Agricultural Soil Management Research Articles

Fungal communities in boreal soils are influenced by land use, agricultural soil management, and depth.

Land use and agricultural soil management affect soil fungal communities that ultimately influence soil health. Subsoils harbor nutrient reservoir for plants and can play a significant role in plant growth and soil carbon sequestration. Typically, microbial analyses are restricted to topsoil (0-30cm) leaving subsoil fungal communities underexplored. To address this knowledge gap, we analyzed fungal communities in the vertical profile of four boreal soil treatments: long-term (24 years) organic and conventional crop rotation, meadow, and forest. Internal transcribed spacer (ITS2) amplicon sequencing revealed soil-layer-specific land use or agricultural soil management effects on fungal communities down to the deepest measured soil layer (40-80cm). Compared to other treatments, higher proportion of symbiotrophs, saprotrophs, and pathotrophs + plant pathogens were found in forest, meadow and crop rotations, respectively. The proportion of arbuscular mycorrhizal fungi was higher in deeper (>20cm) soil than in topsoil. Forest soil below 20cm was dominated by fungal functional groups with proposed interactions with plants or other soil biota, whether symbiotrophic or pathotrophic. Ferrous oxide was an important factor shaping fungal communities throughout the vertical profile of meadow and cropping systems. Our results emphasize the importance of including subsoil in microbial community analyses in differently managed soils.

Farming and biochar in the EU and the road to sustainability: Drawing connections through the Common Agricultural Policy and the regulation of organic and carbon farming

AbstractConsidering the significant impact of agriculture on the environment, there is corresponding potential residing in proper management of agricultural soils and in farming. Agricultural systems are instrumental to achieving climate and environmental goals and for paving the road towards sustainability. However, this requires a transition from business‐as‐usual agriculture and farming, which must be supported by policy and legislation through systemic and coordinated measures. Other more pointed measures, such as the targeted use of certain technologies, for example, the proper use of biochar, can also be leveraged. But what is the state of play in the pursuit of sustainability in farming in the EU legislation and policy? How significant are these developments for biochar in the transition towards sustainability? This article considers these issues in relation to three different yet connected policy and legislative fields in the broader agriculture domain: the Common Agricultural Policy, organic farming and the emerging domain of carbon farming.

Impact of Biochar on Nitrogen-Cycling Functional Genes: A Comparative Study in Mollisol and Alkaline Soils.

Biochar has gained considerable attention as a sustainable soil amendment due to its potential to enhance soil fertility and mitigate nitrogen (N) losses. This study aimed to investigate the effects of biochar application on the abundance of key N-cycling genes in Mollisol and alkaline soils, focusing on nitrification (AOA, AOB, and nxrB) and denitrification (narG, norB, and nosZ) processes. The experiment was conducted using soybean rhizosphere soil. The results demonstrated that biochar significantly altered the microbial community structure by modulating the abundance of these functional genes. Specifically, biochar reduced narG and nosZ abundance in both soil types, indicating a potential reduction in N2O emissions. In contrast, it promoted the abundance of nxrB, particularly in alkaline soils, suggesting enhanced nitrite oxidation. The study also revealed strong correlations between N-cycling gene abundances and soil properties such as pH, EC (electrical conductivity. Biochar improved soil pH and nutrient availability, creating favorable conditions for AOB and Nitrospira populations, which play key roles in ammonia and nitrite oxidation. Additionally, the reduction in norB/nosZ ratios in biochar-treated soils suggests a shift towards more efficient N2O reduction. These findings highlight biochar's dual role in enhancing soil fertility and mitigating greenhouse gas emissions in Mollisol and alkaline soils. The results provide valuable insights into the sustainable management of agricultural soils through biochar application, emphasizing its potential to optimize nitrogen-cycling processes and improve soil health. Further research is needed to explore the long-term impacts of biochar on microbial communities and nitrogen-cycling under field conditions.

Reducing Cd and Pb Accumulation in Potatoes: The Role of Soil Passivators in Contaminated Mining Soils.

