Agricultural Systems Research Articles

Innovation platforms in practice: a conceptual framework

ABSTRACT The agricultural innovation systems (AIS) approach holds promise for researchers seeking to gain deeper understanding of how actors, norms, and knowledge interact and drive improvements in the agricultural sector in developing countries. However, use of the AIS framework in empirical research is limited and conceptual and operational frameworks are needed. In this paper we have created a conceptual framework for how innovation platforms (IPs), a unique type of multistakeholder meetings, contribute to the AIS approach by fostering innovation, networking, and performance. The conceptual framework is then applied to a case study of the Feed the Future Innovation Lab for Livestock Systems (LSIL). Findings from the case study analysis showed the meetings fostered innovative thinking, strengthened networks, and shared knowledge among actors. While the generalisability of the case is limited, the study demonstrates how future research could use the conceptual framework for advancing knowledge around AIS and IP meetings.

Balancing the right to food and environmental sustainability: A call for holistic transformation

This paper conducts an in-depth examination of the intricate nexus between the right to food and ecosystem conservation, recognizing the fundamental importance of addressing these interlinked issues for sustainable global development. Anchored in international and national legal frameworks, the right to food is explored not only as a moral imperative but as a binding human rights obligation. The analysis spans a broad spectrum, encompassing the impact of human activities such as population growth, climate change, and intensive agricultural practices on natural resources, biodiversity, and environmental sustainability. The literature review highlights the far-reaching repercussions of food access constraints on marginalized populations, emphasizing the profound relationship between food and the environment. The study underscores the critical role of biodiversity, soil health, and climate change in shaping food security challenges, with a particular focus on the consequences of industrial agriculture. The examination of agroecology emerges as a central theme, offering a holistic approach that integrates ecological, health, social, and economic considerations into agricultural and food systems. The methodology involves a comprehensive review of published studies in the specified domains, providing a robust foundation for unraveling the complex dynamics and interdependencies between the right to food, ecosystem conservation, and the broader context of climate change and human activities. The paper puts forth a series of recommendations, emphasizing the need for policies that integrate human rights into agricultural actions, enhanced inclusivity for smallholder farmers, widespread adoption of agroecology, and educational campaigns to raise awareness. Agroecology is positioned as a key solution, not only for its contributions to climate resilience but also for its positive impact on soil health, biodiversity conservation, and long-term environmental sustainability. The paper advocates for a paradigm shift in global agricultural strategies, emphasizing integrated, sustainable approaches that prioritize inclusivity, environmental stewardship, and the well-being of present and future generations. The recommendations serve as a blueprint for policymakers, practitioners, and stakeholders to collaboratively work towards a future where food security coexists harmoniously with ecosystem conservation, ensuring a sustainable and equitable world for all. Key words: Right, Food, Ecosystem, Conservation, Sustainable, Climate, Biodiversity, Agroecology, Agriculture, Policy

Social and economic importance of new bamboo species established in three municipalities of the North Eastern Mountain range of Puebla, Mexico

The study was conducted in three municipalities of Puebia, Mexico. The objectives were to identify the species of bamboo in the North Eastern region of Puebla, know the climatic conditions and agronomic systems where it grows, characterize the socioeconomic situation of the producers, and identify the contribution to the family economy. A review of the history of cultivation in Mexico was carried out at the National Herbarium of Mexico (MEXU). For the collection of information, it was considered that the bamboo system was within the local agricultural system and selection of municipalities was based on the productive relationship of the crop and the introduction of species in the area. Sixty-four surveys were done of bamboo producers through the questionnaire with social, economic, and productive variables related to the bamboo production system. In the Puebla’s North Eastern Mountain range there are two new species of bamboo, Bambusa oldhamii and Guadua angustifolia, both with different characteristics of uses and established in two production systems, the commercial and family system. At present they have a low commercialization of some bamboo derivatives and little use as food. The region is considered one of extreme proverty. The two species have a high potential for environmental adaptation agronomically they are developed as a single crop in backyards and used in various commercial activities. The lack of use of the crop in the region and its rapid natural expansion due to the environmental conditions for its growth, induces the tendency to consider it as an undesirable plant

