Management Of Agricultural Areas Research Articles

A novel approach to identify priority areas for optimal nutrient management in mixed land-use watersheds through nutrient budget assessment

Excessive nutrient supply in agricultural regions has led to various environmental issues, thereby requiring concentrated management owing to its persistent upward trend. Nutrient budgets (NBs), a vital agricultural environmental indicator, are employed for nutrient management in agricultural areas, using data surveyed by administrative agencies. However, the spatial extent of nutrient data for nutrient budgeting is limited by administrative boundaries according to the surveying organization, posing challenges in interpreting spatial patterns at the watershed level. In this study, a novel approach was developed to identify priority nutrient management areas by applying hot spot spatial analysis to watershed-level NBs, considering hydrological characteristics. This method was applied to approximately 850 subwatersheds across the Republic of Korea, where land cover characteristics are complex. Reassessing nutrient budgets at the watershed scale, accounting for overlapping administrative boundary areas and crop cultivation ratios, indicated similar levels between the two methods. Hot spot analysis revealed that watersheds with elevated NBs mirrored the spatial patterns of livestock excreta and cropland. The spatial distribution characteristics of watersheds with high nutrient levels in rivers corresponded with the concentration characteristics of industrial and commercial areas. Therefore, applying watershed-level NBs based on land cover ratios that consider nutrient input characteristics in agricultural regions is deemed appropriate for selecting priority nutrient management areas. Collectively, this study presents a method for selecting nutrient management priority areas by simultaneously considering the spatial characteristics of various environmental factors, such as land cover, livestock excreta, river water quality, and land area-based watershed-specific NBs. The proposed approach, considering mixed land cover characteristics, is anticipated to be valuable for selecting priority management areas in watersheds with diverse pollution sources. Future research is needed to explore nutrient budgets within watersheds, the influence of land use on pollution sources, and their correlation with water quality.

Effects of pasture intensification and sugarcane cultivation on non-target species: A realistic evaluation in pesticide-contaminated mesocosms

Conventional soil management in agricultural areas may expose non-target organisms living nearby to several types of contaminants. In this study, the effects of soil management in extensive pasture (EP), intensive pasture (IP), and sugarcane crops (C) were evaluated in a realistic-field-scale study. Thirteen aquatic mesocosms embedded in EP, IP, and C treatments were monitored over 392 days. The recommended management for each of the areas was simulated, such as tillage, fertilizer, pesticides (i.e. 2,4-D, fipronil) and vinasse application, and cattle pasture. To access the potential toxic effects that the different steps of soil management in these areas may cause, the cladoceran Ceriophania silvestrii was used as aquatic bioindicator, the dicot Eruca sativa as phytotoxicity bioindicator in water, and the dipteran Chironomus sancticaroli as sediment bioindicator. Generalized linear mixed models were used to identify differences between the treatments. Low concentrations of 2,4-D (<97 μg L−1) and fipronil (<0.21 μg L−1) in water were able to alter fecundity, female survival, and the intrinsic rate of population increase of C. silvestrii in IP and C treatments. Similarly, the dicot E. sativa had germination, shoot and root growth affected mainly by 2,4-D concentrations in the water. For C. sancticarolli, larval development was affected by the presence of fipronil (<402.6 ng g−1). The acidic pH (below 5) reduced the fecundity and female survival of C. silvestrii and affected the germination and growth of E. sativa. Fecundity and female survival of C. silvestrii decrease in the presence of phosphorus-containing elements. The outcomes of this study may improve our understanding of the consequences of exposure of freshwater biota to complex stressors in an environment that is rapidly and constantly changing.

