Methane, a potent greenhouse gas, is a significant contributor to global warming. One of the primary natural sinks for atmospheric methane is forest soils, which, teeming with special microorganisms, actively consume methane through a process called methanotrophy. However, this natural balance is being disrupted mainly by the conversion of forest lands into agricultural areas. This land-use change often leads to a reduction in the area covered by methane-consuming soils, exacerbating the overall methane emissions problem.

Chernevaya Taiga is a unique forest ecosystem in Siberia, known for intense microbial activity related to the nitrogen and carbon cycles. However, studies focusing on methane cycling and the isolation of methanotrophs within these forests have not been conducted. We hypothesized that active methanotrophs might be present in these soils with specialized adaptations to harsh environmental conditions.

We isolated methanotrophic consortium; T1 exhibited exceptionally high methane oxidation rates from the dark gray soil of the Сhernevaya taiga, Tomsk region. 16S rRNA gene profiling revealed the predominance (74%) of Methylocystis. It was established that the introduction of the T1 into the agrosoil with low methane oxidation activity resulted in an increased methane uptake rate. Furthermore, measuring the accumulation of CO₂ in the samples correlates well with the methane oxidation rate and confirms the high activity of the introduced culture as a methane sink. Nevertheless, the number of 16S rRNA gene copies reached 3.9 × 10⁹ and changed minimally over a period of four weeks. Concurrently, the number of pmoA gene copies remained at a relatively high level of 8.81 × 10⁵ – 1.47 × 10⁶, which indicates the significant presence of methanotrophs within the agrosoil microbial community.

The research was funded by a grant # 25-24-20102 of the Russian Science Foundation (https://rscf.ru/en/project/25-24-20102/).

Dry root rot is one of the most important wheat diseases worldwide, including in Morocco. This study aimed to evaluate the health status of five no-till soils compared to a conventionally tilled soil in terms of the dry root rot severity, microbial biodiversity, and potential inoculum level of Fusarium culmorum. To assess the disease severity, a root rot-susceptible variety, “Ourgh”, was grown under greenhouse conditions in six natural soils collected from three regions (Abda, Chaouia, and Ourdigha), each with different previous crops (lentils, fallow, wheat, barley, and forage). The disease severity was assessed at the flowering on the roots and stem internodes, and the microbial biodiversity was estimated using microbial counting techniques. These evaluations were also performed after artificial inoculation with F. culmorum. Root rot symptoms, confirmed through pathogen isolation from infected roots and stems, were observed in all six soils at varying levels. Three pathogenic genera were identified—Fusarium spp., Alternaria spp., and Bipolaris (B. sorokiniana)—with Fusarium spp. being present in all the soils. The no-till soils showed higher microbial diversity than the conventionally tilled soil, which was dominated by bacteria, except the soil from Ourdigha with barley as the previous crop, in which the fungal and bacterial levels were similar. Inoculation increased the microbial diversity and disease severity and reduced the plant height without significantly affecting the dry biomass. Except for in this latter soil, the microbial profiles shifted post-inoculation, with soils becoming either bacteria-dominant or balanced. The soil type, texture, and crop history (except a crop history of barley) had no significant impact on the microbial biodiversity. These findings highlight potential natural resistance mechanisms against F. culmorum for exploitation in future biological control strategies.

The use of sawdust-fortified topsoil as a growing medium has emerged as a promising approach to promote increase in yield and promotion of sustainability in agriculture. Given that different crops have varying soil requirements, it is essential to determine the optimal ratio of sawdust to topsoil for each crop. This study investigates the effect of sawdust-fortified topsoil on the growth and development of mini-stem propagated plantain suckers, using the detached corm (split) technique—a macropropagation method used in generating healthy plantain mini-stems. This experiment compared the effect of varying ratios of topsoil (TS) and sawdust (SD), namely, 100TS (control), 50TS50SD, 60TS40SD, and 70TS30SD, on plantain mini-stems. Growth parameters recorded across five replicates per treatment included stem height, stem girth, leaf number, and leaf area. Data were analyzed using ANOVA via SPSS.