This work aimed to explore safe techniques for the utilization of farmland surrounding mining areas contaminated with heavy metals-specifically cadmium (Cd) and lead (Pb)-in order to achieve food security in agricultural production. A potato variety (Qingshu 9) with high Cd and Pb accumulation was used as the test crop, and seven treatments were set up: control (CK), special potato fertilizer (T1), humic acid (T2), special potato fertilizer + humic acid (T3), biochar (T4), calcium magnesium phosphate fertilizer (T5), and biochar + calcium magnesium phosphate fertilizer (T6). The remediation effect of the combined application of different passivators on the accumulation of cadmium and lead in potatoes in the contaminated soil of a mining area was studied. The results showed that, compared with CK, all passivator treatments improved the physical and chemical properties of the soil and reduced the available Cd and Pb content in the soil and in different parts of potatoes. The T6 treatment yielded the most significant reduction in the available Cd and Pb content in the soil, the Cd and Pb content in the potato pulp, and the enrichment factor (BCF) and transfer factor (TF) of the potatoes. Compared with T4 and T5, the content of available Cd in the soil decreased by 1.22% and 4.71%, respectively; the soil available Pb content decreased by 3.13% and 3.02%, respectively; the Cd content in the potato pulp decreased by 68.08% and 31.02%, respectively; and the Pb content decreased by 31.03% and 20.00%, respectively. The results showed that the application of biochar combined with calcium magnesium phosphate fertilizer had a better effect in terms of reducing the available Cd and Pb content in the soil and the Cd and Pb content in the potato flesh compared to their individual application. Biochar and calcium magnesium phosphate fertilizer can synergistically increase the content of soil available nutrients and reduce the activity of heavy metals in the soil to prevent the transfer and accumulation of cadmium and lead to potatoes, as well as improve their yield and quality. The results of this study provide technical support for safe potato planting and agricultural soil management.

Predictive soil nutrient modeling with spectral data and machine learning in four major Indonesian Provinces located on the island of java

Abstract This study provides a detailed analysis of predicting soil nutrient content using spectral data and machine learning techniques in four Indonesian provinces: West Java, Central Java, Yogyakarta (DIY), and East Java. The research collected 145 soil samples to predict various key soil nutrients, such as N Total, NH4, NO3, P Total, P Available, K Total, K Available, C Organic, and pH. The study used linear regression (LR) and deep neural networks (DNN) with a deep cross-network (DCN) architecture to model the relationships between soil spectral data and nutrient content. LR was used as a baseline model to understand linear relationships between spectral features and soil properties and identify the most influential spectral frequencies in predicting soil nutrient levels. On the other hand, the DNN model captured complex, non-linear patterns within the data. Results showed that while the DNN model displayed advanced capabilities, the LR model generally outperformed it in predictive accuracy, particularly for nutrients like N-Total, P-Total, and K-Total. The findings highlight the potential of combining spectral data with advanced machine-learning techniques for precise soil nutrient estimation, which could significantly enhance agricultural productivity and soil management practices in Indonesia.

Transforming Irrigated Agriculture in Semi-Arid and Dry Subhumid Mediterranean Conditions: A Case of Protected Cucumber Cultivation

Pressure from population growth and climate change stress the limited water resources in the Mediterranean region and threaten food security and social stability. Enhancing food production requires the transformation of irrigation systems and enhancement of local capacity for sustainable water and soil management in irrigated agriculture. The aim of this work is the conversion of traditional irrigation practices, by introducing the practice of optimal irrigation scheduling based on local ET estimation and soil moisture monitoring, and the use of continuous feeding by fertigation to enhance both water and nutrient use efficiency. For this, two trials were established between August and November 2023 in two different pedoclimatic zones (Serein and Sultan Yacoub) of the inner Bekaa Plain of Lebanon, characterized by semi-arid and dry subhumid conditions and different soil types. Greenhouse cucumber was tested to compare the prevailing traditional farmers’ practices with the advanced, technology-based, methods of water management. Results showed a significantly higher amount of water applied by the farmers to the protected cucumber, with a potential for average saving of 105 mm of water applied in each season by improved practices. Water input in the traditional practices revealed potential stress to plants. With more than 20% increase in cucumber yield by the transformed practices, a general trend was observed in the fertilization approach and amounts, resulting in lower nutrient recovery in the farmer’s plots. The science-based practices of water and nutrient management showed higher application and agronomic water use efficiency of full fertigation, exceeding 60%, associated with double and triple higher nitrogen use efficiency, compared to those results obtained by the traditional water and fertilizer application methods. The monitored factors can contribute to severe economic and environmental consequences from nutrient buildup or leaching in the soil–groundwater system in the Mediterranean region.

