The study evaluated the potential of portable near-infrared (NIR) spectroscopy to predict soil physicochemical properties in coffee and cocoa production systems in Amazonas, Peru. A total of 126 topsoil samples were initially collected using a stratified sampling design. One coffee sample was excluded from the spectral dataset because no corresponding NIR spectral record was available, resulting in a final dataset of 125 samples (69 coffee and 56 cocoa) used for predictive modeling. Soil properties were determined using standard laboratory reference methods, and spectral data were acquired using a portable NeoSpectra spectrometer operating in the 1350–2550 nm range. Predictive models were developed using Random Forest (RF), Support Vector Machine (SVM), Neural Networks (NN), and Partial Least Squares Regression (PLSR), and their performance was evaluated using nested five-fold cross-validation.The predictive performance of portable near-infrared (NIR) spectroscopy varied according to the soil property, production system, preprocessing technique, and machine learning algorithm. Coffee soils showed higher predictive performance than cocoa soils. The best results were obtained for clay (R²CV = 0.775; RPDCV = 2.276) using Random Forest with first-derivative preprocessing, followed by phosphorus (R²CV = 0.772; RPDCV = 2.037) using Partial Least Squares Regression with band-depth preprocessing. Soil pH and silt also showed satisfactory predictive performance in coffee soils. In cocoa soils, potassium exhibited the highest predictive capability (R²CV = 0.454; RPDCV = 1.378) using Support Vector Machine with second-derivative preprocessing, although the overall model performance was lower than that observed for coffee soils. Portable NIR spectroscopy provided potentially useful estimates for selected soil properties, particularly clay, phosphorus, pH, and silt in coffee soils. However, its predictive performance was strongly dependent on the soil property, preprocessing strategy, machine learning algorithm, and production system.
The soil-gas diffusivity (ratio of gas diffusion coefficients in soil and pure air), Dp/D0, controls the mobility of gases in variably saturated soils, including aeration, emission and uptake of greenhouse gases. Previous soil-gas diffusivity studies have focused on lower-organic soils. Here, Dp/D0 was measured on intact soil cores at six different soil-water matric potentials between -30 and -1000 cm H2O (pF between 1.5 to 3) on 127 Danish peat top soils (12-52% SOC). The SOC level was not found to be main control of Dp/D0 for peat soils. Dp/D0 versus soil-air content (ε) curves varied as much within a narrow SOC interval (e.g., 30-36% SOC) as for the whole range. In contrast to previous observations for lower-organic soils, it was found that at each pF level, Dp/D0 increased linearly with ε, the slope, the Penman pore continuity index P, increased linearly with pF. Previous Dp/D0 models developed for lower-organic soils (typically < 4% SOC) failed to describe Dp/D0 for peat soils. A soil-water characteristic curve-dependent model (Buckingham-Burdine-Campbell, BBC) well predicted Dp/D0 for peat soils. A modified WLR model with inputs of actual and effective air-filled porosity (ε*, taken as ε around pF3) was developed. The BBC and modified WLR models were successfully validated against independent data for high-organic soils representing different climate zones and organic matter quality. This work provides a better understanding of and models for gas diffusion in high-organic soils, setting a platform for including soil-air phase properties when evaluating soil functions, security, and capital.
