Soil Fertility Analysis Research Articles

Strengthen farmers' fertilizer self-sufficiency in the tourist area with a reduce-reuse-recycle system

Mining activities at Tebing Breksi are a vital source of income for the community in Sambirejo village, Sleman Regency, Yogyakarta. However, these activities have caused several environmental issues, such as lowered pH levels, reduced soil fertility, shallow soil profiles, and water scarcity. Additionally, mining has led to biodiversity loss and land degradation, making post-mining reclamation essential to restore the area's environmental and social functions. This project aimed to enhance the community’s skills in soil analysis and the production of liquid organic fertilizer using effective methods. The activities took place in the Tebing Breksi tourist area, located in Nglengkong, Sambirejo Village, Prambanan District, Sleman Regency. The project included a Focus Group Discussion (FGD), soil fertility analysis using test kits, and the creation of liquid organic fertilizer from household waste. During the FGD, it was discovered that the local community had not received prior training on producing fertilizer from household and organic waste. Until then, they relied on expensive commercial fertilizers to quickly stabilize soil pH. Through this training, the community learned how to perform rapid soil chemical analysis and produce liquid organic fertilizer independently. As a result, they can now apply the fertilizer locally, improving soil conditions and reducing their reliance on costly commercial products.

Fertility and quality of arable soils in Poland: spatial–temporal analysis of long-term monitoring

Soil quality is a globally important issue from the point of view of food production, maintenance of appropriate environmental quality and ecological balance. Assessing its quality and fertility using indices is one of the methods that make it possible to formulate recommendations for good soil management. The aim of the study was, therefore, to determine the spatial and temporal distribution of soil properties in the context of soil quality assessment (SQI) and soil fertility assessment (SFI, SEF, NIV, and SSFI) using the example of a Central European country (Poland). The inverse distance-weighted spatial interpolation technique was used to estimate the spatial distribution of soil quality and fertility indicators. So far, no research has been carried out that would include a comprehensive analysis of soil fertility and quality indicators in such a large research area over many years. The results of 216 points of monitoring the chemistry of arable soils in Poland from the period 1995–2020 for 28 physicochemical soil parameters were considered. The analyses carried out showed significant variability in the properties of the described soils in Poland, as evidenced by the principal component analysis (PCA) and the coefficient of variation (exceptions: bulk density, pH). It was found that heavy metals (Zn, Cd, Cu) were responsible for the deterioration of soil properties. The results obtained for different indices were different (SFI – most soils with good fertility, SEF – high fertility, NIV – soils highly enriched with nutrients, SQI – average soil quality). It was found that the SSFI is the most appropriate indicator among the analyzed indicators for Polish conditions in relation to arable soils, as it is adapted and calibrated to the specifics of this area. The Spearman correlation matrix showed that the largest group of statistically highly significant parameter pairs belonged to heavy metals (Ni/Zn, Zn/Pb, Zn/Cu, Ni/Cu). In contrast, the strongest correlations were recorded for Ni (with effective cation exchange capacity (ECEC), Mn, Mgav, Zn, Cu). The assessment revealed limiting factors and temporal trends in the overall evaluation of the quality of the country’s agricultural soils, which are important from the point of view of both sustainable development and agricultural production.

Geospatial Analysis of Soil Fertility in Muzaffarpur District, Bihar, India: Integrating GPS and GIS Technologies

The soil fertility maps generated using Global Positioning System (GPS) and Geographic Information Systems (GIS) serve as crucial tools for effective nutrient management decision-making. However, soil fertility data for the Minapur, Kanti, and Marwan blocks of Muzaffarpur district, Bihar, India was found to be insufficient. Therefore, a soil fertility inventory research was conducted in these three blocks to create thematic soil fertility maps. A total of 40 geo-referenced composite soil samples were collected from various locations within the study area using a handheld GPS device. The processed soil samples were analyzed for various soil fertility parameters using standard methods. Soil nutrient status and fertility maps were then created using ArcGIS software with Inverse Distance Weighted (IDW) interpolation techniques. The results clearly indicated that the soil reaction was alkaline, with a pH value exceeding 7.5. The content of soil organic matter, potassium, and sulphur was found to be low to medium, while available nitrogen and phosphorus levels were recorded as very low in these blocks. Finally it is concluded that the study generated thematic soil fertility maps for Minapur, Kanti, and Marwan blocks of Muzaffarpur district, Bihar, revealing alkaline soil with low to medium organic matter, potassium, and sulphur and very low nitrogen and phosphorus levels.

