Agricultural Management Practices Research Articles

Effect of Biochar Application on the Improvement of Soil Properties and Buckwheat (Fagopyrum esculentum Moench) Yield on Two Contrasting Soil Types in a Semi-Arid Region of Inner Mongolia

Biochar application to soil is widely recognized as a promising agricultural management practice to increase crop production by enhancing the physical, chemical, and microbiological properties of the soil. Despite the fact that numerous studies have investigated biochar production and alterations in soil properties, the effects of biochar on contrasting soils within the same region remain poorly understood, especially for semi-arid regions. Therefore, a three-year field experiment was initiated in 2020 wherein biochar was applied once to a buckwheat field at rates of 0, 20, 40, and 60 Mg ha−1 (BC0: no biochar; BC1: 20 Mg ha−1; BC2: 40 Mg ha−1; BC3: 60 Mg ha−1) for two soil types (aeolian sandy and grey meadow soil) in the northeast of Inner Mongolia, China. The soil water storage (SWS), nutrient contents (organic matter, available nitrogen, phosphorus, and potassium), microbial biomass (carbon, nitrogen, and phosphorus), and enzyme activities (urease, invertase, and alkaline phosphatase) were assessed at a soil depth of 0–15 cm as part of the soil quality assessment, and the buckwheat grain yield was estimated for crop productivity evaluation. The results showed that biochar amendment improved selected soil physicochemical and microbiological properties and buckwheat yields for both soil types. Compared to BC0, the biochar addition increased buckwheat yields, on average, by 11.23% to 22.82% in aeolian sandy soil and by 7.36% to 14.87% in grey meadow soil across three years. The results of principal component analysis (PCA) and random forest analysis (RFA) indicate that soil available nutrients and microbiological properties were the most important factors influencing buckwheat yields in aeolian sandy soil and grey meadow soil, respectively. Based on RFA, the available potassium, phosphorus, and nitrogen were found to contribute at rates of 13.10%, 10.06%, and 8.12%, respectively, to buckwheat yields in aeolian sandy soil. In contrast, alkaline phosphatase, urease, and microbial biomass carbon contribute 20.26%, 8.48%, and 7.82%, respectively, to the buckwheat yields in grey meadow soil. Following biochar addition, there was greater improvement in soil health and buckwheat production for aeolian sandy soil than grey meadow soil. In conclusion, biochar addition is an effective practice for improving soil health and crop productivity in both aeolian sandy soil and grey meadow soil in semi-arid regions.

Analyzing vegetation health dynamics across seasons and regions through NDVI and climatic variables

This study assesses the relationships between vegetation dynamics and climatic variations in Pakistan from 2000 to 2023. Employing high-resolution Landsat data for Normalized Difference Vegetation Index (NDVI) assessments, integrated with climate variables from CHIRPS and ERA5 datasets, our approach leverages Google Earth Engine (GEE) for efficient processing. It combines statistical methodologies, including linear regression, Mann–Kendall trend tests, Sen's slope estimator, partial correlation, and cross wavelet transform analyses. The findings highlight significant spatial and temporal variations in NDVI, with an annual increase averaging 0.00197 per year (p < 0.0001). This positive trend is coupled with an increase in precipitation by 0.4801 mm/year (p = 0.0016). In contrast, our analysis recorded a slight decrease in temperature (− 0.01011 °C/year, p < 0.05) and a reduction in solar radiation (− 0.27526 W/m2/year, p < 0.05). Notably, cross-wavelet transform analysis underscored significant coherence between NDVI and climatic factors, revealing periods of synchronized fluctuations and distinct lagged relationships. This analysis particularly highlighted precipitation as a primary driver of vegetation growth, illustrating its crucial impact across various Pakistani regions. Moreover, the analysis revealed distinct seasonal patterns, indicating that vegetation health is most responsive during the monsoon season, correlating strongly with peaks in seasonal precipitation. Our investigation has revealed Pakistan's complex association between vegetation health and climatic factors, which varies across different regions. Through cross-wavelet analysis, we have identified distinct coherence and phase relationships that highlight the critical influence of climatic drivers on vegetation patterns. These insights are crucial for developing regional climate adaptation strategies and informing sustainable agricultural and environmental management practices in the face of ongoing climatic changes.

