scholarly journals Determination of soil fertility constraints in two paddy soils of the western highland zone of Cameroon

2021 ◽  
Vol 6 (3) ◽  
pp. 268-276
Author(s):  
Ngoucheme Mamouda ◽  
Tabi Fritz Oben ◽  
Lontsi Meli Gilles Raoul ◽  
Yerima Bernard Palmer Kfuban
Keyword(s):  
Soil Fertility ◽  
Soil Quality ◽  
Total Nitrogen ◽  
Pearson Correlation ◽  
Principal Component ◽  
Paddy Soils ◽  
Soil Quality Index ◽  
Data Set ◽  
Management Interventions ◽  
Basic Cations

Information on soil fertility status and variability are essential in understanding the potential of soils and their management interventions in agriculture. The present study aimed at examining the soil quality or fertility of two paddy soils with different productivity in the Western Highland Zone of Cameroon. Twelve soil samples were collected in each of both study location at a standard depth of 0-30 cm and analyzed to find soil texture, Organic Carbon (OC), basic cations (Calcium Ca, Magnesium Mg, Potassium K and Sodium Na), Cation Exchange Capacity (CEC), soil pH, phosphorus (P), and Total Nitrogen (TN). Most measured soil characteristics showed different degrees of variability in soil nutrients ranging from low to very high in both soils. Both soils were acidic (pH <5.5), consistently deficient in total nitrogen, phosphorus, basic cations, and had high OC and CEC. Pearson correlation analysis and principal component analysis were used to identify appropriate soil quality indicators. P and Na in Koutaba and P, Mg, and CEC in Santchou constituted minimum data set (MDS) and accounted for 94% and 100% of the quality variation among soils. A Soil Quality Index (SQI) was developed base on the MSD method, Santchou and Koutaba received SQI of 0.48 and 0.73. The paddy soils of Koutaba were more fertile than those of Santchou. The low level of P and Mg were considered to be the major constraints limiting the productivity in both locations. These results suggest that, the management of inherent soil properties is based on-site specific situations.

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 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 Mapping Soil Quality in Various Land Uses as a Basis for Soil Management in Wonogiri, Indonesia

2020 ◽  
Vol 11 (2) ◽  
pp. 127-135
Author(s):  
Mujiyo MUJIYO ◽  
Suntoro SUNTORO ◽  
Restu Prasetyaning TYAS ◽  
Aktavia HERAWATI ◽  
Hery WIDIJANTO
Keyword(s):  
Land Use ◽  
Soil Quality ◽  
Microbial Biomass Carbon ◽  
Principal Component ◽  
Soil Management ◽  
Agroforestry System ◽  
Land Uses ◽  
Soil Quality Index ◽  
Data Set ◽  
Quality Status

Soil quality is closely related to environment because soil is not only viewed as a growing media for plants but also encompasses various environmental and health functions. It is important to know the quality of soil in order to keep it healthy, productive, and optimally functioning. This research aims to evaluate soil quality status in various land uses and to learn the land factors that are related to soil quality. Soil quality index (SQI) represents the soil quality status. SQI will then be used as the basis for soil management. A descriptive explorative research study was carried out in the Giritontro Sub-district, Wonogiri District, Indonesia. SQI indicators were obtained from 12 existing Land Mapping Units (LMU). SQI was obtained by determining the Minimum Data Set (MDS) with a Principal Component Analysis (PCA) test. Then SQI was mapped and statistically analyzed to determine the influence of land use and the determinant factors of SQI. Results showed that SQI in all area is class 3 or moderate. SQI was significantly influenced by land use. SQI in paddy field is 9.09% higher than crop fields and 2.27% higher than of plantations. Indicators which are significantly related to SQI are bulk density, porosity, cation exchange capacity, available P, available K and microbial biomass carbon (MBC). The type of soil management that can be implemented to improve soil quality includes addition of organic or inorganic fertilizer and adoption of an agroforestry system.

scholarly journals Assessment of Paddy Soil Quality Index Based on Differences in the Productivity of Paddy in Wonogiri Regency

