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22 pages, 7171 KiB  
Article
Distribution Characteristics, Mobility, and Influencing Factors of Heavy Metals at the Sediment–Water Interface in South Dongting Lake
by Xiaohong Fang, Xiangyu Han, Chuanyong Tang, Bo Peng, Qing Peng, Linjie Hu, Yuru Zhong and Shana Shi
Water 2025, 17(15), 2331; https://doi.org/10.3390/w17152331 - 5 Aug 2025
Abstract
South Dongting Lake is an essential aquatic ecosystem that receives substantial water inflows from the Xiangjiang and Zishui Rivers. However, it is significantly impacted by human activities, including mining, smelting, and farming. These activities have led to serious contamination of the lake’s sediments [...] Read more.
South Dongting Lake is an essential aquatic ecosystem that receives substantial water inflows from the Xiangjiang and Zishui Rivers. However, it is significantly impacted by human activities, including mining, smelting, and farming. These activities have led to serious contamination of the lake’s sediments with heavy metals (HMs). This study investigated the distribution, mobility, and influencing factors of HMs at the sediment–water interface. To this end, sediment samples were analyzed from three key regions (Xiangjiang River estuary, Zishui River estuary, and northeastern South Dongting Lake) using traditional sampling methods and Diffusive Gradients in Thin Films (DGT) technology. Analysis of fifteen HMs (Pb, Bi, Ni, As, Se, Cd, Sb, Mn, Zn, V, Cr, Cu, Tl, Co, and Fe) revealed significant spatial heterogeneity. The results showed that Cr, Cu, Pb, Bi, Ni, As, Se, Cd, Sb, Mn, Zn, and Fe exhibited high variability (CV > 0.20), whereas V, Tl, and Co demonstrated stable concentrations (CV < 0.20). Concentrations were found to exceed background values of the upper continental crust of eastern China (UCC), Yangtze River sediments (YZ), and Dongting Lake sediments (DT), particularly at the Xiangjiang estuary (XE) and in the northeastern regions. Speciation analysis revealed that V, Cr, Cu, Ni, and As were predominantly found in the residual fraction (F4), while Pb and Co were concentrated in the oxidizable fraction (F3), Mn and Zn appeared primarily in the exchangeable fractions (F1 and F2), and Cd was notably dominant in the exchangeable fraction (F1), suggesting a high potential for mobility. Additionally, DGT results confirmed a significant potential for the release of Pb, Zn, and Cd. Contamination assessment using the Pollution Load Index (PLI) and Geoaccumulation Index (Igeo) identified Pb, Bi, Ni, As, Se, Cd, and Sb as major pollutants. Among these, Bi and Cd were found to pose the highest risks. Furthermore, the Risk Assessment Code (RAC) and the Potential Ecological Risk Index (PERI) highlighted Cd as the primary ecological risk contributor, especially in the XE. The study identified sediment grain size, pH, electrical conductivity, and nutrient levels as the primary influencing factors. The PMF modeling revealed HM sources as mixed smelting/natural inputs, agricultural activities, natural weathering, and mining/smelting operations, suggesting that remediation should prioritize Cd control in the XE with emphasis on external inputs. Full article
(This article belongs to the Section Water Quality and Contamination)
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20 pages, 9066 KiB  
Article
Dynamic Modeling of Poultry Litter Composting in High Mountain Climates Using System Identification Techniques
by Alvaro A. Patiño-Forero, Fabian Salazar-Caceres, Harrynson Ramirez-Murillo, Fabiana F. Franceschi, Ricardo Rincón and Geraldynne Sierra-Rueda
Automation 2025, 6(3), 36; https://doi.org/10.3390/automation6030036 - 5 Aug 2025
Abstract
Poultry waste composting is a necessary technique for agricultural farm sustainability. Composting is a dynamic process influenced by multiple variables. Humidity and temperature play fundamental roles in analyzing its different phases according to the environment and composting technique. Current developments for monitoring these [...] Read more.
