Cover Crops Research Articles

Scientometric analysis of cover crop management: Trends, networks, and future directions

This research paper presents a comprehensive scientometric analysis of English articles from the Scopus database regarding the topic of cover crop management from 1956 to March 2024. Through the analysis of the annual production trend, total production, a co-occurrence network of keywords, co-authorship networks, and co-citation networks, the data was mapped and visualized using VOSviewer and Bibliometrix software. There was an exponential increase in publications from 1991 onwards. The predominant subject was Agricultural and Biological Sciences and the most relevant journals, authors, and documents were related to this topic. Additionally, the most productive country was the United States, but in terms of article production per surface area, other countries, such as Switzerland and The Netherlands, evidence the great weight of cover crop management in these countries. The identified research topics were related to the application of different crops as cover crops and the effects on different cultivars, also soil quality improvement, and fertilization and nutrient efficiency. An emerging research topic was found to be the usefulness of cover crops as effective tools for climate change adaptation and mitigation strategies in agriculture. Future research in the field of cover crop management could be directed towards climate-adaptive cover crop species and varieties, the use of technological innovations for cover crop monitoring, and management and analysis of the economic and social impacts of cover crop adoption.

Influence of crop rotation, the treatment of crop residues, and the application of nitrogen fertilizers on soil properties and maize yield

AbstractThis inquiry is aimed at discerning the impact of various agricultural practices, such as crop rotation, the incorporation of plant residues, and the application of mineral fertilizers, on soil health and crop productivity, notably focusing on maize production. Cultivation included maize (Zea mays), velvet beans (Mucuna pruriens), soybeans (Glycine max), and vetch (Vicia sativa). After harvest, maize seeds were sown across all 48 plots to evaluate the influence of preceding crop rotation on soil properties and maize yield. Hypotheses posited in the study suggested that crop rotation, nitrogen fertilizer application, and the incorporation of crop residues positively impact soil fertility. The study further argues that the utilization of cover crops in crop rotation aids in nitrogen retention within the soil and enhances yield. The results were processed utilizing a two‐way analysis of variance (ANOVA) with interaction and post hoc comparisons. The findings confirm that crop rotation, nitrogen fertilizer application, and incorporation of crop residues influence soil fertility. The study found that crop rotation and nitrogen fertilizers have a significant impact on soil properties. Crop rotations such as “velvet beans‐maize” and “soybeans‐maize” increased soil fertility by 10%–15% compared to crop rotations of “vetch‐maize” and maize monocultures. Nitrogen fertilizers increased the total nitrogen content in the soil by 5%–10% in both years. Crop residues also positively affected soil properties, increasing pH and total nitrogen by 1%–5%. The study demonstrates that crop rotation, nitrogen fertilizers, and crop residues can be effective management methods for improving soil fertility and reducing the risk of nitrate leaching.

No-tillage farming enhances widespread nitrate leaching in the US Midwest

Abstract Conservation tillage has been promoted as an effective practice to preserve soil health and enhance agroecosystem services. Changes in tillage intensity have a profound impact on soil nitrogen cycling, yet their influence on nitrate losses at large spatiotemporal scales remains uncertain. This study examined the effects of tillage intensity on soil nitrate losses in the US Midwest from 1979–2018 using field data synthesis and process-based agroecosystem modeling approaches. Our results revealed that no-tillage (NT) or reduced tillage intensity (RTI) decreased nitrate runoff but increased nitrate leaching compared to conventional tillage. These trade-offs were largely caused by altered water fluxes, which elevated total nitrate losses. The structural equation model suggested that precipitation had more pronounced effects on nitrate leaching and runoff than soil properties (i.e. texture, pH, and bulk density). Reduction in nitrate runoff under NT or RTI was negatively correlated with precipitation, and the increased nitrate leaching was positively associated with soil bulk density. We further explored the combined effects of NT or RTI and winter cover crops and found that incorporating winter cover crops into NT systems effectively reduced nitrate runoff but did not significantly affect nitrate leaching. Our findings underscore the precautions of implementing NT or RTI to promote sustainable agriculture under changing climate conditions. This study provides valuable insights into the complex relationship between tillage intensity and nitrate loss pathways, contributing to informed decision-making in climate-smart agriculture.

