Search Results (221)

High-Andean grasslands in the Central Andes of Peru are severely degraded by Lepidium meyenii (maca) cultivation, compromising pasture structure and forage availability for sustainable livestock production. A factorial field experiment evaluated restoration timing and pasture-oriented seed mixtures by manipulating resting time after abandonment (0, 1, 2, and 3 years) and restoration treatment (control; Festuca dolichophylla monoculture; full mixture of Dactylis glomerata + Lolium spp. + Trifolium repens + F. dolichophylla; and mixture without F. dolichophylla) across 64 plots. Vegetation was assessed eight months after seeding, and responses were analysed with ordination, PERMANOVA with restricted permutations, PERMDISP, and generalised linear models and mixed-effects models for diversity metrics. Community composition differed significantly among resting times and seed treatments, with resting time explaining the largest proportion of variance (R² = 0.353), followed by treatment (R² = 0.236), while the interaction was significant but smaller (R² = 0.102, p = 0.002). PERMDISP detected significant differences in multivariate dispersion for both Resting Time and Treatment, indicating that compositional differences may reflect both centroid shifts and heterogeneity among groups. Passive recovery and Festuca-only plots showed slower, more variable compositional change, whereas productive mixtures produced clearer, treatment-specific trajectories over time, suggesting possible divergence in community development patterns, rather than providing formal evidence of distinct alternative stable states. Establishment was consistently high for D. glomerata and Lolium spp., supporting rapid ground cover, which may be associated with short-term forage potential, while F. dolichophylla showed chronically low establishment consistent with limited germination performance. The invasive Pennisetum clandestinum was most pronounced under passive recovery and was reduced under seeded mixtures, suggesting a potential competitive suppression effect. Overall, early seeding with productive mixtures appeared to influence community assembly trajectories, while resting time remained the dominant driver of compositional variation, suggesting potential implications for restoration management in maca-degraded landscapes, although outcomes related to sustainable grazing systems were not directly evaluated. Full article

Understanding how land management influences soil carbon (C) and nitrogen (N) dynamics is critical for improving ecosystem resilience and carbon sequestration potential in semiarid rangelands. This study used classical field- and laboratory-based methods to assess soil organic carbon (SOC), organic matter (OM), and N content at 13 sites across four ecological provinces in eastern Oregon, USA. Treated sites—where traditional rangeland restoration and management practices had been applied to them (i.e., juniper removal, sagebrush removal, post-fire grass seeding, and land conversion to pasture)—were paired with adjacent untreated control sites. Soil samples were collected at two depths, 0 to 10 cm and 15 to 25 cm and analyzed for C, N, OM, bulk density (BD), soil volumetric water content (SVWC), porosity, and texture. Soil C and N stocks were calculated on an area basis (t ha⁻¹), and statistical analyses were conducted using one-way ANOVA and correlation tests. Treated sites generally exhibited higher soil C, N, and OM content compared to untreated sites, particularly in the upper 10 cm of soil. Data obtained from the two soil depths (0 to 10 cm and 15 to 25 cm) were averaged and assumed to represent the top 30 cm of the soil profile, corresponding to the effective rooting zone at each field. The site where sagebrush removal was followed by grass seeding exhibited the highest soil C and N stocks (115.8 t C ha⁻¹ and 9.2 t N ha⁻¹, respectively). This site also had the highest OM content (9.53%), which was observed in the topsoil layer (0 to 10 cm) across all sites and depths. Strong positive correlations between C and N were detected across all sites (mean r = 0.92), while negative correlations were observed between soil C and bulk density at several locations. Results suggest that vegetation management practices such as woody plant removal and grass establishment can enhance soil C storage and nutrient retention in semiarid rangeland ecosystems. These findings provide baseline data to inform land management strategies aimed at improving soil health and carbon sequestration potential in the Pacific Northwest region in the USA. Full article