Poultry waste composting is a necessary technique for agricultural farm sustainability. Composting is a dynamic process influenced by multiple variables. Humidity and temperature play fundamental roles in analyzing its different phases according to the environment and composting technique. Current developments for monitoring these variables include automation via intelligent Internet of Things (IoT)-based sensor networks for variable tracking. These advancements serve as efficient tools for modeling that facilitate the simulation and prediction of composting process variables to improve system efficiency. Therefore, this paper presents the dynamic modeling of composting via forced aeration processes in high-mountain climates, with the intent of estimating biomass temperature dynamics in different phases using system identification techniques. To this end, four dynamic model estimation structures are employed: transfer function (TF), state space (SS), process (P), and Hammerstein–Wiener (HW). The and model quality, fitting results, and standard error metrics of the different models found in each phase are assessed through residual analysis from each structure by validation with real system data. Our results show that the second-order underdamped multiple-input–single-output (MISO) process model with added noise demonstrates the best fit and validation performance. Full article
(This article belongs to the Topic Digital Agriculture, Smart Farming and Crop Monitoring)
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20 pages, 2299 KiB  
Article
Valorization of Waste Mineral Wool and Low-Rank Peat in the Fertilizer Industry in the Context of a Resource-Efficient Circular Economy
by Marta Huculak-Mączka, Dominik Nieweś, Kinga Marecka and Magdalena Braun-Giwerska
Sustainability 2025, 17(15), 7083; https://doi.org/10.3390/su17157083 - 5 Aug 2025
Abstract
This study aims to evaluate eco-innovative solutions in the fertilizer industry that allow for waste valorization in the context of a resource-efficient circular economy. A comprehensive reuse strategy was developed for low-rank peat and post-cultivation horticultural mineral wool, involving the extraction of valuable [...] Read more.
This study aims to evaluate eco-innovative solutions in the fertilizer industry that allow for waste valorization in the context of a resource-efficient circular economy. A comprehensive reuse strategy was developed for low-rank peat and post-cultivation horticultural mineral wool, involving the extraction of valuable humic substances from peat and residual nutrients from used mineral wool, followed by the use of both post-extraction residues to produce organic–mineral substrates. The resulting products/semifinished products were characterized in terms of their composition and properties, which met the requirements necessary to obtain the admission of this type of product to the market in accordance with the Regulation of the Minister for Agriculture and Rural Development of 18 June 2008 on the implementation of certain provisions of the Act on fertilizers and fertilization (Journal of Laws No 119, item 765). Elemental analysis, FTIR spectroscopy, and solid-state CP-MAS 13C NMR spectroscopy suggest that post-extraction peat has a relatively condensed structure with a high C content (47.4%) and a reduced O/C atomic ratio and is rich in alkyl-like matter (63.2%) but devoid of some functional groups in favor of extracted fulvic acids. Therefore, it remains a valuable organic biowaste, which, in combination with post-extraction waste mineral wool in a ratio of 60:40 and possibly the addition of mineral nutrients, allows us to obtain a completely new substrate with a bulk density of 264 g/m3, a salinity of 7.8 g/dm3 and a pH of 5.3, with an appropriate content of heavy metals and with no impurities, meeting the requirements of this type of product. A liquid fertilizer based on an extract containing previously recovered nutrients also meets the criteria in terms of quality and content of impurities and can potentially be used as a fertilizing product suitable for agricultural crops. This study demonstrates a feasible pathway for transforming specific waste streams into valuable agricultural inputs, contributing to environmental protection and sustainable production. The production of a new liquid fertilizer using nutrients recovered from post-cultivation mineral wool and the preparation of an organic–mineral substrate using post-extraction solid residue is a rational strategy for recycling hard-to-biodegrade end-of-life products. Full article
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15 pages, 5152 KiB  
Article
Assessment of Emergy, Environmental and Economic Sustainability of the Mango Orchard Production System in Hainan, China
by Yali Lei, Xiaohui Zhou and Hanting Cheng
Sustainability 2025, 17(15), 7030; https://doi.org/10.3390/su17157030 - 2 Aug 2025
Viewed by 195
Abstract
Mangoes are an important part of Hainan’s tropical characteristic agriculture. In response to the requirements of building an ecological civilization pilot demonstration zone in Hainan, China, green and sustainable development will be the future development trend of the mango planting system. However, the [...] Read more.
