Soil Health Assessment Research Articles

Nematode Communities in Soils of the Same Volcanic Origin across a Gradient of Naturalization: From Intensive Agriculture to Forest

Nematodes play a key role in ecological environments. Biotic indices based on soil nematode community are effectively used for assessing soil health status. This work represents the opportunity to investigate three different management practices continuously maintained for 40 or more decades on soils with the same geological origin. This unique feature allows us to reduce variables and link biotic with abiotic factors. Therefore, the nematode communities of three neighboring volcanic soils under different managements were examined. The maximum values in soil biodiversity were found in the forest environment in which all the trophic groups were detected and well balanced. Instead, in permanent grassing and carnation crop greenhouse (CG), biodiversity indices progressively decreased with the intensification of agricultural practices. Furthermore, CG showed a stronger dominance of a specific plant-parasitic nematode identified as Heterodera daverti. Nematode indicators demonstrated that changes in the nematode community gradually varied from anthropic to natural environments whereas soil properties were feebly correlated to nematode community indicators. In conclusion, we demonstrated that biodiversity and ecological indices applied to the soil nematode community are effective at detecting alterations due to anthropogenic impact. Nematodes seem to be susceptible to perceiving the soil dynamics.

A method for evaluating the effects of gentle remediation options (GRO) on soil health: Demonstration at a DDX-contaminated tree nursery in Sweden

Healthy soils provide valuable ecosystem services (ES), but soil contamination can inhibit essential soil functions (SF) and pose risks to human health and the environment. A key advantage of using gentle remediation options (GRO) is the potential for multifunctionality: to both manage risks and improve soil functionality. In this study, an accessible, scientific method for soil health assessment directed towards practitioners and decision-makers in contaminated land management was developed and demonstrated for a field experiment at a DDX-contaminated tree nursery site in Sweden to evaluate the relative effects of GRO on soil health (i.e., the ‘current capacity’ to provide ES). For the set of relevant soil quality indicators (SQI) selected using a simplified logical sieve, GRO treatment was observed to have highly significant effects on many SQI according to statistical analysis due to the strong influence of biochar amendment on the sandy soil and positive effects of nitrogen-fixing leguminous plants. The SQI were grouped within five SF and the relative effects on soil health were evaluated compared to a reference state (experimental control) by calculating quantitative treated-SF indices. Multiple GRO treatments are shown to have statistically significant positive effects on many SF, including pollutant attenuation and degradation, water cycling and storage, nutrient cycling and provisioning, and soil structure and maintenance. The SF were in turn linked to soil-based ES to calculate treated-ES indices and an overall soil health index (SHI), which can provide simplified yet valuable information to decision-makers regarding the effectiveness of GRO. The experimental GRO treatment of the legume mix with biochar amendment and grass mix with biochar amendment are shown to result in statistically significant improvements to soil health, with overall SHI values of 141 % and 128 %, respectively, compared to the reference state of the grass mix without biochar (set to 100 %).

Enzymatic Diagnostics of Soil Health of the European Part of Russia with Lead Contamination

Lead (Pb) is one of the most common environmental pollutants. Lead has an acute toxic effect on soil biotas and the enzymatic system of soils. The objective of this study is to carry out enzymatic diagnostics of soil health in the European part of Russia after Pb contamination. As a part of the simulation experiment, Pb (at maximum permissible concentrations (MPCs) of 1, 10, and 100) was used to contaminate 12 types of soils in the south and center of the European part of Russia, which differed in their physical and chemical properties. To assess soil health, the activity of oxidoreductases (catalase, dehydrogenases, and cysteine reductase) and hydrolases (invertase, urease, and phosphatase) was studied. Most enzymes were inhibited with increased Pb dosage. The most sensitive soils to Pb contamination, assessed by enzyme activity, are soils of semi-deserts and dry steppes. Cysteine reductase is considered the most sensitive enzyme to Pb contamination. The most informative indicators for Pb contamination were phosphatase, cysteine reductase, and invertase. The P (phosphatase) cycle and the redox enzyme (catalase) also have instability in Pb-contaminated soils. The C (invertase and dehydrogenases) and N (urease) cycles do not change significantly when contaminated with lead. The results of this study can be used for the diagnostics of the condition of soils in different natural areas after Pb contamination.

