Arable Land Research Articles

Enhancing Soil Salinity Evaluation Accuracy in Arid Regions: An Integrated Spatiotemporal Data Fusion and AI Model Approach for Arable Lands

Soil salinization is one of the primary factors contributing to land degradation in arid areas, severely restricting the sustainable development of agriculture and the economy. Satellite remote sensing is essential for real-time, large-scale soil salinity content (SSC) evaluation. However, some satellite images have low temporal resolution and are affected by weather conditions, leading to the absence of satellite images synchronized with ground observations. Additionally, some high-temporal-resolution satellite images have overly coarse spatial resolution compared to ground features. Therefore, the limitations of these spatiotemporal features may affect the accuracy of SSC evaluation. This study focuses on the arable land in the Manas River Basin, located in the arid areas of northwest China, to explore the potential of integrated spatiotemporal data fusion and deep learning algorithms for evaluating SSC. We used the flexible spatiotemporal data fusion (FSDAF) model to merge Landsat and MODIS images, obtaining satellite fused images synchronized with ground sampling times. Using support vector regression (SVR), random forest (RF), and convolutional neural network (CNN) models, we evaluated the differences in SSC evaluation results between synchronized and unsynchronized satellite images with ground sampling times. The results showed that the FSDAF model’s fused image was highly similar to the original image in spectral reflectance, with a coefficient of determination (R2) exceeding 0.8 and a root mean square error (RMSE) below 0.029. This model effectively compensates for the missing fine-resolution satellite images synchronized with ground sampling times. The optimal salinity indices for evaluating the SSC of arable land in arid areas are S3, S5, SI, SI1, SI3, SI4, and Int1. These indices show a high correlation with SSC based on both synchronized and unsynchronized satellite images with ground sampling times. SSC evaluation models based on synchronized satellite images with ground sampling times were more accurate than those based on unsynchronized images. This indicates that synchronizing satellite images with ground sampling times significantly impacts SSC evaluation accuracy. Among the three models, the CNN model demonstrates the highest predictive accuracy in SSC evaluation based on synchronized and unsynchronized satellite images with ground sampling times, indicating its significant potential in image prediction. The optimal evaluation scheme is the CNN model based on satellite image synchronized with ground sampling times, with an R2 of 0.767 and an RMSE of 1.677 g·kg−1. Therefore, we proposed a framework for integrated spatiotemporal data fusion and CNN algorithms for evaluating soil salinity, which improves the accuracy of soil salinity evaluation. The results provide a valuable reference for the real-time, rapid, and accurate evaluation of soil salinity of arable land in arid areas.

A Study on the Spatiotemporal Dynamics of Land Cover Change and Carbon Storage in the Northern Gulf Economic Zone of Guangxi Based on the InVEST Model

In recent years, the international community has increasingly focused on the “dual carbon” issue, as human-induced land use changes significantly impact ecosystem structure and carbon cycling. This study analyzes land use changes in the economic zone of the northern Gulf of Guangxi from 1980 to 2020, utilizing the InVEST model to simulate spatiotemporal changes in carbon storage and conducting zoning studies through spatial analysis. The findings reveal that ① forest land and arable land dominate the northern Gulf of Guangxi’s land use, with notable changes observed in forest land, unused land, and construction land areas. Forest land and construction land have increased by 1761.5 km2 and 1001.19 km2, respectively, while unused land has decreased by 1881.18 km2 from 2000 to 2020. ② The total carbon storage values in the northern Gulf of Guangxi in 1980, 2000, and 2020 were, respectively, 504.91 × 106/t, 487.29 × 106/t, and 500.31 × 106/t, with the expansion of construction land and conversion of forest land being the main reasons for the decrease in carbon storage. ③ In the northern Gulf of Guangxi, there is a slight upward trend in total carbon storage values over time. Spatially, higher carbon storage values are observed in mountainous and hilly areas at high altitudes, while the central and southern coastal areas exhibit lower carbon storage values. ④ The local spatial autocorrelation results reveal that Pu Bei County exhibits high–high clustering of carbon storage, while He Pu County undergoes a transition from high–low to low–low clustering, and several other administrative areas in Beihai demonstrates low–low clustering. Due to the imperative of economic development, the expansion of urban construction land encroaches upon ecological land, resulting in a decline in carbon storage. Therefore, in the Northern Gulf of Guangxi, it is essential to implement measures such as reforestation and establish ecological protection areas such as forests, grasslands, and wetlands to develop effective carbon sequestration methods and compensate for the carbon loss caused by the expansion of construction land.