Insights into pupal development of Bactrocera dorsalis: factors influencing eclosion

In the life cycle of the oriental fruit fly where larvae reside within fruits and adults exhibit high activity, the pupal stage occurs in the soil, closely tied to agricultural soil management. This study investigates the impact of four variables (body orientation, burial depth, soil particle size, and pH) on Bactrocera dorsalis’ physiological preferences, eclosion rates, and pupal stage duration. Notably, body orientation, burial depth, soil texture (particle size), and pH affect eclosion rates. The fruit fly demonstrates a preference for a supine position during eclosion, with average eclosion rates of 97.33%, contrasting with decreases to 78.00% in a head-down position. Soil with mixed particle sizes is detrimental to pupal eclosion, reducing the eclosion rate to 56.67%. And at a pH of 9.98, eclosion rates decrease to 16.67%. These factors significantly influence eclosion rates However, these factors do not significantly alter the duration of the pupal stage, with mean changes not exceeding one day when experimental conditions are modified. These findings suggests that soil manipulations affecting these variables could reduce eclosion rates without compromising the uniformity of adult emergence. This study provides a foundation for environmentally friendly pest control practices and addresses gaps in the pupal stage research of the oriental fruit fly.

Unveiling the impact of low-molecular-weight organic acids on enrofloxacin sorption in North China agricultural soil: Insights and implications

Low-molecular-weight organic acids (LMWOAs) play a crucial role as components of dissolved organic matter in soil, influencing the sorption/desorption, degradation, and plant uptake of diverse pollutants within the agricultural soil ecosystem. This study delves into the sorption behavior and mechanism of the fluoroquinolone antibiotic enrofloxacin (ENR) on agricultural soil in North China, focusing on the impact of LMWOAs. Through batch equilibrium experiments, we explored the sorption/desorption kinetics of ENR under varying conditions such as temperature, pH, ion strength, and ion type, with the addition of acetic acid, oxalic acid, and citric acid individually. Our findings reveal that the sorption and desorption kinetics of ENR—whether with or without LMWOAs—conformed well to the pseudo-second-order kinetic model (R2 ≥ 0.997). The presence of LMWOAs notably enhanced ENR sorption while impeding desorption in soil, with oxalic acid demonstrating the highest promotion effect followed by acetic acid and citric acid. Moreover, the sorption capacity and affinity of ENR decreased with rising solution pH, dropping from 96.8%-98.5% to 30.9%–34.4%. Acidic conditions favored ENR retention in soil, with inhibition of sorption escalating alongside increasing ionic strength. LMWOAs, soil solution pH, and coexisting ions emerge as pivotal factors shaping ENR sorption behavior. Furthermore, LMWOA presence intensified desorption hysteresis of ENR on soil, with a desorption hysteresis coefficient (HI) ≤ 0.124. These results suggest that LMWOAs restrict ENR mobility in the local soil environment, heightening the risk of its accumulation in soil and crops. This study offers valuable insights into the intricate interplay among LMWOAs, ENR sorption dynamics, and environmental outcomes, underscoring the importance of understanding such complexities in agricultural soil management.

Assessment of nature-based solutions for water resource management in agricultural environments: a stakeholders' perspective in Southern Italy.

This paper explores the potential implementation of Nature-Based Solutions (NBSs) in agriculture, specifically focusing on soil and water management in Southern Italy, particularly in the Apulia and Basilicata regions. Through a tailored questionnaire, it investigates farmers' perceptions of the utility of NBSs, addressing key issues in the region and evaluating their role in addressing soil and water management challenges. Findings reveal primary challenges such as drought, floods, and water pollution, with soil erosion being a major concern. Several NBSs, including wetlands and bioswales, demonstrate consistent utility and performance, while disparities exist for agroforestry and strip cropping. The study underscores a significant gap in the economic valuation of NBSs, emphasizing the need for comprehensive assessments that incorporate livability improvements, water quality enhancement, and socio-cultural benefits. Additionally, an analysis of NBS implementation across Italian agriculture reveals limited case studies, suggesting the need for strategic expansions to meet Sustainable Development Goals. This research offers critical insights into the effectiveness and challenges of NBSs in agricultural soil and water management, advocating for enhanced stakeholder engagement and the development of multidimensional evaluation frameworks to support sustainable practices.

