Soil Management Practices Research Articles

Modeling soil acidity (pH) dynamics under extreme agroclimatic conditions in Horro Guduru Wallaga Zone, northwestern Ethiopia.

Soil plays a critical role in nutrient availability, microbial activity, and fertility in agriculture. However, the effects of agroclimatic conditions on soil pH are not well understood, particularly in the Horro Guduru Zone of Ethiopia. This study aimed to investigate the soil pH under extremely wet and dry conditions across 3 shared socioeconomic pathway (SSP) scenarios: SSP1-2.6, SSP2-4.5, and SSP5-8.5. Baseline agroclimatic data (1981-2010) and future projections (2041-2070) were obtained from the European Commission Climate Change Services. Soil pH data at a 250m resolution were extracted from the FAO-UNESCO global soil map. Missing values, multicollinearity, and outliers were addressed before modeling. Predictive models, including neural networks, generalized regression, and bootstrap forests, were validated, with the generalized regression model showing the best performance. The results indicate that soil pH decreases under consecutive dry‒wet conditions and increases with increasing maximum day temperatures across all scenarios. Soil pH is significantly influenced by the number of consecutive dry days, consecutive wet days, and maximum day temperature. The SSP1-2.6 and SSP2-4.5 scenarios resulted in improved pH levels, whereas SSP5-8.5 led to a decrease in soil pH, averaging 5.79 and decreasing to 5.54. These findings suggest that under SSP5-8.5, soil health and farming productivity may be compromised. This study emphasizes the need to adjust soil management practices based on prevailing climatic conditions to ensure soil health and agricultural sustainability.

Phytolith-Mediated Biocarbon Sequestration

The sequestration of biocarbon primarily arises from natural mechanisms and is acknowledged as a critical measure in mitigating climate change. An inactive form of carbon, known as phytolith occluded carbon, is sequestered within plants and persists in soil for thousands of years following the breakdown of vegetation. Formation, distribution and storage of phytolith occluded carbon are the major factors affecting phytolith-mediated biocarbon sequestration. Crop area, crop duration, aboveground net primary productivity, crop, plant species, plant parts, age of plant, age of plant parts, cell components, phytolith morphotypes, and mean annual precipitation are some of the factors affecting the formation of phytolith occluded carbon. The stability and dissolution of phytolith occluded carbon in the soil are determined by carbon dioxide, temperature, climate zone, topography, soil, and phytolith properties characteristics. The phytolith distribution in the soil is affected by soil type and depth, tillage, bioturbulence, percolation, and phytolith morphotypes. By adopting proper soil and crop management practices phytolith mediated biocarbon sequestration can be enhanced.

Toxicological effects and stress tolerance mechanisms in Triticum durum (Nachit) and Triticum aestivum (Ibtissam) under caesium stress

ABSTRACT This study examines the toxic effects of caesium (Cs) on Triticum aestivum (Ibtissam) and Triticum durum (Nachit), focusing on seed germination, root and shoot growth, and overall growth parameters. Cs exposure significantly impairs growth, with dose-dependent reductions in germination, root and shoot lengths, and fresh/dry weights. Notably, T. durum shows greater resilience to Cs stress than T. aestivum, maintaining better growth at higher Cs levels. The differing tolerance suggests T. durum may have more effective mechanisms to mitigate Cs toxicity. These findings highlight wheat’s sensitivity to Cs and T. durum’s potential for cultivation in contaminated soils. This research enhances understanding of Cs toxicity in wheat and offers insights for developing Cs-tolerant crops and better soil management practices.

Assessment of nitrogen and phosphorus losses due to erosion in compost-treated and non-treated vineyard soils: effect of rainfall intensity

Vineyards in Mediterranean areas suffer from significant soil degradation through erosion, due to rainfall and soil characteristics, as well as soil management practices. Previous studies pointed out the nutrient losses produced by erosion and the benefits that some management practices could have on reducing erosion. This research tried to evaluate the effect of events of different intensities and to assess whether the beneficial effect of compost amendment may pose a potential risk of nutrient loss and environmental pollution in particular under high-intensity events. The study compared soil and nutrient losses in compost-treated and non-treated vineyard soils after rainfall events of different intensities analyzed over 2 years in two vineyards. Runoff samples were collected by triplicate in treated and non-treated soils. Sediment and nitrogen and phosphorous concentrations in the runoff samples were analyzed. The results reveal a reduction in runoff rates and an increase in soil water content in compost-treated soils, which represents a benefit for rainfed vineyards. Both nitrogen and phosphorus losses depended on rainfall characteristics. Although for low intensities there were no significant differences in the amount of nutrient lost by runoff in both treated and non-treated soils, nitrogen and phosphorus losses were higher after high-intensity rainfall events in compost-treated soils. With the expected increase in high-intensity rainfall events associated with climate change in the Mediterranean region, organic amendments should be applied in several splits or incorporated into the soil to avoid increased nutrient loss to water bodies.

