scholarly journals ANALISIS KUALITAS TANAH PADA LAHAN TEGALAN BERPASIR DI DAS MIKRO SUPITURUNG, KABUPATEN KEDIRI, JAWA TIMUR

2021 ◽  
Vol 8 (2) ◽  
pp. 527-537
Author(s):  
Mochamad Fikri Kurniawan ◽  
Mochtar Lutfi Rayes ◽  
Christanti Agustina
Keyword(s):  
Soil Quality ◽  
Quality Indicators ◽  
Soil Texture ◽  
Quality Index ◽  
Survey Method ◽  
Soil Quality Indicators ◽  
Soil Quality Index ◽  
N Content ◽  
Total N ◽  
Organic C

Soil quality is the ability of soil that plays a role in maintaining plant productivity, preserving and maintaining water availability and supporting human activities. Soil quality assessment is measured based on indicators that describe important soil processes based on the physical, chemical and biological properties of the soil. The level of soil quality in a plot of land is assessed based on the soil quality index. This research was conducted from August to December 2020 in the Supiturung Micro Watershed, Kediri Regency, East Java using a graphical survey method based on the Land Map Unit. Soil samples were taken at a depth of 0-20 cm at each observation point (20 points) for analysis in the laboratory. Soil quality indicators are determined based on key soil properties with the Minimum Data Set (MDS) method, with soil quality indicators from soil physical properties including texture, bulk density, porosity and soil chemical properties including pH, available-P, exchangeable-K, total-N, organic-C. Soil quality index was calculated by weighting soil quality indicators with criteria which divided into 5 classes, i.e. (i) very low class (0.00-0.19), (ii) low (0.20-0.39), (iii) moderate (0.40-0.59), (iv) good (0.60-0.79) and (v) very good (0.80-1.00). The results showed that the soil in land unit 2 had different limiting factor values on the percentage of sand and dust from the soil texture, the total-N content of the soil and the organic-C content of the soil which caused differences in soil quality. There are two indicators of soil quality, namely the percentage of dust from the soil texture and the total N content of the soil which has the most influence on the soil quality index.

scholarly journals Assessing Soil Quality for Sustainable Cropland Management Based on Factor Analysis and Fuzzy Sets: A Case Study in the Lhasa River Valley, Tibetan Plateau

2018 ◽  
Vol 10 (10) ◽  
pp. 3477 ◽  
Author(s):  
Fuqiang Dai ◽  
Zhiqiang Lv ◽  
Gangcai Liu
Keyword(s):  
Land Use ◽  
Tibetan Plateau ◽  
Soil Quality ◽  
Quality Index ◽  
Soil Types ◽  
The Tibetan Plateau ◽  
Soil Quality Index ◽  
Total N ◽  
Organic C ◽  
Land Use Types

Ecologically fragile cropland soils and intensive agricultural production are characteristic of the valley area of the Tibetan Plateau. A systematic assessment of soil quality is necessary and important for improving sustainable cropland management in this area. This study aims to establish a minimum data set (MDS) for soil quality assessment and generate an integrated soil quality index for sustainable cropland management in the Tibetan Plateau. Soil samples were collected from the 0–20 cm depths of agricultural land in the middle and lower reaches of the Lhasa River. These samples were analyzed by routine laboratory methods. Significant differences were identified via statistical test between different soil types and land use types for each soil property. Principal component analysis was used to define a MDS of indicators that determine soil quality. Consequently, effective porosity, pH, total organic C, total N, available P, and catalase were identified as the final MDS. The soil quality index was obtained by the fuzzy-set membership function and the linear weighted additive method. The soil quality index differed significantly between the soil types and land use types. The soil quality can be ranked based on their indices in the following order: 1. Grain land with meadow soils, 2. Grain land with steppe soils, 3. Greenhouse vegetable land with fluvo-aquic soils, 4. Grain land with fluvo-aquic soils. The soils with higher soil quality indices exhibited better soil structure, higher nutrient contents, and superior resistance to water and nutrient loss. While the intensive tillage practices associated with vegetable production could reduce the values for effective porosity, pH and catalase, the application of appropriate fertilizers increased the values for total organic C, total N and available P. Therefore, the MDS method is an effective and useful tool to identify the key soil properties for assessing soil quality, and provides guidance on adaptive cropland management to a variety of soil types and land use types.