Soil toxicity in a protected area in Brazil: Cytotoxic, genotoxic, and toxic effects

The Campos de Palmas Wildlife Refuge (CPWR) (Brazil) is a full protection Conservation Unit (CU) formed by private properties, where the use of land and natural resources are allowed sustainably according to the rules of the CU Management Plan. Inadequate practices of land use and occupation within this CU can affect its quality and the organisms that depend on them. Considering the above, the objective of the present study was to biomonitor different land uses and occupations within the CPWR and its surroundings, during the four seasons of a year, using the bioindicators Allium cepa (cytotoxicity and genotoxicity tests) and Eisenia fetida (leakage test). The soil samples were collected in areas of silviculture, agriculture, and native grasslands within the CU and agriculture outside the limits of the CPWR. The use by silviculture (spring) and native grassland (summer) showed cytotoxic effects for A. cepa. The use by agriculture outside the CPWR (spring) showed genotoxic effect and stimulation of mitotic cell division. For the animal bioindicator, the use by agriculture within the CPWR (winter), native grassland (autumn and spring), silviculture (autumn and spring), and agriculture outside the CU (spring) showed a toxic effect. A PCA analysis showed a correlation between the results of toxicity, cytotoxicity, and genotoxicity with the presence of macronutrients and metals in the evaluated soil samples. Possibly influenced by their soil composition characteristics (silviculture and native grassland) or the management of agricultural areas. In addition, samples from the rainy season (spring) showed higher ecotoxicity. These results show that biomonitoring through different organisms is important for evaluating environmental quality and indicate the need for the implementation of preventive measures in the CPWR to avoid the toxic, cytotoxic, and genotoxic effects found. They also ensure the integrity of this CU and the active protection of the environment and biodiversity.

Forestry Bioeconomy Contribution on Socioeconomic Development: Evidence from Greece

Forests are of utmost importance for sustainability because of their ongoing contributions to biodiversity protection, fertility management in agricultural areas, and the well-being of people. However, few studies have focused on the extent to which the bioeconomy of forests impacts a country’s social and economic development. This study aimed to examine the bioeconomy contribution of forestry to social and economic development using Greece as a case study. Data was collected from 312 professionals in the forestry and finance sectors of Greece using a survey questionnaire. Forests are associated with direct and indirect contributions that impact human livelihood and contribute toward a country’s economic development. However, the role of forestry in development is affected by policy-related and human-made challenges. The difficulties are primarily caused by shifts in how economic activity is distributed from the agricultural to the industrial to the service sectors, different government policies intended to increase forest cover, and in other instances, as a result of the role of global capital and trade. The forestry contributions to global commerce, national economies, employment, and family incomes remain consistent throughout all these patterns of loss, stabilization, and recovery. It was established that the bioeconomy can increase the benefits of forests by further exploiting forest wealth (biomass, resins) with the direct and indirect benefits for forest-related societies and local economies. In addition, the management and exploitation of forests by adopting bioeconomy practices, allows the attainment of important skills, knowledge, and new fields of entrepreneurship.

Evaluating nitrate transport and accumulation in the deep vadose zone of the intensive agricultural region, North China Plain

Evaluation of the nitrate transport process in the deep vadose zone (DVZ) is important for groundwater quality management, especially in intensive agricultural regions, such as the North China Plain (NCP). The NCP produces ~20% of the total food grain in China, owing to timely groundwater irrigation and excessive chemical N fertilizer applications, and faces severe groundwater environmental degradation. This study evaluated the potential impacts of intensive agriculture on groundwater quality by investigating nitrate accumulation and transport in the DVZ of wheat-maize double-cropping field based on sediment sampling (maximum depth of 45.2 m) over three sub-regions of the NCP. The results showed that legacy nitrate‑nitrogen (NO3−-N) accumulated in the DVZ ranged from 118.5 to 6302.8 kg N ha−1 across the NCP; it increased with depth at an average rate of ~157 kg ha−1 m−1. Nitrate transport and accumulation in the DVZ were spatially varied and mainly controlled by the DVZ sediment textures, in addition to water and nitrogen inputs from the ground surface. Coarse sediments retained lower soil water content, resulting in less nitrogen storage; however, they provided greater nitrate transport velocity. Higher transport velocities observed in the alluvial-proluvial fan allowed chemical N fertilizer to reach the water table. However, in other regions, nitrate transport velocities were lower than the water table decline rates, implying that groundwater quality may not have been impaired by chemical N fertilizer. Furthermore, a reductive environment was identified in some areas with fine sediments, indicating a favorable environment for denitrification in the DVZ. The findings of the current study could provide an important foundation for groundwater quality management in agricultural areas, such as the NCP and similar regions.