Approaching soil health from a practitioner perspective – Placing practices before indicators for Australian cotton and other producers

AbstractSoil health, how it is defined and characterized, has long been a topic of debate, but its importance has never been in doubt. The FAO has provided a unifying definition of what soil health is, but uncertainty remains as to how it will be measured. While finding suitable soil health indicators remains challenging, there is growing pressure from external drivers on land managers to demonstrate they are valuing their soil health. With these issues in mind, the Australian cotton industry developed a soil health framework with the potential to address both competing demands. Taking a lead from the human health management, which focuses on prevention through promotion of adoptable healthy activity principles, and incorporating principles from the existing soil frameworks, we conceived one that is relevant to Australian cotton farmers. The outcome promotes beneficial but non‐prescriptive land management practices, which have mechanisms in place to financially reward growers for adoption and facilitates industry monitoring. The Soil Health Framework, also has potential for other agricultural sectors and represents a solution to the current impasse over soil health assessment.

Validation of a new gamma ray soil bulk density sensor

AbstractSoil compaction and soil bulk density are key soil properties affecting soil health and soil ecosystem services like crop production, water retention and purification and carbon sequestration. The standard method for soil bulk density measurements using Kopecky rings is very labour intensive, time consuming and leaves notable damage to the field. Accurate data on bulk density are therefore scarce. To enable large‐scale data collection, we tested a new portable gamma ray sensor (RhoC) for in situ field and dry bulk density measurements up to 1 m depth. In this first validation study, measurements with the RhoC‐sensor were compared with classic ring sampling. Measurements were made in two agricultural fields in the Netherlands (a sandy clay loam and a sandy soil), with large variation in subsoil compaction. At 10 locations within each field, three soil density profiles were made. Each profile comprised six depth measurements (every 10 cm from 10 to 60 cm depth) using the RhoC‐sensor and Kopecky rings, resulting in 30 pairwise profiles and 180 measurements in total per field. At an average soil density of 1.5 g/cm3, the relative uncertainty was 9% for the Kopecky rings and 15% for the RhoC‐sensor. Because the RhoC‐sensor is easy and quick to use, the higher relative uncertainty can easily be compensated for by making additional measurements per location. In conclusion, the RhoC‐sensor allows a reliable quantitative in situ assessment of both field and dry bulk density. This provides the much‐needed possibility for rapid and accurate assessment of soil compaction. The acquisition of this data supports the calculation of soil organic carbon stocks and is indispensable for (national) soil monitoring, to assess soil health and to inform sustainable land management practices for sustained or improved soil health and provision of soil ecosystem services, such as requested in the proposed EU Directive on Soil Monitoring and Resilience.

Assessing soil functioning: What is the added value of soil organic carbon quality measurements alongside total organic carbon content?

Soil organic carbon (SOC) content is the most widely used soil health indicator, but many soil functions are also influenced by the quality of SOC. Yet, standardized SOC quality parameters that can be used in soil health assessments in addition to SOC content are still in development. Here, we investigated the relationships between various SOC parameters (both quantity and quality) and soil functions.We collected 223 soil samples from arable fields in two contrasting Dutch soil types i.e., marine clay and sand. For each sample, we assessed three soil functions (i.e., biological population regulation, element cycling, and soil structure and water regulation) by measuring five indicators per function. We also analyzed SOC quality with four techniques (C:N-ratio, POX-C, Rock-Eval, POM-MAOM fractionation), resulting in 21 SOC quality parameters, and measured SOC content. We then determined for each soil type how much variation in each function indicator was explained by the SOC parameters and other measured intrinsic soil properties.We found that SOC parameters and intrinsic soil properties explained at most 30 ± 22% of the variation in soil function indicators. SOC content explained 9 ± 16% of the variation across functions and soil types. Including one single SOC quality parameter alongside SOC content never had significant added value in explaining soil functions. Only including multiple Rock-Eval parameters alongside SOC content significantly increased the explained variation compared to SOC content alone, as well as combining multiple parameters from the four different SOC quality techniques.We conclude that the relationships between the SOC quality parameters and soil functions are insufficiently straight-forward to add significant explanatory power to SOC content alone. We recommend that before including SOC quality parameters in soil health monitoring, more emphasis should be put on evaluating their relation to soil functions and their potential redundancy when used alongside SOC content.

