Search Results (3,895)

The chickpea (Cicer arietinum L.) is a key legume crop in Mediterranean agriculture, valued for its nutritional profile and adaptability. However, its productivity is severely impacted by drought stress. To identify microbial solutions that enhance drought resilience, we isolated seven Mesorhizobium strains from chickpea nodules collected in southern Spain and evaluated their cultivar-specific symbiotic performance. Two commercial cultivars (Pedrosillano and Blanco Lechoso) and twenty chickpea germplasms were tested under growth chamber and greenhouse conditions, both with and without drought stress. Initial screening in a sterile substrate using nodulation assays, shoot/root dry weight measurements, and acetylene reduction assays identified three elite strains (ISC11, ISC15, and ISC25) with superior symbiotic performance and nitrogenase activity. Greenhouse trials under reduced irrigation demonstrated that several strain–cultivar combinations significantly mitigated drought effects on plant biomass, with specific interactions (e.g., ISC25 with RR-98 or BT6-19) preserving over 70% of shoot biomass relative to controls. Whole-genome sequencing of the elite strains revealed diverse taxonomic affiliations—ISC11 as Mesorhizobium ciceri, ISC15 as Mesorhizobium mediterraneum, and ISC25 likely representing a novel species. Genome mining identified plant growth-promoting traits including ACC deaminase genes (in ISC11 and ISC25) and genes coding for auxin biosynthesis-related enzymes. Our findings highlight the potential of targeted rhizobial inoculants tailored to chickpea cultivars to improve crop performance under water-limiting conditions. Full article

This study aims to quantify total VOC emissions and evaluate how torrefaction alters the heat of combustion of three agricultural residues. The work examines the amount of VOC emissions during the torrefaction process at various temperatures and investigates the changes in the heat of combustion of agri-biomass resulting from the torrefaction process. The process was carried out at the following temperatures: 225, 250, 275, and 300 °C. Total VOC emission factors were determined. The reaction kinetics analysis revealed that meadow hay exhibited the most stable thermal behavior with the lowest activation energy. At the same time, rye straw demonstrated higher thermal resistance and complex multi-step degradation characteristics. The authors analyze three types of agricultural biomass: meadow hay, rye straw, and oat straw. The research was divided into five stages: determination of moisture content in the sample, determination of ash content, thermogravimetric analysis, measurement of total VOC emissions from the biomass torrefaction process, and determination of the heat of combustion of the obtained torrefied biomass. Based on the research, it was found that torrefaction of biomass causes the emission of torgas containing VOC in the amount of 2–10 mg/g of torrefied biomass, which can be used energetically, e.g., to support the torrefaction process, and the torrefied biomass shows a higher value of the heat of combustion. Unlike prior studies focused on single feedstocks or limited temperature ranges, this work systematically compares three major crop residues across four torrefaction temperatures and directly couples VOC quantifications. Full article

Soil microbial communities are crucial for ecosystem services, soil fertility, and the resilience of agroecosystems. This study investigated how long-term (31 years) agronomic practices—tillage, NPK fertilization, and cropping system—along with measured environmental variables influence the microbial biomass and its community composition in Chernozem soil under corn cultivation. The polyfactorial field experiment included three tillage treatments ((moldboard (MT), ripped (RT), strip (ST)), two fertilization regimes (NPK (N: 160; P: 26; K: 74 kg/ha), and unfertilized control) and two cropping systems (corn monoculture and corn–wheat biculture). The soil samples (0–30 cm) were collected in June and September 2023. Microbial biomass and community structure were quantified using phospholipid fatty acid (PLFA) analysis, which allowed the estimation of total microbial biomass and community composition (arbuscular mycorrhizal (AM) fungi, fungi, Gram-negative (GN) and Gram-positive (GP) bacteria, actinomycetes). Our results showed that microbial biomass increased from June to September, rising by 270% in unfertilized plots and by 135% in NPK-fertilized plots, due to higher soil moisture. Reduced tillage, especially ST, promoted significantly higher microbial biomass, with biomass reaching 290% and 182% of that in MT plots in June and September, respectively. MT had a higher ratio of bacteria-to-fungi compared to RT and ST, indicating a greater sensitivity of fungi to disturbance. NPK fertilization lowered soil pH by about one unit (to 4.1–4.8) and reduced microbial biomass—by 2% in June and 48% in September—compared to the control, with the particular suppression of AM fungi. The cropping system had a smaller overall effect on microbial biomass. Full article