Life cycle assessment of digestate post-treatment and utilization

Three digestate utilization scenarios for bio-fertilizer production are evaluated with life cycle assessment. The aim is to determine the environmental performance of the digestate post-treatment with the goal to decrease the loss of nitrogen and phosphorus, support circular nutrient management, and increase the substitution of mineral fertilizers. The functional unit (FU) of the study is the utilization of 1 kg dry matter raw digestate, in three scenario designs. Scenario 1 (S1) describes a system where the raw digestate is directly spread on soil. In scenario 2 (S2) the raw digestate is processed by centrifugation with two recovered phases (liquid and solid digestate), which are spread on agricultural soil. In scenario 3 (S3) a more advanced post-treatment system is modelled, where the raw digestate is phase separated with centrifugation followed by drying of the solid digestate and further processing of the liquid digestate with a membrane filtration and a reverse osmosis unit. The studied scenarios show a global warming potential ranging from −0.14 (S3) to −0.36 (S1) kg CO2 eq per FU. The fossil resource depletion per FU was decreased in scenario 1 (−0.053 kg oil eq) and scenario 2 (−0.049 kg oil eq) but increased in scenario 3 (0.002 kg oil eq). The terrestrial acidification potential ranges from 0.09 (S3) to 0.18 (S1) kg SO2 per FU. The digestate post-treatment is a sustainable solution able to tackle the problem of excess nutrients and their management in agricultural areas. It could replace conventional nitrogen removal processes (aerobic biological treatment) by a valorization chain keeping the nutrients in closed loop.

Data-based groundwater quality estimation and uncertainty analysis for irrigation agriculture

Accurate groundwater quality estimation is of great significance for effective irrigation management in agricultural areas. However, due to lack of data, the parameterization of the physical models is restricted for large areas with diverse underlying surface conditions. To obtain effective and convenient estimations of groundwater quality with the most accessible data is urgently needed. In this study, the validity of the data-based models in irrigation water quality index estimation was investigated by only using physical groundwater parameters as inputs. 15 combination scenarios of the physical parameters including temperature, pH, electrical conductivity, and dissolved oxygen were examined by support vector machine (SVM), random forests (RF), artificial neural networks (ANN) and extreme learning machine (ELM) models for total dissolved solids (TDS), potential salinity (PS), and sodium adsorption ratio (SAR) estimation for the Zhangye Basin, northwest China. Performance of the artificial intelligence (AI) models was evaluated according to the coefficient of correlation (R), root mean squared error (RMSE), mean absolute percentage error (MAPE), and Nash-Sutcliffe efficiency (NS). The Monte Carlo (MC) approach was performed to assess the uncertainty of the physical groundwater parameters and the sensitivity of the AI models. The results revealed an input pattern, which emphasized the important role of EC and the improving function of pH, in revealing the nature of data-based irrigation water quality index estimation. Results of the uncertainty analysis also confirmed the prominent superiority and robustness of the SVM, RF and ELM models in producing excellent estimations with only physical parameters as inputs. The developed AI models were valuable in estimating irrigation water quality indexes, thus could help decision makers manage irrigation strategies. By using physical groundwater parameters as input variables, the AI models showed prospects in convenient and cost-effective irrigation water quality index estimating.