Mangoes are an important part of Hainan’s tropical characteristic agriculture. In response to the requirements of building an ecological civilization pilot demonstration zone in Hainan, China, green and sustainable development will be the future development trend of the mango planting system. However, the economic benefits and environmental impact during its planting and management process remain unclear. This paper combines emergy, life cycle assessment (LCA), and economic analysis to compare the system sustainability, environmental impact, and economic benefits of the traditional mango cultivation system (TM) in Dongfang City, Hainan Province, and the early-maturing mango cultivation system (EM) in Sanya City. The emergy evaluation results show that the total emergy input of EM (1.37 × 1016 sej ha−1) was higher than that of TM (1.32 × 1016 sej ha−1). From the perspective of the emergy index, compared with TM, EM exerted less pressure on the local environment and has better stability and sustainability. This was due to the higher input of renewable resources in EM. The LCA results showed that based on mass as the functional unit, the potential environmental impact of the EM is relatively high, and its total environmental impact index was 18.67–33.19% higher than that of the TM. Fertilizer input and On-Farm emissions were the main factors causing environmental consequences. Choosing alternative fertilizers that have a smaller impact on the environment may effectively reduce the environmental impact of the system. The economic analysis results showed that due to the higher selling price of early-maturing mango, the total profit and cost–benefit ratio of the EM have increased by 55.84% and 36.87%, respectively, compared with the TM. These results indicated that EM in Sanya City can enhance environmental sustainability and boost producers’ annual income, but attention should be paid to the negative environmental impact of excessive fertilizer input. These findings offer insights into optimizing agricultural inputs for Hainan mango production to mitigate multiple environmental impacts while enhancing economic benefits, aiming to provide theoretical support for promoting the sustainable development of the Hainan mango industry. Full article
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17 pages, 1792 KiB  
Review
The Response Mechanism of Soil Microbial Carbon Use Efficiency to Land-Use Change: A Review
by Zongkun Li and Dandan Qi
Sustainability 2025, 17(15), 7023; https://doi.org/10.3390/su17157023 - 2 Aug 2025
Viewed by 339
Abstract
Microbial carbon use efficiency (CUE) is an important indicator of soil organic carbon accumulation and loss and a key parameter in biogeochemical cycling models. Its regulatory mechanism is highly dependent on microbial communities and their dynamic mediation of abiotic factors. Land-use change (e.g., [...] Read more.
Microbial carbon use efficiency (CUE) is an important indicator of soil organic carbon accumulation and loss and a key parameter in biogeochemical cycling models. Its regulatory mechanism is highly dependent on microbial communities and their dynamic mediation of abiotic factors. Land-use change (e.g., agricultural expansion, deforestation, urbanization) profoundly alter carbon input patterns and soil physicochemical properties, further exacerbating the complexity and uncertainty of CUE. Existing carbon cycle models often neglect microbial ecological processes, resulting in an incomplete understanding of how microbial traits interact with environmental factors to regulate CUE. This paper provides a comprehensive review of the microbial regulation mechanisms of CUE under land-use change and systematically explores how microorganisms drive organic carbon allocation through community compositions, interspecies interactions, and environmental adaptability, with particular emphasis on the synergistic response between microbial communities and abiotic factors. We found that the buffering effect of microbial communities on abiotic factors during land-use change is a key factor determining CUE change patterns. This review not only provides a theoretical framework for clarifying the microbial-dominated carbon turnover mechanism but also lays a scientific foundation for the precise implementation of sustainable land management and carbon neutrality goals. Full article
(This article belongs to the Special Issue Soil Ecology and Carbon Cycle)
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24 pages, 1386 KiB  
Article
Assessing Sustainable Growth: Evolution and Convergence of Green Total Factor Productivity in Tibetan Plateau Agriculture
by Mengmeng Zhang and Chengqun Yu
Sustainability 2025, 17(15), 6963; https://doi.org/10.3390/su17156963 - 31 Jul 2025
Viewed by 142
Abstract
Accurate assessment of green productivity is essential for advancing sustainable agriculture in ecologically fragile regions. This study examined the evolution of agricultural green total factor productivity (AGTFP) in Tibet over the period 2002–2021 by applying a super-efficiency SBM-GML model that accounts for undesirable [...] Read more.