Fertilization is a critical measure for vegetation restoration and ecological reconstruction in degraded grasslands. However, little is known about the long-term effects of different combinations of nitrogen (N), phosphorus (P), potassium (K) on plant and microbial communities in degraded grasslands. This study conducted a four-year (2017–2020) N, P, K addition experiment in the Khorchin Grassland, a degraded typical grassland located in Zhalute Banner, Tongliao City, Inner Mongolia, to investigate the effects of fertilization treatment on plant functional groups and microbial communities after grazing exclusion. Our results showed that the addition of P, NP, and NPK compound fertilizers significantly increased aboveground biomass of the plant community, which is mainly related to the improvement of nutrient availability to promote the growth of specific plant functional groups, especially annual and biennial plants and perennial bunchgrasses. However, the addition of N, P, and NP fertilizers significantly reduced the species diversity of the plant community. At the same time, the addition of N, P, and NP fertilizers and the application of N and NP significantly reduced fungal species diversity but had no significant effect on soil bacteria. Our study provides new insights into the relationships between different types of fertilization and plant community productivity and biodiversity in degraded grasslands over four years of fertilization, which is critical for evaluating the effect of fertilization on the restoration of degraded grassland. Full article

Flavonoids serve as crucial plant antioxidants in drought tolerance, yet their antioxidant regulatory mechanisms within mycorrhizal plants remain unclear. In this study, using a two-factor design, trifoliate orange (Poncirus trifoliata (L.) Raf.) seedlings in the four-to-five-leaf stage were either inoculated with Funneliformis mosseae or not, and subjected to well-watered (70–75% of field maximum water-holding capacity) or drought stress (50–55% field maximum water-holding capacity) conditions for 10 weeks. Plant growth performance, photosynthetic physiology, leaf flavonoid content and their antioxidant capacity, reactive oxygen species levels, and activities and gene expression of key flavonoid biosynthesis enzymes were analyzed. Although drought stress significantly reduced root colonization and soil hyphal length, inoculation with F. mosseae consistently enhanced the biomass of leaves, stems, and roots, as well as root surface area and diameter, irrespective of soil moisture. Despite drought suppressing photosynthesis in mycorrhizal plants, F. mosseae substantially improved photosynthetic capacity (measured via gas exchange) and optimized photochemical efficiency (assessed by chlorophyll fluorescence) while reducing non-photochemical quenching (heat dissipation). Inoculation with F. mosseae elevated the total flavonoid content in leaves by 46.67% (well-watered) and 14.04% (drought), accompanied by significantly enhanced activities of key synthases such as phenylalanine ammonia-lyase (PAL), chalcone synthase (CHS), chalcone isomerase (CHI), 4-coumarate:coA ligase (4CL), and cinnamate 4-hydroxylase (C4H), with increases ranging from 16.90 to 117.42% under drought. Quantitative real-time PCR revealed that both mycorrhization and drought upregulated the expression of PtPAL1, PtCHI, and Pt4CL genes, with soil moisture critically modulating mycorrhizal regulatory effects. In vitro assays showed that flavonoid extracts scavenged radicals at rates of 30.07–41.60% in hydroxyl radical (•OH), 71.89–78.06% in superoxide radical anion (O₂^•−), and 49.97–74.75% in 2,2-diphenyl-1-picrylhydrazyl (DPPH). Mycorrhizal symbiosis enhanced the antioxidant capacity of flavonoids, resulting in higher scavenging rates of •OH (19.07%), O₂^•− (5.00%), and DPPH (31.81%) under drought. Inoculated plants displayed reduced hydrogen peroxide (19.77%), O₂^•− (23.90%), and malondialdehyde (17.36%) levels. This study concludes that mycorrhizae promote the level of total flavonoids in trifoliate orange by accelerating the flavonoid biosynthesis pathway, hence reducing oxidative damage under drought. Full article

This study investigates the spatial heterogeneity of carbon pools in young Betula sp. stands on former arable lands in the southern Moscow region, Russia. The findings could be useful for the current estimates and predictions of the carbon balance in such forest ecosystems. The research focuses on understanding the interactions between plant cover and the environment, i.e., how environmental factors such as stand density, tree diameter and height, light conditions, and soil properties affect ecosystem carbon pools. We also studied how heterogeneity in edaphic conditions affects the formation of plant cover, particularly tree regeneration and the development of ground layer vegetation. Field measurements were conducted on a permanent 50 × 50 m sampling plot divided into 5 × 5 m subplots, in order to capture variability in vegetation and soil characteristics. Key findings reveal significant differences in carbon stocks across subplots with varying stand densities and light conditions. This highlights the role of the spatial heterogeneity of soil properties and vegetation cover in carbon sequestration. The study demonstrates the feasibility of indirect estimation of carbon stocks using stand parameters (density, height, and diameter), with results that closely match direct measurements. The total ecosystem carbon stock was estimated at 80.47 t ha⁻¹, with the soil contribution exceeding that of living biomass and dead organic matter. This research emphasizes the importance of accounting for spatial heterogeneity in carbon assessments of post-agricultural ecosystems, providing a methodological framework for future studies. Full article