Salinity challenges and adaptive strategies in salinization-affected coastal Bangladesh: Implications for agricultural sustainability and water resource management

Abstract Salinization has become a rising global concern due to its notable effects on agriculture and freshwater resources. Coastal region of Bangladesh has been struggling with elevated levels of soil and water salinity, exacerbated by storm surges and rising sea levels. We assessed nutrient and salinity contents in agricultural and homestead lands, and the level of salinity in pond and canal water in six sub-districts in coastal Bangladesh. Finally, using household (HH) survey, focus group discussion (FGD) and key informant interview (KII), we explored the adaptive practices and challenges of salinity issues in agriculture and drinking water management. Soil nitrogen, phosphorus, and potassium contents exhibited significant variations across the sub-districts, which reflect the diversity of agricultural practices and soil management strategies. However, there was no notable difference in soil salinity across the sub-districts, which underscores the commonality of soil salinity as a pressing concern. Shyamnagar (13.99 dS m−1) recorded the highest level of pond water salinity, followed by Assasuni (13.96 dS m−1), Dacope (13.91 dS m−1), Koyra (13.58 dS m−1), Morrelganj (13.33 dS m−1), and Mongla (13.19 dS m−1) sub-districts, which highlights that water salinity decreased from exposed coast to the landward areas. Respondents in HH surveys, FGDs and KIIs identified salinity as a major challenge in agriculture and drinking water. Furthermore, climate-related stresses were recognized as significant challenges impacting crop productivity. The research highlights the feasibility of rainwater harvesting, with 89%–100% of HHs harvest rainwater in HH tanks, as an effective adaptive practice for managing drinking water. The study emphasizes the positive impact of vermicompost in reducing soil salinity levels, which is demonstrated by the 43%–88% of HHs using this practice, indicating its potential as a nature-based solution to address soil salinization. The findings underscore the need for resilient agricultural systems and sustainable water management approaches to tackle these challenges.

Barriers of adopting sustainable soil management practices for organic and conventional farming systems

There is a general consensus among stakeholders about the benefits of sustainable soil management practices for soil health, yet their implementation lags behind expectations. The aim of this paper is to analyse factors supporting or hindering the implementation of sustainable soil management practices in conventional and organic farming systems. This is achieved using a Logit model, based on penalized maximum likelihood estimation on survey data by 76 farmers from 10 federal states in Germany. Affected factors were categorized in two main groups: agricultural soil management practices, and barriers to their implementation. The measures for soil improving agricultural management included (I) structural landscape elements, (II) organic fertilization, (III) diversified crop rotation, (IV) permanent soil cover (V) conservation tillage, (VI) reduced weight pressure, and (VII) optimized timing of wheeling. Results show differences in preferences between conventional and organic farmers for key sustainable soil management practices, including conservation tillage, optimized wheeling timing, reduced weight pressure, and diversified crop rotation. Economic constraints decrease crop rotation diversification in conventional systems by 14%. Conservation tillage raises the chance of a farm being conventional by 16%, while optimizing wheeling timing reduces it by 60%, highlighting soil compaction concerns among organic farmers. Marginal effects confirm that economic factors, not knowledge, are the main barriers to sustainable soil management. Inconsistent policies, lack of support, and insufficient financial incentives from government institutions can hinder the willingness of farmers to adopt these practices, further exacerbating the barriers to adoption.

Evaluating machine learning performance in predicting sodium adsorption ratio for sustainable soil-water management in the eastern Mediterranean

