Search Results (1,605)

Wheat (Triticum aestivum L.) is a crucial global food crop. The intensive crop farming, monoculture cultivation, and impact of climate change affect the susceptibility of wheat cultivars to biotic stresses, mainly caused by soil fungal pathogens, especially those belonging to the genus Fusarium. This situation threatens yield and grain quality through root and crown rot. While conventional chemical fungicides face resistance issues and environmental concerns, biological alternatives like seed priming with natural metabolites are gaining attention. Polyamines, including putrescine, spermidine, and spermine, are attractive priming agents influencing plant development and abiotic stress responses. Spermine in particular shows potential for in vitro antifungal activity against Fusarium. Optimising spermine concentration for seed priming is crucial to maximising protection against Fusarium infection while ensuring robust plant growth. In this research, we explored the potential of the polyamine spermine as a seed treatment to enhance wheat resilience, aiming to identify a sustainable alternative to synthetic fungicides. Our findings revealed that a six-hour seed soak in spermine solutions ranging from 0.5 to 5 mM did not delay germination or seedling growth. In fact, the 5 mM concentration significantly stimulated root weight and length. In complementary in vitro assays, we evaluated the antifungal activity of spermine (0.5–5 mM) against three Fusarium species. The results demonstrated complete inhibition of Fusarium culmorum growth at 5 mM spermine. A less significant effect on Fusarium graminearum and little to no impact on Fusarium oxysporum were found. The performed analysis revealed that the spermine had a fungistatic effect against the pathogen, retarding the mycelium growth of F. culmorum inoculated on the seed surface. A pot experiment with Bulgarian soft wheat cv. Sadovo-1 was carried out to estimate the effect of seed priming with spermine against infection with isolates of pathogenic fungus F. culmorum on plant growth and disease severity. Our results demonstrated that spermine resulted in a reduced distribution of F. culmorum and improved plant performance, as evidenced by the higher fresh weight and height of plants pre-treated with spermine. This research describes the efficacy of spermine seed priming as a novel strategy for managing Fusarium root and crown rot in wheat. Full article

Urban agriculture (UA) is emerging as a promising strategy for sustainable food production in response to growing environmental pressures. Indoor vertical farming (IVF), combining Controlled Environment Agriculture (CEA) with Building-Integrated Agriculture (BIA), enables efficient resource use and year-round crop cultivation in urban settings. This study assesses the environmental performance of a prospective IVF system located on a university campus in Portugal, focusing on the integration of photovoltaic (PV) energy as an alternative to the conventional electricity grid (GM). A Life Cycle Assessment (LCA) was conducted using the Environmental Footprint (EF) method and the LANCA model to account for land use and soil-related impacts. The PV-powered system demonstrated lower overall environmental impacts, with notable reductions across most impact categories, but important trade-offs with decreased soil quality. The LANCA results highlighted cultivation and packaging as key contributors to land occupation and transformation, while also revealing trade-offs associated with upstream material demands. By combining EF and LANCA, the study shows that IVF systems that are not soil-based can still impact soil quality indirectly. These findings contribute to a broader understanding of sustainability in urban farming and underscore the importance of multi-dimensional assessment approaches when evaluating emerging agricultural technologies. Full article

Organic farming represents a paradigm that emphasises a balance between production and environmental sustainability. In the European Union (EU), organic farming has evolved into a global production system with harmonised standards and increasing market demand. Compared with conventional agriculture, it produces greater environmental benefits. The European Green Deal and the Farm to Fork (F2F) strategy highlight the role of organic farming in achieving the EU’s climate and environmental goals, aiming to use at least 25% of the total agricultural area for organic farming by 2030. This research assesses the contributions of Member States towards achieving the objectives of the European Green Deal and F2F strategy and increasing the number of organic farming areas in the future. The research assessed the performance of EU Member States during the period of 2018–2022 and for the projected period up to 2030, using indicators outlined in the Common Agricultural Policy (CAP) Strategic Plan. EU Member States were classified by their historical growth in organic farming areas and their required future performance to meet targets. The results showed that the increase in organic farming areas across the EU is a sign of a shift towards more sustainable farming, although performance varied among Member States. Overall, performance tended to improve in seventeen Member States, remained stable in nine, and declined in only one. Full article