Impacts of adaptation to climate change on farmers’ food security and level of sesame production in Western Ethiopia

The existence of multiple stresses and poor adaptive capacity make Africa most susceptible to climate change. In Ethiopia the potential adverse effects of climate change on the agricultural sector, the main stay of the country’s economy, are major concerns. To ensure food security, reducing the vulnerability of agricultural systems through different feasible adaptation strategies is one of the policy options in response to climate change impact This study is a first of its kind in examining the relative effectiveness of various adaptation strategies in ensuring farmers’ food security and enhancing level of sesame production in rural area of Western Ethiopia. In addition to data obtained from meteorological stations, cross-sectional data were collected interviewing 400 farm households. Descriptive statistics, two-stage least square (2SLS) and double-hurdle (D-H) models were used to analyze the data. The results of the study indicate that households are adapting using various strategies to the looming climate change in the area. The study also indicated that, though sesame production was negatively impacted by the climate hazards, smallholders have continued its production at minimum level due mainly to its high value crop character. 2SLS estimation results revealed that rainfall and temperature variability have negative impact on household’s food security. Moreover, the result indicates effectiveness of climate adaptation strategies namely agronomic practices, irrigation and soil and water conservation in reducing climatic risks and ensuring household food security. The result also implicitly indicated that farmers continued to adapt sesame production under risk climate and it is contributing to farmers’ food security. Further, the result revealed that climate change adaptation strategies have positively impacted the level of sesame production. Consequently, policy that augments households’ climate awareness and promotes adaptation decision and strategies could help reducing risks pertaining to climate and thereby improves farmers’ food security status and production of high value export potential crop—sesame.

Integrating Livestock with Crops and Forestry for Sustainability

Global per capita consumption of animal protein is set to rise, particularly in developing economies, leading to a dramatic increase in meat consumption from 133 million tons in 1980 to 452 million tons by 2050. Notably, 86% of this increase, or 279 million tons, is expected to occur in developing countries. The expansion of animal-based agricultural systems, which cover 45% of the Earth's land area, presents significant challenges. These systems contribute substantially to agricultural emissions, including greenhouse gases such as nitrous oxide (N2O) and methane (CH4), and account for 8% of global water usage. The livestock sector is largely comprised of resource-constrained smallholders in developing nations. Environmental impacts arise from the lack of integration with other agricultural and forestry practices, disrupting the natural cycles of carbon, water, nitrogen, phosphorus, and sulfur. This disruption leads to increased emissions of N2O and CH4, water contamination, land degradation, and biodiversity loss. To address these challenges and support the United Nations' Sustainable Development Goals (SDGs) related to poverty reduction (SDG #1), hunger alleviation (SDG #2), clean water and sanitation (SDG #6), and climate action (SDG #13), it is essential to integrate livestock with crop and tree farming. Strategies to improve sustainability include incorporating pastures into crop rotations, using controlled grazing techniques, practicing agro-forestry such as alley cropping, and implementing systems like ley farming. Additional measures include precision feeding and protein matching to reduce enteric fermentation, repurposing emissions of CH4 and N2O, and effective manure management. Addressing greenhouse gas emissions through diverse approaches, reducing product wastage, minimizing antibiotic use, and restoring rangelands to enhance soil carbon storage are also critical for achieving sustainable livestock practices.

