soil layer (0–15 cm). Each indicator of the MDS was transformed into a dimensionless score based on scoring functions (linear and non-linear) and integrated into four SQIs. The weighted non-linear index (WNLI) was identified as the most sensitive for all the AESs and was recommended as an index for future assessments. Based on this index, the quantification of soil quality under several cropping systems was carried out for sub-humid, semi-arid and arid AESs and the most suitable cropping system was identified. WLNI was positively and significantly correlated (R2= 0.79,p< 0.01) with wheat equivalent yield for all the cropping systems. This clearly indicated that the index may be used satisfactorily for quantifying soil quality.

scholarly journals Soil Quality and Evaluation of Spatial Variability in a Semi-Arid Ecosystem in a Region of the Southeastern Iberian Peninsula (Spain)

Land ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 5
Author(s):  
Fernando Santos-Francés ◽  
Antonio Martínez-Graña ◽  
Carmelo Ávila-Zarza ◽  
Marco Criado ◽  
Yolanda Sánchez-Sánchez
Keyword(s):  
Organic Carbon ◽  
Soil Properties ◽  
Soil Quality ◽  
Water Retention ◽  
Mediterranean Ecosystem ◽  
Arid Ecosystem ◽  
Scoring Functions ◽  
Data Set ◽  
Preliminary Estimation ◽  
Semi Arid

In the last two decades, as the importance of soil has been recognized as a key component of any ecosystem, there has been an increased global demand to establish criteria for determining soil quality and to develop quantitative indices that can be used to classify and compare that quality in different places. The preliminary estimation of the attributes involved in soil quality was made taking into account the opinion of the experts and our own experience in a semi-arid ecosystem. In this study, 16 soil properties have been selected as potential indicators of soil quality, in a region between Campo de Montiel and Sierra de Alcaraz (Spain): sand and clay percentage, pH, electrical conductivity (EC), soil organic carbon (OC), extractables bases of change (Na, K, Ca and Mg), cationic exchange capacity (CEC), carbonate calcium equivalent (CCE), bulk density (BD), water retention at 33 kPa field capacity and 1500 kPa permanent wither point (GWC33 kPa and GWC1500 kPa), coefficient of linear extensibility (COLE) and factor of soil erodibility (K). The main objective has been to develop an adequate index to characterize the quality of the soils in a semi-arid Mediterranean ecosystem. The preliminary estimation of the attributes involved in soil quality was made considering the opinion of the experts and our own experience in semi-arid ecosystems. Two indicator selection approaches have been used to develop the Soil Quality Index (SQI) (total data set -TDS- and minimum data set -MDS-), scoring functions (linear -L- and nonlinear -NL-) and methods (additive -A-, additive weighted -W- and Nemoro -N-. The quality indices have been calculated, considering the properties of the soil control section (between 0 and 100 cm depth), using 185 samples, belonging to horizons A, B and C of 51 soil profiles. The results have shown that the election of the soil properties, both of the topsoil and subsoil, is an important help in establishing a good relationship between quality, soil functions and agricultural management. The Kriging method has been used to determinate the spatial distribution of the soil quality grades. The indices that best reflect the state of soil quality are the TDS-L-W and TDS-L-A should go as sub-indices, as they are the most accurate indices and provide the most consistent results. These indices are especially indicated when carrying out detailed or semi-detailed studies. However, the MDS-L-W and MDS-L-A should go as sub-indices, which use only a limited number of indicators, are best for large-scale studies. The indicators with the greatest influence on soil quality for different land uses and those developed on different rocks, using linear scoring functions, are the following: (Clay), (GWC1500 kPa) and (Ca). These results can also be expressed as follows: the best soils in this region are deep soils, with a clay texture, with high water retention and a neutral or slightly basic pH. However, the indicators with the greatest influence on soil quality, using nonlinear scoring functions, are: (OC Stock), (Ca) and (CaCO3). In other words, the most important indicator is the organic carbon content, which is not logical in the case of a region in which the soils have an excessively low SOC content (0.86%).

scholarly journals Soil Quality Assessment Strategies for Evaluating Soil Degradation in Northern Ethiopia

2014 ◽  
Vol 2014 ◽  
pp. 1-14 ◽  
Author(s):  
Gebreyesus Brhane Tesfahunegn
Keyword(s):  
Soil Quality ◽  
Expert Opinion ◽  
Soil Degradation ◽  
Management Practices ◽  
Principal Component ◽  
Eragrostis Tef ◽  
Northern Ethiopia ◽  
Scoring Functions ◽  
Soil Quality Index ◽  
Triticum Vulgare

Soil quality (SQ) degradation continues to challenge sustainable development throughout the world. One reason is that degradation indicators such as soil quality index (SQI) are neither well documented nor used to evaluate current land use and soil management systems (LUSMS). The objective was to assess and identify an effective SQ indicator dataset from among 25 soil measurements, appropriate scoring functions for each indicator and an efficient SQ indexing method to evaluate soil degradation across the LUSMS in the Mai-Negus catchment of northern Ethiopia. Eight LUSMS selected for soil sampling and analysis included (i) natural forest (LS1), (ii) plantation of protected area, (iii) grazed land, (iv) teff (Eragrostis tef)-faba bean (Vicia faba) rotation, (v) teff-wheat (Triticum vulgare)/barley (Hordeum vulgare) rotation, (vi) teff monocropping, (vii) maize (Zea mays) monocropping, and (viii) uncultivated marginal land (LS8). Four principal components explained almost 88% of the variability among the LUSMS. LS1 had the highest mean SQI (0.931) using the scoring functions and principal component analysis (PCA) dataset selection, while the lowest SQI (0.458) was measured for LS8. Mean SQI values for LS1 and LS8 using expert opinion dataset selection method were 0.874 and 0.406, respectively. Finally, a sensitivity analysis (S) used to compare PCA and expert opinion dataset selection procedures for various scoring functions ranged from 1.70 for unscreened-SQI to 2.63 for PCA-SQI. Therefore, this study concludes that a PCA-based SQI would be the best way to distinguish among LUSMS since it appears more sensitive to disturbances and management practices and could thus help prevent further SQ degradation.