Response of soil quality degradation to cultivation and soil erosion: A case study in a Mollisol region of Northeast China

Soil degradation is endangering agricultural and ecological sustainability in the Mollisol region of Northeast China. Cultivation and soil erosion are the primary drivers degrading soil quality. However, few studies have comprehensively quantified the effects of cultivation and soil erosion on soil quality degradation in Mollisols. Therefore, three sampling sites with similar landscapes, erosion environments and agricultural management practices were selected. The cultivation chronosequence was determined using a space-for-time substitution approach, including 1) forestland without cultivation (0 yr, stage I), 2) farmland with few cultivation years (< 20 yr, stage II), and 3) farmland with many cultivation years (> 80 yr, stage III). Soil erosion was quantified using the caesium-137 (137Cs) and black soil thickness. Sixteen soil physicochemical indicators were analyzed, and soil quality and its degradation were evaluated using an integrated soil quality index (SQI) and a soil degradation index (SDI), respectively. The results showed that soil erosion was profoundly accelerated by cultivation. Soil organic carbon (SOC), bulk density (BD), mean weight diameter (MWD) and soil erodibility (K) factor were selected to develop the SQI. The SQI was higher in stage I (0.61±0.05) than in stages II (0.49±0.06) and III (0.52±0.03) and decreased with increasing soil erosion rate, implying that cultivation and soil erosion exacerbated the degradation of soil quality. Furthermore, cultivation and soil erosion contributed 16.0–51.1% and 2.0–18.4% to the changes in soil quality, respectively, and their combination further amplified the impacts (8.4–61.5%). Cultivation and accelerated soil erosion driven by cultivation led to the degradation of soil quality; the former controlled the degradation processes mainly by decreasing the MWD, and the latter induced soil quality degradation by reducing the SOC and increasing the K factor. These findings are important for advancing our understanding of the driving forces and mechanisms of soil degradation in the Mollisol region.

A Comprehensive Perception of Biological Control Potential of Endophytes and Quality Refinement of Lagenaria siceraria.

Agriculture and livestock management practices known as organic farming rely more on internal processes than external inputs. Natural environments depend heavily on diversity, and organic farming incorporates both the stated purpose of fostering diversity as well as the use of diversity as a management tool. A more complete understanding of agriculture in terms of agro-ecology has begun to be questioned by the traditional reductionist approach to the study of agriculture. Therefore it is necessary to be aware more about the significance of microbes in processes including soil growth, plant nourishment, and the eradication of plant disease, pest, and weeds. In this study, fluorescent Pseudomonas strain (EFP56) and Trichoderma harzianum were studied for antifungal and antibacterial activity against four common root rot fungi and four common laboratory bacteria in vitro experiments. Furthermore, soil-borne disease surveillance and nutritional quality of Lagenaria siceraria, fluorescent Pseudomonas strain (EFP56) and Trichoderma harzianum were combined with neem cake and cotton cake to check their efficacy. Through the application of organic soil amendments in combination with biocontrol agents improved the quality of vegetables and their nutritional value by raising their polyphenol, carbohydrate, and protein content as well as enhancing antioxidant scavenging status. The experiments were conducted in pots and in fields to confirm their efficacy rate. The final outcomes also revealed greater induction of defense system, disease lessening and enriched fruit quality. Consortium of neem cake and cotton cake with bio-stimulants can regulate biotic as well as abiotic stress.