Organic Management and Intercropping of Fruit Perennials Increase Soil Microbial Diversity and Activity in Arid Zone Orchard Cropping Systems

Organic farming encourages soil management practices that can improve soil health and fertility by increasing soil organic matter inputs and system sustainability. This study evaluated the effect of three years of continuous organic farming and intercropping orchard treatments on soil microbial diversity, microbial enumeration, respiration, soil fertility and fruit yields. Organic management resulted in higher soil organic matter content, Olsen P, and water holding capacity, but did not affect soil pH, electrical conductivity (EC), K, or Na levels. Growth parameters measured on all fruit trees were not significantly different among treatments. The enumeration of bacteria was significantly higher in organic plots when compared to conventionally managed plots. Soil respiration and substrate-induced respiration were significantly higher in the organic diverse plots in comparison to both conventional systems. The genomic analysis of prokaryotes (16S rRNA) and eukaryotes/fungi (ITS) revealed a significantly higher number of taxa, Shannon H index, and Equitability index in the organic systems for both prokaryotes and eukaryotes, in comparison to conventional farming, all of which are indicators of system sustainability. The relative abundance of Operational Taxonomic Units (OTUs) previously reported as diazotrophs, denitrifiers, or involved in the sulfur cycle, as well as Arbuscular Mychorrizae Fungi (AMF)/glomeromycotan, were highest in the organically managed soils than in the conventional plots. A multivariate correlation network clustering revealed that the microbial communities within the organic and conventional soils had strong dissimilarities regarding soil microbial niches. Our work provides evidence that organic management can be used for increasing soil microbial diversity and soil health, leading to higher levels of sustainability in fruit orchard systems.

The Role of Organic Amendments and Their Impact on Soil Restoration: A Review

Soil organic matter (SOM) plays a pivotal role in maintaining soil health by enhancing its physical, chemical, and biological properties. It improves soil structure, water retention, nutrient availability, and microbial activity, contributing significantly to sustainable agriculture. Organic amendments, including animal manure, compost, biosolids, crop residues, and various organic by-products, are widely used to restore degraded soils by increasing SOM content. These amendments not only supply essential nutrients but also promote biological aggregation, suppress soil-borne pathogens, and improve soil's resistance to environmental stressors such as drought and heavy metal toxicity. The positive impacts of organic amendments on soil properties are well-documented, with key benefits including increased soil organic carbon (SOC), improved nutrient cycling, enhanced microbial diversity, and greater water-holding capacity. Organic materials such as compost and animal manure have been shown to significantly improve soil fertility and restore degraded soils. The application of green manure and crop residues also boosts soil biodiversity, enhances rhizospheric processes, and supports overall ecosystem resilience. This paper emphasizes the importance of adopting holistic soil management practices that include organic amendments, conservation tillage, and sustainable cropping systems to address soil degradation. By focusing on replenishing SOM, improving nutrient availability, and increasing soil biodiversity, these practices can contribute to the long-term sustainability of agricultural systems and environmental health. The restoration of soil organic matter is essential for enhancing soil quality and mitigating degradation, ultimately ensuring food security and ecosystem stability for future generations.