Soil quality indices and their application in the hilly loess plateau region of China

Soil Research ◽  
2006 ◽  
Vol 44 (3) ◽  
pp. 245 ◽  
Author(s):  
Mingxiang Xu ◽  
Yunge Zhao ◽  
Guobin Liu ◽  
Robert M. Argent
Keyword(s):  
Soil Quality ◽  
Quality Indicators ◽  
Loess Plateau ◽  
Quality Index ◽  
Shaanxi Province ◽  
Soil Quality Indicators ◽  
Soil Quality Index ◽  
Plateau Region ◽  
Significant Difference ◽  
Hilly Loess Plateau

Soil quality in the hilly Loess Plateau region of China is seriously degraded due to hillside cultivation and severe soil erosion. No established methods are available for evaluating the regional soil quality nor has integrated soil quality assessment been conducted in the region. Our objectives were to (i) develop soil quality models and assessment methods, (ii) verify the representativeness of selected soil quality indicators, and (iii) evaluate landuse effects on regional soil quality. The research was conducted on 707 km2 of typical hilly Loess Plateau in Shaanxi province, China. Soil samples (total 208) were taken from 5 catchments under 10 different landuse types. Two integrated evaluation methods (weighted summation and weighted product) and 2 indicator sets (a whole and a minimum set) were tested, each producing a soil quality index. Quantitative evaluation of soil quality in different landuse types was also performed. The results showed that the weighted product method provided better differentiation of soil quality between landuses. The minimum indicator set of 8 soil quality indicators, selected by factor analysis from a complete set of 29 soil attributes, reflected all or most of the information of the whole set in assessing regional soil quality. Soil quality index (SQI) values under different landuse types ranged from 0.842 for natural woodland to 0.150 for orchard. Index values for orchard, cropland, revegetated grassland, and planted grassland were significantly less than those for 6 other landuse types, whereas planted shrubland, planted woodland, and natural grassland indices were significantly less than those for greenhouse, natural shrubland, and natural woodland. No significant difference in SQI was found between orchard, cropland, revegetated grassland, and planted grassland, or between planted shrubland and planted woodland. Overall, it was found that soil quality was generally poor across the region, except for natural woodland, shrubland and greenhouse areas.

scholarly journals The effect of land use on soil quality in Giriwoyo Sub-district, Wonogiri Regency

2020 ◽  
Vol 8 (2) ◽  
pp. 2559-2568
Author(s):  
M Mujiyo ◽  
Yosua Yoga Setyawan ◽  
Aktavia Herawati ◽  
Hery Widijanto
Keyword(s):  
Land Use ◽  
Soil Quality ◽  
Quality Index ◽  
Microbial Biomass Carbon ◽  
Available P ◽  
Soil Quality Index ◽  
Data Set ◽  
Total N ◽  
Organic C

Determination of soil quality in Giriwoyo Sub-district, Wonogiri Regency, will generate a Soil Quality Index which can be used as a reference for soil cultivation for optimal productivity. This research was a descriptive exploratory with a survey approach. The survey area consisted of 12 land mapping units (LMU) with 3 replications for each LMU. Determination of LMU based on soil type, land use, slope and rainfall. The parameters used were BD (bulk density), porosity, organic C, pH, CEC (cation exchange capacity), BS (base saturation), available P, available K, total N, and MBC (microbial biomass carbon) that represented the physical, chemical and biological properties of the soil. Principal Component Analysis (PCA) analysis was performed to obtain the Minimum Data Set (MDS). The Soil Quality Index (SQI) at each LMU was calculated by multiplying the PCA result score (Wi) with the score for each selected indicator (Si). The result showed that the Soil Quality Index at each LMU was low. The highest Soil Quality Index was found in fields land use with an SQI of 0.34. The soil indicator that limited the soil quality was available P.

scholarly journals The use of multivariate statistical analysis and soil quality indices as tools to be included in regional management plans. A case study from the Mashhad Plain, Iran