Prediction of Soil Temperature in Wheat Field Using Machine Learning Models

ABSTRACT Wheat is a very vital cereal crop in the development of a nation’s economy and agricultural sector. A crucial element that profoundly affects the growth and productivity of wheat is the soil temperature. As an insulating layer, straw mulch controls the soil temperature. Field measurement of the soil temperature is time-consuming and costly; therefore, the present study investigates the applicability of random forest (RF), support vector machine (SVM) and generalized regression neural network (GRNN) models for estimating soil temperature in wheat fields covered with straw mulch using meteorological, soil cover and agronomical parameters. A field study was conducted on the wheat cultivar with two soil cover treatments for measuring the soil temperature at three depths (5, 50 and 80 cm). Soil plant analysis development value; soil cover and depth; daily meteorological data such as average air temperature, average relative humidity, sunshine hours and vapor pressure were used as inputs for machine learning models in training and testing. Statistical performance indicators showed applicability of three models with a root mean square error (RMSE) ranging from 0.245–0.595°C, 0.867–0.886°C and 0.557–0.812°C, Nash-Sutcliffe efficiency (NSE) ranging from 0.917–0.987, 0.823–0.836 and 0.804–0.935 and Lin’s concordance correlation coefficient (CCC) ranging from 0.949–0.991, 0.887–0.897 and 0.881–0.957 for the RF, SVM and GRNN, respectively. Results indicated better performance of the RF model for predicting the soil temperature at different depths in the case of both crop and soil cover conditions. Also, the uncertainty analysis indicated the better performance of RF with R-factor and P-factor value of 0.40 and 0.84, respectively.

Multi-year soil response to conservation management in the Virginia Coastal Plain

In the coastal plain region of the United States, conservation agriculture practices are being implemented to improve soil health, minimize environmental impacts, and improve farm profitability. Common practices include cover cropping and conservation tillage using strip tillage, minimal tillage, or no tillage. However, the soil response to specific combinations of conservation tillage and cover crop rotations remains poorly quantified. The objective of this research was to evaluate changes in soil properties from different combinations of conservation management. Four tillage systems – conventional, strip, minimal, and no tillage – and three winter cover rotations – fallow, winter cash crop, and high-biomass cover crop – were tested in a split-plot design. Bulk density, depth to a root-restrictive layer, soil carbon concentration, soil carbon stock, field-saturated hydraulic conductivity, and yield were measured over a seven-year period. Bulk density and field-saturated hydraulic conductivity showed greater temporal variation in the strip tillage and conventional tillage practices. Depth to root-restrictive layer was consistently highest in the strip and minimal tillage treatments, which both included implements designed to alleviate subsoil compaction. Treatments that combined conservation tillage with a winter cover (i.e., cash crops or high-biomass cover crops) had greater increases in soil carbon concentrations and carbon stock. Summer cash crop yield was significantly increased following the high-biomass cover crop treatment in 2 out of the 7 years. Altogether, soil carbon showed a more consistent response to conservation management than the other soil properties, which tended to show greater variability based on the time since disturbance (e.g., tillage). Conservation management practices therefore need to be consistently applied for multiple years in order to improve soil properties such as bulk density and saturated hydraulic conductivity.

Enhanced root zone soil moisture monitoring using multitemporal remote sensing data and machine learning techniques

