Soil Quality Assessment Research Articles

Assessment of soil quality in texturally different and salt-affected soils of trans-gangetic plains of India

Assessment of soil quality in texturally different and salt-affected soils of trans-gangetic plains of India

Assessing the Influences of Grassland Degradation on Soil Quality Through Different Minimum Data Sets in Southwest China

Establishing a suitable and useful soil quality (SQ) assessment tool is imperative for the accurate evaluation of the effect of environmental changes on SQ. This study constructed four soil quality indexes (SQIs) based on different minimum data sets and weighted additive models to evaluate the influence of grassland degradation on SQ in northwest Guizhou, China. A total of 19 soil properties, including six physical properties, six chemical properties, and seven microbial properties, were measured at soil depths 0–20 cm to construct the SQIs. Results showed that 18 soil indicators were selected as the potential SQ indicators in the total data set. Based on the principal component analysis, four indicators, soil organic carbon (SOC), mean weight diameter, α-glucosidase, and β-acetylglucosaminidase, were selected in the minimum data set (MDS). However, six indicators, SOC, pH, β-1,4-xylosidase, β-acetylglucosaminidase, Clay, and Bulk Density, were selected for the selective MDS. Despite the notable inter-correlation among the four established SQIs, the SQI derived from the selective MDS and weighted additive model demonstrated heightened sensitivity and capacity for differentiation with respect to grassland degradation because of the high values of F and CV. Grassland degradation significantly reduced the SQ, and the value of SQ under severely degraded grassland was reduced by 51% compared with that under non-degraded grassland. Under the lightly degraded grassland, the reduction in soil physical quality was the primary reason for the total SQ decline, while the reduction in soil microbial and chemical reduction resulted in a significant decline in total SQ under the severely degraded grassland. In conclusion, greater attention should be paid to the SQ reduction resulting from grassland degradation in the study area, and the SQI established by selective MDS and weighted additive model should be used as a suitable and useful SQ assessment tool to evaluate the influence of environmental changes on SQ in Southwest China and other similar areas.

Relationship Between the Integral Indicator of Soil Quality and the Cadastral Value of Agricultural Lands

In the current conditions of development of the country’s market economy, the methodological support for cadastral land valuation requires effective modernization and improvement of the existing mechanisms for determining cadastral value for a fair distribution of land tax among landowners. In this regard, the aim of the study was to develop a methodology for taking into account the qualitative state of soils in the cadastral valuation of agricultural lands in the conditions of an active land market, as well as to modernize the method for taking into account the quality of soils within the framework of the income approach in the conditions of a depressed land market. The study was conducted based on a set of scientific methods: the analytical method was used to conduct an analysis of the scientific review of the problem area and to substantiate the relevance of the study, a cycle of laboratory experiments was conducted using mechanical and chemical analyses, the construction of thematic maps was carried out using the dispersion method, the regression modeling method was used to determine the cadastral value of garden plots, and the land rent capitalization method was used to calculate the cadastral value of agricultural land. Research results were as follows: Methodological recommendations were provided for taking into account the quality of soils in the form of an integral indicator of physical and chemical properties in the model for calculating the specific indicator of cadastral value (SICV) of garden and vegetable lands in the conditions of an active land market. The method of accounting for the qualitative state of soil fertility in the form of a weighted quality score of an agricultural land plot was modernized when determining the specific gross income within the framework of the land rent capitalization method used to calculate the SICV. Based on field work and laboratory experiments, current indicators of soil fertility status were obtained, and soil quality scores for Saint Petersburg were calculated. The possibility of using an integral indicator (soil quality score) as a cost factor instead of a large number of fertility status indicators was proven. Also, models for calculating the SICV of garden and vegetable plots were built for the conditions of an active land market, according to which the cadastral value of land plots in Saint Petersburg was calculated for subsequent land taxation. For agricultural lands, using the example of a land plot of a high-commodity agricultural enterprise (Leningrad Region), the cadastral value was also calculated using the proposed income approach method. The scientific significance of the study lies in the improvement of the methodological foundations of cadastral valuation, as well as the technology of taking into account the quality of soils when calculating the cadastral value. The practical significance of the study lies in the applicability of the results of soil quality assessment and models for calculating the SICV for land taxation; individual market valuation for lending, purchase, and sale; lease of agricultural land; and allocation of land plots on account of a land share. In the area of developing a set of melioration measures on agricultural lands, including the development and implementation of agricultural technologies and technical means to improve soil fertility, the results of laboratory studies to determine the physical and chemical properties of soils can be used. The obtained soil quality scores for Saint Petersburg are also applicable to identifying unused and degraded lands for their transfer to other types of use.