Assessment of soil fertility in Xinjiang oasis cotton field based on big data techniques

Assessing soil fertility through traditional methods has faced challenges due to the vast amount of meteorological data and the complexity of heterogeneous data. In this study, we address these challenges by employing the K-means algorithm for cluster analysis on soil fertility data and developing a novel K-means algorithm within the Hadoop framework. Our research aims to provide a comprehensive analysis of soil fertility in the Shihezi region, particularly in the context of oasis cotton fields, leveraging big data techniques. The methodology involves utilizing soil nutrient data from 29 sampling points across six round fields in 2022. Through K-means clustering with varying K values, we determine that setting K to 3 yields optimal cluster effects, aligning closely with the actual soil fertility distribution. Furthermore, we compare the performance of our proposed K-means algorithm under the MapReduce framework with traditional serial K-means algorithms, demonstrating significant improvements in operational speed and successful completion of large-scale data computations. Our findings reveal that soil fertility in the Shihezi region can be classified into four distinct grades, providing valuable insights for agricultural practices and land management strategies. This classification contributes to a better understanding of soil resources in oasis cotton fields and facilitates informed decision-making processes for farmers and policymakers alike.

Exploring the potential of Canavalia ensiformis for phytoremediation of B10 biodiesel-contaminated soil: insights on aromatic compound degradation and soil fertility

The widespread use of petroleum-based fuels poses a significant environmental problem due to the risks associated with accidental spills. Among the treatments available, phytoremediation is increasingly accepted as an effective and low-cost solution. This study aimed to evaluate the degradation of the aromatic fraction of biodiesel B10 and the soil fertility analysis in artificially contaminated soils treated with phytoremediation. The experimental design consisted of a 3x3 factorial, with three types of soil treatment: control, autoclaved, and planted with C. ensiformis L, and three levels of B10 biodiesel contamination: 0, 1, and 2%, to simulate spills of 30,000 and 60,000 L ha−1. The soil was analyzed at three depths: 0–10, 10–20, and 20–30 cm. The results indicated that aromatic compound degradation after phytoremediation was superior to 92,76% and 88,65% for 1% and 2% B10 soil contamination, respectively. The fuel contamination affected soil fertility, reducing the availability of phosphorus and zinc while increasing the Total Organic Carbon (TOC), pH, and the availability of manganese and iron for plants.

Characterizing River Manafwa Floodplain and Adjacent Soils

The objective of this study was to characterise Manafwa River floodplain and adjacent soils. Soil samples were collected from 0 - 20 cm depth in fallowed and cultivated Manafwa floodplain soils for laboratory analysis. Treatments included upland (control), floodplains fallowed for a year, floodplains fallowed for over a year, cultivated floodplains within 5 m and 50 m away from the river banks. Each treatment was replicated three times (3 blocks), and samples collected were analysed for K, Na, available P, total N, exchangeable acidity, pH, organic matter, moisture content, sand, silt, and clay. The soil sampling results were subjected to statistical Analysis of Variance (ANOVA) using Randomised Complete Block Design (RCBD), and the difference between treatment means were dictated using F-, student’s t and F-LSD/pairwise comparison tests. There was statistically no significant (p > 0.05) difference among different floodplains and uplands studied. Upland soils posted 71.67% for the highest pH and 0.09%, 0.87%, 9.74 ppm, 2.23 ppm and 7.264% for the lowest available N, organic matter, Phosphorous, Sodium and Moisture Content, respectively. Cultivated floodplain soil posted highest total P at 29.16 ppm and pH at 6.39% while fallowed floodplains lowest pH at 5.34%, highest available N at 0.32%, highest organic matter at 4.02%, highest K at 21.33%, highest Na at 13.93%, highest exchangeable acidity at 2.32 Cmol/Kg, highest clay content at 14.33%, lowest sand composition at 38.00%, highest silt composition at 54.8% and highest Moisture Content of 32.472%. As depicted by soil fertility analysis results, Manafwa River floodplain and adjacent soils have the capacity to accommodate and boost crop production and productivity. Any nutrients lost to leaching could be gained from subsequent fallowing and sustainable soil fertility management, proper drainage, crop rotation, adding organic manure, and cover cropping, among others