Accurate root zone soil moisture (RZSM) estimation using remote sensing (RS) in areas with dense vegetation is essential for real-time field monitoring and precise irrigation scheduling. Traditional methods often face challenges due to the dense crop cover and the complexity of soil and climate interactions. These challenges include the coarse spatial resolution of available soil moisture products, the influence of vegetation and surface roughness, and the difficulty of estimating RZSM from surface data. Aiming to overcome these limitations, two RZSM estimation methods were developed by combining synthetic aperture radar (SAR) data from Sentinel-1 (VV and VH polarizations) and optical and thermal RS data from Landsat-8. These data sources were used in conjunction with various machine learning (ML) models such as M5-pruned (M5P), support vector regression (SVR), extreme gradient boosting (XGBoost), and random forest regression (RFR) to improve the accuracy of soil moisture estimation. In addition to RS data, soil physical and hydraulic properties, meteorological variables, and topographical parameters were selected as inputs to the ML models for estimating the RZSM of sugarcane crops in Khuzestan, Iran. This study identified the temperature vegetation dryness index (TVDI) as a critical parameter for estimating RZSM in combination with the Sentinel-1 SAR data under high vegetation conditions. In both methods, the RFR algorithm outperformed, with similar performance, the XGBoost, SVR, and M5P algorithms in estimating soil surface moisture (R2 = 0.89, RMSE = 0.04 cm3cm−3). However, the accuracy of the RFR algorithm decreased with increasing depth for both the optical-thermal and combined SAR and optical-thermal RS data. This decrease was more pronounced in the combined approach, particularly for the root zone, where the RMSE reached approximately 0.073 cm3cm−3. Accordingly, the key findings demonstrated that the optical-thermal RS data outperformed the SAR RS data for retrieving RZSM in high-vegetated areas. However, combining TVDI with SAR data is a substantial improvement that opens a new path in radar-based RZSM estimation methods under high vegetation conditions.

Residues of Symbiont Cover Crops Improving Corn Growth and Soil-Dependent Health Parameters

Cover crops have emerged as a crucial tool in promoting sustainable agricultural practices, particularly in improving soil quality and soil–plant health. This study investigates the impact of single cover crop plants each with varying fungal and/or bacterial symbiosis capacities in a pot experiment. The growth of non-symbiont Ethiopian mustard (Brassica carinata), the associative bacterium symbiont black oat (Avena strigosa) and the double (fungus–bacterium) endosymbiont broad bean (Vicia faba) was studied on three distinct soil types, namely a less-fertile sandy soil (Arenosol), an average value of loam soil (Luvisol) and a more productive chernozem soil (Chernozem). Beside the biomass production, nitrogen content and frequency of AM fungi symbiosis (MYCO%) of cover crops, the main soil health characteristics of electrical conductivity (EC), labile carbon (POXC) and fluorescein diacetate enzyme activity (FDA) were assessed and evaluated by detailed statistical analysis. Among the used soil types, the greatest biomass production was found on Chernozem soil with the relatively highest soil organic matter (2.81%) content and productivity. Double symbiotic activity, assessed by soil nitrogen content and mycorrhiza frequency (MYCO%), were significantly improved on the lowest-quality Arenosols (SOM 1.16%). In that slightly humous sandy soil, MYCO% was enhanced by 45%, indicating that symbiosis was crucial for plant growth in the less-fertile soil investigated. After the initial cover crop phase, the accumulated biomass was incorporated into the Luvisol (SOM 1.64%) soil, followed by the cultivation of corn (Zea mays, DK 3972) as the main crop. The results indicate that incorporating cover crop residues enhanced labile carbon (POXC) by 20% and significantly increased the FDA microbial activity in the soil, which positively correlated with the nutrient availability and growth of the maize crop. This study emphasizes the importance of selecting suitable cover crops based on their symbiotic characteristics to improve soil quality and enhance soil–plant health in sustainable agricultural systems.