Shifting from Trade-Offs to Synergies in Ecosystem Services Through Effective Ecosystem Management in Arid Areas

Human activities continuously alter the delivery of ecosystem services (ESs), which play a crucial role in human well-being. There is a pressing need for effective ecological management strategies that consider the spatial heterogeneity of ESs to support the transition from trade-offs to synergies. This study focuses on the Haba River Basin and examines characteristics of land-use change and the shift from trade-offs to synergies. The results indicate that from 1990 to 2000, the initial phase of land development, 10.65% of the land experienced change. Subsequently, during the intensive period of land development from 2000 to 2010, 30.29% of the land underwent significant transformation, with approximately 78% of grassland, sparse grassland, forested land, and desert converted into arable land. However, between 2010 and 2020, as the focus shifted towards the establishment of native vegetation. The intensity of land development decreased, and only a small percentage (3.65%) of the total area underwent changes. Based on an in-depth analysis of spatial heterogeneity from 1990 to 2020, it is believed there has been a shift from trade-offs to co-benefits between 2000–2010 and 2010–2020. The years 2010 and 2020 were pivotal time nodes for the transition from trade-offs to synergies and for reducing trade-offs, with NPP identified as a critical driving factor for comprehensive ES (CES) functions. By considering the trade-off–synergy relationship and hotspots of ecological service functions, combined with unified water resource management policies, comprehensive ecological management measures tailored to different regions are proposed. These measures have facilitated the implementation of robust ecological protection policies to shift ES development from trade-offs to synergies in arid areas, thereby enhancing overall ecosystem service functions in the Haba River Basin. The research findings offer crucial scientific support and guidance for ecosystem management in arid areas, particularly within Central Asia.

The practice of protecting agricultural land in Jiangsu Province of China

The safeguarding of agricultural land is rooted in national land surveys and remote sensing data, which are enhanced by contemporary information technology. This framework facilitates the monitoring and regulation of unauthorized alterations in cultivated land usage. This paper aims to analyze land policies at the national, provincial, and local levels, investigate the cultivated land protection strategies implemented within the research region, where the policies have gained societal acceptance, and propose recommendations and countermeasures to enhance the development and utilization of land resources. The central issue of this study is to identify the challenges in achieving a balance between human activities and natural ecosystems. To address this issue, the research employs a combination of literature review, semi-structured interviews, text analysis, and content analysis, emphasizing the integration of empirical fieldwork and theoretical frameworks. Key areas of focus include: (a) the current state of the farmland protection system, (b) the legal foundations for local enforcement, (c) the systematic mechanisms for implementing arable land protection, and (d) the coordinated oversight system involving both the Party and government. Notably, the practice of cultivated land protection faces several challenges, primarily stemming from two factors. Firstly, there exists a disconnect between the economic interests of certain illegal land users and the objectives of land management, which hinders effective enforcement. Secondly, environmental repercussions arise from misinterpretations of land policy or non-compliant land development practices aimed at profit, which contradict the goals of ecological sustainability. The study examines two approaches to address the issue: the distribution and effective use of land resources, and the capacity for monitoring and early warning systems. Findings indicate that Dongtai City in Jiangsu Province has rigorously implemented all national land management policies, while also preserving the adaptability of local townships in practical applications, thereby ensuring the consistency of both the quality and quantity of arable land.