Soil literacy is increasingly relevant to soil security, soil stewardship and sustainable land management, particularly in regions exposed to erosion, drought, wildfire impacts, desertification risk and land-use change. This study assessed soil literacy among school students surveyed in the Porto Metropolitan Area, Portugal, using a multidimensional index-based framework. A cross-sectional survey was administered to third-cycle and secondary students, and 424 valid responses were analysed. Seven dimensions were assessed: soil knowledge, soil functions awareness, soil degradation perception, soil threats recognition, soil protection measures recognition, behavioural awareness and affective-civic orientation. Composite indices were transformed to a common 0–100 scale and psychometrically assessed using internal consistency statistics, corrected item-total correlations and exploratory factor analysis. Group differences were examined using non-parametric tests with false-discovery-rate adjustment, associations among indices using Spearman correlations, and multidimensional profiles using PERMANOVA. The indices showed acceptable to excellent internal consistency, while the Overall Soil Literacy Index was interpreted as a secondary synthesis rather than as a substitute for the component profile. Students obtained higher scores for soil functions awareness, behavioural awareness and recognition of protection measures, but lower scores for soil knowledge, soil degradation perception and affective-civic orientation. PERMANOVA showed statistically significant but small associations between student characteristics and the multivariate soil literacy profile. The results indicate that students recognise soil usefulness more strongly than the processes that generate, transform and degrade it. The study provides a reproducible, psychometrically assessed framework for soil literacy research and identifies regional priorities for locally strengthening soil education as part of soil-security connectivity.
Evaluating the long-term outcomes of reclamation requires assessment not only of soil fertility but also of soil functioning within a Soil Security perspective. This study assessed soil fertility status and the Soil Quality Index (SQI) in reclaimed tidal lowlands after >30 years of cultivation in Typology A and Typology B areas of Banyuasin Regency, South Sumatra, Indonesia. Soil chemical properties were analyzed and compared using Welch’s t-test or Mann–Whitney U test according to data distribution, while effect sizes were quantified using Cohen’s d and rank-biserial correlation. Both typologies exhibited strongly acidic conditions (pH 4.0–5.0), moderate cation exchange capacity (14–25 cmol kg⁻¹), low base saturation (11–43%), low available K, moderate total N, relatively high organic C (1.3–13.0%), and loam to clay loam textures. Significant differences between typologies were observed for cation exchange capacity, base saturation, and soil pH, whereas available P, available K, total N, and organic C did not differ significantly. Soil fertility in both typologies remained constrained primarily by persistent acidity and low base saturation. SQI values were 0.74 for Typology A and 0.70 for Typology B, indicating moderate soil quality in both typologies. Within the Soil Security framework, differences between typologies were mainly related to the capacity dimension, particularly nutrient retention and buffering functions, whereas SQI reflected the current soil condition under long-term management. The persistence of chemical limitations indicates that reclaimed tidal lowlands remain dependent on liming, nutrient replenishment, water management, and organic matter maintenance to sustain agricultural productivity and long-term soil security.
Nature-positive farming, an approach that improves crop production while increasing resilience and harmony between nature and society, is expected to enhance soil health and increase soil water infiltration. However, limited research exists on how diverse nature-positive farming practices affect soil health and soil water infiltration dynamics. This study assessed the impact of three nature-positive farming practices on soil water infiltration and the relationship with other soil properties. For this, soil water infiltration was measured using a SATURO dual-head infiltrometer, and selected soil health parameters were measured in soil samples collected from 0-15 cm depth of the respective fields. The results show significantly higher water infiltration rates in nature-positive practices than their respective controls, with infiltration rates 86% to 198% higher in nature-positive management than in controls. Identifying factors regulating infiltration rate using a linear mixed-effects model shows 70 % of the total variation in infiltration was governed by soil health indicators, with water stable aggregates being the most critical factor, accounting for 49% of the total variation. Nature-positive management could be a sustainable solution to improve soil health and security in semi-arid agroecosystems, and stability of soil aggregates plays a critical role in improved water functions, including soil water infiltration, irrespective of the nature-positive practices.
Conservation management practices have the potential to improve soil health status and ensure that agricultural lands remain productive for future generations, especially in regions with degraded soils. To assess the soil health benefits of conservation management in the Central Claypan Area of Missouri, two long-term (30-yr) agronomic production systems and an ecological reference site were compared. Study systems included a corn (Zea mays) - soybean (Glycine max) - wheat (Triticum aestivum) rotation under no-till with cover-crops (ASP), a corn-soybean rotation with tillage and no cover-crops (BAU), and a remnant native prairie which served as an ecological reference site (TP). A suite of soil health indicators were measured from soil samples collected to a depth of 0–15 cm. Indicators included physical, chemical, and biological properties. Overall, soil health indicators were greatest at TP followed by ASP and BAU. Soil organic carbon and total nitrogen were not sensitive to differences in agricultural management practices, although the more dynamic soil health indicators, such as total protein, permanganate oxidizable carbon, alkali-absorbed soil respiration, and fresh soil respiration, were significantly greater under ASP relative to BAU management. This study demonstrated the utility of dynamic soil health indicators, especially in formerly degraded soils, even after 30 years of conservation management.