Application of Sentinel 2 Satellite Imagery for Sustainable Groundwater Management in Agricultural Areas—Chtouka Aquifer, Morocco

In semi-arid regions that are characterized by large agricultural activities, a high volume of water is needed to cover the water requirements for agricultural production. Due to low precipitation and the associated limited availability of surface water, aquifers often represent the main source of irrigation water in these regions. Especially in coastal aquifers, high groundwater abstraction rates may change the flow dynamics of the aquifer and may lead to saltwater intrusion. In this study, within the framework of German–Moroccan international cooperation, the agricultural areas for the summer period 2019 of the Chtouka coastal aquifer in southern Morocco are classified using optical and multi-spectral Sentinel 2 data. Based on the developed land use maps, the groundwater abstraction for irrigation is then quantified by referring to local farmers’ irrigation practices. Following this approach, the total amount of groundwater abstraction is estimated at 157 million m3 for the summer period 2019 in the Chtouka aquifer.

Insect pest diversity of standing crops and traditional pest management in agricultural areas of Mandakini Valley, Garhwal Himalaya, Uttarakhand, India

AI Publications is an open access peer review international journal to publish the article in the field of Agriculture, Horticulture, Food science, Rural Development, Environment and Health Research, Chemistry, Mathematics,Physics.

Spatial variability of soil properties in red soil and its implications for site-specific fertilizer management

Assessing spatial variability and mapping of soil properties constitute important prerequisites for soil and crop management in agricultural areas. To explore the relationship between soil spatial variability and land management, 256 samples were randomly collected at two depths (surface layer 0–20 cm and subsurface layer 20–40 cm) under different land use types and soil parent materials in Yujiang County, Jiangxi Province, a red soil region of China. The pH, soil organic matter (SOM), total nitrogen (TN), cation exchange capacity (CEC), and base saturation (BS) of the soil samples were examined and mapped. The results indicated that soils in Yujiang were acidified, with an average pH of 4.87 (4.03–6.46) in the surface layer and 4.99 (4.03–6.24) in the subsurface layer. SOM and TN were significantly higher in the surface layer (27.6 and 1.50 g kg−1, respectively) than in the subsurface layer (12.1 and 0.70 g kg−1, respectively), while both CEC and BS were low (9.0 and 8.0 cmol kg−1, 29 and 38% for surface and subsurface layers, respectively). Paddy soil had higher pH (mean 4.99) than upland and forest soils, while soil derived from river alluvial deposits (RAD) had higher pH (mean 5.05) than the other three parent materials in both layers. Geostatistical analysis revealed that the best fit models were exponential for pH and TN, and spherical for BS in both layers, while spherical and Gaussian were the best fitted for SOM and CEC in the surface and subsurface layers. Spatial dependency varied from weak to strong for the different soil properties in both soil layers. The maps produced by selecting the best predictive variables showed that SOM, TN, and CEC had moderate levels in most parts of the study area. This study highlights the importance of site-specific agricultural management and suggests guidelines for appropriate land management decisions.

SHui, an EU-Chinese cooperative project to optimize soil and water management in agricultural areas in the XXI century

This article outlines the major scientific objectives of the SHui project that seeks to optimize soil and water use in agricultural systems in the EU and China, by considering major current scientific challenges in this area. SHui (for Soil Hydrology research platform underpinning innovation to manage water scarcity in European and Chinese cropping systems) is large cooperative project that aims to provide significant advances through transdisciplinary research at multiple scales (plot, field, catchment and region). This paper explains our research platform of long-term experiments established at plot scale, approaches taken to integrate crop and hydrological models at field scale; coupled crop models and satellite-based observations at regional scales; decision support systems for specific farming situations; and the integration of these technologies to provide policy recommendations through socio-economic analysis of the impact of soil and water saving technologies. It also outlines the training of stakeholders to develop a basic common curriculum despite the subject being distributed across different disciplines and professions. As such, this article provides a review of major challenges for improving soil and water use in EU and China as well as information about the potential to access information made available by SHui, and to allow others to engage with the project.