Continuous Plant-Based and Remote Sensing for Determination of Fruit Tree Water Status

Climate change poses significant challenges to agricultural productivity, making the efficient management of water resources essential for sustainable crop production. The assessment of plant water status is crucial for understanding plant physiological responses to water stress and optimizing water management practices in agriculture. Proximal and remote sensing techniques have emerged as powerful tools for the non-destructive, efficient, and spatially extensive monitoring of plant water status. This review aims to examine the recent advancements in proximal and remote sensing methodologies utilized for assessing the water status, consumption, and irrigation needs of fruit tree crops. Several proximal sensing tools have proved useful in the continuous estimation of tree water status but have strong limitations in terms of spatial variability. On the contrary, remote sensing technologies, although less precise in terms of water status estimates, can easily cover from medium to large areas with drone or satellite images. The integration of proximal and remote sensing would definitely improve plant water status assessment, resulting in higher accuracy by integrating temporal and spatial scales. This paper consists of three parts: the first part covers current plant-based proximal sensing tools, the second part covers remote sensing techniques, and the third part includes an update on the on the combined use of the two methodologies.

Multi-amplicon nitrogen cycling gene standard: An innovative approach for quantifying N-transforming soil microbes in terrestrial ecosystems

Agriculture accounts for nearly three-fourths of all nitrous oxide (N2O) anthropogenic emissions, a potent greenhouse gas (GHG). Improvements in agricultural management practices are critical for improving plant nitrogen (N) use efficiency and reducing N2O emissions. While implementing “climate-smart” management can reduce N2O emissions, building a linkage between these emissions and the N-cycling microbes that drive them will require N-cycling gene assays that are cost-effective, practical, and accessible to climate-smart researchers. In a recent study, a group of researchers demonstrated the suitability of synthetic oligonucleotides to serve as real-time quantitative PCR (qPCR) standards for quantifying microbial genes in soils. While this study is not based on that study, our results complement their findings and offer fresh insights into this novel methodology. Here, we describe an innovative approach that provides precision in the absolute quantification of five N-transforming target genes (AOB amoA, AOA amoA, nirK, nirS, and nosZ) in soils. Similar to the aforementioned study, our method obviates the cost-intensive aspects of traditional qPCR methods for preparing standard curves in soil microbial ecology (e.g., gel purification of PCR products and in-vivo cloning of plasmids) and is capable of being extended to any biochemical system, or environment of interest. Additionally, our qPCR approach provides several advantages: it utilizes a single multi-amplicon synthetic oligonucleotide, requires only a single dilution series and one stock solution to quantify all gene targets, and contains a non-edaphic gene (ZIKV) that can serve as a soil spike to determine DNA extraction efficiency and DNA recovery estimates. Furthermore, our protocol mitigates PCR inhibition from soil-derived substances using a modified DNA extraction protocol and inhibitor-tolerant polymerase. Ultimately, our work aims to reduce the technical burden on non-biologists/biochemists when conducting soil microbiological assays, support the development of climate mediation practices, and advance climate-smart agriculture goals.

Soil Phosphorus Partition and Transformations Under Diverse Land Uses

ABSTRACT This study investigates soil phosphorus (P) partitioning and transformations through chemical fractionation and modeling across various land uses to elucidate their impact on P dynamics and the potential for eutrophication. Geo-referenced soils (0–30 cm at various depth intervals) were collected from diverse land uses, including corn, soybean, wheat stubble, modified relay intercropping, corn-soybean with rye under conventional tillage and no-till systems, and sheep pastures, alongside an adjacent forest (control). Processed soils were sequentially extracted to quantify soluble reactive (SRP), exchangeable (EP), Ca and Mg bound (CaMgP), Fe and Al bound (FeAlP), particulate organic (POP), residual (RP), and total P pools. Results showed significant effects of land use and soil depth on extracted P pools. Notably, corn-soybean with rye exhibited a higher SRP accumulation (2.8 mg/kg) compared to the forest. The labile (SRP + EP), moderately labile (FeAlP + CaMgP + POP), and non-labile P (RP) pools accounted for 1 to 2, 23 to 29, and 65 to 76% of total P, respectively. The structural equation model elucidated soil P transformation, indicating the contribution of labile, moderately labile, and non-labile P pools to SRP accumulation in various land uses. Our findings underscore the critical link between land use, soil P dynamics, and eutrophication risk, offering valuable insights for developing agricultural management practices aimed at mitigating edge-of-field P loss and protecting water quality against eutrophication.