Accurate assessment of green productivity is essential for advancing sustainable agriculture in ecologically fragile regions. This study examined the evolution of agricultural green total factor productivity (AGTFP) in Tibet over the period 2002–2021 by applying a super-efficiency SBM-GML model that accounts for undesirable outputs. We decompose AGTFP into technical change and efficiency change, conduct redundancy analysis to identify sources of inefficiency and explore its spatiotemporal dynamics through kernel density estimation and convergence analysis. Results show that (1) AGTFP in Tibet grew at an average annual rate of 0.78%, slower than the national average of 1.6%; (2) labor input, livestock scale, and agricultural carbon emissions are major sources of redundancy, especially in pastoral regions; (3) technological progress is the main driver of AGTFP growth, while efficiency gains have a limited impact, reflecting a technology-led growth pattern; (4) AGTFP follows a “convergence-divergence-reconvergence” trend, with signs of conditional β convergence after controlling for regional heterogeneity. These findings highlight the need for region-specific green agricultural policies. Priority should be given to improving green technology diffusion and input allocation in high-altitude pastoral areas, alongside strengthening ecological compensation and interregional coordination to enhance green efficiency and promote high-quality development across Tibet. Full article
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17 pages, 3112 KiB  
Article
Impacts of Conservation Tillage on Soil Organic Carbon Mineralization in Eastern Inner Mongolia
by Boyu Liu, Jianquan Wang, Dian Jin and Hailin Zhang
Agronomy 2025, 15(8), 1847; https://doi.org/10.3390/agronomy15081847 - 30 Jul 2025
Viewed by 198
Abstract
Soil organic carbon (SOC) mineralization plays the critical role of regulating carbon sequestration potential. This process is strongly influenced by agricultural practices, particularly tillage regimes and straw management. However, the complex interactions between tillage methods, straw types, and application rates in terms of [...] Read more.
Soil organic carbon (SOC) mineralization plays the critical role of regulating carbon sequestration potential. This process is strongly influenced by agricultural practices, particularly tillage regimes and straw management. However, the complex interactions between tillage methods, straw types, and application rates in terms of SOC dynamics, especially in semi-arid agroecosystems like eastern Inner Mongolia, remain poorly understood. In this study, we assessed the combined effects of no tillage (NT) vs. rotary tillage (RT), three straw types (maize/MS, wheat/WS, and oilseed rape/OS), and three application rates (0.4%/low, 0.8%/medium, and 1.2%/high) on SOC concentration and mineralization using controlled laboratory incubation with soils from long-term plots. The key findings revealed that NT significantly increased the SOC concentration in the topsoil (0–20 cm) by an average of 14.5% compared to that in the RT. Notably, combining NT with medium-rate wheat straw (0.8%) resulted in the achievement of the highest SOC accumulation (28.70 g/kg). SOC mineralization increased with straw inputs, exhibiting significant straw type × rate interactions. Oilseed rape straw showed the highest specific mineralization rate (33.9%) at low input, while maize straw mineralized fastest under high input with RT. Therefore, our results demonstrate that combining NT with either 0.8% wheat straw or 1.2% maize straw represents an optimal application strategy, as the SOC concentration is enhanced by 12–18% for effective carbon sequestration in this water-limited semi-arid region. Therefore, optimizing SOC sequestration requires the integration of appropriate crop residue application rates and tillage methods tailored to different cropping systems. Full article
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30 pages, 12776 KiB  
Article
Multi-Source Data Integration for Sustainable Management Zone Delineation in Precision Agriculture
by Dušan Jovanović, Miro Govedarica, Milan Gavrilović, Ranko Čabilovski and Tamme van der Wal
Sustainability 2025, 17(15), 6931; https://doi.org/10.3390/su17156931 - 30 Jul 2025
Viewed by 193
Abstract
Accurate delineation of within-field management zones (MZs) is essential for implementing precision agriculture, particularly in spatially heterogeneous environments. This study evaluates the spatiotemporal consistency and practical value of MZs derived from three complementary data sources: electromagnetic conductivity (EM38-MK2), basic soil chemical properties (pH, [...] Read more.