2019 ◽  
Vol 45 (2) ◽  
pp. 687 ◽  
Author(s):  
J. Rodrigo-Comino ◽  
A. Keshavarzi ◽  
A. Bagherzadeh ◽  
E.C. Brevik
Keyword(s):  
Particle Size ◽  
Calcium Carbonate ◽  
Organic Carbon ◽  
Soil Properties ◽  
Bulk Density ◽  
Soil Quality ◽  
Quality Indicators ◽  
Quality Index ◽  
Soil Quality Indicators ◽  
Soil Quality Index

Several methods have been used to model reality and explain soil pedogenesis and evolution. However, there is a lack of information about which soil properties truly condition soil quality indicators and indices particularly at the pedon scale and at different soil depths to be used in land management planning. Thus, the main goals of this research were: i) to assess differences in soil properties (particle size, saturation point, bulk density, soil organic carbon, pH and electrical conductivity) at different soil depths (0-30 and 30-60 cm); ii) to check their statistical correlation with soil quality indicators (CEC, total N, Olsen-P, available K, exchangeable Na, calcium carbonate equivalent, Fe, Mn, Zn, and Cu); and, iii) to elaborate a soil quality index and maps for each soil layer. To achieve this, forty-eight soil samples were analysed in the laboratory and subjected to statistical analyses by ANOVA, Spearman Rank coefficients and Principal Component Analyses. Finally, a soil quality index was developed based on indicators of sensitivity. The study was conducted in a semiarid catchment in northeast Iran with irrigated farming and well-documented land degradation issues. We found that: i) organic carbon and bulk density were not similar in the topsoil and subsoil; ii) calcium carbonate and sand content conditioned organic carbon content and bulk density; iii) organic carbon showed the highest correlations with soil quality indicators; iv) particle size conditioned cation-exchange capacity; and, v) heavy metals such as Mn and Cu were highly correlated with organic carbon due to non-suitable agricultural practices. Based on the communality analysis to map of soil quality, CEC, Mn, Zn, and Cu had the highest weights (≥0.11) at both depths, coinciding with the same level of relevance in the multivariate analysis. Exchangeable Na, CaCO3, and Fe had the lowest weights (≤0.1) and N, P, and K had intermediate weights (0.1- 0.11). In general, the map of the soil quality index shows a lower soil quality in the subsoil increment than in the topsoil.

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 Spatial Variability of Physical Soil Quality Index of an Agricultural Field

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Sheikh M. Fazle Rabbi ◽  
Bina R. Roy ◽  
M. Masum Miah ◽  
M. Sadiqul Amin ◽  
Tania Khandakar
Keyword(s):  
Spatial Variability ◽  
Bulk Density ◽  
Soil Quality ◽  
Quality Indicators ◽  
Quality Index ◽  
Crop Production ◽  
Field Investigation ◽  
Agricultural Field ◽  
Soil Quality Indicators ◽  
Soil Quality Index

A field investigation was carried out to evaluate the spatial variability of physical indicators of soil quality of an agricultural field and to construct a physical soil quality index (SQIP) map. Surface soil samples were collected using10  m×10 m grid from an Inceptisol on Ganges Tidal Floodplain of Bangladesh. Five physical soil quality indicators, soil texture, bulk density, porosity, saturated hydraulic conductivity (KS), and aggregate stability (measured as mean weight diameter, MWD) were determined. The spatial structures of sand, clay, andKSwere moderate but the structure was strong for silt, bulk density, porosity, and MWD. Each of the physical soil quality indicators was transformed into 0 and 1 using threshold criteria which are required for crop production. The transformed indicators were the combined into SQIP. The kriged SQIPmap showed that the agricultural field studied could be divided into two parts having “good physical quality” and “poor physical soil quality.”