Mineral dust and pedogenesis in the alpine critical zone

Abstract. The influence of mineral dust deposition on soil formation in the mountain critical zone was evaluated at six sites in southwestern North America. Passive samplers collected dust for 2 years, and representative soil and rock were gathered in the vicinity of each dust sampler. All materials (dust, soil, and rock) were analyzed to determine their mineralogy (with X-ray diffraction), geochemistry (with inductively coupled plasma mass spectrometry (ICP-MS)), and radiogenic isotope fingerprint (87Sr/86Sr and εNd). In addition, the grain size distribution of dust and soil samples was determined with laser scattering, and standard soil fertility analysis was conducted on the soil samples. Results reveal that minerals present in the dust but absent in the local bedrock are detectable in the soil. Similarly, the geochemistry and isotopic fingerprint of soil samples are more similar to dust than to local bedrock. End-member mixing models evaluating soil as a mixture of dust and rock suggest that the fine fractions of the sampled soils are dominated by dust deposition, with dust contents approaching 100 %. Dust content is somewhat higher in soils compared to bedrock types more resistant to weathering. These results emphasize the dominant control that mineral dust deposition can exert on pedogenesis in the mountain critical zone.

Analysis of soil fertility and toxic metal characteristics in open-pit mining areas in northern Shaanxi

The study specifically focused on the Hongliulin mining area, where a total of 40 soil samples were meticulously collected and analyzed from within a 1000 m radius extending from the tailings dam. The findings revealed that soil pH within the 0–1000 m range generally leaned towards the alkaline side. In terms of soil nutrient content, encompassing factors such as soil organic matter (SOM), total nitrogen (TN), total phosphorus (TP), total potassium (TK), alkali nitrogen (AK), available phosphorus (AP), and quick-acting potassium (AK), the variations fell within the following ranges: 2.23–13.58 g/kg, 0.12–0.73 g/kg, 0.18–1.15 g/kg, 9.54–35.82 g/kg, 2.89–6.76 mg/kg, 3.45–11.25 mg/kg, and 5.86–130.9 mg/kg. Collectively, these values indicate relatively low levels of soil nutrients. Within the 0–500 m range of soil samples, the average concentrations of Cd, Hg, Pb, and As were 0.778, 0.198, 24.87, and 17.92 mg/kg, respectively. These concentrations exceeded the established soil background values of Shaanxi Province and emerged as the primary pollutants in the study area. Within this same range, the mean values of eight toxic metals (Pi) were ranked in the following descending order: 1.726 (Hg), 1.400 (As), 1.129 (Cr), 1.109 (Pb), 0.623 (Zn), 0.536 (Cd), 0.309 (Cu), and 0.289 (Ni). With the exception of Hg, As, Cr, and Pb, which exhibited slight pollution, the other toxic metals were found to be within acceptable pollution limits for this sampling range, in line with the results obtained using the geo-accumulation index method. The average potential ecological risk index for the eight toxic metals in the study area stood at 185.0, indicating a moderate overall pollution level. When assessing individual elements, the proportions of ecological risk attributed to Hg, As, Pb, and Cd were 34.57%, 27.44%, 25.11%, and 23.11%, respectively. This suggests that the primary potential ecological risk elements in the study area are Hg and As, followed by Cd and Pb. Notably, toxic metals Hg and Pb, as well as As and Pb, exhibited significant positive correlations within the sampling area, suggesting a common source. An analysis of the relationship between soil physicochemical properties and toxic metals indicated that soil pH, SOM, TN, and TP were closely linked to toxic metal concentrations. The toxic metal elements in the research area's soil exhibit moderate variability (0.16 < CV < 0.36) to high variability (CV > 0.36). Within the range of 0–200 m, the CV values for Cd and Hg exceed 1, indicating a high level of variability. The coefficient of variation for SOM, TP, AP, AK and TK is relatively high with the of 2.93, 2.36, 2.36, 21.01, 7.54. The soil in the sampling area has undergone significant disturbances due to human activities, resulting in toxic metal pollution and nutrient deficiencies.