Accurate delineation of within-field management zones (MZs) is essential for implementing precision agriculture, particularly in spatially heterogeneous environments. This study evaluates the spatiotemporal consistency and practical value of MZs derived from three complementary data sources: electromagnetic conductivity (EM38-MK2), basic soil chemical properties (pH, humus, P2O5, K2O, nitrogen), and vegetation/surface indices (NDVI, SAVI, LCI, BSI) derived from Sentinel-2 imagery. Using kriging, fuzzy k-means clustering, percentile-based classification, and Weighted Overlay Analysis (WOA), MZs were generated for a five-year period (2018–2022), with 2–8 zone classes. Stability and agreement were assessed using the Cohen Kappa, Jaccard, and Dice coefficients on systematic grid samples. Results showed that EM38-MK2 and humus-weighted BSP data produced the most consistent zones (Kappa > 0.90). Sentinel-2 indices demonstrated strong alignment with subsurface data (r > 0.85), offering a low-cost alternative in data-scarce settings. Optimal zoning was achieved with 3–4 classes, balancing spatial coherence and interpretability. These findings underscore the importance of multi-source data integration for robust and scalable MZ delineation and offer actionable guidelines for both data-rich and resource-limited farming systems. This approach promotes sustainable agriculture by improving input efficiency and allowing for targeted, site-specific field management. Full article
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24 pages, 4061 KiB  
Article
The Impact of Hydrogeological Properties on Mass Displacement in Aquifers: Insights from Implementing a Mass-Abatement Scalable System Using Managed Aquifer Recharge (MAR-MASS)
by Mario Alberto Garcia Torres, Alexandra Suhogusoff and Luiz Carlos Ferrari
Water 2025, 17(15), 2239; https://doi.org/10.3390/w17152239 - 27 Jul 2025
Viewed by 304
Abstract
This study examines the use of a mass-abatement scalable system with managed aquifer recharge (MAR-MASS) as a sustainable solution for restoring salinized aquifers and improving water quality by removing dissolved salts. It offers a practical remediation approach for aquifers affected by salinization in [...] Read more.
This study examines the use of a mass-abatement scalable system with managed aquifer recharge (MAR-MASS) as a sustainable solution for restoring salinized aquifers and improving water quality by removing dissolved salts. It offers a practical remediation approach for aquifers affected by salinization in coastal regions, agricultural areas, and contaminated sites, where variable-density flow poses a challenge. Numerical simulations assessed hydrogeological properties such as hydraulic conductivity, anisotropy, specific yield, mechanical dispersion, and molecular diffusion. A conceptual model integrated hydraulic conditions with spatial and temporal discretization using the FLOPY API for MODFLOW 6 and the IFM API for FEFLOW 10. Python algorithms were run within the high-performance computing (HPC) server, executing simulations in parallel to efficiently process a large number of scenarios, including both preprocessing input data and post-processing results. The study simulated 6950 scenarios, each modeling flow and transport processes over 3000 days of method implementation and focusing on mass extraction efficiency under different initial salinity conditions (3.5 to 35 kg/m3). The results show that the MAR-MASS effectively removed salts from aquifers, with higher hydraulic conductivity prolonging mass removal efficiency. Of the scenarios, 88% achieved potability (0.5 kg/m3) in under five years; among these, 79% achieved potability within two years, and 92% of cases with initial concentrations of 3.5–17.5 kg/m3 reached potability within 480 days. This study advances scientific knowledge by providing a robust model for optimizing managed aquifer recharge, with practical applications in rehabilitating salinized aquifers and improving water quality. Future research may explore MAR-MASS adaptation for diverse hydrogeological contexts and its long-term performance. Full article
(This article belongs to the Section Hydrogeology)
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27 pages, 2978 KiB  
Article
Dynamic Monitoring and Precision Fertilization Decision System for Agricultural Soil Nutrients Using UAV Remote Sensing and GIS
by Xiaolong Chen, Hongfeng Zhang and Cora Un In Wong
Agriculture 2025, 15(15), 1627; https://doi.org/10.3390/agriculture15151627 - 27 Jul 2025
Viewed by 365
Abstract
We propose a dynamic monitoring and precision fertilization decision system for agricultural soil nutrients, integrating UAV remote sensing and GIS technologies to address the limitations of traditional soil nutrient assessment methods. The proposed method combines multi-source data fusion, including hyperspectral and multispectral UAV [...] Read more.