Consumers are increasingly exposed to environmental claims on food products. These claims often lack scientific validation and there are different methodologies that can be used for grounding these claims, which can lead to misleading results. The European Union’s (EU) Environmental Footprint methodology excludes the aggregation of environmental impacts, including damage to human health. This fact reduces transparency and limits the consumers’ ability to make information-based sustainable choices. This study aims to address this issue by calculating aggregated impacts on human health via life cycle assessment (LCA) in the agriculture and food-production sectors. In the study the IMPACT World+ method was used, including trustworthy databases and proper functional unit definition. The assessment encompassed three types of vegetables, four types of fruit, and four types of ready meals. The study also attempts to assess the impact of different farming systems (organic and conventional) on human health. Two standardised functional units, i.e., the unit based on product weight and product energy value were considered for each group of products. Our findings showed significant differences in results when different functional units were used. Additionally, no conclusion could be drawn regarding which farming system is more sustainable. Therefore, it is essential that the regulator clearly defines the criteria for selecting the appropriate functional unit in LCA within the agriculture and food-production sectors. In the absence of these criteria, results should be presented for all alternatives. Although not required by EU regulation, the authors suggest that companies should nevertheless disclose information regarding the environmental impact of agriculture and food production on human health, as this is important for consumers. Full article

Organic farming is widely recognized as a promising practice for sustainable agriculture, yet its long-term ecological impacts remain insufficiently investigated. In this study, we evaluated these impacts by comparing heavy metal concentrations, soil invertebrate communities, and microbial profiles between long-term organic and conventional farming systems. A comparative analysis was conducted on 24 plot soils from two paired organic and conventional farm systems in Beijing, each managed continuously for over 20 years. Our results revealed that soils under organic management consistently contained 10.8% to 73.7% lower heavy metals, along with reduced geo-accumulation indices (I_geo, a standardized metric for soil contamination assessment), indicating decreased contamination risks. In terms of soil fauna, while conventional soils showed higher Collembola abundance, organic farming significantly enhanced Collembola richness and diversity by 20.6% to 55.0%. Microbial sequencing likewise revealed enhanced richness and diversity of bacteria and fungi in organic soils. These microbial communities also displayed shifts in dominant taxa and more stable co-occurrence networks under organic management. Principal component analysis and Mantel tests identified soil pH and nutrients as key drivers of soil biodiversity, while heavy metals also imposed negative influences. Collectively, these findings demonstrate that long-term organic farming not only mitigates environmental risks associated with soil contaminants but also promotes belowground ecological integrity by supporting biodiversity of soil fauna and microbiota. This study highlights the ecological significance of sustained organic practices and provides critical insights for advancing sustainable agricultural developments. Full article

We propose a dynamic monitoring and precision fertilization decision system for agricultural soil nutrients, integrating UAV remote sensing and GIS technologies to address the limitations of traditional soil nutrient assessment methods. The proposed method combines multi-source data fusion, including hyperspectral and multispectral UAV imagery with ground sensor data, to achieve high-resolution spatial and spectral analysis of soil nutrients. Real-time data processing algorithms enable rapid updates of soil nutrient status, while a time-series dynamic model captures seasonal variations and crop growth stage influences, improving prediction accuracy (RMSE reductions of 43–70% for nitrogen, phosphorus, and potassium compared to conventional laboratory-based methods and satellite NDVI approaches). The experimental validation compared the proposed system against two conventional approaches: (1) laboratory soil testing with standardized fertilization recommendations and (2) satellite NDVI-based fertilization. Field trials across three distinct agroecological zones demonstrated that the proposed system reduced fertilizer inputs by 18–27% while increasing crop yields by 4–11%, outperforming both conventional methods. Furthermore, an intelligent fertilization decision model generates tailored fertilization plans by analyzing real-time soil conditions, crop demands, and climate factors, with continuous learning enhancing its precision over time. The system also incorporates GIS-based visualization tools, providing intuitive spatial representations of nutrient distributions and interactive functionalities for detailed insights. Our approach significantly advances precision agriculture by automating the entire workflow from data collection to decision-making, reducing resource waste and optimizing crop yields. The integration of UAV remote sensing, dynamic modeling, and machine learning distinguishes this work from conventional static systems, offering a scalable and adaptive framework for sustainable farming practices. Full article