Continuous and accurate biomass measurement is a critical enabler for control, decision making, and optimization in modern plant production systems. It supports the development of plant growth models for advanced control strategies like model predictive control, and enables responsive, data-driven, and plant state-dependent cultivation. Traditional biomass measurement methods, such as destructive sampling, are time-consuming and unsuitable for high-frequency monitoring. In contrast, image-based estimation using computer vision and deep learning requires frequent retraining and is sensitive to changes in lighting or plant morphology. This work introduces a low-cost, load-cell-based biomass monitoring system tailored for vertical farming applications. The system operates at the level of individual growing trays, offering a valuable middle ground between impractical plant-level sensing and overly coarse rack-level measurements. Tray-level data allow localized control actions, such as adjusting light spectrum and intensity per tray, thereby enhancing the utility of controllable LED systems. This granularity supports layer-specific optimization and anomaly detection, which are not feasible with rack-level feedback. The biomass sensor is easily scalable and can be retrofitted, addressing common challenges such as mechanical noise and thermal drift. It offers a practical and robust solution for biomass monitoring in dynamic, growing environments, enabling finer control and smarter decision making in both commercial and research-oriented vertical farming systems. The developed sensor was tested and validated against manual harvest data, demonstrating high agreement with actual plant biomass and confirming its suitability for integration into vertical farming systems. Full article

Soil phosphorus (P) availability is an important determinant of productivity in Pinus massoniana (Masson pine) forests. The mechanistic bases governing the physiological and growth responses of Masson pine to varying soil P conditions remain insufficiently characterized. This study aims to decipher the adaptive strategies of Masson pine to different soil P levels, focusing on root morphological–architectural plasticity and the allocation dynamics of nutrient elements and photosynthetic assimilates. One-year-old potted Masson pine seedlings were exposed to four P addition treatments for one year: P0 (0 mg kg⁻¹), P1 (25 mg kg⁻¹), P2 (50 mg·kg⁻¹), and P3 (100 mg kg⁻¹). In July and December, measurements were conducted on seedling organ biomass, root morphological indices [root length (RL), root surface area (RSA), root diameter (RD), specific root length (SRL), and root length ratio (RLR) for each diameter grade], root architectural indices [number of root tips (RTs), fractal dimension (FD), root branching angle (RBA), and root topological index (TI)], as well as the content of nitrogen (N), phosphorus (P), carbon (C), and non-structural carbohydrates (NSCs) in roots, stems, and leaves. Compared with the P0 treatment, P2 and P3 significantly increased root biomass, root–shoot ratio, RL, RSA, RTs, RLR of finer roots (diameter ≤ 0.4 mm), nutrient accumulation ratio in roots, and starch (ST) content in roots, stems and leaves. Meanwhile, they decreased soluble sugar (SS) content, SS/ST ratio, C and N content, and N/P and C/P ratios in stems and leaves, as well as nutrient accumulation ratio in leaves. The P3 treatment significantly reduced RBA and increased FD and SRL. Our results indicated that Masson pine adapts to low P by developing shallower roots with a reduced branching intensity and promoting the conversion of ST to SS. P’s addition effectively alleviates growth limitations imposed by low P, stimulating root growth, branching, and gravitropism. Although a sole P addition promotes short-term growth and P uptake, it triggers a substantial consumption of N, C, and SS, leading to significant decreases in N/P and C/P ratios and exacerbating N’s limitation, which is detrimental to long-term growth. Under high-P conditions, Masson pine strategically prioritizes allocating limited N and SS to roots, facilitating the formation of thinner roots with low C costs. Full article

