Search Results (71)

This study explores the relationship between abiotic factors, farming practices, and weed growth in winter wheat fields in Eastern Hungary. It examines the order of weed dominance and the influence of soil, environmental, and agricultural variables on weed composition and diversity before herbicide application. The research was conducted across four sub-regions in the Great Hungarian Plain, each with distinct soil, hydrological, and geographical conditions. Between 2018 and 2021, 103 fields were surveyed and weed species cover was recorded using EPPO-based identification and quadrat sampling. Soil properties, environmental conditions, and farming practices were documented through soil analysis, geographical data, and farmer interviews. Statistical analyses were preformed including ANCOVA, redundancy analysis, and Shannon diversity index calculations. The results show that common weed species include Veronica hederifolia, Stellaria media, and Apera spica-venti, with winter annuals dominating. Soil compaction and salinity affected weed diversity, while increased copper and zinc concentrations had minor effects on weed coverage. Farming practices, particularly tillage systems and fertilizer use, had a significant effect on species richness and diversity. Different regional and annual weed distributions were observed, with correlation between certain tillage systems and specific weed species. The results emphasize the need for climate-conscious farming practices, and we recommend prioritising shallow cultivation and deep loosening over ploughing in order to manage weed populations effectively. These insights contribute to sustainable weed management strategies in cereal production. Full article

Alligator weed (AW; Alternanthera philoxeroides) can have severe ecological and economic consequences by impacting water quality, flow and the growth of native flora and fauna. Plants, both edible and inedible, contain phenolics, compounds that can serve as antioxidants. Using this background information, the study aimed to explore the possible antioxidative nature of AW by incorporating it as a supplement on production performance, gene expression, and antioxidant levels during the summer and winter seasons in improved-variety rural chicks. A total of 400 improved-variety Vanaraja chicks (35 days old), were used in each of the two seasons (summer and winter), making a combined total of 800 birds (n = 400 for each summer and winter season). The chicks were subjected to four experimental dietary treatments over a 35-day period during both seasons. The experimental diet consisted of the following: a control diet without any supplements (C); basal diet + 1% AW (T₁); basal diet + 2% AW(T₂); and basal diet + 4% AW(T₃). The production performance, cytokine gene expression (IFN-γ, IL-1β, IL-6, IL-12 and iNOS) and serum antioxidants, viz. catalase (CAT) and superoxide dismutase (SOD), were evaluated. The results indicated that body weight, average body weight gain and weekly feed intake in the T₁ group was significantly (p < 0.05) higher as compared to the other groups. The FCR in group T₁ was significantly (p < 0.05) lower during winter than in summer. A significant (p < 0.001) upregulation in the expression of IL-6, IL-1β and IL-12 in T₁ as compared to the other groups was reported. IFN-γ, IL-1β, IL-6 and iNOS were significantly (p < 0.001) upregulated in winter. SOD and CAT activity was significantly (p < 0.001) higher in T₁ compared to C, and both were significantly (p < 0.05) higher during winter than in summer. The results suggested that AW has the potential to mitigate the consequences of cold stress on growth, immune response, and antioxidant function during winter. We propose adding 1% AW, which can possibly function as an antioxidant, to the diet of chicks to enhance their production performance and immunity levels. Full article

Recently, there has been growing interest by farmers and researchers in various agroecological approaches enhancing biodiversity and conservation including the use of natural herbicides derived from fungi to provide adequate weed control. This change is driven by growing concerns about herbicide resistance, environmental impacts and regulatory requirements. This review summarizes the results of various studies and highlights the efficacy and benefits of fungal bioherbicides in weed control. Fungi-based bioherbicides utilize the natural weed suppression capability of selected fungi to reduce weed density and competitiveness without completely eradicating the plants and such an approach is at the core of agroecology. Bioherbicides contribute to conservation by providing an environmentally friendly alternative to chemical herbicides. By reducing the reliance on synthetic chemicals, fungal bioherbicides help preserve soil health, water quality and protect non-target species, including beneficial organisms such as pollinators and soil microbes. They also promote biodiversity by selectively targeting specific weed species, leaving native plants and other organisms unharmed and favoring diversified weed flora without the dominance of a few species. Despite their promising potential, bioherbicides face several challenges, including delayed action, production difficulties and the potential toxicity of certain fungal toxins to mammals. This review highlights the growing adoption of fungal bioherbicides as an eco-friendly component of Integrated Weed Management (IWM). Further research is necessary to identify optimal fungal strains for controlling persistent weeds without putting at risk the overall biodiversity and to develop improved formulations for enhanced efficacy. Full article