Enhancing Water Use Efficiency and Carbon Profitability Through the Long-Term Impact of Sustainable Farming Systems

This study aims to enhance water use efficiency, maximize productivity, and minimize environmental impact through the implementation of sustainable agricultural systems using drip irrigation systems. It investigates the effects of biodynamic farming compared to those of organic and conventional methods over a six-year period and focuses on soil properties, water use efficiency, crop yield, and environmental and economic perspectives. Using a biodynamic farming system resulted in an average increase in water use efficiency of 1.96 and 10.67% for maize and 3.62 and 10.68% for faba bean and an increase in maize yield of 1.68 and 0.99%, while the faba bean yield reached 3.25 and 1.57% compared to the organic and conventional farming systems, respectively. The biodynamic system sequestered the highest average soil carbon of 6.16 tons/ha (which is equivalent to 22.45 tons/ha of CO2 emissions), representing a 13% increase compared to the organic system. Additionally, the biodynamic system yielded an increase in total net profit of 5.70 and 21.66% for the maize crop and 6.72 and 22.19% for the faba bean crop compared to the organic and conventional farming systems, respectively. The farming system significantly influenced the soil carbon sequestration and organic carbon.

Unmanned Agricultural Machine Operation System in Farmland Based on Improved Fuzzy Adaptive Priority-Driven Control Algorithm

Autonomous driving technology for agricultural machinery can maximise crop yield, reduce labour costs, and alleviate labour intensity. In response to the current low degree of automation and low tracking accuracy of driving paths in agricultural equipment, this research proposes an unmanned agricultural machinery operating system based on an improved fuzzy adaptive PD control algorithm. Firstly, mechanical kinematic models and fuzzy adaptive control algorithms are introduced to achieve autonomous driving, and parameter settings and speed adjustments are made while considering errors. Secondly, in the autonomous driving operation system, taking a certain rice machine as an example, perception information, trajectory design, dynamic control, operation supervision, and remote control design are carried out. The experimental results show that the improved fuzzy algorithm exhibits smaller deviation results in driving path tracking, with an average error between the actual path and the expected path of less than 0.001 m. In different testing scenarios, compared with the actual control results, the maximum deviation of the control system platform in straight sections is less than 2.8 m, which is more stable. More than 95% of the lateral deviation results in the road sections are within 0.11 m. And the tracking distance error of the proposed method in the straight and curved segments is relatively small, far smaller than other comparative algorithms. The unmanned agricultural machinery operation system proposed in this study can significantly improve the efficiency and accuracy of agricultural machinery work, promote the development of intelligent and modern agricultural machinery, and provide reference value and important contributions to social and economic development as well as the progress and promotion of related technologies.

Indigenous and Local Knowledge: Instruments towards Achieving SDG2: A Review in an African Context

This study seeks to review African indigenous and local knowledge in farming systems that are used as instruments for the achievement of sustainable development. Hence the idea of sustainability, indigenous and local knowledge paying reference to Zero Hunger. Limited studies have indicated the importance of indigenous knowledge systems as a fundamental driver for the achievement of SDG2 by 2030. This study envisioned the idea of sustainable development in the context of indigenous and local knowledge as a potential for achievement of Sustainable Development Goal 2. Hence, it emphasizes the necessity of a radical investigation of Indigenous knowledge practices for a more effective local farming system in the African setting that is inclusive and driven by the Indigenous community to harness the untapped riches of indigenous knowledge. Local and Indigenous knowledge are regarded as knowledge systems possessed by cultural groups and, based on their experience and adaptability to local culture and environment, it is important for development, particularly in food security. The study concludes by urging further potential investigation into whether indigenous and traditional knowledge systems as tools can be used to accomplish Sustainable Development Goals in practice.

Effect of Subclinical Mastitis Detected in the First Month of Lactation on the Reproductive Performance of Dairy Cows in Western Algeria

Background: The current study aimed to detect in the first month of lactation the prevalence and risk factors of subclinical mastitis (SCM) and its effects on reproductive performance in dairy cows in western Algeria. Methods: 530 cows from 18 herds were examined in the study. California Mastitis Test (CMT) was used to screen subclinical mastitis for individual cows and a score of two or more for any quarter without any clinical symptoms and abnormalities in milk was considered as positive for SCM. Milk samples positive for subclinical mastitis were subjected to bacteriological analysis. Result: The present study revealed a prevalence of subclinical mastitis of 34.90%, (185 of 530). The most common pathogen identified from CMT-positive milk samples was Staphylococcus aureus with 35.62%. Logistic regression analysis showed that parity, farming system and milking method affect significantly the prevalence of SCM. Subclinical mastitis during the first month of lactation affected significantly the reproductive performance by increasing calving to first service interval (CFSI), calving-to-conception interval (CCI)and number of services per conception (NSPC). The results of this study highlight the importance of mastitis control programs in dairy farms by showing that a high frequency of subclinical mastitis caused by Staphylococcus aureus may have a negative impact on the reproductive performance of dairy cows.