394 Cover crops for efficient grazing systems

Abstract Grazing of cool-season cover crops provides a sustainable solution for extending the grazing season while potentially reducing the environmental impact of conventional row-crop farming practices. The primary objective of this study was to evaluate how different mixtures of cover crops affect stocker performance when grazed. The study was conducted across 18 paddocks that were sown with grass [‘Coker’ oat (Avena sativa)], grass + legume [‘Dixie’ crimson clover (Trifolium incarnatum)], or grass + legume + brassica [‘Turnip’ brassica (Brassica rapa subsp.; rapa)] at the Wiregrass Research and Extension Center in Headland, AL. These paddocks were randomly assigned to either grazed or un-grazed conditions (n = 3). In this study, yearling beef steers with an average body weight (BW) of 266 ± 44 kg were grazed in paddocks using the put and take method to maintain a forage allowance of 1 kg dry matter per kilogram of BW. Forage samples were collected biweekly to analyze biomass, botanical composition, and forage nutritive value. Grazing occurred from January 17 to March 22, 2023 (65 d). Steer BW were recorded at the beginning and end of the grazing season to calculate average daily gain. The data were subjected to analysis as a two-way ANOVA using Glimmix in SAS 9.4 (SAS Institute, Cary, NC), harvest date was considered a repeated measure. No treatment × grazing interaction was observed on forage yield performance [average (AVG) forage yield kg DM/ha; P = 0.460]. In addition, no difference was observed among the different cover crop mixtures (AVG forage yield kg DM/ha; P = 0.670). Grazed paddocks had a greater crude protein when compared with ungrazed paddocks (Grazed vs. Ungrazed %; P = 0. 017). However, there was no effect of cover crop mixture on crude protein (CP) concentration (AVG CP %; P = 0.670 for treatment effect). These results indicate that cool-season annual cover crops can provide sufficient forage yield and quality to support sufficient animal gains, even during the relatively short grazing season. Incorporating cover crops not only improves agricultural sustainability but can also enhance the resilience and long-term health of the agroecosystem.

451 Establishing producer research sites for the development of beef and bison climate-smart agriculture

Abstract Greenhouse gas (GHG) emissions and livestock production are topics that are increasingly intertwined. While livestock production is frequently presented as harmful to the environment, this perception fails to consider the carbon sequestration that takes place in livestock grazing systems and the role that grazing ruminants have in maintaining healthy grassland ecosystems. Grazing lands, which are often unsuited to row crop agriculture, are estimated to account for 25% of the global soil sequestration potential for soil carbon storage. Grazing livestock producers are often overlooked in the GHG reduction conversation, despite over 70% of beef GHG emissions being attributed to the cow-calf sector, which is primarily grazing. Furthermore, there is a relative lack of data surrounding the implementation of climate-smart agriculture practices on grazing operations and a lack of cost-effective methods to measure carbon/GHG sinks and sources on these landscapes. The potential climate benefits are considerable, with nearly 940 million acres of rangelands in the U.S. supporting forage-based livestock production. South Dakota State University recently received funding to support a large-scale climate-smart project focused on grazing beef and bison. For this project, we are utilizing the Cottonwood Field Station that has over 80 yr of historical grazing data, along with six grazing beef and bison ranching operations in the Northern Great Plains. The work on these ranches will focus on measuring and monitoring the impacts of climate-smart NRCS land practices, including cover crops, improved pasture and range seedings, prescribed grazing, and prescribed burning. A significant focus will be extensive, annual soil sampling across these operations to continuously monitor changes in soil organic carbon, bulk density, texture, pH, and soil microbiome community profiles. Each operation will have GreenFeed methane pasture units deployed for 5 yr to monitor changes in beef cattle and bison methane emissions in response to climate-smart practice adoption. We are also assessing biodiversity pre and post climate-smart practice adoption, as biodiversity improvements may be one of the most overlooked and yet most important responses to climate-smart land practice implementation. Over the duration of this project, a large-scale, comprehensive data collection will be achieved and used to refine GHG and carbon sequestration estimates associated with range livestock systems. Data resulting from this project will be used to inform research protocols and prediction models, fill knowledge gaps, and shape science-based discussions and marketing strategies for climate-smart agricultural commodities.

Soybean performance under the biomass of Quênia guinea grass cover crops after intercropping with maize

Soil cover biomass in integrated systems can improve agronomic characteristics and impact in soybean productivity. Thus, the objective is to evaluate the desiccation efficiency, biomass production, nutrient accumulation, and soybean productivity in Quênia guinea grass (Panicum maximum cv. BRS Quênia) biomass after with an intercropped with maize in different forms of seeding, in compare the conventional soybean. The experimental design was a randomized block with four replicates. The treatments consisted of cover crop biomass: maize monoculture; Quênia guinea grass monoculture; maize intercropped with Quênia guinea grass within rows; maize intercropped with Quênia guinea grass between rows and an additional soybean treatment without cover biomass. The results showed that the Quênia guinea grass in the different cropping systems presented high desiccation efficiency, showing potential as a cover plant in integrated systems. The intercropping system of maize with Quênia guinea grass between rows is more recommended than seeding in the same rows as maize, because it promotes greater biomass production and nutrient cycling, reflecting in higher soybean productivity. The integrated production systems is a promising and efficient technology for production systems compared to the system of monoculture maize and soybeans without soil cover biomass, which ensures greater sustainability of agricultural systems.