Quantifying the carbon sequestration potential of different soil management practices aimed at increasing organic content in soil and reducing the usage of chemical inputs

<p>The global imperative to address climate change and promote sustainable agriculture has underscored the critical role of soil management practices in enhancing carbon sequestration and reducing greenhouse gas emissions. This research focuses on quantifying the carbon sequestration potential of diverse soil management techniques aimed at increasing organic content in soil while minimizing the use of chemical inputs. It integrates a multidisciplinary approach, conducting field experiments across diverse agroecological regions with different soil types and cropping systems. Key practices under investigation include cover cropping, crop rotations, conservation tillage, compost application, organic amendments, integrated pest management (IPM), and precision agriculture. The study assesses their impact on soil organic carbon levels, greenhouse gas emissions, soil health indicators, and crop productivity through comprehensive data collection and analysis techniques. Statistical analyses and modeling are employed to quantify carbon sequestration rates, evaluate treatment effects, and assess environmental and agronomic benefits. These practices are implemented in controlled trials to assess their impact on soil organic carbon (SOC) levels, greenhouse gas emissions (CO2, CH4, N2O), soil health indicators (microbial biomass, nutrient cycling, soil structure), and crop productivity. Data collection and analysis techniques involve comprehensive soil sampling, greenhouse gas flux measurements, soil health assessments, and crop yield monitoring over multiple growing seasons. Statistical analyses and modeling approaches are employed to quantify the carbon sequestration rates, assess treatment effects on soil health and greenhouse gas emissions, and evaluate the overall environmental and agronomic benefits of the soil management practices. The study aims to contribute valuable insights into evidence-based strategies for promoting sustainable soil management practices that enhance carbon sequestration while maintaining or improving agricultural productivity. The findings will have implications for informing agricultural policies, guiding farm management decisions, and advancing research on climate-smart agriculture. By quantifying the carbon sequestration potential of different soil management practices, this research contributes to the broader goal of achieving climate resilience, environmental sustainability, and food security in agricultural systems.</p>

The Impact of Sorbent Amendments for Mercury Remediation on the Viability of Soil Microorganisms

Mercury (Hg) remediation across contaminated environments in the United States is an ongoing project. As part of the Hg cleanup strategy at East Fork Poplar Creek (EFPC), located in Oak Ridge, TN, the deployment of sorbents is considered. However, the impact of sorbents on soil microorganisms is poorly understood. In this study, we investigated the effect of sorbents on soil microorganism viability and biofilm formation to assess soil health during sorbent application for Hg remediation. We specifically investigated the effect of two engineered sorbents, Organoclay PM-199 and Organoclay MRM (which are manufactured from clay minerals formulated for various remediation applications), on two gram-negative organisms (Serratia marcescens and Burkholderia thailandensis) isolated from the Hg-contaminated EFPC bank soil. Pure cultures of S. marcescens or B. thailandensis were amended with 5% (w/v) and 25% (w/v) PM-199 and MRM, respectively, for 9 days. The samples were harvested, and bacterial cell viability was determined using a BacLight staining kit. Results showed that the growth of sorbent-amended S. marcescens was inhibited in contrast to that of unamended control. Furthermore, biochemical assays were used to analyze bacterial biofilm formation and integral biofilm components. Our results suggest that biofilm formation by sorbent-amended S. marcescens was negatively affected. In contrast, B. thailandensis amended with low concentrations of MRM showed enhanced growth and notable differences in biofilm morphology. These results suggest that the use of organoclay PM-199 and MRM at higher concentrations in field studies may hinder the growth of specific soil microorganisms.

Determination of Minimum Data Set for Soil Health Assessment of Farmlands under Wheat–Maize Crop System in Yanting County, Sichuan, China

The assessment of soil health through a robust index system having a sufficient number of indicators is an important step toward sustainable crop production. The present study aimed at establishing a minimum data set (MDS) from soil functional and nutritional attributes using a dual index system to evaluate the soil health of farmlands under wheat (Triticum aestivum)–maize (Zea mays) crop rotation in Yanting County, Sichuan, China. Farms from 10 villages in the study area were selected, out of which three sites were considered healthy/ideal sites and used as a reference for the remaining seven targeted sites, and soil samples were collected at depth of 20 cm from these farms. The MDS indicators were selected by using principal component analysis (PCA) followed by Pearson’s correlation on 25 attributes. Based on significant values, eight attributes were retained in the final MDS, including the sucrase level, pH, wilting coefficient, water holding capacity, organic matter, NK ratio, total potassium, and available phosphorus. Based on the results, most of the farmland soils in Yanting County were in a healthy condition, accounting for 61.71% of the surveyed samples, followed by sub-healthy, degraded, and weak soils, accounting for 19.64%, 9.71%, and 8.93%, respectively. The values of most of the indicators at the targeted sites were significantly lower than those at ideal sites. Thus, specific steps should be taken by adding soil organic matter, combined with other fertilizers, to enhance the microbial biomass, enzymatic activities, and other biological activities in the soil.

