Sand mining activities from riverbeds or banks can harm the environment, especially water quality, by increasing turbidity, which can endanger ecosystems and human health. This study aims to analyze the water quality of the river around the sand mining area using the Water Quality Index (WQI) method. In this study, water samples were collected at three points: upstream, middle, and downstream, with three repetitions conducted over three consecutive days near the sand mining area of Sembubuk Village, Muaro Jambi Regency. The test results showed significant values in several parameters, including TSS at the midpoint, which reached 252 mg/l. This figure indicates a high number of suspended particles in the water. The turbidity value at the midpoint was also very high, at 285 NTU, indicating very cloudy water. In addition, the DO level at the midpoint of the mining site was the lowest, at 2.21 mg/l. This low DO indicates that the mining process releases oxidized materials trapped in the bottom sediment, which consume oxygen in the water. These parameters individually did not meet the river water quality standards. The method used combined various parameters, and the overall value could reflect the combined conditions of each parameter. Thus, the analysis of the WQI pollution level of the Batanghari River around the sand mining area in Sembubuk Village, Muaro Jambi Regency, indicated that the pollution level was at "Poor" status, with an average WQI value of 50.33. The midpoint had the highest WQI classification value among the points, at 50.42, indicating the greatest contribution of mining activities to the decline in water quality. Although the status improved to "Good" on the second day, this improvement was temporary. Overall, the river's condition remained poor, as its status reverted to "Poor" on the third day.
Peatlands are unique wetland ecosystems that play a significant role in carbon sequestration and maintaining hydrological balance. However, human activities have led to peatland degradation in Indonesia, resulting in the loss of ecosystem services and ecological functions of peat soils as well as increased greenhouse gas emissions. Restoring and rehabilitating peatlands requires sustainable and ecosystem-based approaches that harness local potential. One potential strategy involves the use of indigenous microbes through microbial engineering technology. This literature review highlights the potential of indigenous microbes as a sustainable peatland management strategy in Indonesia. Indigenous microbes, which are naturally adapted to the acidic and nutrient-poor conditions of peatlands, have potential as bioremediation agents, organic matter decomposers, and plant growth promoters. Microbial engineering involves several stages, including isolation, in vitro selection, pot tests, and the formulation of superior microbes for field application. This technology aims to improve soil quality, enhance microbial community structure, and boost land productivity without harming the environment. It can also accelerate the sustainable restoration of peatland functions, support food security, and mitigate climate change. The development of this technology necessitates further research, supportive policies, and the engagement of local communities to ensure its effective and long-term implementation.
Water pollution by heavy metals such as lead (Pb) causes toxic effects that inhibit the growth of aquatic organisms. Bioremediation using microorganisms such as Azotobacter sp. and Pseudomonas sp. is an environmentally friendly approach to reducing Pb toxicity through biological absorption and detoxification mechanisms. This study aimed to determine the most effective combination of biofertilizers in supporting the bioremediation process and the growth of water lettuce (Pistia stratiotes L.). The experiment was conducted in the greenhouse of the University of Singaperbangsa Karawang from January to April 2025 using a single-factor Randomized Block Design (RBD) with nine treatments and three replications. The results showed that treatment B (10 ppm Pb (50 ml Pseudomonas sp. + 25 ml Azotobacter sp.)) produced the highest values across all growth parameters. The combination of these two microorganisms enhanced nutrient availability and phytohormone production, supporting photosynthetic activity and improving the adaptation of Pistia stratiotes L. to Pb exposure, thereby demonstrating potential as an effective bioremediation agent.
Ultisol is a type of soil characterized by relatively low fertility, making it commonly utilized for oil palm plantations. In Sungai Muluk Village, oil palm plantations have surpassed their productive phase, necessitating replanting activities. This condition has resulted in decreased household income among local communities. As an alternative strategy, farmers have adopted red ginger cultivation through an intercropping system. However, the implementation of this system is constrained by soil nutrient deficiencies. This study aims to evaluate the application of cattle/cow manure and boiler ash on changes in the chemical properties of Ultisol soil after oil palm replanting, as well as to optimize the growth of red ginger plants during the maximum vegetative phase. This study used a non-factorial randomized block design with six treatment levels, namely A0 (control), A1 (10 tons ha-1 of cow/cattle manure + 5 tons ha-1 of boiler ash), A2 (15 tons ha-1 of cow manure + 5 tons of ha-1 boiler ash), A3 (15 tons ha-1 of cow manure + 10 tons ha-1 of boiler ash), A4 (20 tons ha-1 of cow manure + 10 tons ha-1 of boiler ash), A5 (20 tons ha-1 of cow manure + 15 tons ha-1 of boiler ash). The parameters observed were pH, exchangeable K, total N, plant height, number of leaves, and fresh weight of rhizomes. The results showed that the application of cow manure and boiler ash to Ultisols after oil palm replanting increased pH, exchangeable cations, plant height, number of leaves, and fresh weight of rhizomes. The combination of cow manure and boiler ash at a dose of 20 tons ha-1 of cow manure + 15 tons ha-1 of boiler ash effectively improved the chemical properties of Ultisol and increased the growth of red ginger plants.