Geospatial Analysis of Soil Fertility in Muzaffarpur District, Bihar, India: Integrating GPS and GIS Technologies

Geospatial Analysis of Soil Fertility in Muzaffarpur District, Bihar, India: Integrating GPS and GIS Technologies

Soil Fertility Analysis using Microarthropod Diversity Index in Coffee-Based Agroforestry in Mount Ungaran, Indonesia

Soil Fertility Analysis using Microarthropod Diversity Index in Coffee-Based Agroforestry in Mount Ungaran, Indonesia

Optimizing Classification Algorithms Using Soft Voting: A Case Study on Soil Fertility Dataset

Classification algorithms are crucial in developing predictive models that identify and classify soil fertility levels based on relevant attributes. However, optimizing classification algorithms presents a major challenge in enhancing the accuracy and effectiveness of these models. Therefore, this research aims to optimize the classification algorithm in soil fertility analysis using ensemble learning techniques, specifically Soft Voting Ensemble. This research method is designed to understand soil fertility levels in modern agriculture by comparing the performance of various classification algorithms and ensemble approaches. Using a dataset from the Purwodadi Department of Agriculture, this study examines the optimization of algorithm parameters such as Random Forest, Gradient Boosting, and Support Vector Machine (SVM) and the implementation of Soft Voting Ensemble. Before applying Soft Voting Ensemble, each algorithm was evaluated with the following results: Random Forest achieved an accuracy of 90.93%, precision of 91.08%, recall of 90.33%, and F1-Score of 90.70%; Gradient Boosting achieved an accuracy of 91.53%, precision of 91.19%, recall of 91.56%, and F1-Score of 91.38%; SVM achieved an accuracy of 88.91%, precision of 89.66%, recall of 87.45%, and F1-Score of 88.54%. After implementing Soft Voting Ensemble, the accuracy improved to 91.63%, with an average precision of 91.21%, recall of 91.77%, and F1-Score of 91.49%. This study divided the data into 80% for training data and 20% for testing data. These findings indicate that the Soft Voting Ensemble has the potential to enhance agricultural productivity and sustainability.

Restoring ex mining area using Pongamia pinnata in Central Kalimantan: a reclamation program alternative base on bioenergy species

Malapari (Pongamia pinnata (L) Pierre) is an endemic species of Leguminosae from southeast Asia, Australia and Afrika. Malapari is one species alternative of Reclamation Program in PT Asmin Bara Bronang. The aims of this study are to know the growth and adaptation rate of Malapari in extrime area after charcoal mining and to introduce the malapari for a alternative species for reclamation program with bioenergy potential species. The research method used is the census method in areas planted with malapari at PT ABB which was observed from 2020 with parameters including malapari growth; survival rate; analysis of soil fertility; biodiversity and carbon estimate. The results showed that malapari growth on post-mining land was very rapid where within 4 years it increased in height by an average of 184,92cm with a diameter growth of 10.76 cm and a survival rate of 87,78%, above ground biomass 584,04kg (274,5kg carbon) with very good leaf growth in fresh dark green The condition of early soil fertility becomes increased after planting. The great hope in this program is that malapari can be an alternative species for post-coal mining forest restoration from local superior species of use that has the potential to be a bioenergy source.