Impacting Arable Farmers’ Perception of Processed Organic Fertilizer Use through Farm Demonstration: Evidence from Maize Farmers in Ogun State, Nigeria

Fertilizer use supports productivity in arable farming. However, improper use of inorganic fertilizers can harm the environment, accelerate climate change and slow down the achievement of the 13th SDG. This study examined the use of farm demonstration in improving maize farmers’ perception of organic fertilizer use in the five major towns in Ikenne LGA of Ogun state. Sixty-five maize farmers were selected for the study using multistage sampling technique. Demonstration plots were established near the farmers to observe the agronomic impact of organic fertilizer use. Results showed that respondents’ average farm size was less than 1 hectare, 58% had undulating or sloppy lands which are vulnerable to degradation. Only 22% of the farmers mostly use organic fertilizers which they source from unprocessed animal waste. Only 32% of the farmers are aware of commercially processed organic fertilizers. Using the pair-sample t-test, the perception level of the farmers at the end of the demonstration was significantly higher than before the demonstration (t = 14.87, p <0.05). The study recommended that perception enhancing intervention be introduced to farmers in order to increase the use of clean and safe commercially available fertilizers.

Stochastic Processes Dominate the Assembly of Soil Bacterial Communities of Land Use Patterns in Lesser Khingan Mountains, Northeast China

To meet the demands of a growing population, natural wetlands are being converted to arable land, significantly impacting soil biodiversity. This study investigated the effects of land use changes on bacterial communities in wetland, arable land, and forest soils in the Lesser Khingan Mountains using Illumina MiSeq 16S rRNA sequencing. Soil physicochemical properties and enzyme activities were measured using standard methods, while microbial diversity was assessed through sequencing analysis. Our findings revealed that forest soils had significantly higher levels of total potassium (2.62 g·kg−1), electrical conductivity (8.22 mS·cm−1), urease (0.18 mg·g−1·d−1), and nitrate reductase (0.13 mg·g−1·d−1), attributed to rich organic matter and active microbial communities. Conversely, arable soils showed lower total potassium (1.94 g·kg−1), reduced electrical conductivity, and suppressed enzyme activities due to frequent tilling and fertilization. Wetland soils exhibited the lowest values primarily due to water saturation, which limits organic matter decomposition and microbial activity. Land use changes notably reduced microbial diversity, with conversion from forest to arable land leading to habitat loss. Forest soils supported higher abundances of Proteobacteria (37.59%) and Actinobacteriota (34.73%), while arable soils favored nitrogen-fixing bacteria. Wetlands were characterized by chemoheterotrophic and anaerobic bacteria. Overall, these findings underscore the profound influence of land use on soil microbial communities and their functional roles, highlighting the need for sustainable management practices.

Impact of Forest Landscape Patterns on Ecological Quality in Coastal Cities of Fujian, China, from 2000 to 2020

The Fujian coastal zone, a key region in China’s coastal belt, has experienced significant landscape and ecological changes due to intense human activities. Understanding the relationship between landscape patterns and ecological quality is critical for sustainable development and ecological protection. Taking the coastal cities, including Fuzhou, Xiamen, and Ningde in Fujian Province of China, as a case, the spatio–temporal changes in landscape patterns and the remote sensing-based ecological index (RSEI) during 2000 and 2020 were explored by the Google Earth Engine (GEE) cloud platform, and then their spatial relationships were identified through Pearson correlation analysis and bivariate spatial autocorrelation analysis. The findings reveal that (1) forest land was the dominant landscape in Fuzhou and Ningde, while cropland prevailed in Xiamen. Significant changes occurred in the land use landscape patterns of the three cities, mainly due to a substantial increase in the built-up land and varying degrees of reduction in arable and forest land. At the landscape level, both Fuzhou and Xiamen exhibited increased landscape fragmentation, while Ningde showed a trend of landscape aggregation; at the class level, forest land in Fuzhou and Xiamen exhibited increased fragmentation, whereas in Ningde, it showed an aggregation trend. (2) Between 2000 and 2020, the ecological–environmental quality of Fuzhou and Ningde continuously improved, while the improvement in Xiamen was less significant. Poor and fair ecological environments in the three cities were mainly concentrated in city centers and coastal zones, and areas of ecological quality degradation were primarily concentrated in coastal zones. (3) Correlation analysis indicates that, whether at the landscape level or the class level, the ecological quality of the three cities is significantly negatively correlated with the fragmentation index and significantly positively correlated with the aggregation index. Moreover, the positive correlation between ecological quality and the forest landscape aggregation index, as well as the negative correlation with the forest landscape fragmentation index, are both significantly stronger than those at the landscape level. As urbanization progresses, forest landscape fragmentation intensifies, especially in city centers and coastal areas, having a significant negative impact on ecological quality. These results highlight the importance of landscape pattern management in maintaining ecological quality. This paper provides insights for coastal cities on balancing urban development with ecological preservation in the context of rapid urbanization.

