scholarly journals Assessment of soil quality indicators under rice ecosystem of Assam, India

2020 ◽  
Vol 41 (6) ◽  
pp. 1655-1664
Author(s):  
A. Gayan ◽  
◽  
D.J. Nath ◽  
B. Bhattacharyya ◽  
N. Dutta ◽  
...  
Keyword(s):  
Soil Quality ◽  
Rice Yield ◽  
Maximum Yield ◽  
Principal Component ◽  
Exchange Capacity ◽  
Biological Parameters ◽  
Quality Indices ◽  
Soil Quality Index ◽  
Rice Soils ◽  
Rice Ecosystem

Aim: To assess the soil quality indices and its impact on rice yield in Upper Brahmaputra Valley Zone of Assam. Methodology: Seventy-three numbers of geo referenced soil samples were collected from the rice ecosystems and analysed for twenty-one soil physical, chemical and biological parameters. The soil quality indices (SQI) were developed using statistical tools like principal component analysis (PCA) techniques and expert opinion (EO). Relative soil quality index (RSQI) was also developed for grouping the soils into categories. Correlation matrices were drawn between different soil quality indices. The optimum values of soil quality indices were computed to sustain 80% or more of the existing in field maximum rice yield (5.20 t ha-1). Results: Multivariate statistics showed that four biological parameters viz., fluorescein di-acetate activity, phosphate solubilising bacteria, total bacterial population and collembolan population and three chemical parameters viz., cation exchange capacity, electrical conductivity? and diethylene tri amine penta acetic acid-Zinc could explain 70.2% of the cumulative variance. RSQI demonstrated that >50% and >30% of soils belonged to medium and good category. The regression of percent relative rice yield obtained from farmers field, illustrated that soil functions based EO-SQI could explain high degree of relationship (R2=0.289; r=0.537*), followed by RSQI (R2=0.284;r=0.532*) and PCA-SQI (R2=0.143; r=0.378*) to explain the variability of soils. The optimum value indicates that the rice soils having PCA-SQI value >0.55 were likely to give 80% or more of the maximum yield of UBVZ of Assam. Interpretation: Approaches of rating of soil quality based on PCA-SQI may be a useful tool, and there is need of more extensive investigations to validate its usefulness for assessment of soil quality in different cropping sequences of Assam.

scholarly journals The impact of traditional land use management on soil quality in Northeastern Himalayas (India)

2021 ◽  
Vol 94 (1) ◽  
pp. 91-109
Author(s):  
Gaurav Mishra ◽  
Jesús Rodrigo-Comino
Keyword(s):  
Land Use ◽  
Soil Quality ◽  
Soil Depth ◽  
Principal Component ◽  
Exchange Capacity ◽  
Exchangeable Cations ◽  
Land Use Management ◽  
Soil Quality Index ◽  
Land Use Types ◽  
The Impact

n the Northeast Himalayas (NEH) region, four major conventional land-use types are forest, Jhum lands, fallow Jhum lands and plantations, but little is known about their sustainability and responses to changes. We collected soil samples at two uniform depths (0-15 and 15-30 cm) from the Zunheboto district of Nagaland (India). The dataset was statistically analyzed by conducting an ANOVA-one way, principal component analysis (PCA) and calculating an additive soil quality index (SQIa). Our results confirmed that sand content, bulk density (BD), porosity, soil organic carbon (SOC), cation exchange capacity (CEC), exchangeable calcium and potassium showed significant statistical differences among soil depths depending on the land use management. PCA results showed that soil texture, BD, porosity, SOC and exchangeable cations could be consideredthe major indicators to define soil quality. After estimating the SQIa, Jhum soils showed the highest values at the surface, while at 15-30 cm soil depth, fallow Jhum soils phase showed the highest ones. The conversion from natural forest to plantation does not hamper the SQ, but their conversion into Jhum may even increase it, for a shorter duration. However, after 1-2 year of cultivation and conversion from Jhum into fallow Jhum land, soil quality could be reduced.

scholarly journals CHEMICAL AND MICROBIOLOGICAL ATTRIBUTES UNDER DIFFERENT SOIL COVER

CERNE ◽  
2017 ◽  
Vol 23 (1) ◽  
pp. 19-30 ◽  
Author(s):  
Elaine Novak ◽  
Laércio Alves Carvalho ◽  
Etenaldo Felipe Santiago ◽  
Irzo Isaac Rosa Portilho
Keyword(s):  
Soil Quality ◽  
Private Property ◽  
Microbial Biomass Carbon ◽  
Principal Component ◽  
Basal Respiration ◽  
Exchange Capacity ◽  
Native Vegetation ◽  
Mato Grosso ◽  
Environmental Recovery ◽  
Short Period

ABSTRACT A challenge for the environmental recovery of degraded areas is the search for soil data. In this process, the microbiological parameters and soil chemicals are potential indicators of soil quality. This study aimed to evaluate soil quality based on microbiological and chemical soil attributes in different areas involving environmental recovery, sugarcane cultivation and remnants of native vegetation located in a rural private property farm in State of Mato Grosso do Sul, Brazil, in Hapludox Eutrophic soil. The microbiological (microbial biomass carbon, basal respiration, microbial quotient and metabolic quotient) and chemical parameters (organic matter, carbon, pH, cationic exchange capacity, sum of bases, potassium, phosphorus, magnesium, calcium, saturation base and potential acidity) were assessed. Data were assessed by variance and multivariate analysis (Principal Component Analysis and cluster analysis). Overall, the results showed highest alteration in the chemical and microbiological characteristics of the soil in sugarcane cultivation area in comparison with other areas. Considering the studied recovery areas, REC1, REC5 and REC7 show chemical and microbiological conditions with most similarity to native vegetation. Despite the short period of the resilience enhancement of environmental recovery areas, the development of vegetation cover and establishment of the microbial community were determined to be important factors for improving soil quality and environmental recovery in several of the areas studied.