Crop management strategies shape the shared temporal dynamics of soil food web structure and functioning

In recent decades, there has been growing interest in exploring the soil biota, highlighting the significance of soil organisms' networks in soil functioning. Here, we use a modeling approach to investigate how changes in cropping practices influence the soil food web dynamics and it relates to that of soil functioning. In an experimental trial, we tested for change in topsoil food webs after shift from conventional to alternative practices (changes in tillage intensity, amount of residues returned and N fertilization rate). Samplings were made in 16 plots of a randomized complete block design during spring of year 0, 2 and 4 after the onset of the trial. Microorganisms, microfauna, mesofauna and macrofauna were sampled, identified and grouped into trophic groups. We built a general soil food web describing plausible carbon flows between these trophic groups and computed several network indices. At the same dates, soil functions linked to C and N dynamics were measured from soil samples. We used a COSTATIS analysis to investigate relationships between temporal sequences of soil functions and soil food web indices. Significant interactive effects of the date and of agricultural systems were found on the mean and the maximum trophic level, the bacterial-to-fungal path ratio, the total biomass and the way biomass accumulates across trophic levels, the number of trophic groups and the functional redundancy in trophic groups. Similarly, organic matter transformations and enzymatic activities showed differences across date and agricultural systems. Results show that temporal changes in soil food web structure and in soil processes related to N and C cycling co-vary following changes in agricultural management practices. Management practices related to tillage exerted stronger effects on soil food web functioning than those related to the export of crop residues or reduction in mineral N fertiliser. For instance, reduced tillage lead to more complex food webs, with increased C and N mineralization in the upper soil layer (0–5 cm), in which most of the residues accumulate. Our results provide insights on soil food webs temporal dynamics, even within a restricted panel of agricultural practices. Our results suggest that changes in agricultural practices influence feedbacks between organisms and the functions they perform, so that a temporal co-structure can be observed in the studied site. Such work could help better understand the mechanisms of resistance or ecological debt during agroecological transition, which could limit or delay expected Nature-based solutions.

"Effects of Floating Aquatic Vegetation and Canal Sediment on Phosphorus in Drainage Discharges in Agricultural Canals: A Case Study in the Everglades Agricultural Area, Florida"

Phosphorus (P) discharge from agricultural and urban drainage is known for causing downstream eutrophication worldwide. Agricultural best management practices that are designed to reduce P load out of farms target different P species from various sources such as fertilizers leaching and farm soil and canal sediment erosion, however, few studies have assessed the impact of floating aquatic vegetation (FAV) on canal sediment and farm drainage water quality. This study evaluated the impact of FAVs on canal sediment properties and P water quality in drainage canals in the Everglades Agricultural Area in south Florida, USA. Non-parametric statistical methods, correlation analysis, trend analysis and principal component analysis (PCA) were used to determine the relationship between FAV coverage with sediment properties and P water quality parameters. Results showed that FAV coverage was correlated with the highly recalcitrant and most stable form of P in the sediment layer (Residual P Pool). FAV coverage also correlated with the dissolved organic P (DOP) which was the smallest P pool (7%) of total P concentration in drainage water, therefore FAV coverage had no correlation with farm P load. The trend analysis showed no trend in farm P loads, despite a decline in FAV coverage at farm canals over an 8-year period. Phosphorus content in the sediment surface layer was strongly associated with farm P load and had a significant correlation with particulate P (PP) and soluble reactive P (SRP) which constituted 47% and 46% of the total P concentration in the drainage water, respectively. Equilibrium P concentration assays also showed the potential to release SRP from the sediment layer. The P budget established for this study reveals that sediment stores the largest P mass (333 kg P), while FAVs store the smallest P mass (8 kg P) in a farm canal, highlighting the significant contribution of canal sediment to farm P discharges. Further research is required to evaluate the impact of sediment removal and canal maintenance practices that help reduce farm P discharges.