Diversity of Soil Macro Arthropods in the Arable Land of Cotton Zone, North Cameroon

Arthropods constitute the most diverse and dominant species of biodiversity in terrestrial ecosystems. Despite this great abundance, our understanding of their ecological organization and diversity remains unknown in certain habitats. The present study aimed to evaluate the diversity of soil macro-arthropods in the arable land of six localities in the arable land of cotton zone of Cameroon. For this purpose, collections of soil macro-arthropods were carried out using Barber traps and subpots for two consecutive years 2018-2019. During the entire duration of the study, nearly 33.423 soil macro-arthropods were collected belonging to 67 species divided into 11 orders and 27 families. After classification, the most abundant insect groups were Coleoptera (36.9%), Hymenoptera (33.5%), and Orthoptera (22.9%), while the groups of Neuroptera, Hemiptera and Isoptera practically a low level of relative abundance. The proportions of the different families of soil macro-arthropods sampled varies from one locality to another and three large families were in the majority: Formicidae (32.4%), Acrididae (19.5%) and Tenobrionidae (15.7%). Soil macro-arthropod samples collected in Kodek, Sanguere Njoï and Gashiga, respectively recorded the highest species richness as well as the Shanon-Weaver Diversity and Evenness index. In all the arable soils of the localities studied, the soil arthropods tend to have an Equidistribution of individuals and Equitability varies from 0.5 to 0.8. The soil macro-arthropods collected in the arable land of the cotton zone of North Cameroon were mainly phytophagous and saprophagous with a strong beneficial potential in these different ecosystems.

What do urban consumers want? Findings from a discrete choice experiment on the preference for locally produced staple food in Central Africa: Evidence from the Democratic Republic of Congo (DRC)

ABSTRACT A discrete choice experiment in Kinshasa (DRC) investigated urban consumers' preferences between imports and local options for five staple foods – cassava, rice, maize, sugar and cooking oil – under a random utility model. We also examined how distance, packaging and price influenced consumer choice. To assess whether preferences could be manipulated, we introduced two treatment groups – local, import – and a control group. We did not find support for a preference for imports. Instead, there is a statistically significant preference for local products, with the exception of sugar. Respondents are willing to pay 28% more for local food, a premium quantified at 1540 CF (.93 USD) per kg for maize and 1091CF (.66 USD) per litre for oil. Packaging is an attribute of influence as the willingness to pay (WTP) in full remains positive when products interact with packaging and with price. There is demand for local products for which consumers are willing to pay a premium. Yet, DRC imports 1.5 billion dollars of food yearly with only 10% of its arable land exploited. The increased urban consumption of imports does not signify a bias against local products, but rather points to structural issues undermining local supply. DRC needs to develop local value chains linking rural farmers to urban markets through the transformation of local foods to meet urban needs and to convert the WTP into a producer surplus benefiting rural livelihoods.

Dynamic impacts of globalization and environmental performance on renewable energy

This study investigates the dynamic relationships between renewable energy consumption, globalization, trade openness, carbon emissions, and arable land in Somalia from 1990 to 2020 using annual time series data from various sources. Employing econometric models such as the ARDL, FMOLS, and DOLS, the analysis reveals significant long-run relationships. A 1% increase in globalization (LnGI) and trade openness (LnTO) boosts renewable energy consumption (LnRE) by 0.123% and 0.020%, respectively, while a 1% rise in carbon emissions (LnCO2) decreases LnRE by 0.088%. Short-run dynamics show similar trends. These findings, validated by FMOLS and DOLS techniques, emphasize the impact of globalization, trade openness, and carbon emissions on renewable energy adoption. Policymakers should promote global integration and trade openness while enforcing strict carbon reduction measures to support renewable energy use and achieve sustainable development goals.