Intercropping systems involving sorghum, grasses, and legumes can enhance forage production and improve sustainability under no-tillage systems. In the context of agricultural systems, the effective selection of rotational species is essential, as they contribute to soil system dynamics and provide feed for livestock. In this study, the dry matter production of grain sorghum (GS: cultivar A 9902), forage sorghum (FS: cultivar Volumax), and dual-purpose sorghum (DPS: cultivar Rancheiro) intercropped with Urochloa brizantha and dwarf pigeon pea was evaluated at five sowing densities (0 to 24 seeds m⁻¹) over two growing seasons (2018 and 2019), conducted in a randomized complete block design under autumn growing conditions. Biometric and productive traits of sorghum were assessed, as well as the dry matter production of the companion species, in order to understand interspecific interactions within the system. Sorghum dry matter yield was not affected by pigeon pea density, indicating high stability of the main crop. Grain sorghum (GS) and forage sorghum (FS) showed higher production in the first season (20,428 and 18,210 kg ha⁻¹, respectively), whereas dual-purpose sorghum (DPS) performed best in the second season (25,388 kg ha⁻¹). GS exhibited the highest panicle production, exceeding the other cultivars by up to 55%. Increasing pigeon pea density enhanced its biomass production but reduced Urochloa production by up to 50%; however, Urochloa showed better performance when intercropped with GS and FS. Sorghum morphological traits were not affected, and overall, the intercropping system maintained sorghum productivity while increasing total biomass, demonstrating potential for silage production and pasture establishment. Full article

Data-driven approaches are increasingly required to optimize biofertilization strategies in forage systems. Machine learning (ML) provides an efficient tool for identifying functional drivers in complex plant–soil–microbe systems, offering important perspectives for precision data-driven agriculture. However, despite its potential, ML remains data-driven in studies involving diazotrophic inoculation using biochar as a pelletizing material, particularly in forage grasses. This study applied ML to predict the key drivers controlling Brachiaria brizantha performance and soil quality under biochar-pelletized diazotrophic bacteria (DB). Five isolates were inoculated with or without biochar, and plant traits and soil attributes, including pH, potassium, phosphorus, sodium, and urease activity were evaluated. These data were integrated into multivariate analyses and ML algorithms, including Linear Discriminant Analysis, Random Forest, and Support Vector Machine, to identify the functional drivers that best discriminate treatment performance and uncover mechanistic functional drivers. All isolates increased soil potassium content, with the highest values in the biochar amended treatments, and a 39% increase. Soil pH and urease activity were significantly modulated by isolate identity, while biomass allocation patterns differed among treatments. Overall, the results highlight that biochar pelletization can enhance the effectiveness of DB inoculants. ML revealed that dry foliar biomass, soil pH, and fresh root weight were the most predictive variables, highlighting consistent signatures explaining plant–soil responses to biochar-pelletized DB. These findings demonstrate that interpretable ML can disentangle complex plant–soil–microbe interactions, support precision biofertilization design, and serve as an efficient decision-support tool for sustainable pasture management. Beyond the present system, this study establishes a transferable and scalable analytical framework for precision biofertilization strategies in forage systems and other biochar-mediated agroecosystems, advancing predictive and data-driven approaches in sustainable agricultural engineering. Full article

The degradation of wetlands and forests is still a threat to the supply and recovery of ecosystem services in the tropics. Studies comparing restoration measures and ecosystem service recoveries are fragmented. This study investigated the spatial extent and drivers of wetland/forest degradation, and assessed the effects of restoration measures on the recovery of ecosystem services and resilient livelihoods. A cross-sectional household survey was conducted targeting households adjacent to restored and unrestored wetland/forest ecosystems. The data was analyzed using a Binary Logistic regression to characterize earlier and recovered ecosystem services between forest and wetland ecosystems. High spatial-resolution optical satellite imagery from the Airbus constellation was obtained and analyzed to examine wetland and forest degradation. Our findings revealed that the spatial extent of degraded land under wetlands and forests decreased between 2023 and 2025. Ecosystem service degradation was primarily driven by chronic poverty, excessive water abstraction, population growth, burning practices, overharvesting of resources, overgrazing, cultivation, infrastructure development, and the invasion of alien species (p < 0.05). The counteractive ecosystem restoration activities undertaken included mobilization and sensitization of communities on wetland restoration, wetland demarcation, revegetation, establishment of flood control measures, and provision of alternative livelihoods (p ≤ 0.05). The multiple direct and indirect ecosystem service recoveries reported were provisioning services (increases in pasture, enhanced livestock production, increased soil productivity, health-related benefits from crops and livestock products) and regulating services (improved water quality/quantity). The ecosystem service recoveries were more significant in the restored wetlands than the forests. The indicators of enhanced ecosystem-based resilient livelihoods included increased household incomes, higher livestock yields, increased crop productivity, improved health from crop/livestock products, improved water quality/quantity, and enhanced scenic beauty and tourism (p < 0.05). The restoration activities in degraded wetland systems had more potential to facilitate full recovery of the wetland ecosystem compared to the absence of interventions. This evidence highlights the need to restore high-ecological-sensitive ecosystems to sustain the delivery of ecosystem services for community and environmental resilience. Full article