Impacts of Climate Change on Agriculture Production in Lam Dong- Vietnam

Purpose: The study aims to investigate how climate change affects the production of key agricultural products tea, coffee, and vegetables in Lam Dong province. The research focuses on assessing specific impacts such as temperature rise, unpredictable rainfall, and extreme weather on crop yield, quality, and farmers’ livelihoods. Additionally, it seeks to propose adaptive strategies to mitigate these impacts while promoting sustainable agricultural practices. Methodology: The study uses a mixed-method approach: Quantitative analysis: Utilizes historical climate data, crop yield records, and soil quality assessments from Lam Dong over the past two decades. Qualitative research: Involves surveys and interviews with local farmers, agronomists, and policymakers to understand on-ground challenges and perceptions of climate change. Geospatial tools: Geographic Information Systems (GIS) and remote sensing are applied to map vulnerable areas and predict future impacts under different climate scenarios. Findings: Rising temperatures and erratic rainfall patterns have led to reduced tea and coffee yields and have disrupted vegetable production cycles. Pests and diseases have become more prevalent, further threatening crops. Smallholder farmers are disproportionately affected due to limited access to resources and technology. However, some opportunities exist, such as shifting cultivation to higher altitudes for coffee and adopting heat-resistant vegetable varieties. Unique Contribution to Theory, Policy Implications and Practical Contributions: This study highlights the intersection of climate science, agriculture, and socioeconomics in a region-specific context, offering insights into how microclimates within Lam Dong interact with global climate trends. It contributes to the broader understanding of climate adaptation in tropical highland agriculture. The study provides practical recommendations for farmers, including diversification of crops, use of precision farming technologies, and strategies for integrated pest and water management. It also emphasizes community-based approaches for knowledge-sharing and collaborative adaptation efforts. In summary, the research offers a comprehensive analysis of the challenges posed by climate change to tea, coffee, and vegetable production in Lam Dong and serves as a foundation for informed decision-making and strategic planning in agriculture.

Corn Cultivation and Its Relationship with Soil Quality: A Focus on Soil Quality Index Methodologies

Corn is a globally important crop, requiring extensive soils and intensive practices to meet the growing human and animal consumption demand. However, intensive agriculture has caused soil deterioration and fertility loss. In response, the Mexican government established the National Soil Strategy for Sustainable Agriculture (ENASAS, acronym in Spanish) to ensure food security and maintain soil fertility. This study develops “Soil Quality Indexes” (SQI) to monitor soil quality under corn cultivation using four methodologies (additive (SQIa), weighted (SQIw), unified weighted (SQIu), and Nemoro (SQIn)) in the Bajio region of Guanajuato, Mexico. Twenty-four physicochemical indicators were analyzed, with four (CLY, WHC, Na, and C/N) identified as key indicators of soil quality and fertility through principal component analysis. Among these, SQIa was the most sensitive and efficient (SI = 2.32, ER = 50) in assessing soil quality, showing values from very low to low (SQIa=0.13 and SQIa=0.39 respectively). Aligned with the ENASAS program, SQIa can help monitor and improve soil quality under corn cultivation, supporting food security through soil conservation. Moreover, SQIa performed similarly to the globally recognized Soil Management Assessment Framework (SMAF), making it a valuable tool for managing and improving agricultural soil quality under similar conditions in both Mexico and worldwide.

Soil quality, risk assessment and source identification of heavy metals in native and improved paddy soil and rice grains from Tamil Nadu, India.