Achieving land degradation neutrality: land-use planning and ecosystem approach

IntroductionThe research purpose is to scientifically substantiate an integrated approach to solving the problem of land degradation, based on the idea of land degradation neutrality (LDN), taking into account ecosystem services when planning land use to maximize the conservation of natural capital. The methodological basis of the research is the provisions and principles of the concepts of sustainable development, achieving LDN, and ecosystem services, as well as the research results revealing various aspects of land use, particularly their degradation.MethodsThe following research methods are used in the paper: dialectical – to determine the cause-and-effect conditions of land degradation; analysis – to highlight the current state of land use in Ukraine and the factors that have led to land degradation; synthesis – for global trends towards achieving LDN; deduction – to explore the possibility of introducing global experience in achieving LDN in Ukraine; structural-functional analysis – to substantiate the feasibility of introducing an ecosystem approach to land-use planning to achieve LDN.ResultsAs a result of the research, the current land degradation state in Ukraine has been analyzed, and ways of achieving LDN in land-use planning through the prism of an ecosystem approach have been substantiated. Based on statistical data, the current and potential levels of arability of the territory of Ukraine have been calculated by natural-climatic zones, and the areas of eroded arable lands in Ukraine have been determined by the erodibility factor (low-eroded, mediumeroded,and highly-eroded).DiscussionFor the first time, a structural-logical scheme has been developed for organizational-economic support for the effective use of degraded and low-productive agricultural lands in the context of implementing the idea of LDN, which is a tool for rational allocation and use of degraded lands. This scheme can serve as a basis for the development of land-use planning strategies for territorial communities, for institutions, and organizations competent in the field of land management.

Identifying the spatial pattern and driving factors of nitrate in groundwater using a novel framework of interpretable stacking ensemble learning

Groundwater nitrate contamination poses a potential threat to human health and environmental safety globally. This study proposes an interpretable stacking ensemble learning (SEL) framework for enhancing and interpreting groundwater nitrate spatial predictions by integrating the two-level heterogeneous SEL model and SHapley Additive exPlanations (SHAP). In the SEL model, five commonly used machine learning models were utilized as base models (gradient boosting decision tree, extreme gradient boosting, random forest, extremely randomized trees, and k-nearest neighbor), whose outputs were taken as input data for the meta-model. When applied to the agricultural intensive area, the Eden Valley in the UK, the SEL model outperformed the individual models in predictive performance and generalization ability. It reveals a mean groundwater nitrate level of 2.22 mg/L-N, with 2.46% of sandstone aquifers exceeding the drinking standard of 11.3 mg/L-N. Alarmingly, 8.74% of areas with high groundwater nitrate remain outside the designated nitrate vulnerable zones. Moreover, SHAP identified that transmissivity, baseflow index, hydraulic conductivity, the percentage of arable land, and the C:N ratio in the soil were the top five key driving factors of groundwater nitrate. With nitrate threatening groundwater globally, this study presents a high-accuracy, interpretable, and flexible modeling framework that enhances our understanding of the mechanisms behind groundwater nitrate contamination. It implies that the interpretable SEL framework has great promise for providing valuable evidence for environmental management, water resource protection, and sustainable development, particularly in the data-scarce area.