We propose a dynamic monitoring and precision fertilization decision system for agricultural soil nutrients, integrating UAV remote sensing and GIS technologies to address the limitations of traditional soil nutrient assessment methods. The proposed method combines multi-source data fusion, including hyperspectral and multispectral UAV imagery with ground sensor data, to achieve high-resolution spatial and spectral analysis of soil nutrients. Real-time data processing algorithms enable rapid updates of soil nutrient status, while a time-series dynamic model captures seasonal variations and crop growth stage influences, improving prediction accuracy (RMSE reductions of 43–70% for nitrogen, phosphorus, and potassium compared to conventional laboratory-based methods and satellite NDVI approaches). The experimental validation compared the proposed system against two conventional approaches: (1) laboratory soil testing with standardized fertilization recommendations and (2) satellite NDVI-based fertilization. Field trials across three distinct agroecological zones demonstrated that the proposed system reduced fertilizer inputs by 18–27% while increasing crop yields by 4–11%, outperforming both conventional methods. Furthermore, an intelligent fertilization decision model generates tailored fertilization plans by analyzing real-time soil conditions, crop demands, and climate factors, with continuous learning enhancing its precision over time. The system also incorporates GIS-based visualization tools, providing intuitive spatial representations of nutrient distributions and interactive functionalities for detailed insights. Our approach significantly advances precision agriculture by automating the entire workflow from data collection to decision-making, reducing resource waste and optimizing crop yields. The integration of UAV remote sensing, dynamic modeling, and machine learning distinguishes this work from conventional static systems, offering a scalable and adaptive framework for sustainable farming practices. Full article
(This article belongs to the Section Agricultural Soils)
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32 pages, 1770 KiB  
Article
Regional Patterns in Weed Composition of Maize Fields in Eastern Hungary: The Balance of Environmental and Agricultural Factors
by Mihály Zalai, Erzsébet Tóth, János György Nagy and Zita Dorner
Agronomy 2025, 15(8), 1814; https://doi.org/10.3390/agronomy15081814 - 26 Jul 2025
Viewed by 437
Abstract
The primary aim of this study was to explore the influence of abiotic factors on weed development in maize fields, with the goal of informing more effective weed management practices. We focused on identifying key environmental, edaphic, and agricultural variables that contribute to [...] Read more.
The primary aim of this study was to explore the influence of abiotic factors on weed development in maize fields, with the goal of informing more effective weed management practices. We focused on identifying key environmental, edaphic, and agricultural variables that contribute to weed infestations, particularly before the application of spring herbicide treatments. Field investigations were conducted from 2018 to 2021 across selected maize-growing regions in Hungary. Over the four-year period, a total of 51 weed species were recorded, with Echinochloa crus-galli, Chenopodium album, Portulaca oleracea, and Hibiscus trionum emerging as the most prevalent taxa. Collectively, these four species accounted for more than half (52%) of the total weed cover. Altogether, the 20 most dominant species contributed 95% of the overall weed coverage. The analysis revealed that weed cover, species richness, and weed diversity were significantly affected by soil properties, nutrient levels, geographic location, and tillage systems. The results confirm that the composition of weed species was influenced by several environmental and management-related factors, including soil parameters, geographical location, annual precipitation, tillage method, and fertilizer application. Environmental factors collectively explained a slightly higher proportion of the variance (13.37%) than farming factors (12.66%) at a 90% significance level. Seasonal dynamics and crop rotation history also played a notable role in species distribution. Nutrient inputs, particularly nitrogen, phosphorus, and potassium, influenced both species diversity and floristic composition. Deep tillage practices favored the proliferation of perennial species, whereas shallow cultivation tended to promote annual weeds. Overall, the composition of weed vegetation proved to be a valuable indicator of site-specific soil conditions and agricultural practices. These findings underscore the need to tailor weed management strategies to local environmental and soil contexts for sustainable crop production. Full article
(This article belongs to the Special Issue State-of-the-Art Research on Weed Populations and Community Dynamics)
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24 pages, 1391 KiB  
Article
Nitrogen Fertilization and Glomus Mycorrhizal Inoculation Enhance Growth and Secondary Metabolite Accumulation in Hyssop (Hyssopus officinalis L.)
by Saeid Hazrati, Marzieh Mohammadi, Saeed Mollaei, Mostafa Ebadi, Giuseppe Pignata and Silvana Nicola
Nitrogen 2025, 6(3), 60; https://doi.org/10.3390/nitrogen6030060 - 26 Jul 2025
Viewed by 320
Abstract
Nitrogen (N) availability often limits primary productivity in terrestrial ecosystems, and arbuscular mycorrhizal fungi (AMF) can enhance plant N acquisition. This study investigated the interactive effects of N fertilization and AMF inoculation on N uptake, plant performance and phenolic acid content in Hyssopus [...] Read more.