Organic management pattern improves microbial community diversity and alters microbial network structure in karst tea plantation

Soil microbiomes play a crucial role in enhancing plant growth, health, and overall agricultural productivity. Nevertheless, the influence of distinct agricultural management practices on the microbial diversity and community structure within tea (Camellia sinensis) plantations has remained enigmatic. This study postulates that organic agricultural management models can enhance microbial diversity and optimise the microbial community structure within tea plantations, indirectly augmenting soil fertility and tea quality. We employed metagenome technology and conducted molecular ecological network analysis to explore the impact of organic management, pollution-free management, and conventional management on the microbial network structure of tea plantation soil in Weng'an County in the southwestern karst region. Soils subjected to organic management exhibited a higher relative abundance of soil microbial and carbohydrate-active enzyme functional genes than those subjected to other management regimes. Additionally, the relative abundance and diversity of dominant bacteria and keystone species were notably higher under organic management than under the other management regimes. Correlation analysis showed that soil microorganisms were closely related to soil fertility and tea quality, respectively. One-way analysis of variance and the structural equation modelling results showed significant variability in soil fertility under the three agricultural management modes and that soil fertility and soil microbial diversity had a direct impact on tea quality (P > 0.05). In conclusion, this study underscores the profound impact of management modes on microbial diversity and community structure within tea plantations. These management practices alter the soil microbial network structure and potential function, ultimately regulating the microecological dynamics of the soil community in tea plantations.

Accounting for the impact of tree size and soil spatial variability on leaching from orchards

Commercial agricultural production of orchards is based on water and fertilizer applications. Over-application and orchard spatial variability lead to water and nitrogen (N) losses through leaching and environmental damage. This work introduces a novel advanced method to quantify N and water leaching at the orchard scale by combining soil monitoring, unmanned aerial vehicle (UAV) imagery to estimate tree size, leaf N and canopy content, and water flow and N transport models. Four neighboring commercial orange orchards were selected, and 48 representative trees were instrumented with suction cups and tensiometers at a depth of 90 cm. The physical properties of the soil profiles in the vicinity of each tree were determined. During 2019–2021, UAV structure-from-motion (SfM) photogrammetry was used to classify the tree sizes into small, medium, and big categories. Soil porewater extraction and soil matric potential measurements were conducted every three weeks, while leaf N contents (LNC) were determined through bimonthly leaf tissue sampling. The LNC, N leaching, soil water state, and N use efficiency (NUE) (the ratio between the mass of plant N uptake and the mass of N applied per area) were strongly related to tree size classification. Results of the calibrated hydrological model illustrated that the 'big' trees exhibited minimal N leaching due to higher transpiration compared to the other tree size categories. An NUE map was established using the calibrated model and field measurements, demonstrating that soil spatial variability minimally affected N leaching compared to tree size distribution. The presented holistic approach can be used to identify N-leaching hotspots, improve orchard scale NUE estimates, and promote sustainable agricultural management practices.

Effects of different management practices on the growth and yield of corn

In Indonesia, corn is an important commodity that serves as the second source of carbohydrates after rice, whose productivity is influenced by management practices applied during cultivation. This research aimed to determine the effects of different management practices on the growth and yield of corn. This research was arranged in a single-factor Randomized Complete Block Design, with different agriculture management practices as treatments, consisting of TI1 = Best Practices (Drip Irrigation + Rice Husk + Mycorrhiza), TI2 = Farmers’ Practices (Furrow Irrigation) + Mycorrhiza, and TI3 = Farmers’ practices (Furrow Irrigation). The data observed were analyzed using Analysis of Variance and followed by the Post Hoc Tukey’s HSD at α= 5%. The results showed that the TI1 produced significantly higher plant height, stem diameter, leaf dry weight, weight of cob with cornhusk and kernel dry weight, and effectively suppressed weed growth compared to TI2 and TI3. TI1 produced a significantly higher number of leaves, root dry weight, and total dry weight compared to TI3, but not significantly different compared to TI2. TI1 produced not significantly different stem dry weight and harvest index compared to TI2 and TI3. The kernel dry weight per plant observed in TI1 was 157.63 g, which was 14.22% and 22.91% higher than in TI2 and TI3, respectively. Based on the coefficient correlation and path analysis, the number of leaves, plant height, and total dry weight should be considered as important plant growth variables to produce high kernel dry weight.