ASSESSMENT OF LOSSES IN THE SUGARCANE HARVESTING PROCESS IN THE IVINHEMA VALLEY REGION

Brazil has approximately 18% of its entire arable land destined for sugarcane production. This raw material is of great economic importance to the country, with production of by-products with high added value, such as sugar, alcohol and ethanol. Some states with larger territorial extension are responsible for large-scale production, mainly in the Central-West, Southeast and North regions of the country. The most prominent state, with 53% of all sugarcane cultivation, is São Paulo, followed by Minas Gerais, Goiás and Mato Grosso do Sul. Given this, with large-scale production, other challenges begin to emerge, such as the need for cultivation within technological aspects that prevent the occurrence of losses in the production system, from the establishment of sugarcane fields and especially their harvesting and transportation, until the arrival of the raw material within the industrial complex for transformation into by-products. The objective of this study was to analyze and quantify the percentage of losses between the harvesting process and receipt in the industry of freshly harvested sugarcane raw material in the Ivinhema Valley region - Mato Grosso do Sul. The methodology used was a case study, which comprised three months of analysis. With the data analyzed, it was possible to verify that the highest percentage of losses occurs for the portion of producers who carry out their own cultivation, sending their raw material to the industry, generating around 44.02% in losses between the total harvested and received. In addition, harvests further away from the industrial complex presented greater losses of around 9.85% in mineral and vegetable impurities, evidencing that transportation may have influenced the time of receipt.

How Can Land Use Management in Traditional Cultural Landscapes Become a Policy Instrument for Soil Organic Carbon Sequestration and Climate Change Mitigation? A Transylvanian Case Study

Changes in land use from high-nature-value grasslands to arable fields reduce the organic carbon stock in soil, increasing atmospheric carbon concentrations. Maintaining grasslands through traditional agricultural techniques can mitigate climate change by transferring atmospheric carbon to the soil. Benefits of soil organic carbon sequestration include improved soil properties and enhanced ecosystem services and biodiversity. With Romania’s ratification of the Paris Agreement, it is crucial to review climate-related agricultural policies and incentivize carbon sequestration practices in organic soils. This paper presents a soil carbon study in Transylvania’s Târnava Mare region, Romania, known for its preserved cultural landscapes. Soil samples were taken at a depth of 60 cm to assess organic carbon pools under grassland and arable land management across three soil classes: Cernisoils, Hidrisoils, and Luvisoils. Several statistical tests were applied to evaluate the most significant drivers of soil organic carbon sequestration including land use, soil class, and soil depth. The results indicate that land management has the largest impact, with grasslands storing 45% more carbon than arable land on average. This finding should be integrated into national climate action plans, prioritizing the preservation of grasslands and sustainable agricultural practices to support soil organic carbon sequestration.

The Cross-Verification of Different Methods for Soil Erosion Assessment of Natural and Agricultural Low Slopes in the Southern Cis-Ural Region of Russia

The conventional measuring methods (runoff plots and soil morphological comparison) and models (WaTEM/SEDEM and regional model of Russian State Hydrological Institute (SHI)) were tested with regard to the Southern Cis-Ural region of Russia, along with data from rainfall simulation for assessing soil erosion. Compared with conventional methods, which require long-running field observations, using erosion models and rainfall simulation is less time-consuming and is found to be fairly accurate for assessing long-term average rates of soil erosion and deposition. In this context, 137Cs can also be used as a marker of soil redistribution on the slope. The data of soil loss and sedimentation rates obtained by using conventional measuring methods were in agreement with the data based on the used contemporary modeling approaches. According to the erosion model calculations and data on the fallout of radionuclides in the Southern Cis-Ural (54°50–25′ N and 55°44–50′ E), the average long-term annual soil losses were ~1.3 t·ha−1 yr−1 in moderate (5°) arable slopes and ~0.2 t·ha−1 yr−1 in meadows. In forests, surface erosion is negligible, or its rates are similar to the rate of soil formation of clay–illuvial chernozems. The rates of soil erosion and sediment deposition on the arable land obtained using different methods were found to be very close. All the methods, including the WaTEM/SEDEM, allowed us to measure both soil erosion and intra-slope sedimentation. The regional SHI model fairly accurately assesses soil erosion in the years when erosion events occurred; however, soil erosion as a result of snowmelt did not occur every year, which should be taken into account when modeling. The concentrations of 137Cs in the topsoil layer (0–20 cm) varied from 0.9 to 9.8 Bq·kg−1, and the 137Cs inventories were 1.6–5.1 kBq·m−2, with the highest values found under the forest. The air dose rate in the forest was higher than in open areas and above the average of 0.12 μSv·h−1 on the slope (0.1 μSv·h−1 in the meadow and 0.08 μSv·h−1 on the arable land), with the value increasing from the watershed to the lower part of the slope in all the areas. The γ-background level in the studied ecosystems did not exceed the maximum permissible levels.