The planting of inter-row cover vegetation has long been practised in Western European fruit-growing regions, yet research in this area remains limited in many countries. With the rise of organic farming, the role and selection of inter-row cover species are becoming increasingly important. Proper species selection enhances weed control and promotes biodiversity, supporting flowering plants and beneficial insects in orchards. The six-year research aimed to develop a multi-species, perennial, multifunctional inter-row cover species mixture for a dry continental climate, which is suitable for soil protection and the displacement of heat-loving, drought-tolerant, invasive weed species. There was another expectation for this native seed mixture to be able to regenerate spontaneously and to be sustainable in the orchard for a long time with minimal maintenance. Based on our results, the two multi-species mixtures (15 and 18 species) successfully reduced the cover of weed species, and their composition changed in the direction of the natural flora characteristic of the area. According to general management practices, native species could not widely appear in the control rows created by mowing the local weed flora. Full article

Many natural areas are colonised by the invasive species Ailanthus altissima (Mill.) Swingle. Its presence in natural ecosystems damages the ecological richness while competing with native flora. A. altissima is one of the most widespread weed species in natural areas of temperate regions such as conservation parks, archaeological sites and communication corridors. Not many active ingredients are available to control this weed since the most popular, glyphosate, has been banned by many municipalities. To test the efficacy of alternative herbicides, naturally occurring populations in Collserola Conservation Park in Barcelona (Catalonia, Spain) were treated with different herbicides using three different techniques. Aclonifen, metribuzin, flazasulfuron, metsulfuron-methyl, fluroxypyr, isoxaflutole + thiencarbazone-methyl and triclopyr mixed with 2.4-D, fluroxypyr, aminopyralid and clopyralid were applied by stem injection, cut stump injection or basal bark techniques to trees of about 5 cm diameter. Cut stump and stem injection both gave almost total control of the trees while basal bark showed more varied results depending on the herbicide. The best control was achieved when flazasulfuron or triclopyr were present as active ingredients and poorer control was observed when using metsulfuron-methyl or isoxaflutole + thiencarbazone-methyl. Aclonifen showed no damage to the trees. Metribuzin worked better if the cut stump injection technique was used. These results showed that several alternatives are available to the use of glyphosate, which has been banned for some uses due to environmental concerns. Full article

Spontaneous vegetation within a managed green space is often regarded as unwelcoming and insignificant weeds. This perception is still deep-rooted among green-space managers and the general public worldwide; they are generally uncertain about the management needs after allowing these groups of flora to take root. The short-term growth dynamics of both spontaneous and planted vegetation should be analyzed, and a widely acceptable, feasible management plan to balance aesthetic and ecological functions should be formulated with the backing of data and analysis for such fast-growing flora in tropical and subtropical regions. A manicured, extensive green roof with only seven (two native, five exotic) plant species was transformed into a renaturalized biotope by replacing 15 native ferns and forb species over 15 months. After planting, a baseline plant survey was conducted, with 54 plant species representing spontaneous growth and 14 planted species alive (7 planted native species survived, plus 7 species planted prior to renaturalization revived). Three quarterly plant surveys recorded the cover-abundance of each species, and the growth dynamics of the planted and spontaneous plant species were evaluated over the first year of study. During each quarterly survey, the number of planted and spontaneous plant species remained stable (ranging from 14 to 16 species and 51 to 54 species, respectively), with a constant turnover of 11 to 12 die-out species and 11 to 12 newly colonized or revived species. Plant coverage of different plant forms fluctuated slightly (within 7%) in the quarterly surveys according to seasonal changes, except for ferns, which outperformed (12% increase in coverage in a year) all the other plant forms. The height of the planted vegetation fluctuated in a year, being shorter during the summer, while the height of spontaneous vegetation remained stable throughout the year, exhibiting resilience to scouring heat. The seasonal growth tendencies of both planted and spontaneous plants were illustrated in relation to their species ranks, and further hierarchical cluster analysis was conducted for the clustering of spontaneous species. Their differential growth patterns provided comprehensive information or supported decisions regarding plant selection and maintenance, which is a scientific novelty within this unexplored topic. Management recommendations based on the findings were suggested to fulfill both aesthetic and ecological needs. Species with stable and less stable growth patterns could be useful to meet maintenance efficiency and biodiversity enhancement needs, respectively. These findings provide insights to form guiding principles for choosing plant species for renaturalization projects. Full article