Soil fertility is a determining factor in agricultural productivity and sustainable land management. This study aims to: 1) analyze soil fertility status in various land uses in Dolokgede Village, Bojonegoro Regency; 2) evaluate the effect of land use on soil physical and chemical properties, and; 3) analyze the relationship between soil parameters as indicators of soil fertility. The study was conducted from May to December 2024. Observation points were determined based on Land Mapping Units (LMU) across three land uses (rice fields, drylands, and forests), where a total of 24 composite soil samples were collected at a depth of 0–20 cm. The samples were analyzed for pH, cation exchange capacity (CEC), base saturation (BS), organic C, total N, available P, exchangeable cations (K, Ca, Mg, Na), texture, bulk density, particle density, and porosity. Soil fertility status was classified and mapped using ArcGIS. Data were analyzed using Analysis of Variance (ANOVA) followed by the Least Significant Difference (LSD) test at a 5% significance level, correlation, and regression. The results showed that total N was low (0.11–0.19%) in all land uses. Available P was very high in rice fields (59.31 ppm) due to intensive fertilization, but moderate in drylands and forests. Exchangeable K and organic C were low, while CEC and BS were very high in all land uses. Land use had a significant effect (p < 0.05) on available P and exchangeable Ca, Na, and Mg, but had no effect on other parameters, including all soil physical properties. An increase in organic C was strongly associated with total N (R² = 0.62), whereas high BS was associated with increased available P (R² = 0.99). Soil fertility status at the study site was determined by chemical factors and fertilizer management rather than changes in physical properties due to land use change. The implications of these findings for sustainable land management include organic matter management and balanced fertilizer use as measures to prevent soil degradation.
In the past two decades, remote sensing-based landslide detection methods have advanced significantly. However, these methods generally remain broad in scope and are not yet capable of identifying landslides as distinct objects with precise locations. This study aims to integrate YOLO v3 into remote sensing applications to enhance the accuracy of landslide detection in sub-watershed (sub-DAS) areas. The study focuses on two sub-watersheds with a history of frequent landslides, namely Kali Konto and Sumber Brantas. Sentinel-2A imagery from 2024 was downloaded for all months and composited to achieve the most stable visualization. Landslide location points were collected through an exploratory approach, incorporating information from the National Disaster Management Agency (BNPB) and local communities. A total of 155 landslide points were recorded in the field and subsequently used as training and validation data. Seventy percent of these points were analyzed using a deep convolutional neural network—YOLO v3—implemented in ArcGIS Pro, while the remaining 30% were used for validation against actual field occurrences.The detection model developed for the Kali Konto and Sumber Brantas sub-watersheds achieved an accuracy of 77%, demonstrating reliable performance in predicting landslide locations. The landslides identified predominantly consisted of slope failures and rockfalls occurring along cut-fill sections of roadside areas. However, this study has certain limitations: the developed model is unable to classify different types of landslides, and the satellite imagery used has a medium resolution, which is not yet advanced enough to fully meet the requirements for sub-watershed-level analyses.