The present study aims to assess the soil quality, source analysis, and risk assessment of heavy metals in native and improved rice paddies in Tamil Nadu, India. The mean values of DTPA-extractable heavy metallevels in native paddy soil were 0.06, 0.52, 2.61, 3.15, 0.48, 39.48, 97.61mgkg-1, while improved paddy soil had values of0.11, 1.98, 0.91, 3.21, 1.54, 20.30, 7.78mgkg-1 for Cd, Pb, Ni, Cu, Zn, Fe and Mn. These levels were belowthe acceptable limits set by Indian and European Union soil quality guidelines. All native rice varieties had grain Pb concentration ranging from 0.71 to 1.34mgkg-1, but all improved rice varieties had higher levels of Cd, Pb, and Fe thenprescribed limits. Nemerow pollution index (NPI) level of Ni indicated high pollution in native soil. Potential ecological risk index (RI) values of Cd indicated moderate risk in improved soil. Based on the EF and TF values, the paddy fields and rice plants are classified as 'severe enrichment' and 'accumulator' of heavy metals (Cd and Pb), respectively. The HI and THQ levels (Ni, Cd and Pb) were > 1 for both adults and children. Principal component analysis (PCA) found that PC1 eigenvalue of 5.63 (40.21%) and 6.91 (49.37%) and PC2 with 4.84 eigenvalue of 5.63 (34.56%) and 3.97 (28.37%) for native and improved soil, respectively, while cluster analysis (CA) revealed three distinct groups between the metals studied.

Identifying Key Indicators for Soil Quality Assessment in Reclaimed Loess Coal Mining Areas of China: A Case Study of the Suancigou Coal Mine, Inner Mongolia

ABSTRACTMining activities cause severe degradation of soil structure and nutrient loss, making land reclamation a crucial measure for restoring ecosystem functions in mining areas. Investigating the key indicators of reconstructed soil quality and their succession patterns enables a robust assessment of reclamation measures, providing a scientific basis for optimising land reclamation strategies and ecological management in mining regions. Existing studies on soil quality assessment have primarily focused on general evaluations, with limited attention given to the specific challenges associated with reconstructed soils in reclaimed underground coal mine areas. This study examines the reclaimed land of the Suancigou coal mine in Inner Mongolia, China. Ten soil physicochemical properties were selected as potential evaluation indicators. Through correlation analysis and principal component analysis, a minimum data set (MDS) was identified for assessing soil quality in reclaimed lands, and a soil quality index (SQI) was subsequently constructed. The findings revealed that: (1) reconstructed soils of different reclamation ages exhibit significant discrepancies in physicochemical properties at the 0‐10 cm and 10‐20 cm depths compared to the original landscape. Despite variations in correlations among soil properties across depths, total nitrogen content (TNC), soil organic matter (SOM), hydrolysable nitrogen and available phosphorus consistently display strong synergistic relationships. (2) The overall quality of the 0‐20 cm reconstructed soil is primarily influenced by pH, soil sand content (SSD), soil silt content (SST) and TNC. Specifically, the MDS for the 0‐10 cm soil layer includes bulk density, SSD, SST and TNC, whereas for the 10‐20 cm layer, the MDS comprises pH, SSD, SST and SOM. (3) The comprehensive soil quality assessment followed the order: OL > R‐7a > R‐11a > R‐3a. By quantifying the interrelationships among soil attributes in reclaimed lands, this study streamlines the soil quality evaluation system, offering theoretical foundations and technical support for evaluating reconstructed soils and optimising land reclamation in mining areas.

Assessing soil quality in association with frozen ground in the source areas of the Yangtze and Yellow Rivers, Qinghai-Tibet Plateau

Assessing soil quality in association with frozen ground in the source areas of the Yangtze and Yellow Rivers, Qinghai-Tibet Plateau

Mapping surface soil organic carbon in the coal–grain composite area: threshold and interaction effects of coal mining activities

BackgroundIn China, the coal–grain composite area accounts for more than 40% of the total cultivated land area, and its soil organic carbon (SOC) content profoundly impacts soil health and food security. However, underground coal mining causes surface subsidence, farmland degradation, and a decline in the SOC pool, severely threatening soil security and long-term crop productivity. Accurately mapping SOC in the coal–grain composite areas is crucial for assessing soil quality and estimating carbon emissions. However, existing studies rarely consider the adverse impacts of mining activities, and the threshold and interaction effects of environmental variables have not been thoroughly investigated. Using 294 samples collected in Peixian county, a typical coal–grain composite area, this study aimed to apply the gradient boosting decision tree (GBDT) model and partial dependence plot to explore the threshold and interaction effects between environmental variables and SOC content, and obtain a spatial map of SOC content.ResultsThe results of the GBDT model showed that SOC content was high in the eastern part and low in the western part, which was mainly influenced by land use, mean annual precipitation, distance from the lake, and distance from mining land. Environmental variables exhibited threshold effects on SOC. For instance, the SOC content increased with distance from the mining area, and increased significantly beyond 15.9 km, indicating that the average effective influence range of mining land was 15.9 km. Similarly, the effective influence ranges of the lake, and irrigated ditch were 23.4 km and 0.2 km, respectively. The interaction effect plots showed that environmental variables were not independent but had complex interactions.ConclusionsThese results highlight the importance of introducing mining activities and considering threshold and interaction effects, which help to understand the spatial pattern of SOC in the coal–grain composite areas.