Soil organic carbon as an indicator of land use impacts in life cycle assessment

Abstract Purpose Anthropogenic activities are a major driver of soil and land degradation. Due to the spatial heterogeneity of soil properties and the global nature of most value chains, the modelling of the impacts of land use on soil quality for application in life cycle assessment (LCA) requires a regionalised assessment with global coverage. This paper proposes an approach to quantify the impacts of land use on soil quality, using changes in soil organic carbon (SOC) stocks as a proxy, following the latest recommendation of the Life Cycle Initiative. Methods An operational set of SOC-based characterisation factors for land occupation and land transformation were derived using spatial datasets (1 km resolution) and aggregated at the national and global levels. The developed characterisation factors were tested by means of a case study analysis, investigating the impact on soil quality caused by land use activities necessary to provide three alternative energy supply systems for passenger car transport (biomethane, ethanol, and solar electricity). Results obtained by applying characterisation factors at local, regional, and national levels were compared, to investigate the role of the level of regionalisation on the resulting impacts. Results and discussion Global maps of characterisation factors are presented for the 56 land use types commonly used in LCA databases, together with national and global values. Urban and industrial land uses present the highest impacts on SOC stocks, followed by severely degraded pastures and intensively managed arable lands. Instead, values obtained for extensive pastures, flooded crops, and urban green areas often report an increase in SOC stocks. Results show that the ranking of impacts of the three energy systems considered in the case study analysis is not affected by the level of regionalisation of the analysis. In the case of biomethane energy supply, impacts assessed using national characterisation factors are more than double those obtained with local characterisation factors, with less significant differences in the other two cases. Conclusions The integration of soil quality aspects in life cycle impact assessment methods is a crucial challenge due to the key role of soil conservation in ensuring food security and environmental protection. This approach allows the quantification of land use impacts on SOC stocks, taken as a proxy of soil quality. Further research needs to improve the assessment of land use impacts in LCA are identified, such as the ability to reflect the effects of agricultural and forestry management practices.

Measurement and analysis of regional water-energy-food nexus resilience with an improved hybrid kernel extreme learning machine model based on a dung beetle optimization algorithm

CONTEXTIn traditional water-energy-food nexus (WEFN) system analysis, the impact of resilience is insufficiently considered, and the accuracy of resilience assessment is low, which can easily lead to system imbalance. Modeling measures can yield optimal evaluation results and provide decision makers with a scientific and efficient basis for management. OBJECTIVEThe objective of this study was to provide a new research paradigm for exploring the sustainable development of WEFN systems by quantitatively and accurately assessing WEFN resilience and identifying its key driving factors. METHODSThe connotation of WEFN resilience was established, and a human-centered conceptual framework for WEFN resilience was constructed. A WEFN resilience evaluation system was scientifically and completely constructed using qualitative and quantitative index screening methods. The hybrid kernel extreme learning machine (HKELM) model was improved based on the dung beetle optimization (DBO) algorithm to measure and analyze the WEFN resilience of the China Beidahuang Group. The CRiteria Importance Through Intercriteria Correlation (CRITIC) method was adopted to calculate the evaluation index weight of the WEFN system of the Beidahuang Group. Model performance verification methods, such as application of the theory of serial number summation, were used to evaluate the performance of the DBO-HKELM model. RESULTS AND CONCLUSIONSThe results showed that over time, the Beidahuang Group's WEFN resilience exhibited a fluctuating upward trend. From 2006 to 2008, WEFN resilience declined to level II because of predatory agricultural production and management practices. From 2008 to 2018, the WEFN resilience increased to level IV due to the protection of uncultivated land, the optimization of irrigation methods, and the increasing maturity of the agricultural modernization development model. Likewise, from 2018 to 2020, the WEFN resilience stabilized at level IV because of the optimization of agricultural planting structures and the reduction in coal consumption. Spatially, the WEFN resilience of various branches of the Beidahuang Group exhibited a trend of “gradually decreasing from north to south.” Differences in certain variables, such as the proportion of area irrigated with electromechanical wells, were the most important factors related to changes in WEFN resilience over time. The DBO-HKELM model has notable advantages over the FA-HKELM and NGO-HKELM models in terms of fitting accuracy, optimization rate, reliability, rationality, and robustness. SIGNIFICANCEThese research results could enrich quantitative assessment methods for determining WEFN system recovery strength and provide scientific support for the safe operation and sustainable development of agricultural economies and societies.