The escalation of rubber plantations has resulted in substantial ecological and environmental consequences. In the Caraga region, rubber (Hevea brasiliensis Muell. Arg.) is identified as an important production system where farming management varies, yet could potentially contribute to the soil quality decline. This study focuses on determining the soil quality index (SQI) of various rubber-based agroforestry systems (RBAS) in Talacogon and Sta. Josefa, Agusan del Sur. It maximizes the Shiny App package in RStudio for analyzing data, specifically for SQI calculation, PCA, db-RDA, and ANOVA, using reliable references. Findings show that both sites are unique pedologically; thus, they were treated separately. It was determined through distance-based redundancy analysis (db-RDA) that variations among factors such as land use management and soil inherent properties were distinct. Across RBAS in TC, Rubber + Falcata (RF) showed the highest SQI (Q2), whereas Rubber + Cacao (RC) showed the highest SQI in SJ. Meanwhile, monocultivation in both sites has exhibited poor to extremely poor SQI. Promoting agroforestry offers resource complementarity and the potential for maintaining good soil quality. It provides a more secure and sustainable management strategy for rubber cultivation. Consequently, the utilization of site-specific SQI in various RBAS has led to the development of tailored fit farming practices for tropical soils. The tool may help identify a suitable companion crop for rubber that minimizes the distressing occurrence of soil degradation.
Oxisols in the Brazilian Cerrado are intensively cultivated due to their strategic importance in producing a range of commodities exported worldwide. To achieve high productivity, a large amount of conventional mineral fertilizer (CMF) must be used, which raises multiple concerns. Composted sewage sludge (CSS) is a promising organic fertilizer that enhances soil health while increasing agricultural sustainability. The objective of this study was to monitor soil chemical quality at two depths (0–0.1 m and 0.1–0.2 m) after CSS applications over three agricultural years under a no-tillage system. The experiment was conducted under field conditions by applying and evaluating five rates of CSS (0.0, 5.0, 7.5, 10.0, and 12.5 Mg ha–1) vs CMF with four replicates. CSS increased sum of bases (37.07 vs 31.22 mmolc kg⁻¹), base saturation (75%vs 58%), and P (33.50 vs 25.00 mg kg⁻¹), as well as Ca (28.75 vs 22.00) and Mg (37.07 vs 31.22 mmolc kg⁻¹) compared to CMF in the surface horizon. Over the three years, the available concentrations of P, Cu, Mn, and Zn increased in the soil with CSS application. The results indicate that CSS can be utilized as a complement to CMF, enhancing the chemical quality and soil security of tropical Oxisols. When applied at a rate of 10.0 Mg ha⁻¹, CSS can enhance soil chemical quality and the soil’s capacity to support crop production and environmental functions, while fostering a connection between urban waste management and agriculture, thereby ensuring sustainable land management in tropical agroecosystems.
This study assesses the security of the Soil Water Storing Function (SWSF) across Australia by operationalising and combining the five dimensions of soil security: capacity, condition, capital, connectivity, and codification. Utilising the pedogenon mapping concept, we quantified the capacity dimension using available water capacity of reference soils (genosoils), and the condition dimension as the deviation of current state (phenosoils) from the reference state within the top one metre. Capital was estimated via production functions linking plant available water capacity to land value. The connectivity dimension integrated spatially interpolated stakeholder survey data. Codification was scored based on the existence of legislative protections for SWSF. These multi-scalar datasets were synthesised using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to rank locations based on their geometric distance from an ideal state. The resulting soil security index ranged from 0.26 to 0.75 (mean = 0.59, SD = 0.05). High-security regions (e.g., Northeast regions) were driven by robust condition and governance, whereas low-security areas (e.g., near Nullarbor Plain) were restricted primarily by inherent capacity and capital in some other scattered areas. The analysis identified the restrictive dimension for each mapping unit (pedogenon), the specific factor most limiting soil security. Soil capacity was found as the most widespread restrictive dimension across Australia for SWSF’s security. This research demonstrates an operational framework that moves beyond biophysical health, providing policymakers with a prescriptive tool to target interventions based on combined biophysical, socio-economic, and regulatory risks.