Maize crop performance on different Agricultural Production Systems and co-inoculation with A. brasilense and T. asperellum

Considering the increasing global population and demand for food, it is crucial to adopt agricultural practices that ensure both food security and environmental preservation. In this context, plant growth-promoting microorganisms (PGPM) and integrated crop-livestock-forestry systems (ICLF) have emerged as promising strategies for sustainable productive intensification. This research aimed to determine the effects of inoculating Azospirillum brasilense and Trichoderma asperellum on maize crops (Zea mays L.) grown in monocropping and ICLF systems. A complete randomized block design was performed in a 4 × 2 factorial arrangement with three replications. The crop systems included maize monocrop (C), crop-livestock (CL), crop-forest (CF), and crop-livestock-forest (CLF). Concomitantly, the co-inoculation (A. brasilense + T. asperellum) was compared to the control management (with no PGPM). CL and C systems with co-inoculation showed the highest yields, while the CF and CLF systems, which include the arboreal component, showed lower yields because of tree shading. CL + co-inoculation treatment was the most significant with increases of 17.14% in shoot dry mass, 43% in 1000-grain weight, and 9.56% in yield (t ha-1) compared to the C + control treatment. Additionally, the CL + co-inoculation treatment overcame the CLF + control by 136.63% in yield. Results indicate that the PGPM co-inoculation in maize within the CL system is an effective strategy for optimizing crop production.

Cassava disease detection using a lightweight modified soft attention network.

Cassava is a high-carbohydrate crop that is at risk of viral infections. The production rate and quality of cassava crops are affected by several diseases. However, the manual identification of diseases is challenging and requires considerable time because of the lack of field professionals and the limited availability of clear and distinct information. Consequently, the agricultural management system is seeking an efficient and lightweight method that can be deployable to edged devices for detecting diseases at an early stage. To address these issues and accurately categorize different diseases, a very effective and lightweight framework called CDDNet has been introduced. We used MobileNetV3Small framework as a backbone feature for extracting optimized, discriminating, and distinct features. These features are empirically validated at the early intermediate stage. Additionally, we modified the soft attention module to effectively prioritize the diseased regions and enhance significant cassava plant disease-related features for efficient cassava disease detection. Our proposed method achieved accuracies of 98.95%, 97.03%, and 98.25% on Cassava Image Dataset, Cassava Plant Disease Merged (2019-2020) Dataset, and the newly created Cassava Plant Composite Dataset, respectively. Furthermore, the proposed technique outperforms previous state-of-the-art methods in terms of accuracy, parameter count, and frames per second values, ultimately making the proposed CDDNet the best one for real-time processing. Our findings underscore the importance of a lightweight and efficient technique for cassava disease detection and classification in a real-time environment. Furthermore, we highlight the impact of modified soft attention on model performance. © 2024 The Author(s). Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Composition of biopesticides for crop protection – current state and prospects (review)

Aim. To summarise and analyse available information on research into biopesticide compositions aimed at enhancing their effectiveness and to assess prospects for the development of this field so as to determine the influence of components on the effectiveness of biopesticides for agricultural crop protection.This review article presents the results of studies of components included in the compositions of microorganism‐based biopesticides based on a system analysis. It is noted that the selection of biopesticide components must be carried out in accordance with the requirements for products recommended for use in ecological and organic farming systems. It is indicated that the choice of optimal formulation is associated with the characteristics of the producer strains, their trophic needs and resistance to biotic and abiotic factors and with the characteristics of the biopesticide application technology (seed treatment, application to the soil or treatment of plants during vegetation), as well as the type of equipment used.Knowledge of the basic requirements for biopesticide formulations will help maintain the viability and biological activity of microbial agents during storage of biopesticides, taking into account the sensitivity of producer strains to environmental conditions. Selection of optimal carriers, adhesives, stabilisers, thickeners and synergists, taking into account the technology of application of the biopesticide and the target pathogen, will facilitate the development and appearance on the market of new biopesticides for protecting agricultural crops from diseases.

