scholarly journals Integrated Crop-Livestock Management Effects on Soil Quality Dynamics in a Semiarid Region: A Typology of Soil Change Over Time

2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
J. Ryschawy ◽  
M. A. Liebig ◽  
S. L. Kronberg ◽  
D. W. Archer ◽  
J. R. Hendrickson
Keyword(s):  
Cluster Analysis ◽  
Soil Quality ◽  
Production Systems ◽  
Principal Component ◽  
Quality Data ◽  
Semiarid Region ◽  
Soil Quality Index ◽  
Total N ◽  
Organic C ◽  
Over Time

Integrated crop-livestock systems can have subtle effects on soil quality over time, particularly in semiarid regions where soil responses to management occur slowly. We tested if analyzing temporal trajectories of soils could detect trends in soil quality data which were not detected using traditional statistical and index approaches. Principal component and cluster analyses were used to assess the evolution in ten soil properties at three sampling times within two production systems (annually cropped, perennial grass). Principal component 1 explained 33% of the total variance of the complete dataset and corresponded to gradients in extractable N, available P, and C : N ratio. Principal component 2 explained 25.4% of the variability and corresponded to gradients of soil pH, soil organic C, and total N. While previous analyses found no differences in Soil Quality Index (SQI) scores between production systems, annually cropped treatments and perennial grasslands were clearly distinguished by cluster analysis. Cluster analysis also identified greater dispersion between plots over time, suggesting an evolution in soil condition in response to management. Accordingly, multivariate statistical techniques serve as a valuable tool for analyzing data where responses to management are subtle or anticipated to occur slowly.

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.

scholarly journals Effects of pumice mining on soil quality

Solid Earth ◽  
2016 ◽  
Vol 7 (1) ◽  
pp. 1-9 ◽  
Author(s):  
A. Cruz-Ruíz ◽  
E. Cruz-Ruíz ◽  
R. Vaca ◽  
P. Del Aguila ◽  
J. Lugo
Keyword(s):  
Bulk Density ◽  
Soil Quality ◽  
Total Nitrogen ◽  
Agricultural Soils ◽  
Microbial Biomass Carbon ◽  
Principal Component ◽  
Available Phosphorus ◽  
Total N ◽  
Organic C ◽  
Study Sites

Abstract. Mexico is the world's fourth most important maize producer; hence, there is a need to maintain soil quality for sustainable production in the upcoming years. Pumice mining is a superficial operation that modifies large areas in central Mexico. The main aim was to assess the present state of agricultural soils differing in elapsed time since pumice mining (0–15 years) in a representative area of the Calimaya region in the State of Mexico. The study sites in 0, 1, 4, 10, and 15 year old reclaimed soils were compared with an adjacent undisturbed site. Our results indicate that gravimetric moisture content, water hold capacity, bulk density, available phosphorus, total nitrogen, soil organic carbon, microbial biomass carbon and phosphatase and urease activity were greatly impacted by disturbance. A general trend of recovery towards the undisturbed condition with reclamation age was found after disturbance, the recovery of soil total N being faster than soil organic C. The soil quality indicators were selected using principal component analysis (PCA), correlations and multiple linear regressions. The first three components gathered explain 76.4 % of the total variability. The obtained results revealed that the most appropriate indicators to diagnose the quality of the soils were urease, available phosphorus and bulk density and minor total nitrogen. According to linear score analysis and the additive index, the soils showed a recuperation starting from 4 years of pumice extraction.

scholarly journals Quantitative Evaluation of Soil Quality Using Principal Component Analysis: The Case Study of El-Fayoum Depression Egypt

2021 ◽  
Vol 13 (4) ◽  
pp. 1824
Author(s):  
Mohamed K. Abdel-Fattah ◽  
Elsayed Said Mohamed ◽  
Enas M. Wagdi ◽  
Sahar A. Shahin ◽  
Ali A. Aldosari ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Cluster Analysis ◽  
Soil Quality ◽  
Quality Index ◽  
Principal Component ◽  
Component Analysis ◽  
Soil Samples ◽  
Western Desert ◽  
Geographical Information ◽  
Soil Quality Index