REPORT OF PRACTICAL CLASS IN AGRICULTURAL AREA WITH THE BACHELOR CLASS IN AGRONOMY IN THE MUNICIPALITY OF TRACUATEUA-PA

Cassava (Manihot esculenta Crantz) is a highly consumed root and a significant source of carbohydrates in Brazil and around the world. In the state of Pará, cassava is vital to the local economy, especially in the municipality of Tracuateua. The culture involves family farmers and serves as an important source of income and subsistence. Different cultivars are used, such as BRS Tapioqueira and BRS Verdinha, which exceed 70 thousand kg/ha with good management. Adequate fertilization, pest control and weed management are essential for high productivity. Irrigation can significantly increase production. On the property of Mr. Benedito Dutra, member of the RENIVA project, the production of seed cassava and cowpea is highlighted. It uses cultivars developed by Embrapa, such as BRS Kiriris, BRS Formosa and BRS Novo Horizonte, which are recommended for industrial use. Dutra also grows cowpeas, using varieties such as BRS Guirá and BRS Natalina, which are highly productive and adapted to local conditions. The property has an irrigated area of ​​23 hectares per central pivot, ensuring crop hydration during dry periods. During the field visit, several areas of experimentation were observed. The experimental plots of cassava and cowpea showed good performance, with a high survival rate and resistance to pests. The integration of advanced soil management, pest control and irrigation practices highlighted the property as an example of innovative agriculture. The experience on Mr. Dutra’s property demonstrated the importance of innovation and adoption of advanced agricultural practices for sustainable and productive agricultural production.

Assessing the Impact of Climate Change on Methane Emissions from Rice Production Systems in Southern India

The impact of climate change on methane (CH4) emissions from rice production systems in the Coimbatore region (Tamil Nadu, India) was studied by leveraging field experiments across two main treatments and four sub-treatments in a split-plot design. Utilizing the closed-chamber method for gas collection and gas chromatography analysis, this study identified significant differences in CH4 emissions between conventional cultivation methods and the system of rice intensification (henceforth SRI). Over two growing seasons, conventional cultivation methods reported higher CH4 emissions (range: from 36.9 to 59.3 kg CH4 ha−1 season−1) compared with SRI (range: from 2.2 to 12.8 kg CH4 ha−1 season−1). Experimental data were subsequently used to guide parametrization and validation of the DeNitrification–DeComposition (DNDC) model. The validation of the model showed good agreement between the measured and modeled data, as denoted by the statistical tests performed, which included CRM (0.09), D-index (0.99), RMSE (7.16), EF (0.96), and R2 (0.92). The validated model was then used to develop future CH4 emissions projections under various shared socio-economic pathways (henceforth SSPs) for the mid- (2021–2050) and late (2051–2080) century. The analysis revealed a potential increase in CH4 emissions for the simulated scenarios, which was dependent on specific soil and irrigation management practices. Conventional cultivation produced the highest CH4 emissions, but it was shown that they could be reduced if the current practice was replaced by minimal flooding or through irrigation with alternating wetting and drying cycles. Emissions were predicted to rise until SSP 370, with a marginal increase in SSP 585 thereafter. The findings of this work underscored an urgency to develop climate-smart location-specific mitigation strategies focused on simultaneously improving current water and nutrient management practices. The use of methanotrophs to reduce CH4 production from rice systems should be considered in future work. This research also highlighted the critical interaction that exists between agricultural practices and climate change, and emphasized the need to implement adaptive crop management strategies that can sustain productivity and mitigate the environmental impacts of rice-based systems in southern India.

No-Till and Crop Rotation Are Promising Practices to Enhance Soil Health in Cotton-Producing Semiarid Regions: Insights from Citizen Science

This on-farm study was conducted to assess the impact of six prevalent crop management practices adopted by growers in West Texas on various indicators of soil health. This study is a part of a citizen science project, where we collaborated with cotton growers who helped with standardized sample and data collection from 2017 to 2022. This project aimed to identify soil management practices that increase carbon sequestration, enhance biological activities, and improve overall soil health. We monitored soil moisture, soil organic matter (SOM), inorganic nitrogen (NH4+-N and NO3−-N) and other exchangeable nutrients, and soil microbial abundances as obtained via fatty acid methyl ester (FAME) in 85 fields, incorporating different management practices during the cotton growing season. In our study, volumetric moisture content (VWC) was increased by no-till, irrigation, and crop rotation, but the addition of residue decreased VWC. No-till, irrigation, and crop rotation increased SOM, but a cover crop decreased SOM. No-till and residue retention also increased microbial biomass carbon (MBC). Tillage, irrigation, and crop rotation influenced the abundance of the main microbial groups, including bacterial, fungi, and arbuscular mycorrhizal fungi (AMF). Additionally, water content, SOM, and microbial abundances are correlated with clay percentage. Our results indicate that no-till and crop rotation are the two most crucial soil management approaches for sustainable soil health. As such, implementing both no-till and crop rotation in the cropping systems has the most promising potential to increase the soil resilience in dryland cotton production in semiarid regions, thereby helping growers to maintain cotton production.