The result showed that all treatments positively influence growth parameters, with Treatment 4 (70TS30SD) showing the most significant effect on stem height, stem girth, and leaf area. This outcome is attributed to a balance ratio between sawdust and topsoil resulting to improved soil structure, balanced nutrient availability, optimal aeration, and water retention.

This study suggests that fortifying topsoil with sawdust, particularly at the ratio of 70TS30SD, can improve the sprouting rate, growth, and development of mini-stem propagated plantain suckers. This finding therefore presents a viable and sustainable alternative to traditional propagation media (i.e., topsoil only) in plantain production. It also provides farmers around tropical regions with a clear practical ratio to adopt.

Soil salinity is an essential constraint to sustainable crop production related to soil fertility, especially in arid and semi-arid regions. This study presents a data-driven approach for mapping soil salinity by integrating field-based electrical conductivity (EC) measurements with remote sensing and geospatial analysis in the district of Mandi Baha Uddin, Pakistan. Eleven georeferenced soil samples were collected and analyzed for EC (range: 0.59–1.06 dS/m), serving as training data for model calibration. Using Landsat 8 Surface Reflectance imagery within Google Earth Engine, spectral indices Normalized Difference Salinity Index (NDSI), Salinity Index (SI), and Brightness Index (BI) were extracted. Among various modeling approaches, a linear regression model was applied to these indices, revealing NDSI as the most significant predictor (coefficient = 3.862), while SI and BI showed negligible contribution. The model achieved moderate accuracy (R² = 0.526, RMSE = 0.089 dS/m). A Random Forest approach yielded higher training accuracy (R² = 0.811) but suffered from overfitting during cross-validation, indicating limited sample size constraints. The regression equation (EC = 3.862 × NDSI + 1.71) was applied in GEE to generate the EC prediction map. The resulting 30-meter resolution EC map was classified into FAO salinity categories and validated through independent field observations. This framework highlights the effectiveness of using freely available satellite data and cloud-based platforms like GEE for cost-effective soil salinity monitoring. This study provides a transferable methodology for precision agriculture, enabling informed land management and crop planning in salinity-affected regions.

Soil survey and characterization were conducted in five identified locations in the province of Capiz, Philippines, to determine the occurrence of problem soils. Site description and soil profiling were done in each site. Soil samples were collected and processed. Soil physical properties that were determined included soil texture, soil structure, soil color, bulk density, and soil porosity. The chemical properties of soil analyzed were pH, soil organic matter, total nitrogen (N), available phosphorus (P), exchangeable potassium (K), calcium (Ca), magnesium (Mg), and electrical conductivity (EC). The microbial respiration rate was determined for the soil's biological properties. The physical, chemical, and biological properties of topsoil and subsoil of the five sites were interpreted using their means and compared with the established values for different soil parameters indicative of each problem soil. Results revealed that the site in Sitio Asag, Barangay Lonoy, Sapian, Capiz, qualified to be a saline soil because of its EC and pH values. The subsoil is a potential acid sulfate soil. The site in Sitio Cabugao, Barangay Burias, Mambusao, Capiz was confirmed to be a nutrient-depleted soil, particularly of N, P, K, Ca, and Mg. The site is also an acidic soil with very shallow true soil. The site in Sitio Proper, Barangay Duyoc, Dao, Capiz, was, at the time of sampling, not considered compact soil. However, the site has the potential tto become compact soil if the production practices remain the same or if not managed properly. The site in Sitio Agkawayan, Barangay Burias, Mambusao, Capiz, proved to be a strongly acidic soil and a nutrient-depleted soil. The site in Sitio Proper, Barangay Agloloway, Jamindan, Capiz, revealed degraded soil and is presently under the state of recovery. Hence, an intervention program was crafted to address the soil problems in each site.