Effect of straw management and nitrogen fertilizer on selected soil properties as potential soil quality indicators of an irrigated Dark Brown Chernozemic soil

1998 ◽  
Vol 78 (3) ◽  
pp. 511-517 ◽  
Author(s):  
J. F. Dormaar ◽  
J. M. Carefoot
Keyword(s):  
Soil Properties ◽  
Soil Quality ◽  
Quality Indicators ◽  
Crop Yields ◽  
Research Centre ◽  
Fertility Level ◽  
Soil Quality Indicators ◽  
Total N ◽  
Organic C ◽  
Straw Management

Cereals grown under irrigation in the Canadian prairies produce large amounts of residues. An experiment initiated at the Agriculture and Agri-Food Canada Research Centre, Lethbridge, Alberta, in the fall of 1986, to investigate five straw management treatments (1, chopped straw/fall tillage [straw incorporated]; 2, chopped straw/spring tillage [straw incorporated]; 3, straw baled/fall tillage; 4, straw baled/spring tillage; 5, straw baled/direct seeding) and three fertilizer N rates (0, 100, and 200 kg N ha−1) on crop yields under irrigation, was sampled in April 1995 to examine the effect of straw management and fertilizer additions on selected soil chemical characteristics as potential soil quality indicators. If yield is not used, can we evaluate soil quality from a soil genesis baseline or is it crop growth driven? Differences among straw management and fertility treatments have already supplied information on the effects of these treatments after 8 yr. The treatment in which the straw was baled and the land not tilled had the highest soil bulk density. Total soil organic C and N were highest for the straw baled/no tillage treatment and the 200 kg N ha−1 application. Total C was higher for the fall than spring tillage treatments, while total N was lower for the spring than for the fall tillage treatments when straw was incorporated. Light fraction (mg kg−1 C) was highest for the chopped straw and zero fertilizer additions. For several biologically related characteristics, e.g., mineralizable N, biomass C, biological index N, and hydrolysable N, there were significant interactions between straw management treatments and fertility levels. Monosaccharides at the zero fertility level were generally of microbial origin, while plant-origin monosaccharides were more prevalent as the fertility level increased. It is concluded that the present use does not lead to soil erosion, does not pollute groundwater, and does grow plants; with the help of outside resources, any one straw management treatment can be considered as valid in the anthropocentric sense of soil quality. Since the interpretation of significant effects of treatment on soil properties must be carefully considered depending on the crop selected, the concept of soil quality is thus open to question and debate. Key words: Soil quality, straw management, intrinsic value, tillage, labile organic matter

scholarly journals Using Modified Soil Quality Index for Determining Ponds Bottom Soil Quality Status of Aquaculture Area BLUPPB Karawang West Java, Indonesia

2016 ◽  
Vol 7 (1) ◽  
pp. 1 ◽  
Author(s):  
Anggoro Prihutomo ◽  
Warih Hardanu ◽  
Atri Triana Kartikasari
Keyword(s):  
Soil Quality ◽  
Quality Index ◽  
C:N Ratio ◽  
Analysis Data ◽  
Chemical Compositions ◽  
Plastic Mulch ◽  
Soil Quality Index ◽  
Total N ◽  
Bottom Soil ◽  
The Impact

<p>The impact of aquaculture activities has led to environmental degradation, especially ponds bottom soil quality. The purpose of this study was to assess the status of the ponds bottom soil quality in different aquaculture systems (traditional and intensive) in BLUPPB Karawang region in a flexible value of soil quality index (SQI). Twenty ponds consisting of 5 traditional of milkfish (<em>Chanos chanos</em>) juvenile rearing ponds and 5 traditional polyculture ponds, 5 intensive of <em>Litopenaeus </em><em>va</em><em>n</em><em>namei</em> shrimp ponds lined with plastic mulch and 5 intensive <em>L. vannamei </em>shrimp earthen ponds. Variables of soil quality parameters examined include physical, chemical and biological of pond bottom soil. Sediment ponds with a depth of 5-10 cm were taken for analysis. Data statistically analyzed using Anova, continued with pos hoc test HSD Tukey. The results showed the ponds soil quality (SQI) of BLUPPB Karawang area has an average of 0.38 ± 0.02 or included in low criteria. Aquaculture systems were not significant (p&gt; 5%) to the general status of ponds soil quality. Aquaculture systems (intensive and traditional) only gave a significant different (p&lt;5%) to the parameter of soil bulk density, c-organic, total N, C:N ratio, total S, total P and soil respiration. Stability of the ponds bottom soil chemical compositions over time make level of intensity does not significantly affect, beside routine sediment removal at the end of cycle in intensive culture.</p>

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