Disentangling the effects of applying pig slurry or its digestate to winter wheat or a catch crop on dissolved C fluxes

The anaerobic digestion industry, which is still developing, generates biogas from organic waste products. A co-product of this process, digestate, is increasingly produced and can be recycled on agricultural land as an alternative to mineral fertilizers. Biogas digestate is a recent product whose chemical composition differs from that of its source material, and additional data still need to be acquired on its effects on dissolved carbon fluxes. The objectives of this study were to assess (i) the effects of applying biogas digestate on dissolved organic carbon (DOC) and dissolved inorganic carbon (DIC) fluxes with different winter crops, (ii) the dynamics of DOC and DIC concentrations during the drainage season, and (iii) the annual dynamics of DOC and DIC fluxes along the soil profile. The study examined effects of applying biogas digestate, pig slurry, or a mineral fertilizer to winter wheat and two catch crops (mustard and a multispecies crop) on DOC and DIC fluxes in the soil. Lysimeters at 40 cm (topsoil) and 90 cm (subsoil) depths were monitored from 2014 to 2023, from November to March (i.e., 9 winter drainage seasons). During the drainage season, the DOC concentration was highest with digestate, and its timing depended on development of the cover crop: from the beginning of the drainage season for mustard and the multispecies crop and around February for wheat. Applying digestate increased the topsoil DOC fluxes (mean of 35.7 ± 13.7 kg.ha−1 with digestate vs. 21.0 ± 6.7 kg.ha−1 with the other treatments), particularly under mustard. Topsoil DIC fluxes were highest with pig slurry due to higher mineralization than that with digestate (mean of 59.1 ± 22.8 kg.ha−1 with pig slurry vs. 46.2 ± 16.3 kg.ha−1 with the other treatments). In the subsoil, DOC fluxes were low (6.2 ± 4.1 kg.ha−1) and DIC fluxes were high (80.0 ± 45.7 kg.ha−1), with no difference among treatments.

Temporal analysis of water chemistry and smallmouth bass (Micropterus dolomieu) health at two sites with divergent land use in the Susquehanna River watershed, Pennsylvania, USA

Monitoring wild fish health and exposure effects in impacted rivers and streams with differing land use has become a valuable research tool. Smallmouth bass (Micropterus dolomieu) are a sensitive, indicator species that exhibit signs of immunosuppression and endocrine disruption in response to water quality changes and contaminant exposure. To determine the impact of agriculture and development on smallmouth bass health, two sites (a developed/agriculture site and a forested site) in the Susquehanna River watershed, Pennsylvania were selected where bass and water chemistry were sampled from 2015 to 2019. Smallmouth bass were sampled for histopathology to assess parasite and macrophage aggregate density in the liver and spleen, condition factor (Ktl), hepatic gene transcript abundance, hepatosomatic index (HSI), and a health assessment index (HAI). Land use at the developed/agriculture site included greater pesticide application rates and phytoestrogen crop cover and more detections and higher concentrations of pesticides, wastewater-associated contaminants, hormones, phytoestrogens, and mycotoxins than at the forested site. Additionally, at the developed/agriculture site, indicators of molecular changes, including oxidative stress, immune/inflammation, and lipid metabolism-related hepatic gene transcripts, were associated with more contaminants and land use variables. At both sites, there were multiple associations of contaminants with liver and/or spleen macrophage aggregate density, indicating that changes at the molecular level seemed to be a better indicator of exposures unique to each site. The findings illustrate the importance of timing for land management practices, the complex mixtures aquatic animals are exposed to, and the temporal changes in contaminant concentration. Agricultural practices that affect hepatic gene transcripts associated with immune function and disease resistance were demonstrated which could negatively affect smallmouth bass populations.

The LTAR Cropland Common Experiment at Upper Mississippi River Basin-St. Paul.