How do long-term fertilization practices alter the channelling of carbon into its fractions across different layers of the soil profile? The potential of soil to sequester carbon is largely determined by how carbon is stored in its fractions. While numerous long-term fertilization studies have investigated carbon fractions, most have primarily focused on the surface soil. Consequently, the extent to which these fertilization practices impact carbon fractions at greater depths within the soil profile remains largely unexamined. This study investigates the impacts of different fertilization practices (100% N, 100% NPK, 150% NPK and 100% NPK+FYM) on different carbon fractions in the deeper layers of soil (0-100cm). The soil samples were collected from an ongoing 51-year long-term experiment that was started in 1971. This study determined total SOC and its fractions including particulate organic matter (POM), light and heavy fraction carbon (LFC and HFC), aggregate associated C, acid hydrolyzable and non-hydrolyzable C (AHC and ANHC), dissolved organic carbon (DOC), fractions of different oxidizability and microbial biomass carbon (MBC). The results showed that 100% NPK+FYM has the highest TSOC stocks up to 100 cm depth. Moreover, 100% NPK+FYM consistently enhanced labile carbon fractions throughout the soil profile (0-100 cm). While all fertilization treatments generally increase carbon fractions, their positive impacts on particulate and density-based organic carbon fractions diminished significantly with increasing soil depth, particularly below 30 cm. Ultimately, our research demonstrates that carbon sequestration and its subsequent persistence in agricultural soils necessitates integrated nutrient management, as evidenced by the sustained positive impact of 100% NPK+FYM on diverse carbon fractions throughout the soil profile, whereas the benefits of chemical fertilizers alone become limited with increasing depth.

Current fertilization practices in the country rely on generalized, empirical methods, resulting in inefficient input use and suboptimal crop management. The high cost and limited spatial resolution of traditional soil analysis restrict farmers' ability to optimize fertilization in maize fields. This project proposes an autonomous unmanned ground vehicle (UGV) for characterizing soil fertility and nutrient content in Zea mays L. (hard yellow maize), a crop critical to Peru’s food security.

The system integrates low-cost sensors to measure pH, electrical conductivity (EC), and nitrogen, phosphorus, and potassium (NPK) levels in maize fields. These sensors are calibrated using a machine learning model based on Random Forest, trained with soil samples analyzed at the Instituto Nacional de Innovación Agraria (INIA). To enable sampling, a mechanism was developed that combines a rotary auger—capable of drilling up to 15 cm—and a vertical displacement system that positions the sensor in the soil. This mechanism also ensures operation in compacted soils, protecting the sensor needles. The sampling system is mounted on a mobile platform equipped with GPS-RTK for geolocation and a ZED stereo camera for autonomous navigation and environmental perception.

The UGV collects measurements across the field and transmits data in real time to a digital platform that generates fertilization maps and reports. The goal is to provide farmers with an accessible tool for improved fertilization decision-making in hard yellow maize cultivation. Field tests at Universidad Nacional Agraria La Molina—including comparisons between sensor data and laboratory analyses—demonstrate the feasibility of autonomous operation and the system’s effectiveness in assessing soil fertility under real conditions.

This innovation fosters the adoption of autonomous robotics for sustainable agriculture, with strong potential to increase yields, improve fertilizer efficiency, and support national food security.