The assessment of soil security represents one of the most comprehensive approaches to understanding and managing soil resources in the 21st century. Building on the soil security framework developed by McBratney and colleagues, this paper focuses on enhancing the efficiency and operationalisation of assessments across the five dimensions of soil security, encompassing 115 individual evaluation activities. Key methodological approaches that support more efficient implementation are synthesised, with particular emphasis on the integration of advanced technologies, including soil spectroscopy, digital soil mapping, remote sensing, and emerging applications of large language models in policy analysis. The pedogenon-based reference system is presented as a foundation for standardising assessments and enabling systematic comparison between natural and human-modified soil systems. Practical considerations, methodological challenges, and sources of uncertainty associated with applying the framework are examined, including the identification of reference conditions in human-impacted landscapes. Strategies are identified to improve the efficiency, consistency, and applicability of soil security and soil condition/health assessments in both research and policy contexts.
Soil science integrates multiple disciplinary traditions that investigate the same material system while relying on distinct concepts, parameters, and measurement practices. As a result, soil properties that are often treated as well-defined material properties may acquire different scientific meanings, which can limit their comparability and lead to ambiguity when applied across mineralogical, pedological, biogeochemical, and engineering contexts. This paper introduces a reflexive analytical framework for examining how soil concepts are defined, represented, and used across disciplinary practices. The framework is structured around three interrelated dimensions—object, mediation, and subject—and is organized into a 3 × 3 analytical matrix that clarifies how soil-related concepts are described, explained, and operationalized within scientific work. The framework is first articulated at the level of soil science as a whole and is then applied to two widely used soil properties: soil organic carbon and shear strength in geotechnical engineering. These applications demonstrate how quantities commonly treated as intrinsic material properties depend on specific definitions, classification schemes, models, and measurement practices. The results highlight that differences in interpretation across disciplines may arise not only from technical factors, but also from differences in how soil properties are defined and used. By making these differences explicit, the framework provides a conceptual basis for clearer cross-disciplinary communication and more robust interpretation of soil data. This is particularly relevant for interdisciplinary contexts such as sustainability and soil security, where consistent integration of soil knowledge is essential.
This study aims to evaluate the effectiveness of a large language model (LLM)-based chatbot in responding to technical agricultural questions commonly asked by farmers, with a focus on its potential to support agricultural self-sufficiency while considering the risks of misinformation. The chatbot’s responses to five frequently asked questions were tested across two contrasting agroecosystems in Indonesia: acidic drylands and swamplands. A total of 33 extension officers in acidic drylands and 37 in swamplands, along with five soil scientists in each ecosystem, assessed the chatbot’s responses using a 0–100 scoring system equivalent to a 1–4 Likert scale. The results showed that extension officers rated the chatbot’s answers higher than soil scientists, with average scores of 88.1 and 80.4 in acidic drylands, and 83.8 and 75.4 in swamplands, respectively. Extension officers categorized the chatbot’s responses as “very accurate,” whereas soil scientists considered them “fair” to “quite accurate.” These findings indicate that the chatbot has the potential to complement extension services by providing farmers with quick, preliminary information, although further refinement is still required for specialized agroecosystem contexts. The study contributes to the growing body of research on digital agricultural advisory services by highlighting both the potential and limitations of LLMs as knowledge intermediaries. The results reinforce the idea that LLMs primarily function as language models rather than knowledge models. They can simulate expertise based on patterns in data but cannot independently verify causal relationships or scientific validity. This research offering insights into the role of AI in supporting agricultural self-sufficiency while mitigating misinformation risks.