The Soil and Water Management Research Unit of the USDA-Agricultural Research Service is located in St. Paul, MN, and conducts long-term research at the University of Minnesota Research and Outreach Center located at Rosemount, MN. As part of USDA's Long-Term Agroecosystem Research (LTAR) network, the croplands common experiment (CCE) at this location is focused on integration of a kura clover (Trifolium ambiguum M. Bieb.) living mulch (KCLM) system into the prevailing 2-year rotation of corn (Zea mays L.) and soybean (Glycine max L.) that is typical of the midwestern Corn Belt. The LTAR-CCE conducted at Rosemount, MN, aims to compare the long-term environmental and agronomic performance of KCLM while identifying challenges and developing management strategies for this alternative practice. The use of a living mulch for this region is advantageous because, once established, it does not require additional time for fall field operations typically associated with winter cover crops. Results from LTAR-CCE studies at this site show that KCLM results in a substantial increase in soil field-saturated hydraulic conductivity and decreases in leaching of nitrate-nitrogen (NO3 --N). Disadvantages of the KCLM system include potential for increased emissions of nitrous oxide (N2O) and reduced crop yields, particularly during drought. Also, the optimal approach for crop row establishment in the spring remains uncertain. Ongoing LTAR-CCE research with KCLM aims to better understand and quantify both benefits and risks across conditions of interannual weather variability and changing climate to develop guidance for suitable adoption and management of this alternative practice.

Cover crop grazing length impacts on soil health and crop productivity in US Coastal Plain soils

AbstractIntroducing integrated crop‐livestock systems into row crop production promotes income diversification and potential soil health benefits through cover crop grazing on degraded soils of the southeastern United States, but effects of these practices on crop yields and soil health in Coastal Plain soils are not well established. A 4‐year study was performed to evaluate the effects of grazing a multi‐species winter cover crop on soil health and crop yields under mid‐February, mid‐March, and mid‐April cattle removal dates and a non‐grazed control within an annual cotton (Gossypium hirsutum L.) and peanut crop rotation (Arachis hypogaea L.). Chemical soil health indicators (soil organic carbon and permanganate oxidizable carbon), physical soil health indicators (water‐stable aggregates and penetration resistance), biological soil health indicators (microbial biomass carbon, soil respiration, and arbuscular mycorrhizal fungi colonization), crop yield, and cover crop biomass were evaluated. Cover crop biomass at termination was reduced by 3660, 5250, and 5610 kg ha−1 for the mid‐February, mid‐March, and mid‐April cattle removal treatments compared to the non‐grazed control. No grazing treatment effects were observed for biological soil properties. Soil organic carbon was higher in the non‐grazed treatment than the mid‐April grazing treatment across 0‐ to 30‐cm depth. Penetration resistance across 0‐ to 50‐cm depth and water‐stable aggregates at the 0‐ to 30‐cm depth were both negatively impacted by increased grazing period lengths. Results from this study suggest that longer cover crop grazing periods have little effect on biological and chemical soil health indicators in the short term but can negatively impact some physical soil health indicators.

Long‐term tillage and cover cropping differentially influenced soil nitrous oxide emissions from cotton cropping system

AbstractClimate‐smart agricultural practices, such as no‐tillage (NT) and cover cropping, have been widely adopted and are anticipated to yield multiple benefits, including soil carbon sequestration, enhancing soil health, and crop yield stability. However, their influence on nitrous oxide (N2O) emissions varies, with the potential of both increasing and decreasing N2O emissions. Increasing N2O emissions under these practices may potentially offset the climate mitigation benefits from increased soil carbon sequestration. We investigated N2O emissions in response to 42 years of long‐term adoption of NT and legume cover crop, under nitrogen (N) rates of 0 and 67 kg N ha−1, in a continuous cotton system in the Southeastern United States. Intensive manual chamber‐based measurements were conducted over two growing seasons (2021–2022 and 2022–2023). Long‐term NT did not significantly affect cumulative N2O emissions during the study period (p > 0.05). Hairy vetch cover crop‐grown plots emitted two to three times more N2O than those without cover crops in 2021–2022, with no significant effect observed in 2022–2023. Cumulative emissions in cover crop plots were greater compared to those in no cover crop plots when fertilized with 67 kg N ha−1 in 2021–2022; however, this trend did not persist in 2022–2023. While interannual variability exists, our results generally suggest that long‐term NT may not increase N2O emissions, hence its adoption could enhance its broader soil health and climate benefits via soil carbon sequestration, whereas managing legume cover crop residues in N‐fertilized systems is critical to mitigate N2O emissions.