Yield variation and yield potential of organic arable crops in Finland derived from statistical data

This study aims to expand and diversify the analysis of crop yields in organic production by utilising the long-term statistical data reported by farmers. We examined the variation of the harvested yields of organic arable crops (season’s ad hoc harvest) on Finnish organic farms and determined the yield potential for different organic crops and in comparison, with conventional counterparts. When comparing median yields per ha, organic yields were on average 65% of conventional yields. The mean yield difference significantly differed between plant species. Among the analysed crops, faba bean performed best, gaining on average 84% of conventional yields, while organic cereals attained an average of 54–68% of conventional yields. The ratio of organic and conventional median yields was compared between geographical regions, and significant regional differences were found. The performance of organic cereals remained stable over the years, but the relative performance of the organic grain legumes, pea and faba bean, depended more on growing conditions. An average yield gap between the best-performing and medianfarms was 38% for organic farms and 28% for conventional farms. This indicates that Finnish organic farms have greater potential to improve the yield level than conventional farms.

Organic cropping systems balance environmental impacts and agricultural production

Agriculture provides food to a still growing population but is a major driver of the acceleration of global nutrient flows, climate change, and biodiversity loss. Policies such as the European Farm2Fork strategy aim to mitigate the environmental impact of land-use by fostering organic farming. To assess long-term environmental impact of organic food production we synthesized more than four decades of research on agronomic and environmental performance of the oldest system comparison experiment on organic and conventional cropping systems (DOK experiment). Two organic systems (bioorganic and biodynamic) are compared with two conventional (manure-based integrated and mineral-based) systems all with the same arable crop rotation including grass-clover, and manure from livestock integrated in all except the mineral-based system. Organic systems used 92% less pesticides and 76% less mineral nitrogen than conventional systems. Nitrogen use efficiency, that also considers biological nitrogen fixation, was above 85% for all systems. Organic fertilization with farmyard manure maintained or increased soil carbon and nitrogen stocks in the long term, especially in the biodynamic system with manure compost. Conventional mineral-based cropping reduced soil organic carbon and nitrogen stocks. Higher soil organic carbon stocks in organic cropping did not translate to increased N2O emissions, which were the main driver for 56% lower soil-based, area-scaled climate impact compared to the integrated conventional system with manure. Organic cropping systems, especially compost-based biodynamic, showed enhanced soil health, richness of micro- and macrofauna and weed species. Highest yields were achieved in integrated conventional system, with highest total nitrogen inputs and enhanced soil health compared to pure mineral fertilization. Yet, these benefits come at the cost of lower nitrogen use efficiency and higher N2O emissions. Despite a rigorous reduction of inputs yields of the organic systems achieved 85% of the conventional systems. We demonstrate at field level that organic cropping systems with reduced external nutrient inputs have less climate impact and a larger in-situ biodiversity, while providing a fertile ground for the future development of sustainable agricultural production systems.

Isolation and Identification of Multi-Traits PGPR for Sustainable Crop Productivity Under Salinity Stress

High salinity poses a significant threat to arable land globally and contributes to desertification. Growth-promoting rhizobacteria assist plants in mitigating abiotic stresses and enhancing crop productivity through the production of siderophores, exopolysaccharides (EPS), solubilisation of phosphate, indole-3-acetic acid (IAA), and other secondary metabolites. This study aimed to isolate, identify, and characterise bacteria that exhibit robust growth-promoting properties. A total of 64 bacterial isolates from the rhizosphere of Miscanthus sinensis were evaluated for plant growth-promoting (PGP) traits, including IAA, EPS, siderophores, and solubilisation of phosphate. Among them, five isolates were selected as plant growth-promoting rhizobacteria (PGPR) based on their PGP features and identified via 16S rRNA sequencing: Enterococcus mundtii strain INJ1 (OR122486), Lysinibacillus fusiformis strain INJ2 (OR122488), Lysinibacillus sphaericus strain MIIA20 (OR122490), Pseudomonas qingdaonensis strain BD1 (OR122487), and Pseudomonas qingdaonensis strain MIA20 (OR122489), all documented in NCBI GenBank. BD1 demonstrated a higher production of superoxide dismutase (SOD) (17.93 U/mg mL), catalase (CAT) (91.17 U/mg mL), and glutathione (GSH) (0.18 U/mg mL), along with higher concentrations of IAA (31.69 µg/mL) and salicylic acid (SA) (14.08 ng/mL). These isolates also produced significant quantities of amino and organic acids. BD1 exhibited superior PGP traits compared to other isolates. Furthermore, the NaCl tolerance of these bacterial isolates was assessed by measuring their growth at concentrations ranging from 0 to 200 mM at 8-h intervals. Optical density (OD) measurements indicated that BD1 and INJ2 displayed significant tolerance to salt stress. The utilisation of these isolates, which enhances plant growth and PGP traits under salt stress, may improve plant development under saline conditions.