Using Artificial Intelligence Algorithms to Analyze Chromatic Attributes for Soil Quality Indicators

Abstract The aim of this study is to estimate soil quality using observable soil color, thereby simplifying the assessment process that traditionally requires expert intervention and extensive analysis. A total of 324 soil samples were collected from a depth of 0–20 cm in the Konya Çumra Plain. These samples underwent color readings and principal component analysis. To estimate soil quality, three different scoring methods Soil Management Assessment Framework (SMAF), (Comprehensive Assessment of Soil Health) CASH, and Linear scoring were employed. The soil quality indicators identified by the analysis include clay, organic carbon, active carbon, calcium, available phosphorus, potassium, available water capacity, and potentially mineralizable nitrogen. The average soil quality scores calculated using SMAF, CASH, and Linear scoring were 0.73, 0.43, and 0.65, respectively. Artificial Neural Network (ANN) analysis revealed R2 values of 0.18 for SMAF, 0.32 for CASH, and 0.70 for Linear scoring. The study shows that soil color can be used to predict soil quality with a high degree of accuracy, with the Linear scoring function being the most effective for soil quality assessments. The results highlight the potential of artificial intelligence (AI) algorithms in facilitating rapid and efficient prediction of soil quality. By leveraging the synergy between observable soil characteristics and advanced AI methodologies, this research simplifies soil quality assessment and enables more accessible and scalable environmental analysis.

Development of soil quality assessment framework: A comprehensive review of indicators, functions, and approaches

Development of soil quality assessment framework: A comprehensive review of indicators, functions, and approaches

Soil quality assessment of greenhouse vegetable production in Ningxia—A low‐contaminated and high‐quality crop base

AbstractDeclining soil nutrients and increasing total metals impair optimum land productivity. Understanding the spatial and temporal variabilities of soil properties helps researchers and farmers to determine the soil's ecological status and provide science‐based recommendations for fertilization, crop suitability, and land use. Ningxia has less industrial waste gas and water pollution, good ecological environment, and is an important green vegetable planting base in China. This study was conducted to investigate the spatial and temporal variabilities of soil nutrients and metal elements in greenhouse conditions. All soil samples were alkaline. The concentration of soil nutrients and metal elements was concentrated in the soil surface (0–30 cm) and increased with cultivation years. A significant difference was observed between the soil planted for more than 11 years and that planted for 0 year (open field). A total of 76.8% of the soil samples’ organic matter concentration had relatively low (10–20 g/kg) and medium grades (20–30 g/kg). And 100% and 84.5% of soil samples’ total nitrogen and available nitrogen concentrations were <40 and <200 mg/kg, respectively, at 0–30 cm. And 68.3% and 95.1% of soil samples’ available potassium (>120 mg/kg) and phosphorus (>20 mg/kg) contents were relatively high and high, respectively. Nearly all soil samples have low metal element concentrations. The soil properties in the Yellow River irrigation region were higher than those in the other areas of principal component 1 (PC1). Comprehensive soil quality in Ningxia showed alkaline conditions and high potassium and phosphorus, along with suitable amounts of available nitrogen and zinc, making it ideal for high‐quality greenhouse vegetable production.

Visual soil assessment as an early indicator of soil quality in the caatinga dry tropical forest under varying degrees of disturbance in the Brazilian semiarid region.

Visual soil assessment as an early indicator of soil quality in the caatinga dry tropical forest under varying degrees of disturbance in the Brazilian semiarid region.

