Creeping perennial weeds are difficult to manage on organic farms in semi-arid regions of the northern Great Plains. Integrated weed management practices that combine biological, cultural, and mechanical controls can improve management of these weeds, but little is known about the soil microbial response to these practices. Our work investigated the soil microbiome response to contrasting, 4-year crop sequences with standard and reduced tillage. The crop sequences included a range of crop competition phases from high (three years of alfalfa, Medicago sativa L.) to low (two years of continuous fallow), within the longer 4-year period, with intermediate levels of crop competition between those two extremes. Soil samples were collected, and bacterial 16S and fungal ITS amplicon sequencing was performed. Differences in alpha diversity were not significant (p > 0.05) between tillage methods. Across all six locations, bacterial alpha diversity was negatively correlated with soil organic matter (R = -0.37, p < 0.001) while fungal alpha diversity was positively correlated (R = 0.17, p = 0.043). Bacterial community composition was not affected by crop sequence or tillage treatment. Fungal community composition was affected by crop sequence (p = 0.00163) and tillage (p = 0.02). The fungal genera Neosetophoma, Boeremia, and Paraphoma were 10 - 35-fold more abundant in continuous alfalfa compared to the mean abundance in the other crop sequences. Reduced tillage led to a 40% reduction in the fungal genus Fusarium, which contains many plant pathogen species. These results suggest that diversified crop sequences and altered tillage methods have minimal impact on bacterial communities, but fungal communities are sensitive to these management changes.

Interrow weed control is used in a wide range of crops, traditionally applied via physical cultivation or banded herbicide application. However, these methods may result in crop damage, development of herbicide resistance, or off-target environmental impacts. Electric interrow weed control presents an alternative, although its potential impact on crop yield requires further investigation. One of the modes of action of electric weed control is the continuous electrode-plant contact method, which passes a current through the weed and into the roots. As the current passes into the roots, it can potentially disperse through the soil to neighboring root systems. Such off-target current dispersion, particularly in moist topsoil with low resistance, poses potential concern for neighboring crops when electric interrow weed control is applied. This research evaluated the continuous electrode-plant contact method, using a Zasso (TM) XPower machine, in comparison with mowing across three trials conducted in 2022 and 2023. Both treatments were used to remove target lupine (Lupinus albus L.) plants adjacent to a row of non-target lupine. Electric weed control was applied to plants in dry soil or following a simulated rainfall event. The trials demonstrated that electric weed control and mowing did not reduce density and biomass of neighboring non-target lupine plants compared with the untreated control. Likewise, pod and seed production, grain size, and protein, as well as grain germinability and vigor of the resulting seedlings, were not reduced by these weed control tactics. This research used technology that was not fit for purpose in broadscale grain crops but concludes that electric weed control via the continuous electrode-plant contact method or mowing did not result in crop damage. Therefore, it is unlikely that damage will occur using commercial-grade electric weed control or mowing technology designed for large-acreage interrow weed control, thus offering nonchemical weed management options.

Canary grass (Phalaris canariensis L.) is a versatile crop with global significance; it is primarily cultivated for its small elliptical seeds, which are used as bird feed and for human consumption. This crop is adapted to various climates and soils, so it can be grown successfully in Hungary. However, challenges such as weed control, climate change impacts, and soil factors require strategic management for sustained success in canary grass cultivation. Our study investigated the impact of management and environmental (as seasonal and soil) factors on pre-harvest weed vegetation in canary grass fields in Southeast Hungary between 2017 and 2020. In addition to showing the weed vegetation of the canary grass, the aim of our work was to promote more effective weed management of canary grass by revealing correlations between soil, seasonality, and management variables, influencing weed diversity and coverage. Using the analysis of covariance (ANCOVA) and correlation tests, we tested significant variables, providing insights into the complex interactions affecting weed composition. A redundancy analysis (RDA) further unveiled the relationships between explanatory variables and weed species' composition. The findings offer valuable information for effective weed management strategies in canary grass cultivation. Our comprehensive study on canary grass fields in Southeast Hungary sheds light on significant factors influencing weed composition and abundance. The average weed coverage was 10.8%, with summer annuals and creeping perennials being the most prevalent life forms. Echinochloa crus-galli, Cirsium arvense, Xanthium italicum, and Setaria viridis were among the dominant species. ANCOVAs revealed the impact of soil, management, and seasonal factors on weed cover, species richness, diversity, and yield levels. Soil properties like texture, pH, and nitrogen content showed varying effects on weed parameters. The vintage effect, tillage systems, and farming practices also played crucial roles. The redundancy analysis highlighted the influence of the year, soil sulfur content, and winter preceding crops on weed composition. In conclusion, the herbaceous vegetation in the studied area is dominated by summer germinating and creeping perennial species. Despite slight differences in average coverage and occurrence, a well-defined set of significant species is evident. Multicollinearity among variables suggests limitations to further increase the number of variables that can be included in the analysis. The ANCOVAs showed that the soil, seasonal, and farming variables significantly influence overall weed vegetation and crop yield, with a lesser impact on species richness and diversity. The reduced RDA model highlights the strong influence of the year on species' composition, emphasizing the inherent factors during canary grass cultivation that are challenging to modify through farming practices.

Weed harrowing is commonly used to manage weeds in organic farming but is also applied in conventional farming to replace herbicides. Due to its whole-field application, weed harrowing after crop emergence has relatively poor selectivity and may cause crop damage. Weediness generally varies within a field. Therefore, there is a potential to improve the selectivity and consider the within-field variation in weediness. This paper describes a decision model for precision post-emergence weed harrowing in cereals based on experimental data in spring barley and nonlinear regression analysis. The model predicts the optimal weed harrowing intensity in terms of the tine angle of the harrow for a given weediness (in terms of percentage weed cover), a given draft force of tines, and the biological weed damage threshold (in terms of percentage weed cover). Weed cover was measured with near-ground RGB images analyzed with a machine vision algorithm based on deep learning techniques. The draft force of tines was estimated with an electronic load cell. The proposed model is the first that uses a weed damage threshold in addition to site-specific values of weed cover and soil hardness to predict the site-specific optimal weed harrow tine angle. Future field trials should validate the suggested model.

Weeds are the most severe and widespread biological constraint on agricultural production systems and cause damage to cropped and non-cropped lands. They reduce crop yield and degrade the quality of the produce, besides raising the cost of production. The intensification of agriculture in the Green Revolution era attracted chemical fertilizers and dwarf varieties coupled with mono-cropping and irrigation practices, which enhanced crop-associated weeds and the widespread use of herbicides for easy control. Pesticides may kill many organisms, both target and non-target species, in the environment, causing an imbalance in the ecosystem. Despite the significant increase in productivity, the environmental repercussions of industrial agriculture, characterized by the use of high-yielding crop varieties and the extensive application of chemical fertilizers and pesticides, have prompted a quest for more sustainable agricultural practices worldwide. One potential alternative lies in innovative approaches that draw upon ecological insights gleaned from studying natural ecosystems. These approaches aim to create ecologically intensive agro-ecosystems. Developing ecologically intensive agro-ecosystems necessitates a deep understanding of the biological dynamics within ecosystems and the integration of traditional agricultural knowledge held by local farmers. Considering the potentiality of appropriate weed management technologies to substantially improve crop productivity, there is an opportunity for the development, popularization, and adoption of effective, economical, and eco-friendly weed management technologies.