This study investigates the long-term effects of rice-rice and rice-cowpea cropping systems on crop productivity, soil carbon dynamics, and soil quality indicators in rice-based systems of Goa state (India). The rice-cowpea system recorded higher soil organic carbon stocks, improved active and passive carbon pools, and total organic carbon content over the rice-rice system. At a 0-5 cm soil depth, the rice-cowpea system exhibited the highest very labile carbon (1.00 g/kg; 0.68 Mg C/ha), total carbon (15.05 g/kg; 10.33 Mg C/ha), and active carbon pool (4.72 g/kg; 3.24 Mg C/ha), highlighting its potential to promote topsoil health. Additionally, the system increased soil carbon sequestration at depths of 5-15 cm, as indicated by significantly higher passive carbon (8.01 g/kg; 11.00 Mg C/ha) and total carbon (10.42 g/kg; 14.30 Mg C/ha) compared to the rice-rice system. Enhanced microbial activities, including higher microbial biomass carbon (367.14 µg C/g soil) and basal soil respiration (105.72 µg CO₂/g soil/h), were observed in the rice-cowpea system, attributed to the nitrogen-fixing abilities of cowpea. Furthermore, a reduced bulk density (1.37 kg/m³), higher soil nutrient levels (nitrogen: 207.46 kg/ha; potassium: 190.98 kg/ha), and improved enzymatic activities emphasize the effectiveness of the rice-cowpea system in enhancing soil health. These findings suggest that the rice-cowpea system has the potential to improve soil quality, mitigate environmental impacts, and enhance crop productivity, thereby representing a viable strategy for sustainable agriculture in rice-dominated regions.
Anthropogenic activities have disrupted the natural carbon (C) balance, contributing to global climate change. Cover crops facilitate C sequestration, but their long-term impacts and deep soil C storage in Missouri remain unexplored. This study examined soil C forms to 100 cm depth under cover crop management in corn [Zea mays (L.)] - soybean [Glycine max (L.) Merr.] rotations. Soil from 5- and 10-year-old cover crop fields in Missouri were sampled to 100 cm depth under no-till cover crop (CC) and no-till no-cover crop (NCC) treatments, and analyzed for soil organic carbon (SOC), potentially mineralizable carbon (PMC), and permanganate oxidizable carbon (POXC). Cover crops increased SOC% and stocks in both fields, with the greatest concentration at 0–5 cm depth. Cumulative SOC stocks for 0–60 cm depth under CC were 10.3% greater in 10-year-old field and 1.63% greater in 5-year-old field than NCC. Interestingly, the 10-year-old field showed strong indicatations of stable C formation. Significantly greater POXC values under CC were observed at 0–5 cm and 45–60 cm depth than NCC in 5-year-old site. Additionally, PMC values were numerically greater under CC at 0–5 cm depth than NCC in both sites. Increased labile C (POXC and PMC) near the surface, suggests enhanced microbial activity and C mineralization. Greater parameter changes were notable in shallow depth (0–45 cm) but less pronounced at deeper depths (45–100 cm). These findings highlighted that long-term cover crop adoption can meaningfully enhance soil C storage in Missouri, including in sub-soils, providing valuable information for C accounting and the system's contribution to climate change mitigation.