Soil salinization is a critical global issue for sustainable agriculture, impacting crop yields and posing a threat to achieving the Sustainable Development Goal (SDG) of ensuring food security. It is necessary to monitor it in detail and uncover its underlying factors at a regional scale. In this context, the present study aimed to evaluate soil health in the eastern Mediterranean region by using the Sodium Adsorption Ratio (SAR) as an indicator of soil salinity in three distinct soil horizons. The main objective of the research was to evaluate the performance of four machine learning (ML) models, including Random Forest (RF), Nu Support Vector Regression (NuSVR), Artificial Neural Network-Multi Layer Perceptron (ANN-MLP), and Gradient Boosting Regression (GBR), for accurate prediction of SAR following the Recursive Feature Elimination (RFE) as a feature selection method. Moreover, SHapely Additive exPlanations (SHAP) was applied as sensitivity analysis to identify the most influential covariates. Main findings of the research revealed that the average clay content in the surface horizon (H10-25cm) was 50.5% ± 10.4, which significantly increased to 57.5% ± 8.7 (p < 0.05). No significant mean differences were detected between the studied horizons for SAR and Na+. ML output revealed that NuSVR outperformed other algorithms in accurately predicting outcomes during both the training and testing stages. Moreover, Scenario 2 (SC2) with seven selected features from the RFE method facilitated highly accurate SAR predictions. Overall, the performance of ML models is ranked as NuSVR > GBR > ANN-MLP > RF. Lastly, SHAP sensitivity analysis identified CEC, Ca+2, Mg+2, and Na+ as the most influential variables for SAR prediction in both the training and testing stages. Hence, the research yielded valuable insights for efficient agricultural soil management at a regional level using state-of-the-art technology.

Efficiency of the Combination of Vermicompost and Zero Valent Iron for the Remediation of Lead, Copper and Aluminum

Aims: Evaluate the efficiency of the combination of vermicompost and zero -valent iron for the remediation of two types of soil with lead, copper and aluminum. Study Design: Observational technique and analysis of soil samples contaminated by mining. Place and Duration of Study: It was applied in the greenhouse in the district of San Juan de Lurigancho and in the Casapalca mining industry located in the district of San Mateo, in the months of February and September 2023. Methodology: The analysis of soil samples contaminated by mining was carried out through the addition of vermicompost amendments and zero -valent iron, seeking to observe the physicochemical changes of the soil and determine the bioavailability of lead, copper and aluminum in the soil. Using the atomic absorption spectrometer, a pH meter; the loss on ignition method, to determine organic matter; A 1.0mol L-1 ammonium acetate solution was used for the cation exchange capacity (CEC) of the soil and vermicompost and for the determination of total potassium (K) method 3050b acid digestion of sediments, sludge and soils was used. Results: The highest efficacy for the remediation of lead, copper and aluminium contaminated soils is produced with a vermicompost dose of 3:1, with 3 kilos of soil + 60 LC and Fe ° (45 g LC + 15 Fe °); obtaining the highest reductions in Pb from 942. 6 mg/kg to 698.5 mg/kg in its final concentration, also for Cu from an initial concentration of 462.4 mg/kg, 323.8 mg/kg was obtained in its final concentration and for Al from a concentration of 9190.2 mg/kg resulted in 6823.8 mg/kg. Obtaining a maximum lead removal of 35.57%, copper 29.60% and aluminium 27.62% from the Casapalca soil. The highest efficiency of the dose of zero valent iron for the remediation of contaminated soils was at a ratio of 3:1 with a dose of 3 kg of soil + 60 Fe° and LC (45 g Fe° + 15LC). Likewise, plant uptake from 2 months after harvest of Cucumis sativus (cucumber) in the remediation of contaminated soils was efficient for all three types of metals at a dose ratio of 5:1, with Al showing a higher uptake in all cases. Conclusion: The effectiveness of remediation of soils contaminated with heavy metals through the combination of vermicompost and zero valent iron highlights the importance of considering sustainable and ecological approaches to agricultural soil management, which could have significant implications for the protection of the environment and human health in areas with contaminated soils.

Improved mapping of heavy metals in agricultural soils using machine learning augmented with spatial regionalization indices

The accurate spatial mapping of heavy metal levels in agricultural soils is crucial for environmental management and food security. However, the inherent limitations of traditional interpolation methods and emerging machine-learning techniques restrict their spatial prediction accuracy. This study aimed to refine the spatial prediction of heavy metal distributions in Guangxi, China, by integrating machine learning models and spatial regionalization indices (SRIs). The results demonstrated that random forest (RF) models incorporating SRIs outperformed artificial neural network and support vector regression models, achieving R2 values exceeding 0.96 for eight heavy metals on the test data. Hierarchical clustering for feature selection further improved the model performance. The optimized RF models accurately predicted the heavy metal distributions in agricultural soils across the province, revealing higher levels in the central-western regions and lower levels in the north and south. Notably, the models identified that 25.78 % of agricultural soils constitute hotspots with multiple co-occurring heavy metals, and over 6.41 million people are exposed to excessive soil heavy metal levels. Our findings provide valuable insights for the development of targeted strategies for soil pollution control and agricultural soil management to safeguard food security and public health.