Shifting cultivation in decline: An analysis of soil fertility and weed pressure in intensified cropping systems in Eastern Amazon

Reconciling forest preservation and agricultural production is a major challenge. In Brazil, environmental laws have been introduced to reduce forest degradation associated with the expansion of agriculture. However, these laws are constraining small-scale family farmers who rely on cassava produced in shifting cultivation. Faced by scarcity of land, farmers are reducing the fallow periods on their farms. In this study, our hypothesis was that the reduction of the fallow period in shifting cultivation systems leads to a depletion of soil fertility and an increase in weed pressure. In the Brazilian Eastern Amazon region, soil fertility and weed infestation indicators were assessed in 36 cassava fields under shifting cultivation with different land-use histories. The frequency of cultivation of the fields in the past 10 years ranged from 1 to 7 and averaged 3.7 ± 2.3. The results show that the most frequently cultivated fields had lower soil fertility, indicated by lower soil organic carbon, total nitrogen and exchangeable potassium and pH. In addition, labor input for weeding and weeding frequency increased with the frequency of cultivation of the fields, indicating that weed pressure increased with intensified crop cultivation and shorter fallow periods. The findings of this study make clear that the current trend of reducing the fallow period in the Eastern Amazon is a threat to the sustainability and productivity of the local shifting cultivation systems. There is an urgent need for alternative production systems that allow for a better weed control and that contribute to restoring and maintaining soil fertility.

Effect of phosphorus and potassium fertilization on summer greengram (Vigna radiata) varieties

This experiment suggests that the utilization of the greengram variety IPM 02-3 is advantageous due to its superiority in terms of performance and adaptability over other varieties investigated. Additionally, application of 50 kg/ha P2O5 and K2O demonstrates comparable performance and profitability to application of 60 kg/ha P2O5 and K2O, making it an economically favourable option. Soil fertility analysis revealed P and K's role in enhancing nutrient dynamics. The relation between soil nutrient levels and greengram yield underscores the multifaceted relationship. In summary, genetic factors, coupled with optimal nutrient management, synergistically affect the growth and yield of greengram.

Increasing the Fertility and Productivity of Marginal Land by Planting Leguminous Plants

Background: Marginal land is dry land which has limited nutrient content so it has relatively low productivity. The development of marginal land use can be optimized with an ecosystem approach strategy through improving soil fertility. Planting leguminous plant species that can fix nitrogen from the atmosphere can increase soil fertility. Methods: This research was conducted to determine the ability of plants (A = Corn; B = Peanuts; C = Green Beans; D = Soybeans) to increase soil fertility and plant productivity. The experiment was designed in a randomized block design consisting of four treatments, each treatment was repeated four times. Soil fertility analysis was carried out before planting (pH, Carbon (%), Nitogen (%) and C/N ) and after planting (pH, Carbon (%), Nitogen (%) and C/N). Productivity (straw (kg/ha), seeds (kg/ha) and effective nodules. Results: The experimental results showed that the planting of legumes had a significant effect on increasing soil fertility and forage productivity, nodulation but lower legume seed production compared to maize

Alfisol Soil Fertility Before Planting and After Harvest as Meloon Planting Media with Bioboost Fertilization

