More than a meat- or synthetic nitrogen fertiliser-substitute: a review of legume phytochemicals as drivers of ‘One Health’ via their influence on the functional diversity of soil- and gut-microbes

Frontiers in Plant Science, Год журнала: 2024, Номер 15

Опубликована: Фев. 21, 2024

Legumes are essential to healthy agroecosystems, with a rich phytochemical content that impacts overall human and animal well-being environmental sustainability. While these phytochemicals can have both positive negative effects, legumes traditionally been bred produce genotypes lower levels of certain plant phytochemicals, specifically those commonly termed as ‘antifeedants’ including phenolic compounds, saponins, alkaloids, tannins, raffinose family oligosaccharides (RFOs). However, when incorporated into balanced diet, such legume offer health benefits for humans animals. They positively influence the gut microbiome by promoting growth beneficial bacteria, contributing health, demonstrating anti-inflammatory antioxidant properties. Beyond their nutritional value, also play vital role in soil health. The containing residues from shoots roots usually remain in-field affect nutrient status diversity, so enhancing functions benefiting performance yield following crops. This review explores ‘one health’ perspective, examining on soil- gut-microbial ecology, bridging gap between nutrition agroecological science.

Язык: Английский

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Spatial Quantification of Cropland Soil Erosion Dynamics in the Yunnan Plateau Based on Sampling Survey and Multi-Source LUCC Data

Опубликована: Янв. 17, 2024

Large scale cropland erosion rates mapping and dynamic monitoring are critical for agricultural planning but extremely challenging. In this study, by using field investigation data collected from 20,155 land parcels in 2,781 sample units the National Soil Erosion Survey, use change two decades Land Use/Cover Database of China (NLUD-C), we proposed a new point to surface approach quantitatively assess long-term based on CSLE model non-homogeneous voting. The results show that Yunnan suffers serious problem with unsustainable mean soil rate 40.47t/(ha·a) ratio 70.11%, which significantly higher than those other types. Engineering control measures (ECMS) have profound impact reducing erosion, without ESMs differs more five times. Over past decades, area continues decrease, net reduction 7461.83 km2 −10.55%, causes corresponding 0.32×108 t (12.12% ) decrease loss. We also quantified different LUCC scenarios extraordinarily high variability was found loss basins periods. Conversion forest contributes most reduction, while conversion grassland 56.18% increase erosion. Considering current speed regulation, it is sharp leads rather treatments. dilemma between Grain Green Policy Cropland Protecting Strategy mountainous areas should be treated carefully shared understanding collaborations roles.

Язык: Английский

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Towards enhanced adoption of soil‐improving management practices in Europe

European Journal of Soil Science, Год журнала: 2024, Номер 75(2)

Опубликована: Март 1, 2024

Abstract Sustainable agricultural soil management practices are key to restore, maintain and improve health. The European Joint Programme for SOIL (EJP SOIL) has identified twelve main challenges in Europe. To assess the potential eventually increase adoption of soil‐improving practices, it is necessary know (i) current levels (ii) socio‐technical barriers influencing their adoption, (iii) bio‐physical limits. This study compiled an inventory relevant conditions, used a survey among scientists these In total, 53 were that address one or several challenges. most was low spatially heterogeneous across Europe, highlighting region‐specific limitations sustainable management. Qualitative interviews conducted explore importance aspects adoption. Using conservation agriculture as example, factors can hinder included availability knowledge adequate machinery, financial risks, farming traditions. Through modelling approach, 54% arable land Europe found be suitable cover cropping, indicating frequently limited by climatic constraints. We propose approach recognizes identifying overcoming barriers, acknowledging limits may expanded innovation.

Язык: Английский

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Automated in-season rice crop mapping using Sentinel time-series data and Google Earth Engine: A case study in climate-risk prone Bangladesh

Journal of Environmental Management, Год журнала: 2023, Номер 351, С. 119615 - 119615

Опубликована: Дек. 12, 2023

High-resolution mapping of rice fields is crucial for understanding and managing cultivation in countries like Bangladesh, particularly the face climate change. Rice a vital crop, cultivated small scale farms that contributes significantly to economy food security Bangladesh. Accurate can facilitate improved production, development sustainable agricultural management policies, formulation strategies adapting climatic risks. To address need timely accurate mapping, we developed framework specifically designed diverse environmental conditions We utilized Sentinel-1 Sentinel-2 time-series data identify transplantation peak seasons employed multi-Otsu automatic thresholding approach map during season (April-May). also compared performance random forest (RF) classifier with using two different combinations: D1, which utilizes from (D1 RF) D2, harvest (D2 RF). Our results demonstrated achieved an overall classification accuracy (OCA) ranging 61.18% 94.43% across all crop zones. The D2 RF showed highest mean OCA (92.15%) among fourteen zones, followed by D1 (89.47%) (85.27%). Although had relatively lower OCA, it proved effective accurately areas prior harvest, eliminating training samples be challenging obtain growing season. In-season area maps generated through this are decision-making regarding adaptive response stresses forecasting area-wide productivity. scalability our space time makes suitable addressing field scarcity challenges Bangladesh offers potential future operationalization.