Soil Microbial Properties of Durum Grown after Camelina, Carinata, Cover Crops, and Fallow

Novel crop rotation is an important factor influencing the composition of soil microorganisms. However, the effect of introducing oilseed and cover crops (CCs) into monoculture durum rotations on soil microbial communities is not clear in the Northern Great Plains. The objective of this study was to evaluate the effects of 2-year durum (Triticum durum D.) rotations with Ethiopian mustard (Brassica carinata A.) or camelina (Camelina sativa L.) or a 10-species forage/CC mix planted to replace fallow rotations with wheat on soil microorganisms. This study was designed as a randomized complete block with three replications in a no-tillage system. The results showed that total bacterial proportion was significantly higher in durum following fallow and camelina compared to durum following CC and carinata. Total fungal proportion was significantly higher in durum following CC compared to durum following oilseed crops and fallow. The fungal-to-bacterial ratio was significantly higher in durum following CC compared to durum following camelina and fallow. The crop species, soil pH and highly variable rainfall influenced the microbial community dynamics. The abundance of specific microbial groups due to crop-related changes might play a key role in the yield of subsequent crops and soil biological health. This study provides valuable insights into the use of CC mix and oilseeds as an alternative crop for fallow in a wheat–fallow system under dryland farming conditions. Future work is required to elucidate the biological mechanisms and functions of the soil microbial communities in the preceding and subsequent crop relative to soil health and crop productivity.

Cover crop alters rhizosphere sediments to recruit plant growth-promoting microorganisms, enhancing peanut production

Peanuts are typically grown in continuous monoculture in China, leading to continuous cropping obstacles and reduced yields. Cover cropping is emerging as a pivotal strategy for enhancing soil quality and promoting sustainable agriculture. However, the effects of cover crops on the rhizosphere environment, and how they benefit subsequent crops, are not well understood. We hypothesize that planting cover crop ryegrass during the winter fallow period could alter peanut rhizosphere sediments, recruit plant growth-promoting microorganisms, and ultimately enhance peanut production. This study aims to fill this gap by investigating the impact of ryegrass cover cropping on rhizosphere sediments and peanut yield. Rhizosphere soil organic carbon, total nitrogen, pH, and soil enzymes, including sucrase, urease, N-acetyl-β-D-glucosaminidase, and β-glucosidase, were analyzed, along with metabolomics, 16S rRNA, and fungal ITS sequence analyses, under traditional planting management (TP) and long-term cover crop (CC) treatments. The results showed that CC treatment significantly increased rhizosphere pH, enhanced soil organic carbon and total nitrogen levels, and elevated soil enzyme activities compared to TP treatment. Metabolomic analysis revealed that CC treatment upregulated compounds such as D-pinitol, palmitoleic acid, fructose, sorbitol, and sucrose, while downregulated compounds including benzoic acid, dodecanoic acid, and carbamic acid. This alteration in metabolite composition influenced the recruitment and function of the microbial community. Specifically, CC treatment markedly enhanced the abundance of growth-promoting microbes such as Bacillus, Paenibacillus, Pseudomonas, Lysobacter, Bradyrhizobium, and Mortierell etc., which are involved in important functions such as chemoheterotrophy, nitrate reduction, and plant saprotroph. Simultaneously, there was a decrease in pathogenic microorganisms, such as Aspergillus flavus and Fusarium oxysporum. Moreover, CC treatment positively influenced peanut root growth, resulting in longer roots and ultimately increase pod yield by 21.15 % compared to traditional winter fallow practices. These findings underscore the potential of cover cropping with ryegrass to improve rhizosphere microecosystem components, and ultimately enhance peanut productivity, providing valuable insights for sustainable agricultural practices.