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.

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.

scholarly journals The Assessment of Soil Quality Index for Paddy Fields with Indicator Biology in Jatipurno Districts, Wonogirl

2019 ◽  
Vol 14 (1) ◽  
pp. 20
Author(s):  
Supriyadi Supriyadi ◽  
Widyatmani Sih Dewi ◽  
Desmiasari Nugrahani ◽  
Adila Azza Rahmah ◽  
Haryuni Haryuni ◽  
...  
Keyword(s):  
Soil Quality ◽  
Quality Index ◽  
Management Practices ◽  
Principal Component ◽  
Biological Indicators ◽  
Paddy Fields ◽  
Soil Quality Index ◽  
Data Set ◽  
Organic Rice ◽  
Minimum Data

Increased rice needs in an extensive use of paddy fields in the Jatipurno, Wonogiri. Managing rice fields can reduce soil quality. Proper management can improve soil quality, Jatipurno has management such as organic, semi-organic and inorganic paddy field management which have a real effect on soil quality. Assessment of soil quality is measured by physical, chemical and biological indicators, where each factor has a different effect. The chemical indicators are often used as the main indicators for determining soil quality, whereas every parameter has the opportunity to be the main indicator. So, biological indicators can play indicators. The main indicators are obtained from the correlation test (p-values &le; 0,05 - &lt; 0,01) and Principal Component Analysis with high value, eigenvalues &gt; 1 have the potential to be used as Minimum Data Sets. The result is biological can be able to use as the Minimum Data Set such as microbial carbon biomass, respiration, and total bacterial colonies. The Soil Quality Index (SQI) of various paddy management practices shows very low to low soil quality values. The management of organic rice systems shows better Soil Quality Index with a score of 0,20 compared to other management. The practice of organic rice management shows that it can improve soil quality.

scholarly journals Soil Quality at Rice Fields with Organic, Semi-organic and Inorganic Management in Wonogiri Regency, Indonesia

2021 ◽  
Vol 36 (2) ◽  
pp. 259
Author(s):  
Supriyadi Supriyadi ◽  
Intan Lestari Prima Vera ◽  
Purwanto Purwanto
Keyword(s):  
Soil Quality ◽  
Rice Field ◽  
Public Awareness ◽  
Pearson Correlation ◽  
Principal Component ◽  
Rice Fields ◽  
Soil Conditions ◽  
Soil Quality Index ◽  
Data Set ◽  
Organic Rice

The high demand of rice is fulfilled by intensification, particularly with the use of chemical fertilizer that allegedly causes land and environmental problems in a long term. As public awareness of environmental health rises, more rice fields are managed organically and semi-organically, but there are still many that manage rice fields inorganically. Assessment of soil quality of the three types of rice field management is important to prove that organic rice fields have better soil quality than semi-organic and inorganic rice fields, as well as to evaluate soil conditions on the location. This research was conducted in Girimarto, Wonogiri, Indonesia, using a descriptive explorative method with a survey approach on three points of each management system of rice fields, which are organic, semi-organic and inorganic rice fields. Statistical analysis was performed by Pearson correlation analysis and principal component analysis (PCA) to determine the indicators affecting soil quality, which are called the minimum data set (MDS). There were selected indicators in this research, including total microbes, base saturation, cation exchangeable capacity and organic carbon. Based on the results of the study, organic rice fields have the best soil quality with a score of soil quality index (SQI) of 2.3, compared to semi-organic rice field SQI (2.2) and inorganic rice field SQI (1.7). The results indicate that organic management contributes to better soil quality and environment.

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 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 Soil Fertility Analysis for the Cultivation of Sugarcane and Rice in Thiruvarur Area

2018 ◽  
Vol 6 (3) ◽  
pp. 407-420
Author(s):  
M. Shanmuganathan ◽  
A. Rajendran
Keyword(s):  
Soil Quality ◽  
Quality Index ◽  
Cost Effective ◽  
Quality Parameters ◽  
Rice Soil ◽  
Quality Indices ◽  
Soil Quality Index ◽  
Time Saving ◽  
Soil System ◽  
Fertility Analysis

In order to improve the yield of any crop, it is absolutely essential to carry out soil testing periodically. This will not only improve the procurement but also will provide eco-friendly ambience. Testing all soil quality parameters will be a laborious and time-consuming process. To overcome this problem, soli quality index can be of immense help. Unlike many water quality indices available, only a very few soil quality indices are in existence. Newly developed soil quality index called Heber soil quality index (HSQI) is widely used to identify and differentiate the various types of soils. The HSQI values of all samples were found to be in the range of 72.36 – 83.83 divulging a fact that the nature of soils inspected in this examination is good for the plantation of sugarcane and rice. The index was found to be time saving and cost-effective method of assessing the fertile nature of the soil for the effective farming of sugarcane and rice. Soil quality assessment in the light of HSQI is proposed to offer a better perceptive of the soil property measures to be taken to improve the quality of soil system for the better yield of any crop including sugarcane and rice.

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