Deep-rooted winter wheat cover crop promotes subsoil organic carbon storage through improved microbial functional traits

Emerging microbial trait-based approaches for soil organic carbon (SOC) storage advocate enhancing specific soil microbial functional traits, such as increased carbon use efficiency (CUE) and enzymatic efficiency (EE) and decreased metabolic quotient (qCO2). These traits facilitate the efficient conversion of crop residues into microbial biomass C (MBC), that is subsequently stabilized as SOC in the soil mineral fraction. However, our current understanding of SOC dynamics in croplands is mainly confined to topsoil or tillage zone, and the field-based evidence for subsoil microbial functional trait dynamics is sparse. To address this knowledge gap, we studied the effect of contrasting long-term agricultural management practices on microbial functional traits favoring SOC accumulation in topsoil and subsoil by conducting a laboratory experiment using 13C labeled glucose addition. Our results show a 19 % increase in Cgrowth (C allocated for microbial biomass growth), 11 % increase in CUE and 14 % increase in EE under no-till (NT) compared to conventional till (CT) in topsoil (0–10 cm) and no difference in these microbial parameters in subsoil (30–40 cm) between NT and CT. Growing a deep-rooted winter wheat (WW) cover crop increased CUE by 28 % in the topsoil and 11 % in the subsoil compared to no-cover treatment. We found separate drivers controlling SOC accumulation in topsoil and subsoil. These drivers are increased particulate organic matter C (POM–C) and Cgrowth, under NT in topsoil and increased Cgrowth over respiration and mineral associated organic matter C (MAOM–C), under WW in subsoil. Overall, our results provide experimental evidence that different microbial functional traits, molded by different long-term conservation practices, dictate SOC storage in agricultural topsoil and subsoil.

The effect of biochar types on carbon cycles in farmland soils: A meta analysis

Application of biochar has been demonstrated to be a successful strategy for boosting soil carbon sequestration and altering the agricultural soil carbon cycle. However, in the studies involving biochar worldwide, the effects of different types of biochar on the soil carbon component response direction and increase are not consistent. Therefore, to assess the effects of applying four types of biochar during the soil carbon cycle on carbon components on a farmland, we performed a meta-analysis of 1150 comparisons from 86 peer-reviewed publications. Generally speaking, the types of biochar raw materials have a significant impact on soil carbon cycle. The application of chaff biochar significantly inhibited (10.0 %) soil respiration, while the application of manure biochar (47.0 %), straw biochar (11.2 %) and wood biochar (8.7 %) showed a strong promotion effect on CO2 emission. In addition, although the soil organic C, microbial biomass C and dissolved organic C all had positive responses to the application of the four biochar types, the degree and increase in their response varied greatly due to the differences in biomass raw materials. Moreover, by increasing the biochar rates applied to coarse-textured soils with low average annual rainfall and an average temperature under controlled circumstances, the relative increase in SOC was encouraged. Meanwhile, applying low temperature pyrolytic biochar (≤400 °C) at a lower rate (<25 t/ha) in the long-term experiment (>3 years) is more beneficial to soil C sequestration and emission reduction. Hence, climatic conditions, agricultural management practices, and initial soil properties jointly constrained and influenced the ability of biochar to alter the soil C cycle. Based on this, our research offers a fresh viewpoint for making a profound study biochar-enhanced soil C cycle.