The Use of Anaerobic Digestate for Greenhouse Horticulture

Agricultural crop production practices are being developed for organic, sustainable, and environmentally friendly farming systems. Developing efficient and resourceful crop fertilizers is significantly important for future agriculture. Various biofertilizers, such as animal manures, composts, and vegetable byproducts, have been successfully applied in agriculture. Anaerobic digestate, organic matter obtained from animal or plant waste processing during anaerobic digestion into biomass, has become popular due to its versatility, multiple purposes, and facile application methods. Digestate has recently been widely used in agriculture to enrich the soil with nutrients and thus increase crop yields. Several studies have shown that anaerobic digestate is a valuable fertilizer that can be used as a biofertilizer in field and greenhouse horticulture. Also, research has been carried out on the use of digestate in hydroponic horticulture. This review presents the research results and discusses the possibilities of using anaerobic digestate in greenhouse horticulture. Its objective is to provide a comprehensive understanding of the application of digestate from various sources and its impact on the growth, progress, yield, and quality of greenhouse-grown vegetables.

Assessment of BxN Hybrids for Fodder Productivity in South Gujarat, India

A field experiment was conducted at Krishi Vigyan Kendra (KVK), Bharuch, Gujarat to evaluate eight Bajra x Napier (BxN) hybrids viz. BNH-10, BNH-11, CO-5, CO-6, DHN-5, DHN-15, Phule Jaywant, and Phule Gunwant for their fodder yield potentials and quality parameters over three years (2021-2024). A Randomized Block Design (RBD) with three replications was employed for the experiment. The pooled results of three years revealed that significant variations were observed in hybrids investigated. The hybrid BNH-11 consistently and significantly outperformed other tested hybrids, demonstrating superior performance across multiple parameters, including plant height (143.25 cm), tillers per plant (26), leaf-to-stem ratio (1.14), green fodder yield (207.05 MT ha⁻¹), dry matter yield (80.36 MT ha⁻¹) and crude protein yield (6.06 MT ha⁻¹). Phule Gunwant closely followed BNH-11, performing on par across all evaluated parameters. These findings indicate that BxN hybrids exhibit substantial potential for fodder production, supporting their use in sustainable livestock farming systems in the region.

Effect of Media on Lablab (Lablab purpureus var. typicus) for Yield and Quality under Soilless Vertical Farming System

Background: Lablab (Lablab purpureus var. typicus) is one of the important leguminous vegetable crops known for its highest content of protein. The area under cultivation is shrinking due to conversion of farm land into non-agricultural purposes. Under these circumstances, soilless vertical farming system is the only alternate cultivation system for increasing production of vegetables. Media play a major role in growth and yield of vegetables under soilless conditions. With this background, the present experiment was carried out to study the effect of growing media in lablab for high yield and quality under soilless vertical farming systems. Methods: Two lablab varieties viz., CO 5 (V1) and Arka Prasidhi (V2) were raised under five different media combinations viz., 100% cocopeat (M1), 50 % cocopeat + 50 % Vermicompost (M2), 50% cocopeat + 50 % FYM (M3), 50% cocopeat + 25% vermicompost + 25% FYM (M4) and Control (M5) with three replications during 2021-2022 and 2022-2023. This experiment was laid out in FCRD. The growth and yield parameters were recorded and the data was subjected to statistical analysis. Result: The experimental results revealed that both the varieties and growing media provided significant impact on growth, yield, quality and uptake of nutrients whereas dry matter content exhibited no significant impact among the different media. The pooled season data revealed that variety CO 5 observed for the overall superior performance while the media combination of 50% cocopeat + 50% Vermicompost considered superior for growth and yield characters where 50% cocopeat + 25% vermicompost + 25% FYM showed superiority for the quality parameters and uptake of nutrients.