Soil fertility is important in the cultivation process. Soil fertility is the potential of the soil to provide nutrients in sufficient quantities in available and balanced forms to ensure optimum plant growth and production. The current availability of nutrients in the soil has decreased as a result of continuous land use with the use of chemical fertilizers in the cultivation process, plus leaching and erosion by rainwater, not least in Alfisol soils. Therefore, fertilization with organic materials is carried out, namely the provision of Bioboost fertilizer. Bio boost is a biological fertilizer containing superior soil microorganisms, useful for increasing soil fertility as a result of soil biochemical processes. One of the applications of organic cultivation is the cultivation of melon (Cucumis melo L.) because melon is a plant that has high economic value and is profitable to be cultivated as a source of income for farmers. Based on this, a study was conducted to determine the nutrient status of Alfisol soil before planting and after harvesting which was used as a Melon plant with various concentrations of Bioobost fertilization. Furthermore, for the analysis of soil fertility, laboratory analysis was carried out by taking 1 kg of disturbed soil samples that had been air-dried and then analyzing soil properties, namely texture, pH (H2O), C-Organic (%), Nitrogen (%), P2O5 (ppm), K (cmol kg-1), Ca (cmol kg-1), Mg (cmol kg-1), Na (cmol kg-1), Na (cmol kg-1), CEC (cmol kg-1), and KB (%). The application of Bio boosts fertilizer showed an increase in the nutrient status of Alfisol soil as a Melon growing from low to moderate categories before planting to medium to high categories after harvest. The more concentration of Bioboost fertilizer given, the soil nutrient status also increases. The concentration of P4 (1100ml bio boost + 400ml water) gave the highest increase in nutrient status.&#x0D; Keywords: bioboost; soil-fertility; melon

Behaviour and Analysis of Soil Fertility Based on ML Models

Behaviour and Analysis of Soil Fertility Based on ML Models

Soil fertility analysis in the Republic of Bashkortostan

The manuscript presents the materials of soil fertility analysis of agricultural lands in the north-eastern forest-steppe of the Republic of Bashkortostan in the conditions of the Salavatskiy district of the republic (Russian Federation). Agrochemical analysis of the humus accumulation, mobile phosphorus, exchangeable potassium was carried out, morphological properties were studied, the thickness of the humus horizon, granulometric composition and soil erosion were determined. During the 49-year period of agricultural land use, it was revealed some of the medium-humus soils passed into the category of high-humus, caused by the fact that the arable lands were not used for cultivating crops and they were withdrawn from circulation and sown with many-year-old grasses. As to the thickness of the humus horizon, low-yielding soils predominate, which occupy 60.11%, average 32.9%. The main land area belongs to slightly washed soils of 67,445.2 ha (58.2%) and unwashed 36,985.5 ha (31.9%). Agricultural lands are mainly characterized as medium-humus (80.3%) and obese (12.1%) ones. Based on the results of the research, an adjustment, digitization and a new soil map of the Salavatskiy district was made with the allocation of the main types and subtypes of soils with the indication of varieties on a scale of 1:25,000.