Assessment of Groundwater Quality for Irrigation in Jhagadia, Netrang and Valia Taluka of Bharuch District in South Gujarat, India

Bharuch, a heavily industrialized district on the west coast, faces challenges like over-extraction and contamination, which threaten its groundwater quality. In response, a post-monsoon 2023 assessment was conducted in the Jhagadia, Netrang, and Valia talukas, where water samples from 78 locations were collected and analyzed. These locations were identified using landforms developed through GIS. The study found that around 40% of the TGA in these blocks is used for agriculture, with 52,106 hectares for single crops and 7,843 hectares for double crops, making up 15.05% of the total cultivated area. Eastern part of Jhagadia and Netrang recorded deep water levels (10–20 m), while other areas had moderately shallow levels (5–10 m). Tube wells were mainly found in Valia, northern Jhagadia, and western Netrang, whereas dug wells dominated eastern Netrang and southeastern Jhagadia. Irrigation water pH ranged from 6.31 to 8.82, averaging 6.97, with higher pH in Jhagadia. Electrical conductivity (EC) was highest in Valia (0.66–2.94 dSm⁻¹), and medium salinity was noted in Jhagadia (1.03 dSm⁻¹) and Netrang (0.71 dSm⁻¹), affecting irrigation suitability. All samples had a SAR classification of S1 (<10). Most water samples were "Suitable" based on RSC, except some in Valia with RSC >1.25 meL⁻¹. Chloride levels varied from 0.50 mg/L-1 to 25.48 mg/L-1. The specific soil management practices, such as gypsum application, improving drainage and the growing of salt-tolerant crop varieties can help mitigate potential negative impacts on crop productivity.

Effects of Various Herbicide Types and Doses, Tillage Systems, and Nitrogen Rates on CO2 Emissions from Agricultural Land: A Literature Review

Although herbicides are essential for global agriculture and controlling weeds, they impact soil microbial communities and CO2 emissions. However, the effects of herbicides, tillage systems, and nitrogen fertilisation on CO2 emissions under different environmental conditions are poorly understood. This review explores how various agricultural practices and inputs affect CO2 emissions and addresses the impact of pest-management strategies, tillage systems, and nitrogen fertiliser usage on CO2 emissions using multiple databases. Key findings indicate that both increased and decreased tendencies in greenhouse gas (GHG) emissions were observed, depending on the herbicide type, dose, soil properties, and application methods. Several studies reported a positive correlation between CO2 emissions and increased agricultural production. Combining herbicides with other methods effectively controls emissions with minimal chemical inputs. Conservation practices like no-tillage were more effective than conventional tillage in mitigating carbon emissions. Integrated pest management, conservation tillage, and nitrogen fertiliser rate optimisation were shown to reduce herbicide use and soil greenhouse gas emissions. Fertilisers are similarly important; depending on the dosage, they may support yield or harm the soil. Fertiliser benefits are contingent on appropriate management practices for specific soil and field conditions. This review highlights the significance of adaptable management strategies that consider local environmental conditions and can guide future studies and inform policies to promote sustainable agriculture practices worldwide.

Groundwater Recharge Response to Reduced Irrigation Pumping: Checkbook Irrigation and the Water Savings Payment Plan

Ongoing investments in irrigation technologies highlight the need to accurately estimate the longevity and magnitude of water savings at the watershed level to avoid the paradox of irrigation efficiency. This paradox arises when irrigation pumping exceeds crop water demand, leading to excess water that is not recovered by the watershed. Comprehensive water accounting from farm to watershed scales is challenging due to spatial variability and inadequate socio-hydrological data. We hypothesize that water savings are short term, as prior studies show rapid recharge responses to surface changes. Precise estimation of these time scales and water savings can aid water managers making decisions. In this study, we examined water savings at three 65-hectare sites in Nebraska with diverse soil textures, management practices, and groundwater depths. Surface geophysics effectively identified in-field variability in soil water content and water flux. A one-dimensional model showed an average 80% agreement with chloride mass balance estimates of deep drainage. Our findings indicate that groundwater response times are short and water savings are modest (1–3 years; 50–900 mm over 10 years) following a 120 mm/year reduction in pumping. However, sandy soils with shallow groundwater show minimal potential for water savings, suggesting limited effectiveness of irrigation efficiency programs in such regions.