Soil security, an emergent property of social-ecological systems, connects soil functions with agricultural production and underpins long-term food security. However, national-scale assessments that integrate ecological and socio-institutional dimensions remain limited, particularly in Latin America. This study develops the first national, participatory Soil Security Index (SSI) for Mexico to inform soil governance and agricultural policy. The SSI operationalizes the five dimensions of soil security—capacity, condition, capital, connectivity, and codification—across agricultural lands through: (i) indicator selection; (ii) compilation and spatial harmonization of global and national datasets; (iii) participatory interpretation and weighting with researchers, government officials, field technicians, and producers; (iv) construction of dimension-specific indices (0–1) and an integrated SSI (0–5); and (v) regional statistical and spatial analysis. Results show that 65% of Mexico’s agricultural soils are insecure or moderately insecure. While soil condition exhibits relatively high values, deficits in capacity, capital, connectivity, and codification reflect structural constraints linked to intrinsic soil properties, intensive management, market integration barriers, limited technical training, and weak governance. Regional contrasts are pronounced: the Central South and Gulf of Mexico regions display the highest SSI values, whereas northern regions exhibit the lowest levels of soil security due to intensive production systems and limited institutional support. Intermediate values across the Yucatán Peninsula, Central West, and South Pacific regions highlight opportunities to strengthen sustainable soil management and producer capacity. The SSI provides a replicable, policy-relevant diagnostic tool for territorial prioritization and the design of differentiated regional interventions, offering an evidence-based foundation for soil governance in Mexico.
Recent advances in X-ray fluorescence (XRF) spectroscopy for Soil Science position it as a promising tool for in situ soil monitoring, although rapid and in situ applications of XRF sensors remain underexplored. This study evaluated the performance of a portable XRF operated in situ using a 5-second scanning time to predict plant-available (av-) Ca, av-Mg, av-K, and cation exchange capacity (CEC) in fresh soil samples (n = 128) from a Brazilian tropical field. Model evaluation was conducted using a novel fitness-for-purpose framework, which considers agronomic thresholds for acceptable prediction errors. Models were calibrated using spectral data obtained under three scenarios: laboratory with 30- and 5-second scanning times, and in the field with 5-second scanning time. We suggested maximum tolerated error thresholds based on regional soil fertility interpretations to classify model performance for semi-quantitative and qualitative applications. Results demonstrated that CEC predictions were suitable for both applications in lab and field conditions; av-Ca models were acceptable for qualitative use in both conditions and for semi-quantitative use in lab only. In contrast, av-Mg and av-K models did not meet reliable results, except for lab-based qualitative prediction of av-K. The proposed evaluation strategy allowed contextual performance assessment, overcoming limitations of conventional metrics such as R² and RPIQ. Overall, portable XRF proved to be a viable tool for rapid, in situ soil fertility diagnostics in tropical soils, particularly for av-Ca and CEC. Its use in mobile labs or directly in the field holds promise for inferring chemical attributes in precision agriculture and pedometric applications.
Understanding the dynamics of labile organic carbon (LOC) is critical for evaluating the short-term impacts of regenerative agricultural practices on soil health. We assessed changes in key LOC fractions such as permanganate oxidizable carbon (POXC) measured by 0.01M, 0.02M, 0.033M potassium permanganate, microbial biomass carbon (MBC), and very labile carbon (CVL) across four long-term conservation agriculture (CA) experiment sites located in contrasting agro-ecological zones of South Asia namely Karnal, Patna, Aduthurai, and Gazipur. At each site, four cropping system scenarios (S) were evaluated: S1, current farmers practice; S2, current farmers cropping system with partial CA; S3, current farmers cropping system with full CA; and S4, diversified crop rotation with full CA. Soil samples were collected from 0-15 and 15-30 cm depth after two cropping cycles. Results showed that POXC, MBC, CVL, oxidizable organic carbon (SOC) and total organic carbon (TOC) increased following CA adoption during the initial years. Across locations, POXC, CVL, and TOC consistently followed the order S4 > S3 > S2 > S1. Compared with S1, POXC values under S3 and S4 were higher by 6-27% (POXC 0.01M), 9-49% (POXC 0.02M), and 16-50% (POXC 0.033M), indicating enhanced carbon recycling in surface soils. Among all LOC fractions, POXC measured at 0.02 M showed the greatest sensitivity to management practices, supporting its suitability as a rapid, cost-effective proxy for soil health assessment. Overall, these findings highlight the potential of integrating regenerative agriculture practices as nature-based solutions and best-management approaches to accelerate carbon farming in tropical and subtropical cereal-based systems.