The prevention of biofilm formation and algal biodeterioration on building materials, particularly on cultural heritage sites, is a growing concern. Due to regulatory restrictions on conventional algicidal biocides in Europe, natural alternatives such as essential oils are gaining interest for their potential use in heritage conservation. This study evaluates the anti-algal activity of Salvia officinalis and Equisetum arvense (essential oils, hydrolates, and extracts) against a mixed culture of five green algae species (Bracteacoccus minor, Stichococcus bacillaris, Klebsormidium nitens, Chloroidium saccharophilum, and Diplosphaera chodatii). The plant materials were processed using hydrodistillation and solvent extraction, followed by chemical characterization through gas chromatography–mass spectrometry (GC-MS). Biological efficacy was assessed by measuring algal growth inhibition, changes in biomass colour, chlorophyll a concentration, and fluorescence. S. officinalis yielded higher extract quantities (extraction yield: 23%) than E. arvense and contained bioactive compounds such as thujone, camphor, and cineole, which correlated with its strong anti-algal effects. The essential oil of S. officinalis demonstrated the highest efficacy, significantly inhibiting biofilm formation (zones of inhibition: 15–94 mm) and photosynthetic activity at 0.5% concentration (reduction in chlorophyll a concentration 90–100%), without causing visible discolouration of treated surfaces (∆E < 2). These findings highlight the potential of S. officinalis essential oil as a natural, effective, and material-safe algicidal biocide for the sustainable protection of cultural heritage sites. Full article

To address the problems of traditional methods that rely on destructive sampling, the poor adaptability of fixed equipment, and the susceptibility of single-view angle measurements to occlusions, a non-destructive and portable device for three-dimensional phenotyping and biomass detection in lettuce was developed. Based on the Structure-from-Motion Multi-View Stereo (SFM-MVS) algorithms, a high-precision three-dimensional point cloud model was reconstructed from multi-view RGB image sequences, and 12 phenotypic parameters, such as plant height, crown width, were accurately extracted. Through regression analyses of plant height, crown width, and crown height, and the R² values were 0.98, 0.99, and 0.99, respectively, the RMSE values were 2.26 mm, 1.74 mm, and 1.69 mm, respectively. On this basis, four biomass prediction models were developed using Adaptive Boosting (AdaBoost), Support Vector Regression (SVR), Gradient Boosting Decision Tree (GBDT), and Random Forest Regression (RFR). The results indicated that the RFR model based on the projected convex hull area, point cloud convex hull surface area, and projected convex hull perimeter performed the best, with an R² of 0.90, an RMSE of 2.63 g, and an RMSEn of 9.53%, indicating that the RFR was able to accurately simulate lettuce biomass. This research achieves three-dimensional reconstruction and accurate biomass prediction of facility lettuce, and provides a portable and lightweight solution for facility crop growth detection. Full article

Understanding the differential impacts of emission sources of volatile organic compounds (VOCs) on formaldehyde (HCHO) levels is pivotal to effectively mitigating key photochemical radical precursors, thereby enhancing the regulation of atmospheric oxidation capacity (AOC) and ozone formation. This investigation systematically selected and analyzed year-long VOC measurements across three urban zones in Shenzhen, China. Photochemical age correction methods were implemented to develop the initial concentrations of VOCs before source apportionment; then Positive Matrix Factorization (PMF) modeling resolved six primary sources: solvent usage (28.6–47.9%), vehicle exhaust (24.2–31.2%), biogenic emission (13.8–18.1%), natural gas (8.5–16.3%), gasoline evaporation (3.2–8.9%), and biomass burning (0.3–2.4%). A machine learning (ML) framework incorporating Shapley Additive Explanations (SHAP) was subsequently applied to evaluate the influence of six emission sources on HCHO concentrations while accounting for reaction time adjustments. This machine learning-driven nonlinear analysis demonstrated that vehicle exhaust nearly always emerged as the primary anthropogenic contributor in diverse functional zones and different seasons, with gasoline evaporation as another key contributor, while the traditional reactivity metric method, ozone formation potential (OFP), tended to underestimate the role of the two sources. This study highlights the primacy of strengthening emission reduction of transportation sectors to mitigate HCHO pollution in megacities. Full article

Invasive plant species pose an increasing threat to mangroves globally. This study assessed the impact of Paspalum vaginatum invasion on carbon loss and early recovery following four years of restoration in a mangrove forest with Rhizophora racemosa in Benin. Organic carbon was quantified in the total biomass, including both aboveground and belowground components, as well as in the soil to a depth of −50 cm. In addition, soil gas fluxes of CO₂, CH₄, and N₂O were measured. Three sites were evaluated: a conserved mangrove, a site degraded by P. vaginatum, and the same site post-restoration via hydrological rehabilitation and reforestation. Invasion significantly reduced carbon storage, especially in soil, due to lower biomass, incorporation of low C/N ratio organic residues, and compaction. Restoration recovered 7.8% of the total biomass carbon compared to the conserved mangrove site, although soil organic carbon did not rise significantly in the short term. However, improvements in deep soil C/N ratios (15–30 and 30–50 cm) suggest enhanced soil organic matter recalcitrance linked to R. racemosa reforestation. Soil CO₂ emissions dropped by 60% at the restored site, underscoring restoration’s potential to mitigate early carbon loss. These results highlight the need to control invasive species and suggest that restoration can generate additional social benefits. Full article