Synanthropic flora (weeds, i.e., spontaneously developed plants) are plants that accompany humans, appearing as a result of anthropopressure as well as after its cessation. The potential of synanthropic flora in shaping green areas usually brings many measurable benefits that depend on land management in cities. This study aimed to determine the preferences and attitudes of adults towards synanthropic flora in settlement units. This article presents survey results from 447 city residents. The obtained results were statistically analyzed using the k-means clustering method to identify segments of respondents with similar attitudes and preferences toward synanthropic flora. Mann–Whitney U tests were employed to determine statistical differences in the demographic variables among the analyzed clusters of respondents. Additionally, multiple regression analysis was performed to identify the opinions and attitudes towards synanthropic flora that may influence their greater acceptance in the vicinity of residential areas. The results obtained in the multiple regression analysis indicate that the respondent’s evaluation of the level of support for the introduction of more synanthropic vegetation into urban greenery (Yw) grows with the increase in the acceptance of synanthropic plants’ occurrence in the surroundings. Residents’ acceptance of synanthropic flora in green areas is at a relatively high level. Full article

Tree of Heaven (Ailanthus altissima (Mill.) Swingle) is a tree native to China which has invaded disturbed areas in many regions worldwide. Its presence endangers natural ecosystems by displacing native species, modifying habitats, changing community structures, and affecting ecosystem processes. Its invasive nature is enhanced by its high ability to reproduce both vegetatively through root regrowth and sexually through seeds. Seeds, which are wind dispersed, are the main mechanism by which this species reaches new habitats. When they germinate and develop the root system, roots emit new shoots that contribute to a rapid increase in the tree density and the subsequent expansion of the population nearby. The contradictory results about the ecological requirements for seeds to germinate and their degree of dormancy and longevity indicate the complexity and difficulty of understanding the mechanisms that govern the biology and adaptability of this plant. The management of this weed aims at its eradication, with programs based on herbicide applications carried out by injecting the active ingredient directly to the trunk. But, not many active ingredients have shown total control, so new ones should be tested in order to increase the range of available herbicides. During the last few decades, some biological agents have been identified, but their efficacy in controlling the tree and their safety for the local flora have not yet been determined. A correct management strategy should take into account all these aspects in order to contain the expansion of this species and, ultimately, allow its eradication. Full article

Gaining a comprehensive understanding of how weed communities respond to both environmental and human-induced factors is of paramount importance in developing effective and ecologically sound weed control strategies. The objectives of the current research were to (1) assess the effect of the main weed management practices used in Greek olive groves on weed species’ diversity; (2) explore the filtering effect of management, site, and soil variables in determining weed species’ composition; and (3) shed light on the association between weed species’ composition and the diversity of the understory vegetation of olive groves. To accomplish these objectives, winter weed species’ coverage was assessed in 116 olive groves, both conventional and organic, distributed across three provinces in southern Greece. The investigation encompassed 29 explanatory variables, categorized into three groups: soil (22), management practices (6), and site conditions (1). It was confirmed that glyphosate use may lower biodiversity and species richness; however, this trend was not universal. In fact, the negative influence of the presence of Oxalis pes-caprae L. on species richness and diversity far outweighed the effect of spraying glyphosate. Redundancy analysis (RDA) revealed that among the 29 variables used to describe the ecological niche, eight (i.e., Mn, Mg, chemical spraying, mowing, rotary tiller, grazing, irrigation, and elevation) were significant and explained 21.5% of the total variation in weed species’ data. Interestingly, the soil Mn concentration was identified as the most influential one, highlighting the importance of soil micronutrients in determining weed species’ composition. The variation partitioning procedure demonstrated that the effect of the management variables on weed species’ composition accounted for 2.2 times the variance of soil variables and 4.5 times the variance of elevation. The present findings might help to enhance optimal management in olive groves that can sustain the biodiversity of flora and, in turn, provide various ecosystem services to agro-ecosystems. Full article