Diverging landscape impacts on macronutrient status despite overlapping diets in managed (Apis mellifera) and native (Melissodes desponsa) bees.

Declining pollinator populations worldwide are attributed to multiple stressors, including the loss of quality forage. Habitat management in agricultural areas often targets honey bees (Apis mellifera L.) specifically, with the assumption that native bees will benefit from an 'umbrella species' strategy. We tested this theory using a conservation physiology approach to compare the effects of landscape composition and floral dietary composition on the physiological status of honey bees and Melissodes desponsa in eastern South Dakota, USA. The total glycogen, lipid and protein concentrations were quantified from field collected bees. Next-generation sequencing of the trnL chloroplast gene from bee guts was used to evaluate dietary composition. The effects of landscape and dietary composition on macronutrient concentrations were compared between bee species. As the mean land-use patch area increased, honey bee glycogen levels increased, though M. desponsa experienced a decrease in glycogen. Protein levels decreased in honey bees as the largest patch index, a measure of single patch dominance, increased versus M. desponsa. Lipids in both species were unaffected by the measured landscape variables. Dietary analysis revealed that honey bees foraged preferentially on weedy non-native plant species, while M. desponsa sought out native and rarer species, in addition to utilizing non-native plants. Both species foraged on Asteraceae, Oleaceae and Fabaceae, specifically Melilotus sp. and Medicago sp. Dietary composition was not predictive of the macronutrients measured for either species. Together, these data highlight the management importance of including patch area in conservation recommendations, as bee species may have divergent physiological responses to landscape characteristics. While solitary bees may forage on weedy introduced plants in agricultural areas, robust strategies should also reincorporate native plant species, though they may not be preferred by honey bees, to maximize overall health and diversity of pollinator communities.

Available Agricultural Area by Utilization Categories and Ownership Structure of Holdings in the Republic of Serbia

The subject of research in this paper is the analysis and presentation of data on agricultural holdings, the structure of available and utilized area. The data and calculated indicators represent a comprehensive overview of the structural characteristics of national agriculture, but they are also an internationally comparable database, based on key features of agriculture. The main goal of this paper is to determine and explain more comprehensively and in detail by using appropriate methods, and based on available data, the condition of utilized agricultural area (hereinafter: UAA) and its quantitative and qualitative characteristics by utilization categories and manner of its use; types of agricultural holdings and statistical regions and lower statistical units of data grouping. Implementation of such a defined basic research goal indicates necessity of more detailed and continuous study of the causes that led to the reduction of available agricultural area and especially its better and more important production categories of utilization and measures and activities to be taken to eliminate or reduce the causes of inadequate management of agricultural area in the coming period. The importance of this research arises from the fact that the results on utilized agricultural area can be used to adopt appropriate measures and undertake certain activities in land and overall agricultural and rural policy related to sustainable utilization, arrangement and protection of agricultural land and more balanced integrated development of rural areas, as well as to find better solutions in the field of utilization, ownership sector and conditions of agricultural area management.

Responses of Phyllostomid Bats to Traditional Agriculture in Neotropical Montane Forests of Southern Mexico.

Bat communities' responses to land use change in neotropical montane forests have scarcely been studied. We hypothesized that, like in lowland forests, a montane agricultural area will have a lower species richness, abundance, diversity and species composition of understory phyllostomid bats than a native forest (montane cloud forest and pine-oak forest). Monthly surveys over the course of a year gave an overall low species richness and abundance (167 captures corresponding to nine species). We found a slight loss of species richness in agricultural areas with respect to the montane cloud forest (one species) and pine-oak forest (two species). However, differences in abundance were noteworthy: 45% and 73% fewer captures in agricultural areas than in the montane cloud forest and pine-oak forest, respectively. Species diversity was higher in the montane cloud forest than the pine-oak forest, but the diversity of agricultural areas did not differ between the types. Species and guild compositions did not differ between crops and forests. At least for the understory phyllostomid bats, and at the spatial scale studied, traditional management of agricultural areas in the study area and the surrounding matrix could explain the similarity in species richness, composition, and diversity between the agricultural area and native montane forests; however, other indicator groups should be evaluated to understand the effects of habitat loss on montane forests.