Trophic transfer of heavy metals across a food chain in a wastewater-irrigated agroecosystem.

Wastewater irrigation is often practiced in arid regions, which can increase the chance of heavy metals contaminating the agricultural system. This contamination poses risks to both the environment and human health. This research looked into how cadmium (Cd), lead (Pb), copper (Cu), and zinc (Zn) move through a food chain involving soil, plants, and arthropods. The study was conducted in El-Gabal El-Asfar, Egypt, comparing treated and untreated wastewater irrigation areas. Six soil-irrigated sites and one reference site were sampled for soil, alfalfa (Medicago sativa), two grasshopper species (Aiolopus thalassinus and Calephorus compressicornis), and a wolf spider (Hogna ferox). The samples were analyzed for their heavy metal content. Metal concentrations in all components of the wastewater irrigated system were significantly higher compared to the reference site. The wolf spider and the soil contained the highest levels of Cd, Pb, and Cu, while the greatest concentrations of Zn were found in the spider and grasshoppers. Despite limited transfer from soil to plant, trace elements biomagnified within the terrestrial food chain, specifically from grasshoppers to wolf spiders. The correlation analysis of metal levels between soils, plants, and arthropods in the present study reflects its transfer across the trophic levels. It suggests that dietary intake is the main source of metal accumulation in arthropods. The present study, therefore, quite clearly indicated the possibility of heavy metal biomagnification in terrestrial food chains of wastewater-irrigated agroecosystems. Continuous monitoring and management of such systems are advocated to avoid environmental and public health risks.

Mango leaf disease diagnosis using Total Variation Filter Based Variational Mode Decomposition

Mango leaf diseases significantly threaten mango cultivation, impacting both yield and quality. Accurate and early diagnosis is essential for effectively managing and controlling these diseases. This study introduces a novel approach for diagnosing mango leaf diseases, leveraging Total Variation Filter-based Variational Mode Decomposition. The proposed method enhances the extraction of disease-specific features from leaf images by decomposing them into intrinsic mode functions while simultaneously reducing noise and preserving important edge information. Experimental results demonstrate that the proposed method effectively isolates relevant patterns associated with various mango leaf diseases, improving diagnostic accuracy compared to traditional methods. Deep learning models, DenseNet121 and VGG-19, are used for feature extraction from sub-band images, and extracted features are concatenated and fed to Random Forest for classification. Utilizing tenfold cross-validation, our model demonstrated enhanced classification accuracy (98.85 %), specificity (99.37 %), and sensitivity (98.0 %) in detecting diseases from Mango leaf images. Feature maps and Gradient-weighted Class Activation Mapping analysis was conducted to visualize and scrutinize the essential regions crucial for accurate predictions. Statistical analysis indicates that our proposed architecture outperforms pre-trained models and existing mango leaf disease detection methods. This diagnostic approach can be a rapid disease detection tool for imaging specialists utilizing leaf images. The robustness and efficiency of the presented work in handling complex and noisy image data make it a promising tool for automated agricultural disease diagnosis systems, facilitating timely and precise interventions in mango orchards.

The delineation of management zones using soil quality indices for the cultivation of irrigated rice (Oryza sativa L.) in Huila, Colombia