Analyzing the soil organic carbon (SOC) stock in dryland areas of southern Shanxi, particularly under the influence of fertilization and mulching conditions, is crucial for enhancing soil fertility and crop productivity and understanding the SOC pool’s resilience to future climate change scenarios in the region. In a long-term experimental site located in Hongtong County, Shanxi Province, soil samples were collected from the 0–100 cm depth over a nine-year period. These samples were analyzed to evaluate the impact of five treatments: no fertilization and no mulching (CK), conventional farming practices (FP), nitrogen reduction and controlled fertilization (MF), nitrogen reduction and controlled fertilization with ridge-film furrow-sowing (RF), and nitrogen reduction and controlled fertilization with flat-film hole-sowing (FH). The average annual yield of wheat grain, SOC stock, water-soluble organic carbon (WSOC), particulate organic carbon (POC), light fraction organic carbon (LFOC), mineral-associated organic carbon (MOC), and heavy fraction organic carbon (HFOC) stocks were measured. The results revealed that the FH treatment not only significantly increased wheat grain yield but also significantly elevated the SOC stock by 23.71% at the 0–100 cm depth compared to CK. Furthermore, this treatment significantly enhanced the POC, LFOC, and MOC stocks by 106.43–292.98%, 36.93–158.73%, and 17.83–81.55%, respectively, within 0–80 cm. However, it also significantly decreased the WSOC stock by 34.32–42.81% within the same soil layer and the HFOC stock by 72.05–101.51% between the 20 and 100 cm depth. Notably, the SOC stock at the 0–100 cm depth was primarily influenced by the HFOC. Utilizing the DNDC (denitrification–decomposition) model, we found that future temperature increases are detrimental to SOC sequestration in dryland areas, whereas reduced rainfall is beneficial. The simulation results indicated that in a warmer climate, a 2 °C temperature increase would result in a SOC stock decrease of 0.77 to 1.01 t·ha⁻¹ compared to a 1 °C increase scenario. Conversely, under conditions of reduced precipitation, a 20% rainfall reduction would lead to a SOC stock increase of 1.53% to 3.42% compared to a 10% decrease scenario. In conclusion, the nitrogen reduction and controlled fertilization with flat-film hole-sowing (FH) treatment emerged as the most effective practice for increasing SOC sequestration in dryland areas by enhancing the HFOC stock. This treatment also fortified the SOC pool’s capacity to withstand future climate change, thereby serving as the optimal approach for concurrently enhancing production and fertility in this region. Full article

Robots are increasingly emerging as effective platforms to overcome a wide range of challenges in agriculture. Beyond functioning as standalone systems, agricultural robots are proving valuable as collaborative platforms, capable of supporting and integrating with humans and other technologies and agricultural activities. In this study, we designed and implemented an automated system embedded in a ground-based robotic platform to support spraying drone operations. The system consists of a robotic platform that carries the spraying drone along with all necessary support devices, including a water tank, chemical reservoirs, a mixer, generators for drone battery charging, and a top landing pad. The system is controlled with a mobile app that calculates the total amount of water and chemicals required and sends commands to the platform to prepare the application mixture. The input information in the app includes the field area, application rate, and up to three chemical dosages simultaneously. Additionally, the platform allows the drone to take off from and land on it, enhancing both safety and operability. A set of pumps was used to deliver water and chemicals as specified in the mobile app. To automate pump control, we used Arduino technology, including both the microcontroller and a programming environment for coding and designing the mobile app. To validate the system’s effectiveness, we individually measured the amount of water and chemical delivered to the mixer tank and compared it with conventional manual methods for calculating chemical quantities and preparation time. The system demonstrated consistent results, achieving high precision and accuracy in delivering the correct amount. This study advances the field of agricultural robotics by highlighting the role of collaborative platforms. Particularly, the system presents a valuable and low-cost solution for small farms and experimental research. Full article