Biochar influences soil health but not yield in 3‐year processing tomato field trials

AbstractBiochar can deliver many agronomic benefits, though effects may be greatest in suboptimal agricultural soils. The objective of this study was to investigate biochar in prime agricultural soils in a Mediterranean climate. In 3‐year irrigated processing tomato (Solanum lycopersicum) field trials, in which three biochars were amended to a sandy and silt loam, biochar did not influence yield. Given the global policy focus on biochar for climate change mitigation and adaptation, however, it is essential to measure more than just agronomic parameters. To this end, a soil health assessment was conducted 2.5 years after biochar amendment. In the fertile silt loam and more nutrient‐limited sandy loam, biochars had a variable but positive effect on pH, electrical conductivity, soil potassium, water stable aggregation, and permanganate oxidizable carbon. There was no effect on soil moisture nor potentially mineralizable nitrogen or carbon. In the silt loam, there was no change in microbial biomass or phospholipid fatty acid (PLFA) composition. In the sandy loam, almond shell biochars were associated with a slight increase in total biomass, an increase in the ratio of fungal to bacteria PLFAs, and reductions in multiple PLFA ratios were typically interpreted as indicators of environmental stress. Results of this study demonstrate that biochar may deliver soil health benefits in agricultural soils in a Mediterranean climate. However, increased soil health does not necessarily engender increased agricultural productivity within a 3‐year period. Furthermore, increases in soil health indicators were inconsistent across soil and biochar types, underscoring the need for site‐ and material‐specific investigation.

A WebGIS-Based System for Supporting Saline-Alkali Soil Ecological Monitoring: A Case Study in Yellow River Delta, China

The monitoring and evaluation of soil ecological environment is very important to ensure the saline-alkali soil health and the safety of agricultural products. It is of foremost importance to, within a regional ecological risk-reduction strategy, develop a useful online system for soil ecological assessment and prediction to prevent people from suffering the threat of sudden disasters. However, the traditional manual or empirical parameter adjustment causes the mismatch of the hyperparameters of the model, which cannot meet the urgent needs of high-performance prediction of soil properties using multi-dimensional data in WebGIS system. For the end, this study aims to develop a saline-alkali soil ecological monitoring system for real-time monitoring of soil ecology in the Yellow River Delta, China. The system applied advanced web-based GIS, including front-end and back-end technology stack, cross-platform deployment of machine learning models, and a database embedded in multi-source environmental variables. The system adopts a five-layer architecture and integrates functions such as data statistical analysis, soil health assessment, soil salt prediction and data management. The system visually displays the statistical results of air quality, vegetation index and soil properties in the study area. It provides users with ecological risk assessment functions to analyze soil heavy metal pollution. Specially, the system introduces a tree structured Parzan estimator (TPE) optimized machine learning model to achieve accurate prediction of soil salinity. The TPE-RF model had the highest prediction accuracy (R2 = 94.48%) in the testing set in comparison with the TPE-GBDT model, which exhibited the strong ability for the nonlinear relationship between environmental variables and soil salinity. The system developed in this study can provide accurate saline-alkali soil information and health assessment results for government agencies and farmers, which is of great significance for agricultural production and saline-alkali soil ecological protection.

A data‐driven topsoil classification framework to support soil health assessment in Minnesota

AbstractSoil health assessments aim to quantify soil health status using indicators linked to ecosystem services such as yield, nutrient cycling, water cycling, or carbon storage. Many indicators are related to soil biological processes, which can be challenging to interpret because they are sensitive not only to management, but also to nonmanagement variables such as soil inherent properties, topography, and climate. Existing studies address this challenge by grouping similar soils by taxonomy, geography, or a combination of these and other variables for soil health assessment. We investigated whether grouping soils based on multiple quantitative topsoil properties could be an alternative to taxonomic or geographic groups. We used an unsupervised classification algorithm, k‐means, to cluster publicly available soil and climate data for Minnesota. Clustering into eight conceptual groups (“clusters”) based on 10 topsoil properties was determined to be the optimal algorithm output. We evaluated the ability of our soil clusters and other grouping methods to explain variance in eight soil health indicators. We found the combination of Major Land Resource Area (MLRA) and soil cluster performed best, explaining as much or more variance than other groupings for five of the eight indicators. The clusters distinguish zones of topsoil variation at the field scale, and MLRAs account for broader scale variation in climate and other landscape factors. The approach we describe is flexible and could be applied at different locations and scales to produce conceptual soil groups and associated maps to support soil health test sampling and interpretation at the field scale.