Recent Innovation in Precision Agriculture and their Impact on Crop and Soil Health: A Compressive Review

The maintenance of soil fertility and on-farm research or demonstrations might be enhanced by precision agricultural technologies. Using state-of-the-art technology, precision agriculture boosts agricultural output without negatively affecting the environment. Utilising cutting-edge technology and data analysis, precision agriculture aims to boost production, minimise waste, and maximise crop yields. This might be a viable approach to addressing some of the main problems facing modern agriculture, such feeding an expanding global population while lessening its impact on the environment. The application of precision agriculture starts with the collection of real-time data from various sources, such as satellite imagery, remote sensing, global positioning systems, geographic information systems, drones, soil sensors, and weather stations. Precision agriculture has become essential in addressing the challenges posed by a growing global population, climate change, and resource constraints. Recognising within-field variability and providing chances for differentiating treatment of sections within a field or industrial unit are what fuel demand for precision agriculture. Precision agriculture technology plays an important part in sustainable soil and crop management in modern agriculture by lowering crop production inputs and managing lands in an ecologically responsible way.

Amended soils with weathered coal exhibited greater resistance to aggregate breakdown than those with biochar: From the viewpoint of soil internal forces

Soil erosion is the first threat to soil functions. Reducing the soil aggregate breakdown strength is a key step to improve the soil’s ability to resist rainfall splash erosion. Soil internal forces have been found to be the initial and important forces driving aggregate turnover. The application of exogenous organic materials can effectively improve soil aggregate stability and the resistance to rainfall erosion of agricultural soils. However, from the perspective of soil internal forces, information about the reduction effects of the exogenous organic materials application on soil aggregate breakdown is scarce, especially in comparing the effects of different materials. In this study, weathered coal and biochar were individually applied to loamy clay soil at rates of 0 %, 1 %, 2 %, and 3 % (w/w). Soil internal forces, aggregate breakdown strength, and splash erosion rate of different amended soils were then examined after four years. The results showed that compared with unamended soils (0 %), both weathered coal and biochar applications clearly increased the van der Waals attractive pressure and thus decreased the positive net pressure between soil particles. Additionally, these materials reduced soil aggregate breakdown strength and splash erosion rate. The application effects of the two materials were increased with their application rates. Under a lower electrolyte concentration in soil solution (0.0001 mol L−1), the aggregate breakdown strength in the soils amended with weathered coal was lower than that with biochar by 9.6 %, 23.2 %, and 17.7 % (when the diameter of broken aggregate was < 10 μm) and by 10.3 %, 20.8 %, and 17.5 % (when the diameter of broken aggregate was < 20 μm) at the 1 %, 2 %, and 3 % application rates, respectively (P < 0.05). Additionally, soils amended with weathered coal exhibited lower splash erosion rates compared to those amended with biochar, particularly at the higher application rate of 3 %. From the viewpoint of soil internal forces, weathered coal appears to be a suitable exogenous organic material for improving soil aggregate stability and anti-erosion ability during rainfall events. Our findings provide valuable insights into utilizing exogenous materials to improve soil resistance to rainfall splash erosion, assisting agricultural soil management in areas frequently affected by rainfall erosion.

Contributions of Different Perennial Grass Species and Their Roots’ Characteristics to Soil Organic Carbon Accumulation

Growing perennial grasses is often cited as one of the possible and most affordable solutions for mitigating climate change. This practice is also recommended for sustainable soil management in agriculture. Our experiment involved timothy grass (Phleum pratense L.), red clover (Trifolium pratense L.), and their mixture; tall oat grass (Arrhenatherum elatius L.), alfalfa (Medicago sativa L.), and their mixture, with the aim of diversifying the annual rotation; and periodical, twice-per-season cultivated plots in the same area (the bare soil fallow). Soil samples were collected in late October after plant vegetation’s first, second, and third growth years from three field replicates at the soil layers 0–0.1 m, 0.1–0.2 m, and 0.2–0.3 m and plant roots—at the beginning of November in the second cultivation year. After three years, the SOC content increased in all the study areas occupied by plants, regardless of their species composition, while it decreased in fallow plots. Grass roots were characterized by the highest C/N ratio (38.2 and 45.5). The roots of the red clover–timothy grass mixture also reached a C/N ratio greater than 30. Based on our research, choosing a combination of at least two plants, such as legumes and grasses, is possibly more effective for enriching the soil with carbon compounds in a short period.