Camelina sativa (CS) is an emerging sustainable oilseed crop with interesting feed application potentialities. The research assessed the potentiality of Camelina sativa (CS) in the diet for free-range laying hens, aiming at reaching a nutritional claim. To this purpose, two feeding groups of hens (n = 100 Livorno hens, n = 25 hens/pen) were farmed outdoor and received either a Control diet, which was a commercial diet for laying hens, or a CS diet. The latter was formulated to include the 5% CS cake and 1% CS oil, replacing conventional feedstuffs. Diets were isoprotein and isoenergy and were available ad libitum throughout the laying period (February–September). At day 1, n = 12 eggs/diet were sampled to assess the initial proximate composition and FA profile. Every 7 days the sampling was repeated to analyze the eggs’ FA profile, up to day 35. At the end of the laying season, n = 6 hens/dietary treatment were slaughtered and subjected to meat quality evaluations. Results highlighted that a 28-day feeding was the period required to obtain 227 mg of C18:3 n-3 and 81 mg of C20:5 n-3 + C22:6 n-3/100 g egg, whereas a further 7 days of feeding trial were ineffective in further enhancing the omega-3 FA content of eggs. CS eggs were comparable to Control ones for overall physical traits, proximate composition, and shelf-life. In addition, at the end of the laying period, the meat of CS hens was also found to be healthier than that of Control ones, thanks to a higher omega-3 FA proportion (p < 0.01), which was, however, not sufficient to reach any nutritional claim. Instead, the proximate composition of CS meat was overall comparable to Control hens. In conclusion, the present research demonstrated that feeding Camelina sativa meal and oil to laying hens is feasible and allows to reach the nutritional claim in eggs “rich in omega-3 FA” after a feeding period of 28 days, without any negative effects on other eggs’ quality trials. Camelina sativa can thus be defined as a promising sustainable feedstuff for the poultry sector for diversification purposes and to enhance the nutritional quality of eggs. Full article

This on-farm study evaluated the effects of a regenerative (plant polyculture) as compared to conventional (monoculture) pasture-based New Zealand dairy production system on milk and yoghurt nutraceutical properties and environmental impact. Milk and yoghurt produced by two adjacent regenerative and conventional farms were sampled throughout the year and analyzed for chemical composition, metabolomics, and microbiome. Milk samples were also collected over four consecutive days (one day after herbage sampling) on four occasions throughout lactation: early lactation (October), peak lactation (December/January), mid-lactation (March), and late lactation (May). Overall, the regenerative system had a lower environmental impact while maintaining a similar yield and the same milk composition compared to conventional systems. Furthermore, milk and yoghurt from the regenerative system had a more favourable profile of phytochemical antioxidants with potential positive benefits to human health (anti-inflammatory and antioxidant). Full article

The diversification of plant protein sources is a strategic priority for European food systems, particularly under the EU Green Deal and Farm to Fork strategies. In this study, dual production of full-fat soy (FFS) and expanded soybean cake (ESC) was evaluated using non-GMO soybeans cultivated under semi-organic conditions in Central Poland. Two agronomic systems—post-emergence mechanical weeding with rotary harrow weed control (P1) and conventional herbicide-based control (P2)—were compared over a four-year period. The P1 system produced consistently higher yields (e.g., 35.6 dt/ha in 2024 vs. 33.4 dt/ha in P2) and larger seed size (TSW: up to 223 g). Barothermal and press-assisted processing yielded FFS with protein content of 32.4–34.5% and oil content of 20.8–22.4%, while ESC exhibited enhanced characteristics: higher protein (37.4–39.0%), lower oil (11.6–13.3%), and elevated dietary fiber (15.8–16.3%). ESC also showed reduced anti-nutritional factors (e.g., trypsin inhibitors and phytic acid) and remained microbiologically and oxidatively stable over six months. The semi-organic P1 system offers a scalable, low-input approach to local soy production, while the dual-product model supports circular, zero-waste protein systems aligned with EU sustainability targets. Full article