Soil Fertility Analysis with Soil Microorganism Indicators

Areca nut and sago are typical fruits of the Papuan Community which produce waste. Utilization of waste for the community itself has not been done optimally, especially in agriculture. One way to overcome the problem of soil fertility is by adding organic matter. Areca nut shell waste and sago stem waste are alternative uses of existing waste by processing it into liquid organic fertilizer (POC) and biochar. Adding organic matter to the soil can increase soil productivity and fertility and can affect soil biological properties by increasing the activity of soil biota which play a role in breaking down and decomposing organic matter so that soil biological properties increase. The purpose of this study was to compare the biological properties of the soil applied with biochar and liquid organic fertilizer (POC) derived from areca nut shell and sago bark waste. The research method consisted of a completely randomized design (CRD) which consisted of 7 treatment levels. The first treatment (SB0) was control (without adding biochar), the second treatment (SB1) was areca nut shell waste biochar, the third treatment (SB2) was sago stem waste biochar, the fourth treatment (SB3) was a combination of areca nut shell and stem biochar. sago, the fifth treatment (SB4) was POC of areca nut shell waste, the sixth treatment (SB5) was POC of sago stem waste, and the seventh treatment (SB6) was a combination of POC of areca nut shell waste and sago stems. The parameters of this study included determining the total bacterial population, total fungal population, soil respiration, organic matter activity, nitrogen fixing activity, pH, Organic-C, and Total-N. Based on the results of the research that has been done, it can be concluded that the treatment in the form of biochar and POC in general has a significant effect on increasing soil pH, Organic-C, Total-N, total bacterial population, total fungi population, soil respiration, Nitrogen fixing activity, and The activity of organic matter. Treatment with biochar (SB1, SB2, and SB3) gave the highest average microbial population which was directly proportional to the respiration rate. Pinang dan sagu merupakan buah khas masyarakat Papua yang menghasilkan limbah. Pemanfaatan limbah bagi masyarakat itu sendiri belum dilkakukan secara optimal, terutama di bidang pertanian. Salah satu cara untuk mengatasi masalah kesuburan tanah adalah dengan pemberian bahan organik. Limbah kulit buah pinang dan limbah batang sagu menjadi alternatif pemanfaatan limbah yang ada dengan diolah menjadi pupuk organik cair (POC) dan biochar. Pemberian bahan organik ke dalam tanah dapat meningkatkan produktivitas dan kesuburan tanah serta dapat mempengaruhi sifat biologi tanah dalam meningkatkan aktivitas biota tanah yang berperan dalam merombak serta mendekomposisi bahan organik sehingga sifat biologi tanah meningkat. Tujuan dari penelitian ini adalah untuk membandingkan sifat biologi tanah yang diaplikasikan dengan biochar dan pupuk organic cair (POC) yang berasal dari limbah kulit buah pinang dan kulit batang sagu. Adapun metode penelitian ini terdiri dari Rancangan Acak Lengkap (RAL) yang terdiri dari 7 taraf perlakuan. Perlakuan pertama (SB0) adalah control (tanpa pemberian biochar), perlakuan kedua (SB1) adalah biochar limbah kulit buah pinang, Perlakuan ketiga (SB2) adalah Biochar limbah batang sagu, Perlakuan keempat (SB3) adalah kombinasi Biochar limbah kulit buah pinang dan batang sagu, perlakuan kelima (SB4) adalah POC limbah kulit buah pinang, Perlakuan keenam (SB5) adalah POC limbah batang sagu, dan Perlakuan ketujuh (SB6) adalah kombinasi POC limbah kulit buah pinang dan batang sagu. Parameter dari penelitian ini meliputi penetapan total populasi bakteri, total populasi fungi, respirasi tanah, Aktivitas perombak bahan organic, aktivitas penambat Nitrogen, pH, C-Organik, dan N-Total. Berdasarkan hasil penelitian yang telah dilakukan dapat disimpulkan bahwa pemberian perlakuan berupa biochar dan POC secara umum memberikan pengaruh yang nyata terhadap kenaikan pH tanah, C-Organik, N-Total, total populasi bakteri, total populasi fungi, respirasi tanah, aktivitas penambat Nitrogen, dan Aktivitas perombak bahan organic. Perlakuan dengan pemberian biochar (SB1, SB2, dan SB3) memberikan rata-rata populasi mikroba tertinggi yang berbanding lurus dengan laju respirasinya.

Comparative Analysis of Pasture Soil Fertility in Semiarid Agro-Silvo-Pastoral Systems

Dryland pastures are usually on soils with a low fertility. However, a high spatial variability is apparent in pasture soils. In consequence, the application of inputs should be based on the particular characteristics of each field and their within-field variability. In this study, a comparative analysis of seven experimental fields (agro–silvo–pastoral ecosystems) in the southwest of the Iberian Peninsula was performed using a probabilistic and objective model. Some soil properties (the texture, cation exchange capacity, soil apparent electrical conductivity, organic matter, nitrogen, potassium and slope) measured at six sampling locations in each field were consolidated in the model. It was verified that the data fit the model and, later, a ranking of all the sampling locations and, consequently, a ranking of all the experimental fields according to the pasture soil fertility was established. Moreover, another output of the model was a ranking of the soil properties according to their influence on the soil fertility: the topographical property, the slope, was the most influential as it is related to the level of other important soil properties, as the textural components. Two fields, Cubillos and Grous, had the highest overall soil fertility levels because the soil samples in these fields were very fertile. However, some samples in the other five fields were also in the group of the most fertile, denoting the existence of an important spatial variability within each field. The proposed method is a rational way to improve the efficiency of the use of fertilisers by adjusting them to the soil pasture fertility.