Isolation, Identification, and Application of Endophytic Fungi from Lavandula stoechas L.: Mitigating Salinity Stress in Hydroponic Winter Cereal Fodder

Soil and irrigation water salinity is a growing global problem affecting farmland, due to poor agricultural practices and climate change, leading to reduced crop yields. Given the limited amount of arable land and the need to boost production, hydroponic systems offer a viable solution. Additionally, endophytic fungi have been shown to mitigate salinity effects through symbiosis with plants. This study evaluated three endophytic fungi isolated from Lavandula stoechas L. in the grasslands of Extremadura (i.e., Diplodia corticola L11, Leptobacillium leptobactrum L15, and Cladosporium cladosporioides L16) for their ability to improve hydroponic forage production under saline conditions. In vitro experiments were conducted assessing plant growth promotion and fungal growth under salinity, followed by research evaluating the impact of fungal inoculation on hydroponic wheat (Triticum aestivum L.) and barley (Hordeum vulgare L.) forages irrigated with NaCl solutions (0, 100, and 200 mM). The results showed improved fungal growth and production of plant growth-promoting substances, which could explain the improved plant germination, shoot and root length, fresh and dry weight, and yield of inoculated plants growing under salinity. Plants inoculated with L15 or L16 showed the best performance overall. L15 demonstrated broader bioactivity in vitro, potentially explaining its superior performance in both wheat and barley growth. Conversely, L16 was more effective in barley, while L11 was beneficial in wheat but detrimental in barley. This study provides a preliminary exploration of the capabilities of these fungi and their optimization for hydroponic forage production.

Radiation Limits the Yield Potential of Main Crops Under Selected Agrivoltaic Designs—A Case Study of a New Shading Simulation Method

Agrivoltaics (APVs) represent a growing technology in Europe that enables the co-location of energy and food production in the same field. Photosynthesis requires photosynthetic active radiation, which is reduced by the shadows cast on crops by APV panels. The design of the module rows, material, and field orientation significantly influences the radiation distribution on the ground. In this context, we introduce an innovative approach for the effective simulation of the shading effects of various APV designs. We performed an extensive sensitivity analysis of the photovoltaic (PV) geometry influence on the ground-incident radiation and crop growth of selected cultivars. Simulations (2013–2021) for three representative arable crops in eastern Austria (winter wheat, spring barley, and maize) and seven different APV designs that only limited to the shading effect showed that maize and spring barley experienced the greatest annual above-ground biomass and grain yield reduction (up to 25%), with significant differences between the APV design and the weather conditions. While spring barley had similar decreases within the years, maize was characterized by high variability. Winter wheat had only up to a 10% reduction due to shading and a reduced photosynthetic performance. Cold/humid/cloudy weather during the growing season had more negative yield effects under APVs than dry/hot periods, particularly for summer crops such as maize. The lowest grain yield decline was achieved for all three crops in the APV design in which the modules were oriented to the east at a height of 5 m and mounted on trackers with an inclination of +/−50°. This scenario also resulted in the highest land equivalent ratios (LERs), with values above 1.06. The correct use of a tracker on APV fields is crucial for optimizing agricultural yields and electricity production.