Background: Conventional practices for the cultivation of “Cipollotto Nocerino” spring onion are mainly based on growers’ experience, and up to 250 kg/ha for N is commonly furnished among growing cycles. Facing the issue of reduced availability of natural resources for crop production (for example mineral resources), we investigated the optimization of the productivity. Methods: In our research, we tested the use of depletion nutrient supply strategy (CAL-FERT^®) to enhance fertilization in accordance with the principle of sustainable agriculture included in the Farm to Fork strategy. In our study, besides the common initial fertilization, three different strategies for cover fertilizations have been elaborated with the support of CAL-FERT^® software. The treatments were as follows: (i) commercial standard fertilization as control (named CF); (ii) fertilization equivalent to 50% of the N applied in the control (named F-50); (iii) fertilization corresponding to 25% of the N applied in the control (named F-25); and (iv) strongly reduced fertilization compared to the control (named F-0). The parameters investigated included the following: plant height, yield, SPAD index, nitrogen use efficiency, dry matter, soluble solid content, and pyruvate contents in bulbs and leaves. Nitrogen content was also analyzed for both hypogeous and epigeous apparatuses. Results: Among the most interesting vegetative results, plant height and SPAD readings were reduced only by the extreme treatment F-0 compared with the other treatments at 104 days after planting. Regarding qualitative and productive parameters, the treatments F-50 and F-25 showed the highest yield without prejudging Soluble Solid Content and reducing pungency. Conclusion: In nutritional experiments, onion could be considered as a crop model to investigate quality in vegetables due to its consumption as fresh product and for its particular response, in terms of yield and quality, to fertilization. The use of simulation software can support the identification of strategies to reduce the nutrient supply without any detrimental effect on yield and other vegetative and qualitative parameters in onion crops. Full article

Winter wheat yield prediction is critical for optimizing field management plans and guiding agricultural production. To address the limitations of conventional manual yield estimation methods, including low efficiency and poor interpretability, this study innovatively proposes an intelligent yield estimation method based on a convolutional neural network (CNN). A comprehensive two-factor (fertilization × irrigation) controlled field experiment was designed to thoroughly validate the applicability and effectiveness of this method. The experimental design comprised two irrigation treatments, sufficient irrigation (C) at 750 m³ ha⁻¹ and deficit irrigation (M) at 450 m³ ha⁻¹, along with five fertilization treatments (at a rate of 180 kg N ha⁻¹): (1) organic fertilizer alone, (2) organic–inorganic fertilizer blend at a 7:3 ratio, (3) organic–inorganic fertilizer blend at a 3:7 ratio, (4) inorganic fertilizer alone, and (5) no fertilizer control. The experimental protocol employed a DJI M300 RTK unmanned aerial vehicle (UAV) equipped with a multispectral sensor to systematically acquire high-resolution growth imagery of winter wheat across critical phenological stages, from heading to maturity. The acquired multispectral imagery was meticulously annotated using the Labelme professional annotation tool to construct a comprehensive experimental dataset comprising over 2000 labeled images. These annotated data were subsequently employed to train an enhanced CNN model based on ResNet50 architecture, which achieved automated generation of panicle density maps and precise panicle counting, thereby realizing yield prediction. Field experimental results demonstrated significant yield variations among fertilization treatments under sufficient irrigation, with the 3:7 organic–inorganic blend achieving the highest actual yield (9363.38 ± 468.17 kg ha⁻¹) significantly outperforming other treatments (p < 0.05), confirming the synergistic effects of optimized nitrogen and water management. The enhanced CNN model exhibited superior performance, with an average accuracy of 89.0–92.1%, representing a 3.0% improvement over YOLOv8. Notably, model accuracy showed significant correlation with yield levels (p < 0.05), suggesting more distinct panicle morphological features in high-yield plots that facilitated model identification. The CNN’s yield predictions demonstrated strong agreement with the measured values, maintaining mean relative errors below 10%. Particularly outstanding performance was observed for the organic fertilizer with full irrigation (5.5% error) and the 7:3 organic-inorganic blend with sufficient irrigation (8.0% error), indicating that the CNN network is more suitable for these management regimes. These findings provide a robust technical foundation for precision farming applications in winter wheat production. Future research will focus on integrating this technology into smart agricultural management systems to enable real-time, data-driven decision making at the farm scale. Full article