Potato (Solanum tuberosum) is a significant global food crop. Intensive cultivation has heightened dependence on chemical fertilizers, leading to environmental and economic issues. A primary challenge in potato cultivation is the supply of phosphorus, which frequently demonstrates low levels due to leaching, inefficient utilization, and escalating fertilizer manufacturing costs. This study investigates the agronomic and economic benefits of employing natural rock amendments, specifically rock phosphate and feldspar, in conjunction with plant growth-promoting rhizobacteria (PGPR) as a sustainable input instead of chemical fertilizers for enhancing the yield and tuber quality of potatoes. A field experiment was executed to evaluate three treatments: conventional chemical fertilizers (T1), reduced chemical fertilizers combined with PGPR Bacillus megaterium and Azotobacter (T2), and natural rock potassium feldspar, and rock phosphate injected with PGPRs (T3). Regarding tuber quality, T2 and T3 exhibited enhanced tuber quality compared to T1. Also, the highest starch content and the lowest reducing sugar content were in T3. Moreover, T3 demonstrated superior soil quality post-harvest, exhibiting an enhanced total phosphorus level in soil compared to the usual chemical fertilizer treatment, in addition to higher tuber quality. T3 decreased operating expenses by 11% and attained a maximum production of 42 tons per hectare. The return on investment was approximately 79%, accompanied by a 28% profit gain ($3,988/ha) compared to T1 ($2,460/ha). The results show that using PGPR with natural rock fertilizers is a cheaper and effective option compared to regular chemical fertilizers, improving production, profits, and the long-term health of the soil.

This study presents the preliminary findings from a field experiment aimed at evaluating the health status of Capsicum pubescens crops, commonly known as rocoto in Peru, using unmanned aerial systems (UASs) equipped with multispectral sensors. C. pubescens is a neglected and underutilized crop with significant agroecological and nutritional value, traditionally cultivated in the Andean highlands but lacking modern cultivation and monitoring practices. The experiment was conducted in the province of Rodríguez de Mendoza, Amazonas, Peru. A DJI Mavic 3M drone, fitted with a multispectral camera, was used to collect aerial imagery over three rocoto crop plots during the production stage. From these images, a Green Area Index (GAI) map was generated, and ten vegetation indices (VIs) were calculated to assess the plant health. Key indicators included the Green Chlorophyll Index (CIgreen), which reached a maximum of 1.22, and the Red Edge Chlorophyll Index (CIred edge), with a peak value of 1.16, both suggestive of active vegetation with a moderate chlorophyll content. The Normalized Difference Vegetation Index (NDVI) and Green NDVI (GNDVI) reached values of 0.99 and 0.92, respectively, indicating a healthy physiological status and high productive potential. These vegetation indices will serve as input variables for machine learning models (multiple linear regression, support vector machines, and random forests), which will be used, combined with feature selection techniques, to further refine crop health assessments. The integration of UAS technologies and artificial intelligence represents an innovative approach to modernize agricultural monitoring of neglected crops such as C. pubescens. This effort supports progress toward the broader goal of revitalizing the cultivation of traditional crops in the Andean–Amazonian region, enhancing food security, and adapting agriculture to climate variability.

Determining the mycoflora of wheat grain is important because it is the basis for making decisions about how to use it. For seed batches, this makes it possible to assess the risk of seed-borne diseases and build an appropriate protection system, including a reasoned approach to the choice of a seed treatment agent. This study was conducted in different zones of Ukraine during 2020-2023. In total, fungi of 12 genera were identified. Among the endophytic mycoflora of winter wheat seeds, Alternaria spp. were most often detected. They were found in all studied samples. The proportion of their presence in the grain varied in the years of research. In some cases, its share reached 78%, and on average, it was 10,7-35,1%. The highest level of contamination was observed in 2022. A high presence of Fusarium spp. was also noted. They were isolated from the vast majority of samples (70-91%). The highest isolation frequency, for Alternaria spp., was observed in 2022. Also, in the same year, the highest level of contamination (in average 7%) was noted. The presence of fungi of other genera was much lower. Epicoccum spp., Penicillium spp., Nigrospora spp., Cladosporium spp., and Aspergillus spp. were isolated every year and had a share in the total complex on average from 0.2 to 2.1% over the years of research. So, Alternaria dominate in the complex of endophytic microflora on winter wheat seeds. Fusarium ranks second in terms of isolation frequency.