Allelopathy, a biological phenomenon where plants release chemicals that influence the growth and development of neighboring flora, offers potential natural alternatives for weed management in agriculture. This study investigated the allelopathic effects of Heliotropium indicum leaf and root extracts on the germination, growth, and biochemical parameters of eight cucurbit crops. Results demonstrated that H. indicum extracts generally inhibited seed germination across all cucurbit species, with aqueous extracts showing a stronger effect than methanol extracts in Lagenaria siceraria at 10.66 ± 0.46% (p < 0.001). The treatment also variably affected shoot and root growth, indicating both inhibitory and stimulatory actions, depending on the crop species and extract type. For instance, in methanol extract treatments, Benincasa hispida’s shoot length was significantly reduced, compared to the control, at 2.1 ± 0.14 cm (p < 0.001). Notably, aqueous leaf extracts enhanced chlorophyll content more effectively than root extracts, suggesting a potential application as a biostimulant, to improve photosynthetic efficiency in certain species, for example, Momordica charantia (p < 0.05). The study further explored the antioxidative potential of the extracts by measuring MDA levels, a biomarker for oxidative stress. MDA levels increased significantly across all species in response to both types of extracts, indicating oxidative stress (L. siceraria p < 0.05). These findings suggest the potential of H. indicum extracts as natural herbicides and biostimulants, though their effects are species-specific and dependent on concentration. This research contributes to understanding the complex interactions in plant allelopathy, and highlights the potential of plant-derived extracts in sustainable agriculture. Full article

In the Mediterranean area, vineyard soils are often characterized by a high stone content. In these contexts, where tools commonly adopted for under-row weed control are frequently damaged, the utilization of a chain mower could be a preferable alternative. This research aims to compare a modified mower with chains with other tools commonly employed that control weeds through tillage, such as motorized discs, blade weeder, and rotary star hoe. Weed control effectiveness, effects on weed flora composition, soil compaction, and operative efficiencies were evaluated. The chain mower allowed us to obtain encouraging results of weed biomass reduction (55.4 and 25.4%, between and around vine trunks, respectively), weed height reduction (35.9%), and weed cover reduction (79.2%), comparable to the other tools. All the tools showed a lower weed control efficacy around vine trunks rather than between them (weed biomass reductions of 24.8% and 52.6%, respectively). Results regarding the effect on weed flora composition seem to confirm this trend. Despite the higher chain mower field time (3.78 h ha⁻¹) and fuel consumption (24.24 kg ha⁻¹) compared to the blade weeder and the rotary star hoe, its versatility in stony soil and its lower impact on soil (soil penetration resistances of 1602.42 and 2262.83 kPa in 2022 and 2023, respectively) compared to the other tools make it a potentially advantageous implement for under-row weed management in vineyards. Further studies could be useful to improve chain mower performance, particularly around vine trunks, by evaluating in different planting layouts different dimensions of both the cutting element and feeler, which allows the vine-skipping mechanism. Full article

The global population’s rapid growth necessitates a 70% increase in agricultural production, posing challenges exacerbated by weed infestation and herbicide drawbacks. To address this, machine learning (ML) models, particularly convolutional neural networks (CNNs), are employed in precision agriculture (PA) for weed detection. This study focuses on testing CNN architectures for image classification tasks using the PyTorch framework, emphasizing hyperparameter optimization. Four groups of experiments were carried out: the first one trained all the PyTorch architectures, followed by the creation of a baseline, the evaluation of a new and extended dataset in the best models, and finally, the test phase was conducted using a web application developed for this purpose. Of 80 CNN sub-architectures tested, the MaxVit, ShuffleNet, and EfficientNet models stand out, achieving a maximum accuracy of 96.0%, 99.3%, and 99.3%, respectively, for the first test phase of PyTorch classification architectures. In addition, EfficientNet_B1 and EfficientNet_B5 stood out compared to all other models. During experiment 3, with a new dataset, both models achieved a high accuracy of 95.13% and 94.83%, respectively. Furthermore, in experiment 4, both EfficientNet_B1 and EfficientNet_B5 achieved a maximum accuracy of 96.15%, the highest one. ML models can help to automate crop problem detection, promote organic farming, optimize resource use, aid precision farming, reduce waste, boost efficiency, and contribute to a greener, sustainable agricultural future. Full article