scholarly journals Evaluation of Soil Quality in Arid Western Fringes of the Nile Delta for Sustainable Agriculture

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Ahmed M. Saleh ◽  
Mohamed M. Elsharkawy ◽  
Mohamed A. E. AbdelRahman ◽  
Sayed M. Arafat
Keyword(s):  
Soil Quality ◽  
Quality Indicators ◽  
Quality Index ◽  
Nile Delta ◽  
Western Desert ◽  
Scoring Functions ◽  
Soil Quality Indicators ◽  
Soil Quality Index ◽  
Quality Grade ◽  
Minimum Dataset

Egypt is currently witnessing an extensive desert greening plan with a target of adding one and a half million feddans to the agricultural area. The present study evaluates the soil quality in the western desert fringes of the Nile Delta using three indicator datasets, which involve the total dataset (TDS), the minimum dataset (MDS), and the expert dataset (EDS). Three quality index models are included: the Additive Soil Quality Index (SQI-A), the Weighted Additive Soil Quality Index (SQI-W), and the Nemoro Soil Quality Index (SQI-N). Linear and nonlinear scoring functions are evaluated for scoring soil and terrain indicators. Thirteen soil quality indicators and three terrain indicators were measured in 397 sampling sites for soil quality evaluation. Factor analyses determined five soil and terrain indicators for the minimum dataset and their associated weights. The linear scoring functions reflected the soil system functions more than nonlinear scoring functions. Soil quality estimation by the minimum dataset (MDS) and Weighted Additive Soil Quality Index (SQI-W) is more sensitive than that by SQI-A and SQI-N quality models to explain soil quality indicators. The moderate soil quality grade is the largest quality grade in the studied area. The minimum dataset of soil quality indicators could assist in reducing time and cost of evaluating soil quality and monitoring the temporal changes in soil quality of the region due to the increased agricultural development.

scholarly journals Developing scoring functions to assess soil quality at a regional scale in rangelands of SW Spain

2020 ◽  
Vol 44 ◽  
Author(s):  
Manuel Pulido Fernández ◽  
Ali Keshavarzi ◽  
Jesús Rodrigo-Comino ◽  
Susanne Schnabel ◽  
Joaquín Francisco Lavado Contador ◽  
...  
Keyword(s):  
Soil Quality ◽  
Regional Scale ◽  
Scoring Functions ◽  
Sw Spain

Changes in soil quality indices at different land uses in Semirom area

2020 ◽  
Author(s):  
Sattar Chavoshi Borujeni ◽  
Elham Chavoshi ◽  
Hamideh Nouri
Keyword(s):  
Land Use ◽  
Organic Matter ◽  
Organic Carbon ◽  
Particulate Organic Carbon ◽  
Soil Quality ◽  
Soil Aggregates ◽  
Land Uses ◽  
Quality Indices ◽  
Wheat Field ◽  
Irrigated Wheat

&lt;p&gt;&lt;strong&gt;Background and Objectives:&lt;/strong&gt; Assessment of soil quality indices is important for identifying the effect of land use on soil function. Soil organic matter (SOM) is a major indicator of soil quality due to its capacity in affecting soil structure by enhancing aggregation. The aim of this study was to quantify the soil quality changes in pasture and agricultural lands around the Semirom city.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Materials and Methods:&lt;/strong&gt; The study was conducted in a completely randomized design with five different levels including pastures, orchards, rain fed farming, irrigated cultivations of wheat and barley with 6 repetitions. A composite random soil sampling was done from the depth of 0-15 cm. Soil properties such as electrical conductivity (EC), pH, wet aggregate stability, particulate organic matter (POM), soil organic carbon (SOC) and carbohydrates were measured in each land use.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results:&lt;/strong&gt; The results showed that organic carbon (OC) and particulate organic carbon (POC) increased significantly in irrigated cultivation as compared to pasture. However particulate organic carbon was lower in rain fed farming compared with pasture. POC content were at least 2 times greater than those values in pasture and rain fed wheat farmlands. The highest carbohydrate amounts were observed in the irrigated wheat field (2 g kg&lt;sup&gt;-1&lt;/sup&gt;) while the lowest values were belonged to the rain fed wheat cultivations (0.94 g kg&lt;sup&gt;-1&lt;/sup&gt;). The content of carbohydrate had an increase of 40% in irrigated wheat field and a decrease of 50% in rain fed wheat field compared with pasture.The orchard and irrigated wheat and barley land uses had the highest mean weight diameter (MWD) of soil aggregates and the lowest values were obtained in the rain fed wheat and barley farming.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusion:&lt;/strong&gt; Overall, the survey results indicate a better soil quality of the orchards and irrigated farmlands, whereas the rain fed farmlands had more feeble soil quality as compared to other investigated land uses. Particulate organic carbon and carbohydrate showed greater sensitivity to land use changes. Therefore, these parameters are better indicators as compared to other investigated indicator for evaluating soil quality in the studied area.&lt;/p&gt;

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