Environmental safety assessment of soils in Khmelnytskyi region based on chemical composition and acidity analysis

Purpose. Environmental safety assessment of Khmelnytskyi region based on a comprehensive analysis of soil chemical composition and acidity for identifying potential environmental risks. Methodology. For soil quality assessment, soil samples were collected and analyzed in accordance with established and approved methods. X-ray fluorescence spectrometry (XRF) was used to determine the chemical content of the soil. The acidity of the soil was determined by measuring the actual acidity in the water extract and the potential acidity in the salt extract. Sampling was carried out on the territory of Derazhnyanska ATC, considering different types of land use. The pollution index (PI) was calculated to assess the level of soil pollution, which compares the actual concentration of chemical elements with the reference values. The spatial variability of chemical element concentrations and acidity indicators was investigated, and appropriate cartographic models of these parameters distribution were created within the study area. Findings. The research of light gray podzolized soils of the Derazhnyanska ATC of Khmelnytskyi region was used to determine the chemical content and acidity of the selected samples. The analysis of the chemical composition of the soil using XRF analysis revealed significant spatial variability in the concentrations of elements, but their content did not exceed the maximum permissible limits. Measurements of the actual acidity in the water extract showed a predominantly neutral or close to neutral reaction of the medium (pH 6.9‒7.9), which is favorable for most crops. However, the determination of potential acidity in the salt extract revealed a wider range of pH values (4.5‒7.2), including samples with an acidic reaction, which may indicate the need for liming of some areas. The calculation of the pollution index showed that most of the studied elements are in the moderate pollution category (1 < PI  3), with the highest values for Ti, V and Pb, indicating potential environmental risks and further monitoring is required. Originality. The first comprehensive assessment of the environmental safety of soils in the Derazhnyanska ATC of Khmelnytskyi region was conducted on the basis of a complex analysis of chemical composition and acidity. A methodology for assessing environmental risk, which takes into account the correlation between the concentration of chemical elements, soil acidity, and environmental safety, was developed and tested. Practical value. The investigation of environmental safety based on the analysis of the chemical composition and acidity of soils in Khmelnytskyi region is important for the sustainable development of the region and environmental protection. The obtained data provide an opportunity to assess the level of anthropogenic pressure on the ecosystem and develop effective measures to improve the ecological state of soils. Identification of areas with high content of pollutants and abnormal acidity allows for targeted environmental protection measures and optimization of agricultural activities, considering environmental risks.

Integration of In Situ and Sentinel-2 Data to Assess Soil Quality in Forest Monitoring: The Case Study of the Vesuvius Fires

The climatic conditions in southern Italy favor the occurrence and spread of forest fires, with severe long-lasting consequences on the local flora and fauna. On the one hand, biological and chemical in situ measurements are typically used to accurately investigate the evolution of the land affected by fires, with limited spatial coverage. On the other hand, Remote Sensing (RS) is a mature technology to complement the in situ campaigns on large regions with adequate revisit time. In this paper, we evaluate the capability of Sentinel-2 data to spatially and temporally extend post-fire in situ analysis on a fire-affected area. In particular, we estimate the soil quality index from Sentinel-2 data and achieve a remarkable coefficient of determination (R2=0.79) and low relative error (er=0.06), highlighting the robustness of the proposed approach. Furthermore, the soil water content and the total iron (Fe) concentrations emerged as pertinent indicators detectable through Near-Infrared and Short-Wave Infrared Sentinel-2 bands. The obtained results prompted an investigation into the post-fire evolution of soil properties, thanks to RS data, in a large area covered by diverse vegetation types. The obtained results encourage a deeper synergic use of in situ and remotely observed data, enabling a comprehensive understanding of soil quality dynamics in fire-affected regions.

Utilisation of Coal Clinker Ash in Transforming the Carbon Content of Sandy Soil

Soil carbon (C)’s importance in soil quality assessment and C sequestration is increasing. Sandy soils, due to their low C content, have low C sequestration potential and therefore require C enhancement. This study aimed to enhance sandy soils’ C content and sesame (Sesamum indicum L.) productivity by applying clinker ash (CA). A 3-year experiment with a completely randomised block design was conducted in an improvised field. Four treatments were replicated six times: Control (sandy only), CA1 (3 mm at 25 t ha−1), CA2 (5 mm at 25 t ha−1), and rice husk biochar as a positive control (14 t ha−1). Hairy vetch (Vicia villosa R.) was the source of plant nutrients incorporated as green manure. C content and fractions were determined from dry soil collected at each harvesting time. There were significant increases in the C content of sandy soil under CA1, with about 129 and 289% change compared to the control in season 1 and season 3, respectively. Also, the C fractions and CN ratio were significantly enhanced by CA1. CA2 improved the yield of sesame by 424 and 64% in season 2 and season 3, respectively. Applying CA to sandy soils improved the C content, increasing C sequestration capabilities, a key climate mitigation strategy.