Soil quality assessment is the first step towards precision farming and agricultural management. In the present study, a multivariate analysis and geographical information system (GIS) were used to assess and map a soil quality index (SQI) in El-Fayoum depression in the Western Desert of Egypt. For this purpose, a total of 36 geo-referenced representative soil samples (0–0.6 m) were collected and analyzed according to standardized protocols. Principal component analysis (PCA) was used to reduce the dataset into new variables, to avoid multi-collinearity, and to determine relative weights (Wi) and soil indicators (Si), which were used to obtain the soil quality index (SQI). The zones of soil quality were determined using principal component scores and cluster analysis of soil properties. A soil quality index map was generated using a geostatistical approach based on ordinary kriging (OK) interpolation. The results show that the soil data can be classified into three clusters: Cluster I represents about 13.89% of soil samples, Cluster II represents about 16.6% of samples, and Cluster III represents the rest of the soil data (69.44% of samples). In addition, the simulation results of cluster analysis using the Monte Carlo method show satisfactory results for all clusters. The SQI results reveal that the study area is classified into three zones: very good, good, and fair soil quality. The areas categorized as very good and good quality occupy about 14.48% and 50.77% of the total surface investigated, and fair soil quality (mainly due to salinity and low soil nutrients) constitutes about 34.75%. As a whole, the results indicate that the joint use of PCA and GIS allows for an accurate and effective assessment of the SQI.

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 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 Arthropod community at different altitudes in Gunung Halimun-Salak National Park, Western Java, Indonesia

2019 ◽  
Vol 20 (6) ◽  
Author(s):  
NOOR FARIKHAH HANEDA ◽  
IWAN HILWAN ◽  
EWI IRFANI
Keyword(s):  
National Park ◽  
Pearson Correlation ◽  
Principal Component ◽  
Environmental Parameters ◽  
Soil Arthropods ◽  
Arthropod Community ◽  
Total N ◽  
Organic C ◽  
Soil Arthropod ◽  
Different Altitudes

Abstract. Haneda NF, Hilwan I, Irfani E. 2019. Arthropod community at different altitudes in Gunung Halimun-Salak National Park, Western Java, Indonesia. Biodiversitas 20: 1735-1742. Gunung Halimun Salak National Park (GHSNP) stores high biodiversity both from its flora and fauna. Parts of the diversity that have not been widely explored are soil arthropods at different altitudes. The aim of this study was to analyze soil arthropod community and the correlation between the attributes of soil arthropods and the environmental factors. The soil arthropods were collected using pitfall traps, placed in several altitudes, i.e., 500 m, 700 m, 900 m, 1100 m, 1300 m, 1500 m, and 1700 m . The attributes of community and environmental parameters were analyzed using Pearson correlation and principal component analysis. The result showed that family Formicidae dominated the soil arthropod community. The diversity of arthropods increased with increasing altitudes. The habitat at the altitudes of 1500 m, 1300 m and 1100 m had a dense canopy, thick litter and high total N and organic C. There was positive correlation between the attributes of soil arthropod community and environment variables.

scholarly journals Performance Analysis and Soil Quality Indexing for Dalbergia sissoo Roxb. Grown in Marginal and Degraded Land of Eastern Uttar Pradesh, India

Land ◽  
2019 ◽  
Vol 8 (4) ◽  
pp. 63 ◽  
Author(s):  
Sheikh Adil Edrisi ◽  
Vishal Tripathi ◽  
Purushothaman Chirakkuzhyil Abhilash
Keyword(s):  
Soil Quality ◽  
Microbial Biomass Carbon ◽  
Uttar Pradesh ◽  
Principal Component ◽  
Climatic Conditions ◽  
Dalbergia Sissoo ◽  
Land Restoration ◽  
Degraded Land ◽  
Soil Quality Index ◽  
Degraded Lands

The successful utilization of marginal and degraded lands for biomass and bioenergy production depends upon various factors such as climatic conditions, the adaptive traits of the tree species and their growth rate and respective belowground responses. The present study was undertaken to evaluate the growth performance of a bioenergy tree (Dalbergia sissoo Roxb.) grown in marginal and degraded land of the Mirzapur district of Uttar Pradesh, India and to analyze the effect of D. sissoo plantations on soil quality improvement over the study years. For this, a soil quality index (SQI) was developed based on principal component analysis (PCA) to understand the effect of D. sissoo plantations on belowground responses. PCA results showed that among the studied soil variables, bulk density (BD), moisture content (MC), microbial biomass carbon (MBC) and soil urease activity (SUA) are the key variables critically influencing the growth of D. sissoo. The SQI was found in an increasing order with the growth period of D. sissoo. (i.e., from 0.419 during the first year to 0.579 in the fourth year). A strong correlation was also observed between the growth attributes (diameter at breast height, R2 = 0.870; and plant height, R2 = 0.861) and the soil quality (p < 0.01). Therefore, the developed SQI can be used as key indicator for monitoring the restoration potential of D. sissoo growing in marginal and degraded lands and also for adopting suitable interventions to further improve soil quality for multipurpose land restoration programs, thereby attaining land degradation neutrality and United Nations Sustainable Development Goals.