Exploring Catalase Activity as A Biological Indicator in Degraded Soils

This study examines the relationship between catalase activity in degraded soils and soil properties, and addresses its potential as an indicator of soil health and productivity. Catalase, a key enzyme reflecting microbial activity and soil aeration, has been analyzed in 30 soil samples collected from the disturbed surface layer (0-15 cm depth) of erosion-prone areas characterized by rubble accumulation on hill slopes and soil compaction in foot slopes. The soil in the study area is classified as Typic Xerortent. Catalase enzyme activity in the soil samples varied between 10.4 and 48 µl O2 g-1 dry soil. In addition to catalase, the physicochemical properties of the soil were also assessed, including pH, electrical conductivity, organic matter content, and texture. Nutrient contents, including nitrogen (0.046-0.239 g N 100 g-1), phosphorus (1.77-20.05 µg P g-1), and potassium (0.01-3.31 meq K 100 g-1), were also measured. A positive correlation was observed between catalase activity and potassium and phosphorus levels, but the relationship with nitrogen was statistically insignificant. These findings suggest that catalase activity can serve as a biological indicator for the early detection of degradation in soils at risk of erosion. The study provides valuable insights into the impact of erosion on soil biochemistry and highlights the role of catalase in assessing soil health and guiding sustainable land management practices.

Advancements in assessing soil health through functional traits and energy flow analysis of soil nematodes

Advancements in assessing soil health through functional traits and energy flow analysis of soil nematodes

Assessment of Soil Health and Soil Quality of Bokaro, District, Jharkhand, India

Taking care of soil health is most importance for sustainable crop production. Soil quality is a blending of soil processes and provides to a measure change in soil condition as related to following factors such as land use, climate patterns, cropping sequences and farming systems. In the present investigation analysis of different physical and chemical characteristics were made to determine soil health of Bokaro district. Results show that soil bulk density was in normal range, soil pore space % varied from 39.85 to 48.32 g cm-3, particle density ranged from 2.24 to 2.69 Mg m-3, water holding capacity varied from 34.23 to 43.86 %. Soil pH and EC were found to be acidic and non-saline in nature respectively while soil organic carbon and available phosphorus were in medium to high range. Available nitrogen and potassium were found to be low to medium range i.e., 197.0 to 219.0 Kg ha - 1 and 201.96 to 266.01 Kg ha -1 and the range of phosphorus varied from 16.96 to 26.68 kg ha -1 respectively. Deficiency of sulphur followed by zinc was found in soils of Bokaro district.

Earthworm coelomocytes as a soil health assessment tool

Different pollutants can disrupt earthworm coelomocytes integrity and functions, and their responses can be applied as biomarkers of sublethal contaminant exposure. In this context, the aim of this study was to develop an in vitro protocol for coelomocyte extraction, maintenance and analysis with regard to soil health status and chemical toxicity profile assessments. The extrusion technique was first tested comparing previously depurated (purged stomach content) and non-depurated and resampled earthworms. After testing, earthworms were exposed to different 2,4D and chloroacetamide concentrations for methodology validation. The values of viability were not affected by food restriction since no statistical difference was observed between non-depurated (sample A) and depurated (sample B) organisms. Regarding to cell density, a significant (p<0;05) reduction of 22% was observed between non-depurated and depurated organisms, indicating that food restriction may affect cell density. However, the non-depurated resampling did not show a significant reduction, indicating that this assessment may not be affect by resampling of the same organism. For both chemical compounds, no change in cell viability was observed at all assessed concentrations and exposure times. However, for cell density, a mainly time-dependent effect was observed for organisms exposed to chloroacetamide, and concentration-dependent effect for organisms exposed to 2,4D. The proportion of immune system cells was altered, mainly after 24 h, with the increasing of granular amoebocytes proportion. The difference in the proportion of granular amoebocytes in earthworms exposed to 2,4D can be explained by the existence of recognition and elimination mechanisms for this chemical substance. Thus, assessments of pollutant responses with in vitro coelomocytes seem to be a powerful tool for ecotoxicological studies.