2017 ◽  
Vol 5 (2) ◽  
pp. 181
Author(s):  
Supriyadi Darsowiyono ◽  
Retno Rosariastuti ◽  
Pranoto Pranoto ◽  
Fitria Okvitasari
Keyword(s):  
Soil Quality ◽  
Paddy Field ◽  
Principal Component ◽  
Soil Improvement ◽  
Soil Quality Index ◽  
Data Set ◽  
Diverse Range ◽  
Available N ◽  
Cultivation Practices ◽  
Using Data

Rice or paddy is a staple food in some countries. The need for food is huge as the population growth increase, in Wonogiri regency majority of the land area is used as paddy field and land intensification is done to improve productivity. Land intensification raises the issues of having no definitive measure about the status of soil improvement after the cultivation practices of Paddy (Oryza sativa) has been done, in addition, the diversity of age utilization of paddy field by farmers resulting the differences in productivity that will affect the quality difference of the paddy field soil. The assessment is aimed to determine the soil quality function whether it’s good or bad after doing such land cultivation practices for a certain period. The assessment of soil quality is using data analysis method from the influential indicators based on the nature of at least the Minimum Data Set (MDS) that is obtained based on calculations of Principal Component Analysis (PCA). Indicators that affect, such as, C-Organic,Bulk Density, K-Available, N-Total, and average soil quality were obtained at all points of the sample with a diverse range of values. With the known SQI values, in the future the efforts to maintain and improve the quality of the soil can be done by considering several important factors.

Soil quality assessment of vegetation restoration after a large forest fire in Daxing’anling, northeast China

2020 ◽  
pp. 1-13 ◽  
Author(s):  
Lihong Wang ◽  
Qiang Fu
Keyword(s):  
Microbial Biomass ◽  
Soil Quality ◽  
Forest Fires ◽  
Microbial Biomass Carbon ◽  
Principal Component ◽  
Vegetation Restoration ◽  
Soil Quality Index ◽  
Data Set ◽  
Microbial Biomass Nitrogen ◽  
A Value

Forest fires significantly change soil function and quality. Finding an effective way to accelerate the restoration of soil quality after forest fires is a major issue. This study investigated the soil quality index (SQI) during vegetation restoration after a fire in a Larix gmelinii plantation, throughout different restoration years. Fifteen physical, chemical, and biological properties of soil were examined using principal component analysis, and soil quality was assessed by SQI. The results revealed that soil physical properties, chemical properties, and enzyme activities showed the most improvement after 24 yr of restoration. Soil microbial biomass carbon content and microbial biomass nitrogen content increased with restoration years. Soil bulk density, microbial biomass nitrogen, sucrase, and catalase were retained in the minimum data set. After 24 yr of restoration, SQI was the highest, with a value of 0.52, followed by natural restoration, 21, 13, and 16 yr; the SQI after 3 yr of restoration was the lowest, with a value of 0.26. Artificial regeneration accelerated the recovery of soil quality after 24 yr. Soil quality should be monitored continuously in the study area.

scholarly journals Soil quality in volcanic soils in a forest biosphere reserve in Mexico

2021 ◽  
Author(s):  
Yaselda Chavarin-Pineda ◽  
Eduardo C. Reynoso ◽  
Eduardo Torres ◽  
Gerardo Cruz-Flores ◽  
Ma. Guadalupe Tenorio-Arvide ◽  
...  
Keyword(s):  
Soil Quality ◽  
Stakeholder Management ◽  
Biosphere Reserve ◽  
Principal Component ◽  
Pine Forest ◽  
Soil Conditions ◽  
Volcanic Soils ◽  
Soil Quality Index ◽  
Data Set ◽  
Significant Difference