In the oilseed–cereal–forage system, information on the performance of grasses of the genus Megathyrsus maximus and on the optimal fertilization levels for forage production is still scarce. Therefore, this study aimed to evaluate forage yield (FY) of pastures established in crop succession systems and subjected to two fertilization regimes during the 2020 and 2021 growing seasons, in the municipality of Rio Verde, Brazil. The experiment evaluated four M. maximus cultivars (Paredão, Zuri, Quênia, and Tamani) under two fertilization rates: maintenance (50, 50, 20, and 3.2 kg ha⁻¹ year⁻¹ of N, K, S, and micronutrients, respectively) and enhanced (150, 150, 40, and 6.4 kg ha⁻¹ year⁻¹, respectively). The Zuri cultivar showed a higher daily forage accumulation rate and greater forage leaf mass compared with the other cultivars. In addition, the Zuri and Paredão cultivars achieved the highest FY, reaching 12.80 and 12.10 Mg ha⁻¹, respectively. The Tamani cultivar exhibited a lower neutral detergent fiber concentration and a higher total digestible nutrient concentration, indicating its potential for systems that prioritize higher forage nutritive value. Zuri and Paredão maximize forage yield in crop succession systems, while enhanced fertilization increases yield by 15%, with adoption dependent on economic feasibility. Full article

Farmland abandonment is becoming a growing land use challenge in the Brazilian Cerrado, yet its extent, spatial distribution, and underlying drivers remain poorly understood. This study addresses the following question: Can deep learning methods reliably identify abandoned farmlands in tropical savanna environments using multispectral satellite images? To answer this question, we used a Fully Connected Neural Network (FCNN) classifier to map abandoned farmlands in the municipality of Buritizeiro, Minas Gerais State, Brazil, using Sentinel-2 images acquired in 2018 and 2022. Seven land use and land cover (LULC) classes were mapped using visible and near-infrared bands, spectral indices, spectral mixture components, and principal components as input parameters for the CNN. The LULC map for 2022 achieved high classification performance (overall accuracy = 94.7%; Kappa coefficient = 0.93). Agricultural areas classified in 2018 as annual croplands, cultivated pastures, eucalyptus plantations, or harvested eucalyptus that transitioned to grasslands or shrublands in 2022 were considered abandoned. Based on this definition, we identified 13,147 hectares of abandoned land in 2022, representing 4.7% of the municipality’s agricultural area in 2018. Most abandoned areas corresponded to eucalyptus plantations established for charcoal production. This study provides the first deep learning-based assessment of farmland abandonment in the Cerrado. Our findings demonstrated the potential of FCNN classifiers for detecting abandoned farmlands in this biome and provide important contribution for public policies focused on ecological restoration, carbon sequestration, and sustainable agricultural planning. Full article

This paper establishes a comprehensive analytical framework for a new transformation of probability measures, denoted by ${\mathcal{T}}_{(a,t)}$, which unifies the classical t- and $T_a$-transformations in free probability. We derive the functional equation characterizing ${\mathcal{T}}_{(a,t)}$ through the Cauchy–Stieltjes transform and explicitly show how it specializes to known deformations when $a=0$ or $t=1$. Within the setting of Cauchy-Stieltjes kernel families, we prove structural symmetry and invariance properties of the transformation, demonstrating in particular that both the free Meixner family and the free analog of the Letac-Mora class remain invariant under ${\mathcal{T}}_{(a,t)}$. Furthermore, we obtain several new limiting theorems that uncover symmetric relationships among fundamental free distributions, including the semicircular, Marchenko–Pastur, and free binomial laws. Full article

This article discusses the issue of pasture degradation in the West Kazakhstan region, which has been caused by a significant rise in the population of saigas (Saiga tatarica). This study aims to quantify agricultural losses and establish the relationship between saiga numbers and ecosystem changes. The research methodology incorporates field observations, agroecological observations, and mathematical analysis. Correlation and regression analyses were performed. The application of correlation and regression models confirmed a statistically significant relationship between the growth of the saiga population and the decline in hay yield: increasing animal numbers lead to a reduction in pasture productivity. The greatest losses were recorded in the Bokeiordinsky district, where grazing pressure exceeded 62.5%. It was concluded that urgent measures are needed to regulate the saiga population, restore degraded land, and introduce rotational grazing. Mechanisms for the adaptive management of wild populations that take into account the interests of the agricultural sector were proposed. The findings obtained can provide a solid foundation for informed decision-making in agricultural and environmental policy within the region. Full article