Nitrogen (N) availability often limits primary productivity in terrestrial ecosystems, and arbuscular mycorrhizal fungi (AMF) can enhance plant N acquisition. This study investigated the interactive effects of N fertilization and AMF inoculation on N uptake, plant performance and phenolic acid content in Hyssopus officinalis L., with the aim of promoting sustainable N management in H. officinalis cultivation. A factorial randomized complete block design was employed to evaluate four AMF inoculation strategies (no inoculation, root inoculation, soil inoculation and combined root–soil inoculation) across three N application rates (0, 0.5 and 1,1 g N pot−1 (7 L)) in a controlled greenhouse environment. Combined root and soil AMF inoculation alongside moderate N fertilization (0.5 mg N pot−1) optimized N use efficiency, maximizing plant biomass and bioactive compound production. Compared to non-inoculated controls, this treatment combination increased N uptake by 30%, phosphorus uptake by 24% and potassium uptake by 22%. AMF colonization increased chlorophyll content and total phenolic compounds under moderate N supply. However, excessive N application (1 g N pot−1) reduced AMF effectiveness and secondary metabolite accumulation. Notably, AMF inoculation without N fertilization yielded the highest levels of anthocyanin and salicylic acid, indicating differential N-dependent regulation of specific biosynthetic pathways. The interaction between AMF and N demonstrated that moderate N fertilization (0.5 g N pot−1) combined with dual inoculation strategies can reduce total N input requirements by 50%, while maintaining optimal plant performance. These findings provide practical insights for developing N-efficient cultivation protocols in medicinal plant production systems, contributing to sustainable agricultural practices that minimize environmental N losses. Full article
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19 pages, 1803 KiB  
Article
Sustainable Crop Farm Productivity: Weather Effects, Technology Adoption, and Farm Management
by Sun Ling Wang, Ryan Olver and Daniel Bonin
Sustainability 2025, 17(15), 6778; https://doi.org/10.3390/su17156778 - 25 Jul 2025
Viewed by 327
Abstract
The main purpose of this study is to understand the potential determinants of sustainable field crop farm productivity. This paper considers a multi-input, multi-output production technology to estimate the effects of aridity on farm-level productivity using a stochastic input distance function. By isolating [...] Read more.
The main purpose of this study is to understand the potential determinants of sustainable field crop farm productivity. This paper considers a multi-input, multi-output production technology to estimate the effects of aridity on farm-level productivity using a stochastic input distance function. By isolating the respective weather components of agricultural total factor productivity (TFP), we can better assess the impact on productivity of adopting various technologies and farm practices that might otherwise be masked by changing climate conditions or weather shocks. We make use of data from Phase 3 of the United States Department of Agriculture (USDA) Agricultural Resource Management Survey (ARMS) between 2006 and 2020. We supplement this estimation using field crop farm productivity determinants, including technology adoption and farm practice variables derived from the ARMS Phase 2 data. We identify several factors that affect farm productivity, including many practices that help farmers make more sustainable use of natural resources. The results show that adopting yield monitoring technology, fallowing in previous years, adding or improving tile drainage, and contour farming each improved farm productivity. In particular, during our study period, conservation tillage increased by over 300% across states on average. It is estimated to increase productivity level by approximately 3% for those adopting this practice. Critically, accounting for local weather effects increased the estimated productivity of nearly all farm practices and increased the statistical significance of several variables, indicating that other TFP studies that did not account for climate or weather effects may have underestimated the technical efficiency of farms that adopted these conservation practices. However, the results also show the impacts can be heterogeneous, with effects varying between farms located in the U.S. northern or southern regions. Full article
(This article belongs to the Special Issue Sustainable Agricultural and Rural Development)
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16 pages, 2199 KiB  
Article
Carbon Footprint and Energy Balance Analysis of Rice-Wheat Rotation System in East China
by Dingqian Wu, Yezi Shen, Yuxuan Zhang, Tianci Zhang and Li Zhang
Agronomy 2025, 15(8), 1778; https://doi.org/10.3390/agronomy15081778 - 24 Jul 2025
Viewed by 267
Abstract
The rice-wheat rotation is the main agricultural cropping system in Jiangsu Province, playing a vital role in ensuring food security and promoting economic development. However, current research on rice-wheat systems mainly focuses on in-situ controlled experiments at the point scale, with limited studies [...] Read more.