Geochemical Background Values for the Characterization of Sediment Contamination with Trace Elements in Romania: A Case Study in the Lower Danube Basin

The contamination of the Lower Danube Basin with trace elements has been the subject of intense study in recent years, with several pollution indices being employed for the assessment of water, soil, and sediment quality. Most pollution indices are calculated by comparing the measured concentration to a reference value, with different values from various sources being used. In this study, the threshold values for trace elements (As, Cd, Cu, Hg, Ni, Pb, and Zn) in Romania were selected based on the median of their concentration in stream sediment from 167 locations, which were carefully selected to be far from contamination sources. The threshold values were established based on a calculation starting from the geochemical concentration presented in the Geochemical Atlas of Romania (scale: 1:3,000,000, developed in 2006 by a collaborative Romanian-German team). By using these thresholds, pollution indices were calculated for nine sampling locations, from which suspended sediment, bottom sediment, and active floodplain sediment samples were collected and analyzed in an accredited laboratory. Most of the selected thresholds were found to be below the limits for sediments established by Romanian legislation, except for Cr and Ni, the higher values of which are consistent with the specific geological background of the country and the broader Balkan region.

Decoding Soil Color: Origins, Influences, and Methods of Analysis

Soil color serves as a critical indicator of its properties and conditions. It is shaped by a complex interplay of mineral and organic matter content, moisture levels, and other environmental variables. Additionally, human activities such as land-use changes and intensive agricultural practices can profoundly alter soil color. Soil color, driven by the presence of organic matter, plays a crucial role in understanding soil fertility. Its strong correlation with soil organic carbon content makes it a valuable parameter for assessing soil quality in agricultural practices. A variety of techniques have been developed to measure soil color, ranging from traditional Munsell color matching to modern color meters. Digital image colorimetry enables rapid on-site assessments of soil color, but environmental conditions such as soil water content and lighting conditions should be considered. Spectroscopic methods, particularly diffuse reflectance spectroscopy, pave the way for a more reliable and accurate composition analysis. Advances in remote sensing and computational methods are combined to explore the intricate relationships between soil color and environmental factors. Such an integrated approach not only enhances scalability but also leads to more insights and actionable strategies for environmental management and sustainable agriculture.

Assessment of soil quality along the elevation gradient of the Seti River watershed in Pokhara Metropolitan City, Nepal.

Soil quality is essential for sustaining agricultural productivity, globally. Hence, this study evaluated the effects of elevation gradients and soil depths on agricultural land quality in the Seti River watershed, Pokhara Metropolitan City (PMC), Nepal. Using a stratified random sampling method, 60 samples were collected across three elevation gradients (500-700m, 700.1-900m, 900.1-1100m) at depths of 0-15cm and 15-30cm. The soil quality index (SQI) revealed good soil quality across all elevations, with values of 0.88, 0.86, and 0.82 for lower, mid, and higher elevations, respectively, despite variations in individual nutrient levels. Elevated nitrogen (N) and phosphorus (P) levels highlighted the need for regulated fertilizer application. Kruskal-Wallis test identified significant decreases in soil organic matter (SOM) and soil organic carbon (SOC) with increasing elevation. Depth-wise analysis showed that the potential of hydrogen (pH) in the topsoil (0-15cm) was nearly neutral, while the subsoil (15-30cm) exhibited weak acidity. Nutrient concentrations, including N, P, and potassium (K), were significantly higher in the topsoil than in deeper layers, indicating a need for prudent nutrient management to minimize leaching and maintain soil health. Accordingly, PMC soils can be considered favorable for agricultural productivity; however, site-specific management strategies should performed. Reducing excessive fertilizer use in low-elevation areas can prevent nutrient imbalances while monitoring and enhancing SOM in higher elevations through compost or green manure application is recommended. These actions can enhance soil fertility, reduce environmental impacts, and promote agricultural resilience.

Assessing Soil Quality and Biomass Productivity Under Wastewater Irrigation in the Indian Arid Region

Assessing Soil Quality and Biomass Productivity Under Wastewater Irrigation in the Indian Arid Region