Improving dual cover crop mixtures to increase shoot biomass production and weed suppression potential

IntroductionCover crop services depend on biomass production and species composition of the cover crop stand. In this study, we investigated the interactions in shoot biomass of dual cover crop mixtures and their competitiveness to suppress weeds before winter under different growing conditions.MethodsA field experiment was performed on sandy loam soil in Triesdorf, Germany, for two consecutive years. The cover crop species white mustard (Sinapis alba L.), oil radish (Raphanus sativus var. oleiformis L.), phacelia (Phacelia tanacetifolia J.), Egyptian clover (Trifolium alexandrinum L.), common vetch (Vicia sativa L.), field pea (Pisum sativum L.), and field bean (Vicia faba L.) were grown in pure stands or dual mixtures. Cover crops were sown in August, and shoot biomass was harvested at the end of the vegetation period. Cover crop shoot biomass was dried, and the share of each species and the sown test weed (Brassica napus L.) were determined.ResultsThe share of shoot biomass of a cover crop species in dual-species mixtures was closely related to its shoot biomass in its pure stand. In both years, mustard and phacelia showed similar interactions in shoot biomass production when growing with a second species. Regarding competitiveness against weeds, cruciferous species outperformed other cover crop species and could suppress weeds even if they were mixed with a less competitive partner. Weed suppression of mixtures with phacelia depended on the second component in the mixture and was more effective in a dry season. Legume species, especially Egyptian clover and common vetch could not suppress weeds in a pure stand.DiscussionOur results show that species with high weed suppression potential as single stands retain this ability in dual cover crop mixtures, regardless of the suppression potential of the second species that completes the mixture.

How Do Off-Season Cover Crops Affect Soybean Weed Communities?

Weeds compete for environmental resources, leading to reduced soybean yield. In this context, integrated weed management strategies related to cultural control with the use of cover crops are necessary. Our aim was to evaluate weed occurrence in soybean systems with different cover crops. Field studies were conducted at Júlio de Castilhos, Santa Maria, Capão do Leão, Barra do Ribeiro, and Santo Ângelo, Rio Grande do Sul, Brazil. A randomized complete block design with four replications was used. Treatments consisted of black oats (Avena strigosa Schreb.), white oats (Avena sativa L.), rye (Secale cereale L.), hairy vetch (Vicia sativa L.), forage turnip (Raphanus sativus L.), and white clover (Trifolium repens L.) in pure stands or in mixtures. The analyzed variables were relative frequency, density, abundance, and importance value index, similarity index of weeds, dry shoot mass of cover crop, and soybean yield. Cover crops containing white or black oats reduced the relative importance value index of weeds, such as Lollium multiforum, Conyza spp., and Bidens pilosa. Forage turnip, hairy vetch, and white clover showed distinct responses. Black oats and forage turnip did not differ from cover crop mixtures in terms of dry shoot mass and grain yield, being superior to fallow, white clover, and hairy vetch.

Exploring the position of farmers within the European green transition: transformation for whom?

Food systems have been framed as a “wicked problem” due to the complex socio-ecological impacts they foster, ranging from contributing nearly a quarter of anthropogenic greenhouse gas emissions to a myriad of social impacts (e.g., health, food safety, and food security). In the European green transition for food systems, multiple actors are involved. However, farmers play a unique and critical role as agricultural land managers and navigators of social, political, and environmental factors. Using cover cropping and intercropping as examples, we illustrate the complexities arising when decision-making and governance at multiple levels lead to tradeoffs and unexpected consequences at the farm scale. Amid complexity, we propose a conceptual model to address the question: how is an agricultural green transition best fostered? We find that changes are incremental, transformative or both depending on the level of analysis. Additionally, incoherence in agronomic recommendations across academic disciplines and policy agendas creates challenges at the farm scale that trickle up and can thwart sustainable agricultural land use. Although transdisciplinarity and knowledge production with farmers through co-creation are essential for food system transformation and can be part of the solution, it is crucial to examine the nature of change processes and to consider how knowledge and innovation are adopted. By balancing top-down and bottom-up approaches and distributing burden from the farm scale to governance and food systems, a more transformative green transition for European food systems with coherence across multiple agroecological objectives could be achieved.