Mechanical under-row weed control in the vineyard emerges as a sustainable choice compared to chemical control, with tillage-based approaches proving especially efficient. A rollhacke, finger weeder, and blade weeder are valid alternatives to commonly used implements that cause excessive soil disruption and display suboptimal efficiency. The trial aimed to compare different under-row weed control strategies in terms of weed control efficacy and operational performance. Among these, in ST1, a tool-holder equipped with both a rollhacke and finger weeder was used at the first and second intervention; in ST2, a rollhacke was used at the first intervention and blade weeder at the second one; in ST3, firstly the tool-holder equipped with a rollhacke and finger weeder was used, then the blade weeder; in ST4, a rollhacke was used first and then the tool-holder equipped with a rollhacke and finger weeder. Weed height, weed cover, and weed biomass were evaluated before the first and after the second intervention. Total field time, fuel consumption, and CO₂ emissions of each strategy were assessed. ST1 proved to be the best compromise in terms of weed control effectiveness and operational performance compared to the other strategies. Indeed, ST1 tendentially achieved a lower weed height (20.42 cm) and weed biomass around vine trunks (105.33 g d.m. m⁻²) compared to the other strategies. In terms of total field time, fuel consumption and CO₂ emissions, ST1 recorded intermediate values equal to 3.85 h ha⁻¹, 15.29 kg ha⁻¹, and 48.72 kg ha⁻¹, respectively. Further studies are needed to evaluate these strategies in different vineyard conditions, considering their effect on weed flora composition. Furthermore, exploring automation technology for real-time implement adjustments based on weed infestation levels could further improve the intervention effectiveness and efficiency. Full article

Weeds affect crop yield and quality due to competition for resources. In order to reduce the risk of yield losses due to weeds, herbicides or non-chemical measures are applied. Weeds, especially creeping perennial species, are generally distributed in patches within arable fields. Hence, instead of applying control measures uniformly, precision weeding or site-specific weed management (SSWM) is highly recommended. Unmanned aerial vehicle (UAV) imaging is known for wide area coverage and flexible operation frequency, making it a potential solution to generate weed maps at a reasonable cost. Efficient weed mapping algorithms need to be developed together with UAV imagery to facilitate SSWM. Different machine learning (ML) approaches have been developed for image-based weed mapping, either classical ML models or the more up-to-date deep learning (DL) models taking full advantage of parallel computation on a GPU (graphics processing unit). Attention-based transformer DL models, which have seen a recent boom, are expected to overtake classical convolutional neural network (CNN) DL models. This inspired us to develop a transformer DL model for segmenting weeds, cereal crops, and ‘other’ in low-resolution RGB UAV imagery (about 33 mm ground sampling distance, g.s.d.) captured after the cereal crop had turned yellow. Images were acquired during three years in 15 fields with three cereal species (Triticum aestivum, Hordeum vulgare, and Avena sativa) and various weed flora dominated by creeping perennials (mainly Cirsium arvense and Elymus repens). The performance of our transformer model, 1Dtransformer, was evaluated through comparison with a classical DL model, 1DCNN, and two classical ML methods, i.e., random forest (RF) and k-nearest neighbor (KNN). The transformer model showed the best performance with an overall accuracy of 98.694% on pixels set aside for validation. It also agreed best and relatively well with ground reference data on total weed coverage, R2 = 0.598. In this study, we showed the outstanding performance and robustness of a 1Dtransformer model for weed mapping based on UAV imagery for the first time. The model can be used to obtain weed maps in cereals fields known to be infested by perennial weeds. These maps can be used as basis for the generation of prescription maps for SSWM, either pre-harvest, post-harvest, or in the next crop, by applying herbicides or non-chemical measures. Full article

The aim of this study is to evaluate the occurrence of weeds under conditions of limited herbicide use due to the protection zone of water resources. A total of 23 weed species were found in maize stands, 19 species were found in wheat stands, and 16 species were found in rapeseed stands. The redundancy analysis (RDA) results show significant differences in weed occurrence and composition due to herbicide regulation in each crop. Changes in weed composition induced by herbicide application limitations lead to a preference for more specialized weed species (specialists) at the expense of widespread species (generalists). Limiting the use of pesticides in sensitive and vulnerable areas, such as water sources, bodies, and watercourses, is justified from the perspective of protecting the aquatic environment and biodiversity. However, such measures can cause weed growth that is difficult to control, and therefore, it is important to search for new methods for weed control in field crops. Determining a balance between safeguarding water resources and addressing agricultural challenges remains crucial for sustainable land and water management. Full article