Язык: Английский

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Estimating Winter Cover Crop Biomass in France Using Optical Sentinel-2 Dense Image Time Series and Machine Learning

Remote Sensing, Год журнала: 2024, Номер 16(5), С. 834 - 834

Опубликована: Фев. 28, 2024

Cover crops play a pivotal role in mitigating climate change by bolstering carbon sequestration through biomass production and soil integration. However, current methods for quantifying cover crop lack spatial precision objectivity. Thus, our research aimed to devise remote-sensing-based approach estimate across various species mixtures during fallow periods France. Leveraging Sentinel-2 optical data machine learning algorithms, we modeled 50 fields representative of France’s diverse cropping practices types. Initial tests using traditional empirical relationships between vegetation indices/spectral bands dry revealed challenges accurately estimating mixed categories due spectral interference from grasses weeds, underscoring the complexity modeling agricultural conditions. To address this challenge, compared several algorithms (Support Vector Machine, Random Forest, eXtreme Gradient Boosting) indices latest available image before sampling as input. Additionally, developed an that incorporates dense time series data, generated Radial Basis Function interpolation. Our findings demonstrated Forest model trained with development period yielded promising results, average R-squared (r2) value 0.75 root mean square error (RMSE) 0.73 t·ha−1, surpassing results obtained single-image snapshots (r2 0.55). Moreover, exhibited robustness accounting factors such diversity, varied climatic conditions, presence weed vegetation—essential approximating real-world Importantly, its applicability extends beyond France, holding potential global scalability. The availability calibration regions timeframes could facilitate broader application.

Язык: Английский

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The Effect of Crop Diversification and Season on Microbial Carbon Use Efficiency Across a European Pedoclimatic Gradient

European Journal of Soil Science, Год журнала: 2025, Номер 76(2)

Опубликована: Фев. 24, 2025

ABSTRACT Microbial transformation of soil organic matter plays a critical role in carbon (C) cycling making it essential to understand how land use and management practices influence microbial physiology its connection C dynamics. One factor that is likely impact crop diversification via on belowground diversity (e.g., chemical heterogeneity inputs, community composition). However, the effect measures potential effects agricultural soils still unclear. To address this knowledge gap, we sampled topsoil from eight experimental sites covering different across Europe (i.e., cover crops, ley farming, vegetation stripes). We used 18 O‐labelling method analyse efficiency (CUE), growth, respiration biomass C. Additionally, second sampling at five selected examined whether growing season influenced diversification. Meta‐analysis revealed no overall CUE, activity, or (SOC). varied with type measure: crops did not affect processing, stripes increased farming enhanced CUE. The largest variation CUE was observed between samplings same sites, indicating seasonal Temperature, precipitation photosynthetically active radiation predicted ( R 2 = 0.36). While significantly storage our study, both SOC. SOC seems be decoupled highly temporally variable bulk rather relate C‐inputs.

Язык: Английский

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Modelling the impact of climate change on runoff and sediment yield in Mediterranean basins: the Carapelle case study (Apulia, Italy)

Frontiers in Water, Год журнала: 2025, Номер 7

Опубликована: Март 13, 2025

Introduction This study analyzes the impact of climate change on streamflow and sediment yield in Carapelle basin, a Mediterranean watershed located Apulia Region Italy. Methods Three model projections (CMCC, MPI, EC-EARTH) under CMIP6 SSP2-4.5 scenario were bias-corrected evaluated using statistical measures to ensure enhanced fit with observed data. The Soil Water Assessment Tool (SWAT) was implemented simulate hydrology yield. calibrated validated measured load data from 2004–2011, demonstrating satisfactory performance for both parameters. Baseline conditions (2000–2020) compared future (2030–2050). Results Climate 2030-2050 indicated temperature increases up 1.3°C average annual rainfall decreases 38% baseline. These changes resulted reduced water across all models. CMCC projected highest reduction mean flow (67%), smaller reductions MPI (35%) EC-EARTH (7%). Correspondingly, 52.8% (CMCC), 41.7% (MPI), 18.1% (EC-EARTH). Despite these overall reductions, spatial analysis revealed that soil erosion remained critical (sediment >10 t ha −1 ) certain areas, particularly steep slopes wheat cultivation. Discussion Integrating considerations into management strategies is essential sustaining river basins conditions. Adaptation such as BMPs NBSs should be reduce mitigate impacts.

Язык: Английский

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Organic farming expansion and food security: A review of foresight modeling studies

Global Food Security, Год журнала: 2024, Номер 41, С. 100765 - 100765

Опубликована: Апрель 25, 2024

Язык: Английский

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Assessing monthly dynamics of agricultural soil erosion risk in Poland

Geoderma Regional, Год журнала: 2024, Номер 39, С. e00864 - e00864

Опубликована: Сен. 11, 2024

Язык: Английский

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Hierarchical classification for improving parcel-scale crop mapping using time-series Sentinel-1 data

Journal of Environmental Management, Год журнала: 2024, Номер 369, С. 122251 - 122251

Опубликована: Авг. 29, 2024

Язык: Английский

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