Conventional intensive farming systems can result in degraded soil. It is therefore important to monitor this effect periodically by delineating management zones (MZ) based on soil quality indices (SQI) in order to maintain and improve the soil characteristics in a precision farming environment and obtain homogeneous rice yields. The aim of this study was to determine and spatialise SQI and delineate MZ for cultivating flooded rice in an area of Fluvisols in Huila, Colombia. Forty-one georeferenced soil samples were collected from the 0 to 20 cm layer, and the physical, chemical and biological attributes of the soil were analysed to calculate the Integrated Quality Index (IQI) and the Nemoro Quality Index (NQI) using linear scoring functions. Geostatistical tools were then used to fit semivariogram models of the SQI, and interpolated using ordinary kriging to map the MZ using the QGIS software. The IQI and NQI showed a moderate spatial correlation, which allowed three distinct MZ to be identified and delineated. Attributes, such as bulk density (Bd), total porosity (TP), soil respiration (SR), available water (AW) and soil organic matter (SOM) were significant and can be used as a guide by farmers for restoring the quality of the soil in rice production. The method proved to be effective, and provided an information base to be used in the local management of areas of rice cultivation in the study region.

Agricultural legacy shapes plant diversity patterns in mountain grasslands of Maramureș and Bukovina: A cross‐border perspective (Ukraine, Romania)

Abstract We investigated farming practices and grassland plant diversity patterns in the historical regions of Maramureș and Bukovina, located in the central Eastern Carpathians of Romania and Ukraine. We explored the influence of social and historical factors on recent grassland plant diversity, including changes and modifications in land use and grassland management practices. We used stratified random sampling to select 48 grassland parcels in eight villages on the Ukrainian‐Romanian borderlands. We identified the factors that affect the composition and diversity of grassland vascular plants and bryophytes at multiple spatial scales and compared the frequency and timing of historical and recent grassland management practices to distinguish between preserved and modified agricultural traditions. In most of the grassland parcels studied (83% in Romania and 78% in Ukraine), traditional land use persisted. Local plant species richness was primarily influenced by management practices, outweighing the impact of topography and soil factors. Regular mowing at appropriate intensity increased the richness of vascular plants, while grazing promoted the richness of bryophyte species. Modifications to farming systems, observed in all studied villages, were mainly due to declining population and livestock numbers. Although the timing of spring and autumn grazing in hay meadows still adhered to tradition, mowing schedules shifted earlier, especially for the first cut of two‐cut hay meadows. Traditional corralling, fertilization and hayseed application have become rare or discontinued in certain villages, while controlled burning has increased. Past use of mineral fertilizers in Ukrainian villages during the Soviet era influenced the recent diversity and composition of vascular plant species, favouring nutrient‐demanding species. Social factors and agricultural policies indirectly affect biodiversity in semi‐natural grasslands, leaving a tangible footprint even in the most remote areas of the Carpathian Mountains. We provide basic recommendations to preserve the remarkable biodiversity of the region. Read the free Plain Language Summary for this article on the Journal blog.

Performance of different wheat varieties and their associated microbiome under contrasting tillage and fertilization intensities: Insights from a Swiss long-term field experiment

Winter wheat is an important global cereal crop. However, conventional farming practices, characterised by intensive tillage and high fertilizer inputs, pose significant threats to the environment. In response, more conservative management practices are being applied aiming to maintain wheat production while promoting a beneficial microbiome. Here, we evaluated the suitability of three different wheat varieties for less intensive agricultural systems, focusing on reduced tillage and fertilizer intensity. The study was conducted over two consecutive years in a Swiss long-term field experiment comparing conventional versus reduced tillage and full fertilization versus half fertilization. In addition, we investigated the composition of plant-associated microbial communities using amplicon sequencing of phylogenetic marker genes, specifically targeting bacteria and fungi in rhizosphere samples and fungi in root samples. Our results revealed that in our study wheat variety most strongly predicted grain yield and quality, independent of tillage and fertilization intensity. Specifically, wheat varieties demonstrated higher yields and N uptake in plots subjected to conventional ploughing and full fertilization compared to those under reduced tillage and half fertilization. We found no significant effect of wheat variety on the composition of microbial communities. However, tillage emerged as the primary factor influencing microbial community composition in the rhizosphere, while fertilization intensity significantly impacted fungal communities in the root system. These findings underscore the complex interplay between agronomic practices, plant genetics, and microbial dynamics in agroecosystems, emphasizing the need for holistic and adaptive approaches and their further development to ensure sustainable crop production.