Spring ecosystems in forest fragments provide important environmental services, but their economic value is rarely included in management decisions. Most management efforts focus only on physical protection, while the way visitors value these ecosystems receives little attention. This study aims to estimate the economic value of spring ecosystem services and analyze the factors influencing visitors’ willingness to pay (WTP). This study also examines the relationship between WTP, water quality indicators, and differences in ecological conditions across several categories of forest fragments. Observations were conducted at sixteen spring locations in East Java, Indonesia. These locations represent large and small forest fragments and two management orientations, namely instrumental and relational. Data on the social and psychological characteristics of visitors were combined with several biophysical indicators, including water quality. Principal component analysis (PCA) was applied to analyze these variables, and economic efficiency was evaluated using an adjusted land equivalent ratio (LER). The results show that WTP is more influenced by visit experience, visitor trust in management, and perceived benefit efficiency than by basic demographic characteristics alone. Fragments with an instrumental orientation show higher economic efficiency compared to those with a relational orientation. Meanwhile, water quality in fragments with a relational orientation is much better, as indicated by high DO and TDS levels and greater and more stable discharge values. These findings indicate differences between economic performance and ecological conditions across forest fragment categories. Therefore, integrating social, ecological, and governance dimensions is essential for developing effective conservation strategies for springs in forest fragments.
Ultisol is a type of soil that has a low pH, high aluminum saturation, and low nutrient content. This study aims to examine the effect of coffee husk biochar and chicken manure on the chemical properties of Ultisol and determine the optimal dose to increase peanut yield. The study used a Randomized Block Design (RBD), with six levels of treatment (B0: Control; B1: 15 t ha-1 Biochar; B2: 10 t ha-1 Biochar + 5 t ha-1 Chicken Manure; B3: 7.5 t ha-1 Biochar + 7.5 t ha-1 Chicken Manure; B4: 5 t ha-1 Biochar + 10 t ha-1 Chicken Manure; B5: 15 t ha-1 Chicken Manure), replicated four times. The observed parameters included soil pH, Organic-C, Available-P, and peanut dry seed yield. The data were analyzed using ANOVA and continued with the Duncan Multiple Range Test (DMRT) at the level of 5%. The results of the study showed that the application of coffee husk biochar and chicken manure had a significant effect on improving the chemical properties of Ultisol, such as increasing soil pH to 5.80 (B4), Organic-C to 3.00% (B2), and increased the Available-P to 35.31 ppm (B4). In addition, in the B3 and B4 treatments, the seed yield increased by 4.20 and 4.22 t ha-1. The recommended optimum dose is a combination of 7.5 t ha-1 of coffee husk biochar and 7.5 t ha-1 of chicken manure (B3).
In the context of cultivation areas, soil plays a highly strategic role because these areas are specifically designated for activities such as agriculture, plantations, fisheries, and animal husbandry. High-intensity use of soil in cultivation areas carries the risk of potential soil degradation if not managed wisely. The initial step in addressing soil degradation is to conduct an inventory of the potential for soil degradation in a given region. The determination of potential soil degradation refers to the guidelines of the Ministry of Environment (2009), using overlay, scoring, and weighting methods. Overall, the Teriak Subdistrict area has a low to moderate potential for soil degradation. In cultivation areas, the largest area with a low level of degradation is designated for horticultural agriculture (843.81 hectares), while the largest area with a moderate level of degradation is dominated by plantation use (10,026.79 hectares) and food crop agriculture (9,241.52 hectares). Factors that most influence the highest soil degradation potential scores include topography with steep slopes (26–40%) and dryland agricultural land use.
Soil Water Holding Capacity (WHC) is a crucial hydrological parameter for tea plant productivity in hilly terrains. Conventional WHC mapping on a large scale is generally constrained by high operational costs and lengthy analysis time. This study aims to evaluate the performance of Random Forest Regression (RFR) and Multiple Linear Regression (MLR) algorithms in predicting the spatial distribution of WHC at the Wonosari Tea Plantation, Malang. Soil sampling was conducted at 16 observation points using a stratified purposive sampling method based on Land Map Units (LMU). To represent water retention capacity in the effective root zone, undisturbed soil samples were collected vertically at depths of 0–20 cm, 20–40 cm, and 40–60 cm at each point, analyzed using a pressure plate apparatus, and integrated into a single profile average value. Six spectral indices were extracted from Sentinel-2A imagery (NDVI, NDSI, NDWI, LSWI, MSI, NMDI) based on their sensitivity to surface moisture and canopy density, then combined with slope data (DEMNAS) as predictor variables. Given the limited sample size, the RFR model validation was performed using the Leave-One-Out Cross-Validation (LOOCV) method to ensure predictive stability. Results showed that the RFR model with a combination of three key variables (NDSI, MSI, and slope) achieved higher accuracy (R²cv = 0.423; RMSEcv = 1.47%) compared to the MLR model (R² = 0.371; RMSE = 1.59%). Feature importance analysis revealed that slope was the most dominant controlling factor (68.5%). This evaluation concludes that the RFR algorithm is more reliable than MLR for modeling the spatial complexity of WHC in hilly areas. The resulting prediction map effectively divides the plantation into three management zones (High, Medium, Low) to support precision irrigation strategies and soil conservation, potentially increasing operational cost efficiency by 30–40%.