Survey on Optimal Crop Prediction using Soil and Weather Analysis

This survey paper provides a comprehensive overview of methodologies, technologies, and approaches for analyzing soil environments to optimize crop production. It covers traditional soil sampling, advanced techniques like remote sensing, and real-time monitoring using sensor networks. The integration of sensor data with IoT and machine learning for decision support is explored. Soil health assessment and site-specific management strategies enabled by precision agriculture are emphasized. Challenges such as data integration and sensor accuracy are addressed, along with future research directions including low-cost sensing solutions and improved data analytics. Overall, the paper serves as a valuable resource for optimizing crop production sustainably, contributing to efficient agricultural practices in a changing climate

Predictive soil health indicators across a boreal forest to agricultural conversion gradient

AbstractA changing climate offers new opportunities to expand agriculture in northern latitudes, and understanding forest‐to‐agriculture land conversion impacts is critical to ensure soil sustainability. Using the Comprehensive Assessment of Soil Health (CASH) framework, we identified a minimum suite of indicators with little collinearity to reliably predict soil impacts during the conversion of boreal forest to agriculture and a time since conversion gradient (forest, <10 years, >10 and <50 years, and >50 years since conversion). We sampled paired forest and agricultural sites and used multiple linear regression to assess 16 indicators and found four‐ and six‐indicator models predicted the CASH score with varying but reasonable accuracy depending on conversion class. Organic matter, water aggregate stability, and pH were consistent predictors across all classes, as well as one or more micronutrients. The CASH framework appears to be more suitable for agricultural soils and as time since conversion proceeds.

Assessment of salt-affected soil in selected rice irrigation schemes in Tanzania: understanding salt types for optimizing management approaches

Salt-affected soils have serious implications for agricultural land quality and productivity, leading to a reduction in the net cultivable area available for food production. This issue has emerged as one of the foremost global challenges in recent years, impacting both food security and environmental sustainability. This research focuses on soil characterizations conducted in three irrigation schemes to understand the types, distribution, and nature of salt-affected soils. Auger observations served as the basic methodology for soil unit delineation in this study. Twelve representative soil pits with a depth of more than 160 cm were described, and undisturbed and disturbed samples were collected and analyzed for physical and chemical properties. The schemes were characterized by low levels of available phosphorus, organic carbon, and total nitrogen, as well as variations in exchangeable bases. Furthermore, 37.5% of the analyzed horizons highlighted the presence of salt-affected soils. Sodium was the predominant cation, followed by magnesium, potassium, and calcium. Likewise, HCO3− was the dominant anion, followed by Cl− and SO42−. The results of this study reveal the existence of two types of salt-affected soil. Uturo irrigation scheme had sodic soils, while the Ndungu irrigation scheme had saline-sodic soils. Additionally, both sodic and saline-sodic soils have been discovered in the Mawala irrigation scheme. The root cause of this challenge is inherent soil conditions, exacerbated by inadequate drainage infrastructure. Therefore, measures such as the application of gypsum followed by salt leaching, improving soil drainage by incorporating organic matter, improving drainage infrastructure, and using rice-tolerant varieties are recommended to mitigate salt stress and improve soil fertility. It is imperative to establish a robust framework for continuous monitoring and regular assessment of soil health to enable timely interventions and informed decisions for sustainable agricultural management.

Nanotechnology-based Sensors for Real-time Monitoring and Assessment of Soil Health and Quality: A Review

Soil health and quality are critical factors in maintaining sustainable agriculture, ecosystem stability, and global food security. Conventional methods for assessing soil properties are often time-consuming, labor-intensive, and lack real-time monitoring capabilities. Nanotechnology has emerged as a promising approach to develop advanced sensors for rapid, in-situ, and continuous monitoring of soil health parameters. This comprehensive review discusses the recent advancements in nanotechnology-based sensors for soil health assessment, their working principles, applications, challenges, and future prospects. We highlight the potential of various nanomaterials, such as carbon nanotubes, graphene, metal oxide nanoparticles, and quantum dots, in fabricating highly sensitive, selective, and robust soil sensors. The integration of these nanosensors with wireless communication technologies and data analytics enables real-time monitoring and precision agriculture practices. Furthermore, we discuss the environmental and ecological implications of deploying nanosensors in soil and the need for standardized protocols and regulations. This review provides valuable insights into the current state-of-the-art and future directions of nanotechnology-based sensors for soil health monitoring, promoting sustainable agriculture and environmental management.