Rhipicephalus microplus, also known as the Asiatic blue tick, is an invasive ectoparasite of significant economic and animal health importance in South Africa. This review synthesises evidence on its ongoing range expansion, which is displacing the native R. decoloratus, driven by factors including climate suitability, livestock movement, and communal grazing practices. The tick’s success is compounded by widespread, multi-class acaricide resistance, which has been documented across all major chemical classes. Molecular diagnostics are crucial for accurate surveillance, and population genetics reveal significant gene flow facilitated by livestock movement. Projections indicate that climate change will further expand the tick’s suitable habitat. Current reliance on chemical control is unsustainable. We conclude that an integrated parasite management (IPM) approach combining strategic acaricide rotation, targeted selective treatments, pasture management, and strict biosecurity is critical for sustainable control. Key recommendations include establishing standardised, national resistance monitoring, validating molecular markers for resistance prediction, and developing farmer-facing decision-support tools. This synthesis provides a framework for research and policy to mitigate the impact of R. microplus at the wildlife-livestock interface in South Africa. Full article

Free-ranging hens are at risk of infection by parasites characterized by certain stages that develop in the soil until attaining the infective phase. To analyze the usefulness of a biological control strategy of helminths affecting pasturing hens, fecal samples containing eggs of the helminths Ascaridia galli and Capillaria spp. were collected and then homogenized with an electric mixer. A total of 64 small areas were established by placing wooden frames (15 × 40 × 30 cm) on the ground and then adding approximately 100 g of a fecal mixture (per area). Four batches of 16 areas were considered: G1, sprayed with 2 × 10⁶ spores of the parasitophagous fungus Mucor circinelloides (day 0) at 0.5 L/m² (=600 mL/area); G2, sprayed with spores twice (every two weeks); G3, sprayed four times (every week); and Control, sprayed weekly with water. After a four-week period, the egg viability reduced for ascarids and capillarids (26% and 27%, respectively) in the control group; 64% and 79% in G1; 71% and 82% in G2; and 79% and 80% in G3. It was concluded that spraying with fungal spores provides a very useful tool for preventing infection by helminths on free-range poultry. Full article

Silage is an essential tool for maintaining productivity, especially during the dry season and when pasture availability is limited. However, it is necessary to establish increasingly efficient methods for producing this feed, seeking to minimize losses and provide maximum nutritional benefit. This study aimed to evaluate the quality of Cenchrus purpureus (Schumach.) Morrone cv. BRS Capiaçu silage with cornmeal addition or after 3 or 5 days of wilting, focusing on fermentative profile, chemical composition, and in situ degradation. A completely randomized design with four treatments and three replicates was used: Control (CON), ensilage with 8% ground cornmeal (SGC), wilting for 3 days (WI3), and wilting for 5 days (WI5), totaling 12 silos. After 120 days, the silages were analyzed for pH, volatile fatty acids, chemical composition, and rumen degradability using three cannulated cows. Data were subjected to ANOVA and Tukey’s test (p < 0.05). The SGC and WI3 treatments showed lower pH (4.55 and 4.52) and butyric acid (0.27 and 0.33%) and higher lactic acid (2.32 and 1.57%) contents compared with CON and WI5 (p < 0.001). They also presented higher dry matter (257.2 and 318.3 g/kg) and crude protein (63.8 and 58.5 g/kg) and lower fiber fractions (p < 0.001). For rumen degradability, SGC had the highest values for fraction “A” and effective degradability of dry matter at 5 and 8%/h passage rates (p = 0.001). Cornmeal addition and 3-day wilting improved silage quality, but only cornmeal enhanced degradability. Full article