The dynamics of soil health

The dynamics of soil health Thomas Gumbricht from Stockholm University and xSpectre, with Sonia Meller from Digit Soil, discuss what we need to know about understanding the dynamics of soil health. Soils are formed by mineral debris, organic matter, water and living organisms. The soil ecosystem takes millennia to form and is sustained by a web of interplay both within the soil and with the vegetation ecosystem it harbours. Our human society wholly depends on soil for food, fodder, fibre, water cleaning, and climate control. But we are mismanaging soils, and in Europe, the majority of soils are considered unhealthy. Intense use of chemicals has depleted soil organisms, compaction causes water to runoff from the surface rather than infiltrate, and ploughing destroys the soil’s vital aggregate structure and oxidises soil organic carbon. The European Commission’s Soil Health and Food Mission aims to address these issues by promoting sustainable soil management practices across the continent.

Greenhouse gas emissions during alfalfa cultivation: How do soil management and crop fertilisation of preceding maize impact emissions?

ContextThe use of alfalfa in rotation with intensive crops is common practice to mitigate the physical and chemical issues arising from intensive farming practices. However, there is a dearth of studies on this practice. Given the current concern regarding climate change and the significant impact agriculture has on greenhouse gas (GHG) emissions, understanding the emissions associated with this practice, as well as the most suitable soil and crop management techniques for their mitigation, is of paramount importance. ObjectiveThe present study aimed to (i) quantify emissions of N2O, CO2 and CH4 in an alfalfa crop following a maize cropping scenario; (ii) to determine which tillage system generates the lowest GHG emissions, and; (iii) to determine how N fertilisation from a preceding intensive maize crop affects GHG emissions during alfalfa cropping period. MethodsA three-year field experiment (2019, 2020 and 2021) was conducted to assess the emissions of N2O, CO2 and CH4 from alfalfa cultivation following a three-year period of irrigated maize. Two soil management practices (no-tillage and conventional tillage) were implemented during both the maize cropping period and the alfalfa establishment. Additionally, the nitrogen (N) fertilisation rates applied to the preceding maize crop were included as a treatment (0, 200, and 400 kg N ha⁻¹, corresponding to zero, medium, and high fertilisation levels, respectively) in a randomized block design with two factors. ResultsEmissions of N2O in alfalfa ranged from 0.05 to 0.32 mg N2O-N m⁻² day⁻¹, being significantly higher only during first month of sampling in the treatments that had received fertilisation. CO2 emissions ranged from 1158 to 4258 mg CO2-C m⁻² day⁻¹. Year-average CH4 fluxes were −0.27 g C ha⁻¹ day⁻¹. The average total dry matter produced by alfalfa was 17700 kg ha⁻¹ year⁻¹, being higher for the no-tillage treatment, though significantly so only during first month of sampling. ConclusionsUnder Mediterranean conditions, the tillage system and mineral N fertilizer rates have a relative effect on greenhouse gas emissions during the alfalfa cropping period. Plots without N fertilization initially produced lower N2O emissions and higher total dry matter, resulting in the lowest scaled emissions. For the tillage treatment, no significant differences were found in emission dynamics, which may be due to the fact that alfalfa does not involve soil disturbance, leading to a homogenization of the treatments. However, the NT treatment showed lower scaled emissions due to higher yields in the first year. Therefore, alfalfa cultivation is characterized by low GHG emissions, high yields, and a notable capacity to mitigate the negative effects of previous intensive crops. SignificanceThis study provides data on GHG emissions during alfalfa cropping in the typical Maize-alfalfa crop rotation under Mediterranean irrigated systems, which is useful for new agricultural policies aimed at reducing pollution in the agricultural sector. Additionally, it demonstrates the capability of this crop to mitigate adverse agronomic and environmental conditions caused by preceding intensive farming practices.