The decline in mustard productivity in recent years has been associated with increasing pest pressure and the uncontrolled use of insecticides. This study aimed to evaluate the effects of a neem leaf–based botanical insecticide and the synthetic insecticide methomyl, applied at three spraying frequencies, on total bacteria, total fungi, soil pH, and pesticide residues. The experiment was arranged in a randomized block design with nested treatments and a separate control. The results showed that the control and the treatments did not differ significantly in total bacterial populations, and insecticide type also had no significant effect. Within the nested factor, methomyl applied at a three-day spraying frequency produced the highest total bacterial population and differed significantly from the other treatments. Total fungal populations did not differ significantly across all treatments. Both types of insecticides increased soil pH compared with the control, with a greater increase observed in methomyl; spraying frequencies of six and nine days produced the highest soil pH values. Residue analysis showed that neither neem nor methomyl triggered the accumulation of persistent semi-volatile residues, and the detected chemical traces more closely reflected soil volatilization dynamics rather than the formation of long-term contaminants. Methomyl increased bacterial populations and soil pH as a short-term degradation response, while the botanical insecticide exerted lower ecological pressure due to its rapid degradation and the absence of stable metabolites. These findings confirm the potential of neem as a more sustainable pest management option and provide a scientific basis for determining pesticide application frequencies that are safe for soil conditions.
The abundant banana plant waste in Paciran, Lamongan, East Java, poses a risk of environmental pollution, but it also contains plant nutrients such as nitrogen, phosphorus, potassium, and organic matter that have the potential to improve the chemical characteristics of Paciran Latosol. This study aims to determine how liquid and solid organic fertilizers derived from banana plant waste in Paciran affect the chemical characteristics of Latosol and to examine how the application of organic fertilizers influences spinach growth. The study employed a non-factorial completely randomized design with nine treatments and three replicates. The treatments included: No Organic Fertilizer Application (P0), Liquid Organic Fertilizer Application at 0.22 ml/pot (equivalent to 25 L/ha) (P1), 0.44 ml/pot equivalent to 50 L/ha (P2), 0.66 ml/pot equivalent to 75 L/ha (P3), 0.88 ml/pot equivalent to 100 L/ha (P4), Application of Solid Organic Fertilizer at 4.36 g/pot, equivalent to 5 tons/ha (P5), 8.72 g/pot equivalent to 10 tons/ha (P6), 13.08 g/pot equivalent to 15 tons/ha (P7), and 20 tons/ha (P8). The results of the study indicate that the application of organic fertilizer has a significant effect on increasing the pH of H₂O, organic carbon, cation exchange capacity (CEC), available nitrogen, available phosphorus, and available potassium in Latosol, as well as on spinach growth, including plant height, number of leaves, and fresh weight. The application of solid organic fertilizer at a rate of 13.08 g/pot, equivalent to 15 tons/ha (P7), yielded the best results in improving both the chemical characteristics of Latosol and spinach growth.
Ambon City a high level of vulnerability to floods due to steep topography, extreme rainfall, and land use that exceeds land capability. Floods pose a serious threat to community safety and cause damage to infrastructure. Risk reduction requires an accurate and well-implemented early warning system. This study aims to analyze the spatial level of flood disaster risk, examine the distribution of extreme rainfall during rainfall events, and assess the accuracy of the Impact-Based Forecast and Warning Services System (IBFWS). The research method includes spatial analysis using a Geographic Information System (GIS) through an overlay approach of three risk components: hazard, vulnerability, and capacity. The study also applies Inverse Distance Weighting (IDW) methods for spatial interpolation of 24-hour rainfall data from the events on May 11 and May 30, 2023, and conducts spatial validation of the IBFWS prediction results against actual landslide occurrences. The results show that 75.6% of Ambon City falls into the high-risk category for floods. Multiple linear regression analysis indicates that slope gradient is the most significant variable influencing floods hazard, with an R² value of 90.6% and an S value of 0.120. Spatial validation and field verification demonstrate that the accuracy of the IBFWS reached 94% for the floods event on May 11 and 100% for the event on May 30, 2023. These findings indicate that the IBFWS functions as a reliable early warning system to support floods disaster risk reduction in Ambon City.