Effect of Soil pH Variation on Peanut Plant Growth

This research investigates the qualitative effects of soil pH variation on peanut plant growth, aiming to provide insights into the complex interactions between soil properties and plant responses in agricultural ecosystems. Through semi-structured interviews with ten informants, supplemented by insights synthesized from prior research and theoretical frameworks, the study explores perceived relationships, implications for soil health and nutrient availability, challenges, opportunities, and practical implications for peanut production. Key findings highlight the critical influence of soil pH on peanut growth and productivity, with deviations from optimal pH levels affecting nutrient availability, root health, and overall plant vigor. Participants underscore the importance of targeted soil management practices, including lime application, organic matter incorporation, and crop rotation, in optimizing soil pH and supporting resilient peanut production systems. The study identifies challenges in soil pH management, such as limited accessibility of soil testing services and inadequate farmer knowledge, while also highlighting opportunities for innovation and improvement. The insights gleaned from the study contribute to advancing knowledge in agricultural sciences and inform evidence-based soil management practices for sustainable peanut production.

NETmicroplastic in agricultural soil and its impact on soil properties

AbstractImplementing “soil health” means sustainable management of agricultural soils, avoiding toxicities, and sensible use of resources to minimize waste. In this context, the use of plastic in agriculture in form of plastic products, the application of polymers and additives in fertilizers, and plastic input through littering and tyre wear demands our special attention. Uncertainty and open questions relating to effects of plastic and its degradation products such as microplastic (MP) on the soil environment, the soil biota, and human health partly result from the lack of robust and standardized detection and measurement methods. Also, environmental, economic, and societal problems around MPs in soil cannot be adequately addressed due to lack of coordination among the various relevant players and initiatives in research and policy. NETmicroplastic (www.net-microplastic.eu) responds to the need of connecting among a fragmented research &amp; innovation and policy landscape by creating a community‐supported environment. The network fosters provision of solid data for science‐based impact assessment of MP in soil together with much‐needed technological innovations, including biodegradable alternatives to conventional plastic. Here, we reflect upon a number of action fields that are key to the NETmicroplastic initiative from small to large‐scale perspectives. In addition, we portray the overall awareness situation around MP in soil.

Have Agricultural Land-Use Carbon Emissions in China Peaked? An Analysis Based on Decoupling Theory and Spatial EKC Model

Assessing the emission-peaking process of agricultural land use provides valuable insights for mitigating global warming. This study calculated agricultural land-use carbon emissions (ALUCEs) in China from 2000 to 2020 and explored the peaking process based on quantitative criteria. Further, we applied the Tapio decoupling index and environmental Kuznets curve (EKC) model to discuss the robustness of the peaking process. The main conclusions are as follows: (1) From 2000 to 2020, China’s average ALUCEs were 368.1 Mt C-eq (1349.7 CO2-eq), peaking at 396.9 Mt C-eq (1455.3 Mt CO2-eq) in 2015 before plateauing. Emissions from agricultural materials and soil management had entered the declining period, while those from rice cultivation were in the peaking period, those from straw burning were still rising, and those from livestock breeding remained at the plateauing phase. (2) The provinces of Beijing, Tianjin, and nine others saw a decline in ALUCEs, while Hainan, Guizhou, and another nine provinces observed plateauing, and Ningxia, Qinghai, and six other provinces experienced peaking. (3) Decoupling analysis confirmed that emission-peaking states remained stable even with agricultural growth. Instead of an inverted U-shaped relationship, we found an N-shaped relationship between ALUCEs and agricultural GDP. The spatial EKC model indicated that the peaking process had spillover effects between provinces. It is recommended that China accelerate ALUCE mitigation based on the source and phase of emissions, considering the peaking process and magnitude.