Exploring the inclusion of soil management practices in erosion models towards the improvement of post-fire predictions

Wildfires are recognized for having a strong impact on forest soils, a situation aggravated by inadequate pre-fire land management practices. Land management operations, such as plowing, are routinely carried out for cultural reasons and can impact soils for decades after their implementation. Therefore, it is crucial to take into account the pre-fire land management history when predicting post-fire sediment losses in burnt areas. This consideration is critical for a realistic assessment of soil erosion risk and, consequently, for effectively implementing emergency stabilization and/or rehabilitation measures.The aim of the study was to integrate pre-fire land management practices into erosion models, to enhance post-fire sediment losses predictions at slope scale. To accomplish this goal, both Multiple Linear Regression (MLR) and the revised-Morgan-Morgan-Finney model (revised-MMF) were applied in the Colmeal burnt area (Central Portugal). These models were adapted to account the impacts of different management options, specifically no plowing, downslope-plowing and contour-plowing, on the erosive response following a wildfire.The results revealed fluctuations in the performance of both models across different soil management, and over time since the wildfire. Despite the observed variability, it is important to highlight the positive outcomes achieved with the revised-MMF model over the three monitoring years where contour-plowing was applied. These results demonstrate that the best model performances are achieved when soil management is individualized and analyzed independently. Similarly, the MLR model exhibited improved performance when incorporating management practices into its predictions. This study confirms that disturbances on topsoil, whether caused by wildfires or soil management operations, play key roles in driving change in soil erosion. Hence, integrating these factors into models is essential for providing relevant information for the development of mitigation and/or restoration strategies in areas at high risk of erosion.

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.

Using convolutional neural network combined with multi-scale channel attention module to predict soil properties from visible and near-infrared spectral data

With the increasing demand for precision agriculture and sustainable land management, it is crucial to quickly and accurately predict soil properties. However, there are still challenges in predicting large-scale soil properties. This study proposes a new convolutional neural network architecture (MCA-CNN) combined with visible and near-infrared spectroscopy for predicting soil properties. The architecture introduces a multi-scale channel attention mechanism, aiming to more effectively capture complex features in the spectrum. The performance of the MCA-CNN model was tested on a large-scale dataset and compared with partial least squares (PLS), extreme gradient boosting tree (XGBoost), and conventional convolutional neural network (CNN) models. The predictive performance of different models in organic carbon (OC), nitrogen (N), pH, Clay, Salt, and Sand was analyzed. The results showed that the MCA-CNN model had the best predictive performance on all soil properties, achieving the lowest root mean square error (RMSE) and the highest coefficient of determination (R2), the R2 of OC, N, pH, Clay, Silt, and Sand are 0.95, 0.93, 0.95, 0.80, 0.58, 0.64, respectively. The RMSE of OC, N, pH, Clay, Silt, and Sand are 16.60 g kg−1, 0.96 g kg−1, 0.31, 4.89 %, 8.27 %, and 11.61 %, respectively. Further research has found that soil types (mineral soil and organic soil) affect the predictive performance of OC. It is necessary to distinguish between mineral soil and organic soil when predicting soil OC content. In addition, the effectiveness of the model transfer strategy was explored for situations with small soil sample sizes. By fine-tuning the pre-trained model, the performance of the model can be significantly improved, which provides a feasible solution for predicting soil properties in situations of data scarcity. In summary, this study not only confirms the potential application of deep learning in the field of soil science, but also provides new technological avenues for future soil management and agricultural practices.

Enhancing crop production in the Haihe Basin while addressing challenges related to water quantity and quality

To tackle the challenge of ensuring food security while managing water availability and quality constraints in the Haihe Basin, a critical grain-producing region in China with a dense population and severe water degradation issues, we have developed a comprehensive spatial optimization (CSO) strategy. This approach integrates various crop and soil management practices, land consolidation, and cutting-edge breeding technologies. It also uses a spatial planning model based on linear programming, considering water quantity and quality constraints. Our research shows that crop yields may drop by 14 % (3780 Kt) compared to levels in 2017 due to restrictions on groundwater extraction and nitrogen (N) concentrations in leaching or runoff. However, by strategically maximizing overall crop yields through the integrated CSO strategy without changing the crop production structure, the total crop yield could potentially increase by 81 % (21,817 Kt) while using 3.0 % (86 Kha) less cultivated land than in 2017. This would help to fulfill the projected food demand in 2050. If the integrated aims to minimize the sown area after fulfilling the demand for crops in 2050, around 28 % of the sown area, or 820 Kha cropland, could be reduced compared with 2017. This reduction may save more land for natural conversation. Furthermore, total N losses, including ammonia, nitrous oxide emissions, runoff, and leaching, could be reduced by 23 %–43 % (139–252 Kt), depending on the specific optimization strategy goals. The stepwise integrated optimization strategy provides a feasible framework for the Haihe Basin, enabling the maintenance or even enhancing current crop yields while safeguarding water quality and quantity.