Soil-bound heavy metals have been a major and growing environmental issue in recent decades of time, especially across developing nations in the context of rapid urbanization and industrial development. So far, very few studies have examined the spatial distribution of heavy metal contamination in agri-and/or industrial soils. The objective of this review article is to analyze, identify, evaluate and synthesize the existing knowledge on heavy metal contamination in soils across diverse industrial and agri-based land uses worldwide. The PRISMA 2020 method was used in this review article, involving the selection of 22 journal articles that met the criteria for further study and discussion. Heavy metal contamination in soils is due mainly to industrial activities (82% of the studies) and agricultural activities (64%), whereas both sources of contamination were identified in 45% of the studies. On the other hand, the well-known spatial analysis methods for the spatial distribution of soil heavy metals are kriging and IDW. For the industrial sector, individual heavy metals such as Pb, Cr, Ni, and Zn are of greater concern than in the agricultural sector. These metals accumulate in the environment and the food chain, causing short-term and long-term diseases. The choice of spatial analysis techniques to examine the distribution of heavy metals can be modified based on the availability and reliability of the data. The results provide great guidance to researchers and policymakers in designing and implementing effective strategies for prevention, surveillance, and reduction of exposure to heavy metals worldwide.
Coastal alluvial paddy soils exhibit chemical characteristics influenced by hydrological dynamics, sedimentation processes, and the interaction between seawater and freshwater. Assessing the dynamics of soil chemical properties in both surface and subsurface layers is essential to understand the vertical distribution of nutrients, identify potential nutrient losses or accumulation, and support more accurate and sustainable soil fertility management. This study aimed to analyze the correlation between soil chemical properties in the topsoil (0–20 cm) and subsoil (20–50 cm) of coastal alluvial paddy soils. The parameters analyzed included pH H₂O, pH KCl, electrical conductivity (EC), cation exchange capacity (CEC), base saturation, total nitrogen, and exchangeable cations (Ca, Mg, K, and Na). Correlation analysis was conducted using statistical tests at a 5% significance level. The results showed significant correlations between soil chemical properties in the topsoil and subsoil, indicating strong vertical nutrient dynamics within the soil profile. In the topsoil, pH plays a key role in controlling phosphorus availability and cation balance, while in the subsoil, pH and salinity more strongly influence CEC, base saturation, and exchangeable cations. In addition, topsoil properties such as organic carbon and total nitrogen are associated with nutrient distribution in the subsoil through leaching and water movement processes. These findings provide important insights for improving sustainable soil fertility management in coastal paddy fields.
Tin mining is a daily activity carried out by some of the people in Lampur Village. Mining activities have an impact on the land that is left behind in the form of a decline in land quality. Land evaluation is needed to identify the potentials and constraints that exist in an area. The approach applied in this study involved matching primary and secondary data with the criteria for oil palm growth and development. Primary data were obtained by conducting laboratory analyses of cation exchange capacity (CEC), texture, pH, base saturation, and salinity. Secondary data included humidity, temperature, and rainfall. The results of the analysis show that former tin mining land is actually classified as unsuitable or N with texture as a constraint. The soil texture at 10 points is dominated by a sand fraction of 98%, causing the soil at the study site to be coarse in texture and requiring improvement efforts. Temperature (tc) is a permanent constraint that cannot be improved because it is natural. Constraints such as oxygen availability (oa), nutrient retention (nr), and erosion hazard (eh) can be improved to enhance land quality and class. Potentially, former tin mining land can be improved through remediation efforts, thereby increasing land quality while considering certain limiting factors.
Research on the identification of soil composition and Laevistrombus canarium (Gonggong) composition has been successfully conducted. Identification testing for all samples was performed using XRD and XRF. Diffraction data analysis was carried out using match!2 software and quantitative analysis was conducted using Rietveld refinement. The study found that, using XRF, the main soil constituent is Si and the main Gonggong constituent is Ca. The phases identified using Match!2 software in the soil samples were Quartz, Osumilete and Biotite. Furthermore, the phase identified in the Gonggong sample was CaCO3 single phase. Finally, the study found that the soil tested lacked macronutrients, such as N, needed for plants to grow well. To obtain these macronutrients, Laevistrombus canarium (Gonggong) has potential as an additional soil amendment to improve soil fertility. The implication is that the land in Batam has the potential for sustainable agriculture.