The consumption and farming of insects are gaining global attention as sustainable alternatives to conventional protein sources. Industrial processing of insects into powders or pastes complicates species identification, raising concerns about product authenticity, food safety, and potential fraud. In Western countries, particularly in Europe, the sector is expanding under a stringent regulatory framework, especially regarding rearing substrates, which hinders economic development. This study aimed to assess the species authenticity of commercial insect-based food and feed products and detect the presence of animal-derived DNA from unauthorized substrates. A total of 119 samples (pure insect meals and processed products) were collected from various origins. Species-specific real-time PCR assays targeted Tenebrio molitor, Hermetia illucens, Alphitobius diaperinus, Acheta domesticus, Bombyx mori, and Gryllodes sigillatus, alongside assays for ruminant, porcine, and poultry DNA. High-throughput sequencing (HTS) using metabarcoding confirmed and broadened species detection. Most samples contained the declared species; however, cases of mislabeling, substitution, and cross-contamination were observed. A few insect meals contained animal DNA which could suggest potential use of prohibited substrates. These findings highlight the urgent need for standardized authentication methods and improved transparency to ensure regulatory compliance, consumer trust, and sustainable development of the insect-based sector. Full article

Energy generation from renewable sources has increased exponentially worldwide, particularly wind energy, which is converted into electricity through wind turbines. The growing demand for renewable energy has driven the development of horizontal-axis wind turbines with larger dimensions, as the energy captured is proportional to the area swept by the rotor blades. In this context, the dynamic loads typically observed in wind turbine towers include vibrations caused by rotating blades at the top of the tower, wind pressure, and earthquakes (less common). In offshore wind farms, wind turbine towers are also subjected to dynamic loads from waves and ocean currents. Vortex-induced vibration can be an undesirable phenomenon, as it may lead to significant adverse effects on wind turbine structures. This study presents a two-dimensional transient model for a rigid body anchored by a torsional spring subjected to a constant velocity flow. We applied a coupling of the Fourier pseudospectral method (FPM) and immersed boundary method (IBM), referred to in this study as IMERSPEC, for a two-dimensional, incompressible, and isothermal flow with constant properties—the FPM to solve the Navier–Stokes equations, and IBM to represent the geometries. Computational simulations, solved at an aspect ratio of $\varphi =4.0$, were analyzed, considering Reynolds numbers ranging from $Re=150$ to Re = 1000 when the cylinder is stationary, and $Re=250$ when the cylinder is in motion. In addition to evaluating vortex shedding and Strouhal number, the study focuses on the characterization of space–time symmetry during the galloping response. The results show a spatial symmetry breaking in the flow patterns, while the oscillatory motion of the rigid body preserves temporal symmetry. The numerical accuracy suggested that the IMERSPEC methodology can effectively solve complex problems. Moreover, the proposed IMERSPEC approach demonstrates notable advantages over conventional techniques, particularly in terms of spectral accuracy, low numerical diffusion, and ease of implementation for moving boundaries. These features make the model especially efficient and suitable for capturing intricate fluid–structure interactions, offering a promising tool for analyzing wind turbine dynamics and other similar systems. Full article