Scenarios of climate change, extensive land use, soil degradation, the loss of native forest cover due to monoculture expansion, and pasture scarcity pose new challenges to livestock farming worldwide. Associated crops emerge as an alternative to mitigate these factors; however, selecting compatible species that do not generate competition and optimize the attributes of the forage is a necessity. Therefore, this study evaluated the effect of a maize and bean association, and cutting time on the morphological variables, yield, and nutritional composition of forage. A randomized complete block design (RCBD) with a 3A × 3C factorial arrangement and three blocks was used. Factor A (associations) had three levels: INIA-604-Morocho maize monoculture (M), M+PER1003544 chaucha bean association (M+F1), and M+PER1003551 chaucha bean association (M+F2). Factor C (maize cutting stage) had three levels: R2 (blister grain), R3 (milky grain), and R4 (pasty grain). A total of 27 experimental units were established. No silage was made; the nutritional quality was evaluated as the raw material for silage. The treatments modulated key attributes for silage. In R4, the M+F2 association (INIA-604-Morocho + PER1003551) showed a higher percentage of dry matter in the system (32.36%) and better mixture quality due to a lower NDF and ADF (48.22% and 23.29%) and higher digestibility and protein values (62.10% and 9.53%). In addition, dry matter yields increased compared with R2 in M+F1 (134.16%), M+F2 (90.56%), and M (138.48%). Although R3 maximized green forage, R4 offered the best combination of quantity and quality for silage (as raw material), reducing the risk of deterioration and improving forage use efficiency. In general, combining maize with beans and adjusting the cut to R4 optimizes the production and quality of the raw material for silage, with the criterion that these findings pertain to pre-ensiled material and should be validated in future studies. Full article

The application of dolomitic limestone is a recommended practice for improving pastures established on acidic soils. On the other hand, pasture availability should determine the adjustment of the biotic load. The aim of this study is to evaluate the potential of pasture plant community composition as an indicator to assess the effects of intensification strategies in the Montado ecosystem, specifically soil pH correction and/or increasing animal stocking rate. Forty-eight sampling areas of a biodiverse pasture were monitored on a 4-ha plot located at the Mitra farm (Évora district; southern Portugal). The experimental design included four treatments: with and without limestone application (respectively, DL and WDL) × traditional low stocking rate (LSR, 7 sheep ha⁻¹) and high stocking rate (HSR, 18 sheep ha⁻¹). Floristic composition, structural parameters, and diversity metrics were recorded and analyzed using multivariate statistical tools. Pasture diversity was assessed through the computation of richness indices, with plant species identified as ecological indicators representative of each study area. The results showed Rumex pulcher, Trifolium subterraneum, Plantago lanceolata, and Lolium rigidum as botanical indicators of the four treatments of this study, respectively, LSR in untreated soil, HSR in untreated soil, HSR in treated soil, and LSR in treated soil. The results also show that soil amendment led to a more distinct and stable pasture floristic composition (PFC) compared to untreated areas. Conversely, the stocking rate (SR) played a secondary but still ecologically relevant role. Notably, HSR appears to reduce the need for lime application to achieve a balanced floristic composition and desirable plant community structure, potentially lowering soil amendment costs without compromising pasture quality. In LSR areas, the application of lime was essential to significantly improve the floristic richness, the vegetation cover, and the presence of legumes. Full article

Productive and healthy soils are essential in agriculture and other economic uses of land which depend on plant growth, and are under increasing pressure globally. The physical properties of soil, its porosity and pore structure, also have a significant impact on a wide range of environmental factors, such as surface water runoff and greenhouse gas exchange. Methods exist for evaluating soil porosity that are applied in a laboratory environment or by inserting sensors into soil in the field. However, such methods do not readily sample adequately in space or time and are labour-intensive. The purpose of the current study is to investigate the potential for estimation of soil porosity and pore size using the strength of reflection of audio pulses from natural soil surfaces. Estimation of porous material properties using acoustic reflections is well established. But because of the complex, viscous interactions between sound waves and pore structures, these methods are generally restricted to transmissions at low audio frequencies or at ultrasonic frequencies. In contrast, this study presents a novel design for an integrated broad band sensing system, which is compact, inexpensive, and which is capable of rapid, non-contact, and in situ sampling of a soil structure from a small, moving, farm vehicle. The new system is shown to have the capability of obtaining soil parameter estimates at sampling distances of less than 1 m and with accuracies of around 1%. In describing this novel design, special care is taken to consider the challenges presented by real agriculture soils. These challenges include the pasture, through which the sound must penetrate without significant losses, and soil roughness, which can potentially scatter sound away from the specular reflection path. The key to this new integrated acoustic design is an extension of an existing theory for acoustic interactions with porous materials and rigorous testing of assumptions via simulations. A configuration is suggested and tested, comprising seven audio frequencies and three angles of incidence. It is concluded that a practical, new operational tool of similar design should be readily manufactured. This tool would be inexpensive, compact, low-power, and non-intrusive to either the soil or the surrounding environment. Audio processing can be conducted within the scope of, say, mobile phones. The practical application is to be able to easily map regions of an agricultural space in some detail and to use that to guide land treatment and mitigation. Full article