Integrated Hydro-Economic Modeling for Sustainable Water Resources Management in Data-Scarce Areas: The Case of Lake Karla Watershed in Greece

Hydro-economic models can serve as valuable tools to improve the understanding of system details, as well as to support decision-making and water resources management. However, hydro-economic models are not practically implemented as intended and are mainly used in academic settings due to their complexity and data requirements. This study presents a holistic hydro-economic framework for sustainable water resources management, in a simple and understandable way for policy-makers. It is examined under various management, climate and pricing scenarios. The proposed framework is based on: (a) the modeling of water balance and (b) the use of various hydro-economic outputs (e.g., irrigation water value, farmers’ utility, efficiency indexes, direct costs, etc.). The proposed methodology can be applied to data-scarce areas, such as the Lake Karla watershed, Greece. Lake Karla watershed is a typical rural Mediterranean area. The results are encouraging on hydro-economic modeling with limited data, indicating that the establishment of a new management approach could be very beneficial in terms of water use efficiency. Hence, this research can provide an appropriate and suitable approach for facilitating water management in agricultural areas and for implementing the European Framework Directive 2000/60/EC.

Uso de FAO-56 y cintilómetro para estimar la evapotranspiración de sorgo (Sorghum bicolor L.) y sus componentes: evaporación del suelo y transpiración de la planta

Estimating evapotranspiration (ETc) is essential for water planning and management in agricultural areas, particularly in arid and semi-arid regions; ETc partitioning into soil evaporation (E) and plant transpiration (T) would allow the use of more eff icient water management strategies. The aims of the present study were to estimate daily evapotranspiration of sorghum and its components, using the FAO-56 method with the dual crop coeff icient (dual Kc) approach and scintillometer method, and to determine the single crop coeff icient (Kc) and basal crop coeff icient (Kcb) values for different development seasons. Results have shown that using the dual Kc approach allows reasonable simulation of ETc in comparison to values estimated using the scintillometer method. ETc estimated with both methods was 413.8 and 406.3 mm, respectively, resulting in a 1.8% overestimation for FAO-56. Root mean square error (RMSE) was 0.584 mm d-1 and Willmott’s agreement coeff icient (d) was 0.91. Evaporation estimated with FAO-56 was 17.1% of ETc, while with the scintillometer it was 21.6% of ETc. The RMSE of the estimated E values was 0.397 mm d-1 and d = 0.94, while, when comparing T, calculated RMSE was 0.371 mm d-1 and d = 0.98. Kc values estimated with the FAO-56 method were 0.68, 1.06 and 0.4 for initial, middle and end season of the crop, while for the scintillometer, values were 0.75, 0.94 and 0.41, respectively.

Geographical Relationship between Ungulates, Human Pressure and Territory

Despite the fact that at the global level, half the planet’s wildlife population has declined since 1970, this trend is not homogeneous across species and areas. Indeed, focusing on the ungulates, their increasing population and density has become worrisome in several rural areas. Favoured by economic and social changes often related to human activities, ungulates have conquered areas where coexistence with humans is difficult to maintain as a result of the damage that ungulates cause to agricultural activities and forests. This work aims to analyse the relationship between the number of ungulates and the characteristics of a specific area they inhabit. Applying a Geographically Weighted Regression analysis (GWR), we analysed and tested the spatial non-stationarity of the relationship between ungulates and human activities. Mugello, an area in central Italy, was selected for this study. This area was chosen due to the presence of a high number of ungulates that interact in different territorial scenarios, including urban agglomerations located in the flat zone, agricultural areas in the central-northern part and forested areas in the northern part of Mugello. This article looks at the way the number of ungulates is directly related to human activities in a specific territory. This contributes to the literature by providing useful information to stakeholders for future planning and wildlife management in agricultural areas within the limits of sustainability. Moreover, the social and economic implications are significant, especially considering such agricultural areas are at risk of being damaged by the presence of ungulates. The result of the analysis has validated the use of GWR, highlighting the relationship of selected variables and the number of ungulates.