Forest soils respond dramatically to management changes compared to other soils influenced by different land-use forms. This work aimed to compare the soil conditions in four different zones in a temperate forest in a biosphere reserve in Mexico, using a minimum data set (MDS) based on volcanic soils properties to develop a soil quality index (SQI). For this purpose, two different MDSs were used, one obtained from an expert opinion and the other through a multivariate principal component analysis (PCA). The soil quality assessment was conducted in a biosphere reserve in Mexico, where volcanic soils predominate. Four different areas were studied. Overall, six different types of SQI were calculated for each area, for which linear and nonlinear functions were used and the additive and weighted method. The six SQI showed a significant difference between the four areas of study. The zone with the highest SQI values was the zone with a preserved pine forest, followed by the zone with a pine forest managed by the population, and the zones with a pine forest and grassland in recovery showed the lowest SQI. The linear score indices obtained by the PCA indicated the better ability to differentiate the calculated SQI values, which would provide information to contribute to the stakeholder management and decision making in the protection, conservation and management of the ecosystems present in the biosphere reserve.

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 Evaluasi Kualitas Tanah Sawah Intensif dan Sawah yang Dikonversikan untuk Kebun di Subak Kesiut Kerambitan Tabanan

2020 ◽  
Vol 10 (1) ◽  
pp. 1
Author(s):  
I DEWA MADE ARTHAGAMA ◽  
I MADE DANA
Keyword(s):  
Soil Quality ◽  
Paddy Soil ◽  
Field Survey ◽  
Research Area ◽  
Paddy Soils ◽  
Minimum Data Set ◽  
Data Set ◽  
Minimum Data ◽  
Better Than

 Evaluation Quality of Intensif Paddy Soils and Conversion Paddy Soils to Garden at Subak Kesiut Kerambitan Tabanan. This experiment conducted to evaluate intensif Paddy Soils and conversion paddy soils to garden at SubakKesiut Kerambitan Tabanan. There were two steps applied in this study including field survey to determine the research area and points soils sampling; analysis soils properties are: physic, chemistry and soils biology for get minimum data set to determine the soil quality at Laboratory of Soils and Enveronment Faculty of Agriculture Unud. The results of this study showed: the soil quality of intensif paddy soils is better than conversion paddy soils to garden, that showed with SQR at intensif paddy soil is 18 and at conversions paddy soil is 25. The limiting faktor at conversion paddy soils to garden is P available, there are less than at intensif paddy soils.

scholarly journals Using Soil Survey Database to Assess Soil Quality in the Heterogeneous Taihang Mountains, North China

2018 ◽  
Vol 10 (10) ◽  
pp. 3443 ◽  
Author(s):  
Shoubao Geng ◽  
Peili Shi ◽  
Ning Zong ◽  
Wanrui Zhu
Keyword(s):  
Land Cover ◽  
Soil Quality ◽  
Soil Type ◽  
Quality Evaluation ◽  
Vegetation Index ◽  
Controlling Factors ◽  
Soil Survey ◽  
Boosted Regression Trees ◽  
Soil Quality Index ◽  
Data Set

Soil quality evaluation is an effective pathway to understanding the status of soil function and ecosystem productivity. Numerous studies have been made in managed ecosystems and land cover to quantify its effects on soil quality. However, little is coincident regarding soil quality assessment methods and its compatibility in highly heterogeneous soil. This paper used the soil survey database of Taihang Mountains as a case study to: (i) Examine the feasibility of soil quality evaluation with two different indicator methods: Total data set (TDS) and minimum data set (MDS); and (ii) analyze the controlling factors of regional soil quality. Principal component analysis (PCA) and the entropy method were used to calculate soil quality index (SQI). SQI values assessed from the TDS and MDS methods were both significantly correlated with normalized difference vegetation index (p < 0.001), suggesting that both indices were effective to describe soil quality and reflect vegetation growth status. However, the TDS method represented a slightly more accurate assessment than MDS in terms of variance explanation. Boosted regression trees (BRT) models and path analysis showed that soil type and land cover were the most important controlling factors of soil quality, within which soil type had the greatest direct effect and land cover had the most indirect effect. Compared to MDS, TDS is a more sensitive method for assessing regional soil quality, especially in heterogeneous mountains. Soil type is the fundamental factor to determining soil quality. Vegetation and land cover indirectly modulate soil properties and soil quality.

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