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>

Assessing soil-quality indices for subtropical rice-based cropping systems in India

Soil Research ◽  
2016 ◽  
Vol 54 (1) ◽  
pp. 20 ◽  
Author(s):  
Nirmalendu Basak ◽  
Ashim Datta ◽  
Tarik Mitran ◽  
Satadeep Singha Roy ◽  
Bholanath Saha ◽  
...  
Keyword(s):  
Soil Quality ◽  
Cropping Systems ◽  
Principal Component ◽  
Exchange Capacity ◽  
Microbial Biomass C ◽  
Organic C ◽  
Soil Attributes ◽  
Labile C ◽  
Chemical Attributes ◽  
Minimum Dataset

Rice-based cropping systems are the foundation of food security in countries of Southeast Asia, but productivity of such systems has declined with deterioration in soil quality. These systems are different from other arable systems because rice is grown under submergence, and this may require a different set of key soil attributes for maintenances of quality and productivity. A minimum dataset was screened for assessing quality of soils belonging to three Soil Orders (Inceptisols, Entisols and Alfisols) by using statistical and mathematical models and 27 physical, chemical and biological attributes. Surface soils were collected from farmers’ fields under long-term cultivation of rice–potato–sesame cropping systems. Most of the attributes varied significantly among the Soil Orders used. Four or five key attributes were screened for each Soil Order through principal component and discriminate analysis, and these explained nearly 80% and 90% of the total variation in each Soil Order dataset. The attributes were dehydrogenase activity (DHA), available K, cation exchange capacity (CEC) and pHCa for Inceptisols; organic C, pHCa, bulk density, nitrogen mineralisation (Nmin) and β-glucosidase for Entisols; and DHA, very labile C, Nmin and microbial biomass C for Alfisols. Representation of the screened attributes was validated against the equivalent rice yield of the studied system. Among the selected key soil attributes, DHA and CEC for Inceptisols, organic C for Entisols, and Nmin and very labile C for Alfisols were most strongly correlated with system yield (R2 = 0.45, 0.77 and 0.78). Results also showed that biological and chemical attributes were most sensitive for indicating the differences in soil quality and have a strong influence on system yield, whereas soil physical attributes largely varied but did not predict system yield.

Determination of soil organic carbon and nitrogen at the field level using near-infrared spectroscopy

2002 ◽  
Vol 82 (4) ◽  
pp. 413-422 ◽  
Author(s):  
P D Martin ◽  
D F Malley ◽  
G. Manning ◽  
L. Fuller
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Analytical Data ◽  
Principal Component ◽  
Soil Samples ◽  
Organic N ◽  
Least Squares Regression ◽  
Total N ◽  
Organic C

This study explored the use of near-infrared spectroscopy (NIRS) for the rapid analysis of organic C (Corg) and organic N (Norg) in the A horizon of soil within a single field. Soil was sampled throughout a field in Manitoba, Canada to capture soil variability associated with topography. The soil samples were oven-dried and treated with acid to remove carbonates, after which C and N were determined by dry combustion. In this study, portions of the dried soil samples not treated with acid were scanned with a near-infrared scanning spectrophotometer between 1100 and 2500 nm. Correlating the spectral and the chemical analytical data using multiple linear regression or principal component analysis/partial least squares regression gave useful correlations for Corg. Over the range of 0–40 mg g-1 Corg, NIR-predicted values explained 75–78% of the variance in the chemical results. Results were improved to 80% for calibrations developed for the 0–20 mg g-1 organic C range. Useful results were not obtained for Norg although the literature shows that total N in soil is predictable using NIRS. It is likely that the acid treatment altered the composition of the samples in an inconsistent manner such that the chemically analyzed samples and those scanned by NIRS were different from each other in Norg concentration or composition. Extrapolation of these Corg results to the landscape scale implies that NIRS has potential to be a suitable method for mapping C for the purposes of monitoring C sequestration. Key words: Near-infrared spectroscopy, soil, carbon, nitrogen, topography, soil monitoring

Sign in / Sign up

Export Citation Format

Share Document