The presence of heavy metals in soil and water can be absorbed by plants growing in soil and water can have negative effects on humans. Biofertilizer containing microorganisms and producing exopolysaccharides (EPS) have the potential to be used as bioremediation agents. The study aims to determine the optimal combination of dosage and type of biofertilizer on cadmium (Cd) uptake the and the growth of water hyacinth (Eichhornia crassipes). The method used was a single-factor Randomized Block Design (RBD) with 9 treatments and 3 replications, resulting in 27 experimental units. The research data were analyzed using an F-test. If a significant effect was detected, the data were further tested using Duncan's Multiple Range Test (DMRT) at the 5% level. The results showed that the treatments had a significant effect on Cd uptake and plant growth. Treatment D (8 ppm Cd (25 mL Azotobacter)) yielded the highest results for plant height (31,33 cm), number of leaves (18,111 leaves), root length (27,499 cm), dry weight (28,777 g), and wet weight (135,22 g). Treatment D (8 ppm Cd (25 mL Azotobacter)) resulted in the lowest Cd uptake in roots (0,649 mg ), while Treatment I (16 ppm Cd) yielded the highest Cd content in water.
Maize is a key food commodity underpinning the economy of the Simpang Raya District, yet its yield has fallen to 3.6 tonnes per hectare. Imbalanced or inadequate fertilisation can lead to excessive nutrient uptake by plants, resulting in a decline in soil fertility. This study evaluates soil nutrient availability and fertility status to guide effective soil management aimed at optimising maize growth in Simpang Raya District, Banggai Regency. Using field surveys and kriging interpolation, the spatial distribution of soil nutrients was mapped, followed by comparison with soil fertility standards to determine fertility status. The methods used provided a high level of accuracy and the best estimates for determining soil fertility. Overall, this suite of methods represented a cost-effective and efficient solution for mapping soil fertility across extensive agricultural areas. The research results indicated that the study site had a soil pH of 5.6–6.2 (slightly acidic) and organic carbon (C) of 0.35–1.71%, with an average of 0.99% (very low). Phosphorus (P) content ranged from 7.51–32.01 ppm with an average of 18.09 (moderate), whilst potassium (K) ranged from 8.56–24.20 mg/100g, with an average of 16.55 (low). Cation Exchange Capacity (CEC) was classified as moderate, with an average of 20.93 cmol(+)/kg, ranging from 8.79–25.32 cmol(+)/kg, and Base Saturation (BS) averaged 32.68% (low), ranging from 14.02–58.71%. Overall, soil fertility for maize crops in the Simpang Raya District was classified as low to moderate. Management through liming and the application of organic fertiliser were strongly recommended. To improve soil quality, necessary interventions include liming, land rehabilitation, and the application of bio-fertilisers/biochar to increase organic carbon and base saturation. These measures require support in the form of organic fertiliser subsidies and intensive extension services from the government, particularly for the Simpang Raya District.
Soil fertility status is a key factor in determining the sustainability and productivity of agricultural systems, especially in areas with acidic soils such as Ultisols and Inceptisols. Land management without accurate nutrient status information can lead to misapplied fertilizers, low input efficiency, and continued soil fertility decline. This study aims to evaluate the status of primary macronutrients nitrogen (N), phosphorus (P), and potassium (K) in Ibru Village, Mestong Subdistrict, Muaro Jambi Regency as a basis for developing recommendations for more appropriate and sustainable land management. The study was conducted using a soil survey method with a 350 × 350 m grid at a 1:25,000 map scale. Land units were determined by overlaying soil texture, slope gradient, and land-use maps, yielding 12 Homogeneous Land Units (SLH) representing shrubland, oil palm, and rubber plantations. Disturbed soil samples were collected at 0–30 cm depth and analyzed for soil pH, organic C, total N, total P, and total K. The results showed that most of the soils were classified as very acidic to acidic (pH 3.82–5.83), with low to high organic C content (1.08–5.18%), low to moderate total N (0.12–0.29%), generally very low total P due to fixation in acidic soil conditions, and total K ranging from very low to high. These findings emphasize the importance of survey-based soil fertility evaluation and homogeneous land units as a basis for site-specific nutrient management.