Crop Classification in a Heterogeneous Arable Landscape Using Uncalibrated UAV Data

Land cover maps are indispensable for decision making, monitoring, and management in agricultural areas, but they are often only available after harvesting. To obtain a timely crop map of a small-scale arable landscape in the Swiss Plateau, we acquired uncalibrated, very high-resolution data, with a spatial resolution of 0.05 m and four spectral bands, using a consumer-grade camera on an unmanned aerial vehicle (UAV) in June 2015. We resampled the data to different spatial and spectral resolutions, and evaluated the method using textural features (first order statistics and mathematical morphology), a random forest classifier for best performance, as well as number and size of the structuring elements. Our main findings suggest the overall best performing data consisting of a spatial resolution of 0.5 m, three spectral bands (RGB—red, green, and blue), and five different sizes of the structuring elements. The overall accuracy (OA) for the full set of crop classes based on a pixel-based classification is 66.7%. In case of a merged set of crops, the OA increases by ~7% (74.0%). For an object-based classification based on individual field parcels, the OA increases by ~20% (OA of 86.3% for the full set of crop classes, and 94.6% for the merged set, respectively). We conclude the use of UAV to be most relevant at 0.5 m spatial resolution in heterogeneous arable landscapes when used for crop classification.

Spiders (Arachnida: Araneae) in Agricultural Land Use Systems in Subtropical Environments

ABSTRACT Changes in land use management in agricultural areas can affect the biodiversity of spider families. This study aimed to evaluate spider diversity in different land use systems with capture by two sampling methods, and to identify soil properties that can modulate the occurrence of spiders. Five land use systems, representative of traditional agricultural areas, were evaluated in the west of Santa Catarina, Brazil, to establish a scale of land use intensity: native forest, eucalyptus reforestation areas, pastures, crop-livestock integration [...]

What is the potential of cropland albedo management in the fight against global warming? A case study based on the use of cover crops

Land cover management in agricultural areas is a powerful tool that could play a role in the mitigation of climate change and the counterbalance of global warming. First, we attempted to quantify the radiative forcing that would increase the surface albedo of croplands in Europe following the inclusion of cover crops during the fallow period. This is possible since the albedo of bare soil in many areas of Europe is lower than the albedo of vegetation. By using satellite data, we demonstrated that the introduction of cover crops into the crop rotation during the fallow period would increase the albedo over 4.17% of Europe’s surface. According to our study, the effect resulting from this increase in the albedo of the croplands would be equivalent to a mitigation of 3.16 MtCO2-eq.year−1 over a 100 year time horizon. This is equivalent to a mitigation potential per surface unit (m2) of introduced cover crop over Europe of 15.91 gCO2-eq.year−1.m−2. This value, obtained at the European scale, is consistent with previous estimates. We show that this mitigation potential could be increased by 27% if the cover crop is maintained for a longer period than 3 months and reduced by 28% in the case of no irrigation. In the second part of this work, based on recent studies estimating the impact of cover crops on soil carbon sequestration and the use of fertilizer, we added the albedo effect to those estimates, and we argued that, by considering areas favourable to their introduction, cover crops in Europe could mitigate human-induced agricultural greenhouse gas emissions by up to 7% per year, using 2011 as a reference. The impact of the albedo change per year would be between 10% and 13% of this total impact. The countries showing the greatest mitigation potentials are France, Bulgaria, Romania, and Germany.