Leaf chlorophyll content (LCC), leaf area index (LAI), and above-ground biomass (AGB) are important growth parameters for characterizing potato growth and predicting yield. While deep learning has demonstrated remarkable advancements in estimating crop growth parameters, the limited availability of field data often compromises model accuracy and generalizability, impeding large-scale regional applications. This study proposes a novel deep learning model that integrates multi-task learning and few-shot learning to address the challenge of low data in growth parameter prediction. Two multi-task learning architectures, MTL-DCNN and MTL-MMOE, were designed based on deep convolutional neural networks (DCNNs) and multi-gate mixture-of-experts (MMOE) for the simultaneous estimation of LCC, LAI, and AGB from Sentinel-2 imagery. Building on this, a few-shot learning framework for growth prediction (FSLGP) was developed by integrating simulated spectral generation, model-agnostic meta-learning (MAML), and meta-transfer learning strategies, enabling accurate prediction of multiple growth parameters under limited data availability. The results demonstrated that the incorporation of calibrated simulated spectral data significantly improved the estimation accuracy of LCC, LAI, and AGB (R² = 0.62~0.73). Under scenarios with limited field measurement data, the multi-task deep learning model based on few-shot learning outperformed traditional mixed inversion methods in predicting potato growth parameters (R² = 0.69~0.73; rRMSE = 16.68%~28.13%). Among the two architectures, the MTL-MMOE model exhibited superior stability and robustness in multi-task learning. Independent spatiotemporal validation further confirmed the potential of MTL-MMOE in estimating LAI and AGB across different years and locations (R² = 0.37~0.52). These results collectively demonstrated that the proposed FSLGP framework could achieve reliable estimation of crop growth parameters using only a very limited number of in-field samples (approximately 80 samples). This study can provide a valuable technical reference for monitoring and predicting growth parameters in other crops. Full article

Field bindweed (Convolvulus arvensis L.) is a competitive herbaceous perennial weed that reduces productivity in irrigated pastures. Grazing might reduce competition by field bindweed when it begins growth in the spring, thereby encouraging encroachment by desirable grass species during the summer. To test this hypothesis, a two-year study was conducted in two adjacent, privately owned, irrigated, warm-season perennial grass pastures (replicates) that were heavily infested with field bindweed. Study sites were near Tucumcari, NM, USA. The fields were grazed with exclosures to evaluate ungrazed management. Aboveground biomass of field bindweed, other weeds, and perennial grass were measured, and field bindweed plants were counted in May of 2018 and 2019. There was no difference between years for any variable. Other weed biomass and field bindweed biomass and plant numbers were reduced (p < 0.05) by grazing (61.68 vs. 41.67 g bindweed biomass m⁻² for ungrazed and grazed management, respectively, and 108.5 and 56.8 bindweed plants m⁻² for ungrazed and grazed management, respectively). Otherwise, perennial grass production was unaffected by either year or management. These results indicate that grazing can be an effective tool to reduce field bindweed competition in warm-season perennial grass pastures. Full article

Biomass is gaining increasing importance as a renewable energy source in the global energy mix, offering a viable alternative to fossil fuels and contributing to the decarbonization of the energy sector. Among various types of biomass, agricultural residues such as bean stalks represent a promising feedstock for the production of solid biofuels. This study analyzes the impact of particle size and selected briquetting parameters (pressure and temperature) on the physical quality of briquettes made from bean stalks. The experimental procedure included milling the raw material using #8, #12, and #16 mesh screens, followed by compaction under pressures of 27, 37, and 47 MPa. Additionally, the briquetting die was heated to 90 °C to improve the mechanical durability of the briquettes. The results showed that both particle size and die temperature significantly influenced the quality of the produced briquettes. Briquettes made from the 16 mm fraction, compacted at 60 °C and 27 MPa, exhibited a durability of 55.76%, which increased to 82.02% when the die temperature was raised to 90 °C. Further improvements were achieved by removing particles smaller than 1 mm. However, these measures did not enable achieving a net calorific value above 14.5 MJ·kg⁻¹. Therefore, additional work was undertaken, involving the addition of biomass with higher calorific value to the bean stalk feedstock. In the study, maize straw and miscanthus straw were used as supplementary substrates. The results allowed for determining their minimum proportions required to exceed the 14.5 MJ·kg⁻¹ threshold. In conclusion, bean stalks can serve as a viable feedstock for the production of solid biofuels, especially when combined with other biomass types possessing more favorable energy parameters. Their utilization aligns with the concept of managing local agricultural residues within decentralized energy systems and supports the development of sustainable bioenergy solutions. Full article