Environmental benefits of ozonated water for sustainable grapevine disease control: A life cycle and carbon sequestration analysis

The oxidative capacity of ozone makes it a highly effective biocide, widely used in the food and processing industry, as well as in drinking water plants. In a context of tighter restrictions on the use of synthetic plant protection products at the regulatory level, wineries are looking for alternative methods to control diseases, making the application of ozonated water an option to consider. To determine the environmental sustainability of this alternative vineyard disease control treatment, an environmental impact assessment was conducted using the Life Cycle Assessment (LCA) methodology. The assessment was carried out in a vineyard located in the D.O. Rías Baixas of Galicia, located in northwestern Spain. The analysis was conducted on the basis of two functional units: i) 1 kg of grapes and ii) 1 ha of land managed and using a cradle-to-gate boundary system. Ten impact categories were assessed using the ReCiPe method, except for the water scarcity indicator, which was quantified using AWARE.The environmental sustainability of the vineyard was further analyzed by measuring its carbon sequestration potential to obtain a more complete environmental profile. The RothC-26.3 model was chosen to estimate absolute carbon sequestration and annual sequestration rate from 2020 to 2040. Since the ozone-only scenarios lost all harvest, no environmental assessment was performed for such scenarios. For the remaining scenarios, the findings suggest that those using a combination of ozonated water and fungicides have the worst environmental performance due to notable reductions in grape yield and more frequent disease control interventions, particularly in certain scenarios. When evaluating environmental performance per hectare of land managed, the scenario using ozonated water with a limited number of disease control interventions exhibited the most favorable environmental profile, primarily due to reduced use of fungicides and disease control passes. In addition, the main contributors to the vineyard environmental profile identified were diesel fuel combustion during field operations, fertilizer use and production, and irrigation. In addition, the research indicates that the vineyard sequesters carbon annually, but this alone is insufficient to offset its greenhouse gas emissions. However, it is estimated that through the application of more appropriate soil management practices, the vineyard could achieve carbon neutrality and potentially increase soil carbon stocks over time.

Integration of machine learning and process‐based model outputs via ensemble Kalman filter enhanced space–time modelling of soil organic carbon in a highly human impacted area

AbstractAccurate prediction of soil organic carbon stock (SOCS) dynamics in areas with intensive human activities is crucial for developing sustainable soil management practices and climate change mitigation strategies. This study investigated the spatiotemporal dynamics of SOCS by collecting a total of 1219 topsoil samples in southern Jiangsu Province of China in 1980, 2000 and 2015, and compared the performance of three predictive models: random forest (RF), RothC, and a hybrid model of RF‐RothCEnKF. The hybrid model integrated outputs from the process‐based RothC model and the data‐driven RF model using the Ensemble Kalman Filter (EnKF) for sequential model state updates. Results showed that the three models presented similar spatial patterns of SOCS from 1980 to 2015, with relatively higher SOCS mainly distributed in the areas surrounding Taihu Lake. The mean SOCS change rates estimated by the RF‐RothCEnKF model represented an overall net increase of 0.04 t C ha−1 yr.−1 during that period. The RF‐RothCEnKF model exhibited high prediction accuracy, with an R2 of .52, a mean absolute error (MAE) of 7.38 t C ha−1, and a root mean square error (RMSE) of 9.13 t C ha−1 in 2015. This highlighted the RF‐RothCEnKF's ability to enhance performance when the individual RF model (R2 = .47, MAE = 7.66 t C ha−1, and RMSE = 9.42 t C ha−1) and the RothC (R2 = .13, MAE = 8.77 t C ha−1, and RMSE = 10.87 t C ha−1) fell short. Our findings may not only provide a framework for integrating process‐based and machine learning models to enhance the accuracy and adaptability of SOCS modelling in areas affected by intensive human activities, but also offer some guidance for developing sustainable agricultural practices and carbon management strategies in complex environmental settings.