This study examines whether perceived soil erosion risks are sufficient to drive the adoption of Vetiver System Technology (VST) for soil and water conservation, employing an integrated framework based on the Technology Acceptance Model (TAM) and Protection Motivation Theory (PMT). Using survey data from 561 Filipino farmers in Cebu Province, analyzed through Partial Least Squares Structural Equation Modeling (PLS-SEM), the study explores key determinants of adoption, such as perceived severity, vulnerability, response efficacy, response cost, perceived ease of use, and perceived usefulness. Findings reveal that perceived usefulness is the strongest predictor of adoption, followed by response efficacy and perceived severity, with perceived ease of use indirectly influencing adoption via usefulness. While perceived soil erosion risks (severity and vulnerability) are significant, they are not sufficient on their own; practical factors like usefulness and efficacy play a more decisive role. Interestingly, response cost did not significantly deter adoption, suggesting the importance of demonstrating benefits and providing practical implementation support. Further analysis highlights the moderating role of demographic factors, including age, gender, and education, on these relationships. The study underscores the need for tailored interventions, awareness campaigns, and training programs to enhance VST adoption, particularly in resource-constrained settings. By integrating TAM and PMT, this research advances understanding of dynamic factors influencing sustainable technology adoption and provides actionable insights for policymakers and stakeholders in developing countries. It highlights the critical need to align motivational and usability factors with environmental conservation goals to effectively address soil erosion challenges.
Nitrogen is an essential nutrient for all living organisms and plays a critical role in plant growth and crop production in agricultural ecosystems. Although crop yields are significantly increased by application of chemical nitrogenous fertilizers, but their excessive use causes serious environmental concerns, including soil degradation, water pollution and reduced agricultural sustainability. Harnessing the soil microbiome for enhancing nutrient availability and crop productivity holds tremendous potential to provide an eco-friendly solution and also help in alleviating the associated environmental issues. Various soil microorganisms are involved in biogeochemical cycling of nitrogen (N) that regulate supply of utilizable N for microbial and crop uptake, its loss in biosphere, and subsequently affecting nitrogen use efficiency (NUE) in agroecosystems. Multiple N transformation processes mediated by soil microbes include mineralization and biological nitrogen fixation resulting into release of ammonia, which is assimilated/immobilized into organic biomass by plants and microorganisms. Ammonia is transformed to nitrate through nitrification process; some of nitrate gets assimilated and part of it is released in biosphere through denitrification process. Thus, soil-inhabiting microorganisms and their interactions with plants are vital for modulating N cycling processes, in improving NUE, increasing crop yields and for minimizing environmental impacts. This review summarizes the role of soil microbiomes in different N transformation processes, their regulation for NUE improvement, contributions of these N cycling processes in promoting soil health and crop productivity. A potential microbe-based approach for nutrient management is proposed using nitrogen-fixing microbes as biofertilizers for improving N availability in agroecosystems, while reducing dependence on synthetic fertilizers.
Soil erosion threatens food systems, water regulation, and ecosystem health in West Africa. The region faces both water erosion, yet monitoring remains fragmented and weakly connected to policy. This short communication synthesises fit for purpose Earth observation approaches for erosion monitoring and sets out a practical route to embed them in decision making. We summarise optical and radar approaches, including SAR time series and interferometry, aerosol products for dust, and new hyperspectral and high revisit constellations. We emphasise calibration and validation with plots, gully surveys, drones, and community observations. We diagnose key barriers to policy uptake, including limited human and technical capacity, institutional fragmentation, lack of standard methods, product usability gaps, financing constraints, and few documented success cases. We then propose an operational pathway aligned with UNCCD Land Degradation Neutrality and SDG 15.3.1 reporting, with clear roles for national agencies and regional initiatives such as WASCAL, SERVIR West Africa, Digital Earth Africa, and the network of African geomatics professionals. Embedding validated satellite indicators into routine policy cycles can identify hotspots, target measures, and track outcomes, advancing soil security while supporting countries’ 2030 LDN commitments.