The rice-wheat rotation is the main agricultural cropping system in Jiangsu Province, playing a vital role in ensuring food security and promoting economic development. However, current research on rice-wheat systems mainly focuses on in-situ controlled experiments at the point scale, with limited studies addressing carbon footprint (CF) and energy balance (EB) at the regional scale and long time series. Therefore, we analyzed the evolution patterns of the CF and EB of the rice-wheat system in Jiangsu Province from 1980 to 2022, as well as their influencing factors. The results showed that the sown area and total yield of rice and wheat exhibited an increasing–decreasing–increasing trend during 1980–2022, while the yield per unit area increased continuously. The CF of rice and wheat increased by 4172.27 kg CO2 eq ha−1 and 2729.18 kg CO2 eq ha−1, respectively, with the greenhouse gas emissions intensity (GHGI) showing a fluctuating upward trend. Furthermore, CH4 emission, nitrogen (N) fertilizer, and irrigation were the main factors affecting the CF of rice, with proportions of 36%, 20.26%, and 17.34%, respectively. For wheat, N fertilizer, agricultural diesel, compound fertilizer, and total N2O emission were the primary contributors, accounting for 42.39%, 22.54%, 13.65%, and 13.14%, respectively. Among energy balances, the net energy (NE) of rice exhibited an increasing and then fluctuating trend, while that of wheat remained relatively stable. The energy utilization efficiency (EUE), energy productivity (EPD), and energy profitability (EPF) of rice showed an increasing and then decreasing trend, while wheat decreased by 46.31%, 46.31%, and 60.62% during 43 years, respectively. Additionally, N fertilizer, agricultural diesel, and compound fertilizer accounted for 43.91–45.37%, 21.63–25.81%, and 12.46–20.37% of energy input for rice and wheat, respectively. Moreover, emission factors and energy coefficients may vary over time, which is an important consideration in the analysis of long-term time series. This study analyzes the ecological and environmental effects of the rice-wheat system in Jiangsu Province, which helps to promote the development of agriculture in a green, low-carbon, and high-efficiency direction. It also offers a theoretical basis for constructing a low-carbon sustainable agricultural production system. Full article
(This article belongs to the Section Agroecology Innovation: Achieving System Resilience)
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19 pages, 3806 KiB  
Article
Farmdee-Mesook: An Intuitive GHG Awareness Smart Agriculture Platform
by Mongkol Raksapatcharawong and Watcharee Veerakachen
Agronomy 2025, 15(8), 1772; https://doi.org/10.3390/agronomy15081772 - 24 Jul 2025
Viewed by 345
Abstract
Climate change presents urgent and complex challenges to agricultural sustainability and food security, particularly in regions reliant on resource-intensive staple crops. Smart agriculture—through the integration of crop modeling, satellite remote sensing, and artificial intelligence (AI)—offers data-driven strategies to enhance productivity, optimize input use, [...] Read more.
Climate change presents urgent and complex challenges to agricultural sustainability and food security, particularly in regions reliant on resource-intensive staple crops. Smart agriculture—through the integration of crop modeling, satellite remote sensing, and artificial intelligence (AI)—offers data-driven strategies to enhance productivity, optimize input use, and mitigate greenhouse gas (GHG) emissions. This study introduces Farmdee-Mesook, a mobile-first smart agriculture platform designed specifically for Thai rice farmers. The platform leverages AquaCrop simulation, open-access satellite data, and localized agronomic models to deliver real-time, field-specific recommendations. Usability-focused design and no-cost access facilitate its widespread adoption, particularly among smallholders. Empirical results show that platform users achieved yield increases of up to 37%, reduced agrochemical costs by 59%, and improved water productivity by 44% under alternate wetting and drying (AWD) irrigation schemes. These outcomes underscore the platform’s role as a scalable, cost-effective solution for operationalizing climate-smart agriculture. Farmdee-Mesook demonstrates that digital technologies, when contextually tailored and institutionally supported, can serve as critical enablers of climate adaptation and sustainable agricultural transformation. Full article
(This article belongs to the Special Issue Smart Farming Technologies for Sustainable Agriculture—2nd Edition)
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