WSN-Driven Advances in Soil Moisture Estimation: A Machine Learning Approach

Soil moisture estimation is crucial for agricultural productivity and environmental management. This study explores the integration of Wireless Sensor Networks (WSNs) with machine learning (ML) and deep learning (DL) techniques to optimize soil moisture estimation. By combining data from WSN nodes with satellite and climate data, this research aims to enhance the accuracy and resolution of soil moisture estimation, enabling more effective agricultural planning, irrigation management, and environmental monitoring. Five ML models, including linear regression, support vector machines, decision trees, random forests, and long short-term memory networks (LSTM), are evaluated and compared using real-world data from multiple geographical regions, which includes a dataset from NASA’s SMAP project, supplemented by climate data, which employs both active and passive sensors for data collection. The outcomes demonstrate that the LSTM model consistently outperforms other ML algorithms across various evaluation metrics, highlighting the effectiveness of WSN-driven approaches to soil moisture estimation. The study contributes to the advancement of soil moisture monitoring technologies, offering insights into the potential of WSNs combined with ML and DL for sustainable agriculture and environmental management practices.

Biochar dose-dependent impacts on soil bacterial and fungal diversity across the globe

Biochar, a widely used material for soil amendment, has been found to offer numerous advantages in improving soil properties and the habitats for soil microorganisms. However, there is still a lack of global perspectives on the influence of various levels of biochar addition on soil microbial diversity and primary components. Thus, in our study, we performed a global meta-analysis of studies to determine how different doses of biochar affect soil total carbon (C), nitrogen (N), pH, alpha- and beta-diversity, and the major phyla of both bacterial and fungal communities. Our results revealed that biochar significantly increased soil pH by 4 %, soil total C and N by 68 % and 22 %, respectively, in which the positive effects increased with biochar doses. Moreover, biochar promoted soil bacterial richness and evenness by 3–8 % at the biochar concentrations of 1–5 % (w/w), while dramatically shifting bacterial beta-diversity at the doses of >2 % (w/w). Specifically, biochar exhibited significantly positive effects on bacterial phyla of Acidobacteria, Bacteroidetes, Gemmatimonadetes, and Proteobacteria, especially Deltaproteobacteria and Gammaproteobacteria, by 4–10 % depending on the concentrations. On the contrary, the bacterial phylum of Verrucomicrobia and fungal phylum of Basidiomycota showed significant negative responses to biochar by −8 % and −24 %, respectively. Therefore, our meta-analysis provides theoretical support for the development of optimized agricultural management practices by emphasizing biochar application dosing.

Factors Affecting the Land Investment Decisions in the Old Members of the European Union: A Systematic Literature Review

In response to concerns over land concentration and access within the European Union, this study seeks to elucidate the factors influencing farmers’ decisions to invest in land and the consequent growth of farm size. Employing a systematic literature review utilizing the PRISMA method, we delve into theoretical and empirical studies to bridge the gap between agricultural management practices and land market dynamics. Our analysis reveals a complex interplay of endogenous and exogenous factors, including technological advancements, farm characteristics, demographic factors, macroeconomic conditions, and policy environment, significantly impacting investment behaviours and farm growth trajectories. The research highlights the underexplored impact of external factors like policy and land regulation, which are scarcely addressed in empirical studies despite their substantial influence on farm-size evolution and investment decisions. Furthermore, the study emphasizes the need for future research to incorporate a more comprehensive framework that integrates internal farm dynamics with broader economic and policy contexts, thereby facilitating a deeper understanding of the agricultural sector’s resilience and sustainability. The findings underscore the critical role of adopting innovative methodologies and approaches to fully understand the dynamics of farm growth and land investments, aiming to support policymakers, stakeholders, and researchers in fostering sustainable agricultural practices.

Crop cover and nutrient levels mediate the effects of land management type on aquatic invertebrate richness in prairie potholes.

Aquatic invertebrates provide important ecosystem services, including decomposition and nutrient cycling, and provide nutrition for birds, fish, amphibians, and bats. Thus, the effects of agricultural land management practices on aquatic invertebrates are relevant to farmers, wildlife biologists, and policymakers. Here, we used data on aquatic invertebrates (159 taxa, 73 to species, 75 to genus/family) collected in 40 wetlands in the Canadian prairies to test for direct and indirect relationships among land management types (perennial cover, organic, minimum tillage, conventional), landscape structure (cropland and wetland cover within the surrounding landscape), and water quality (total nutrient levels, turbidity) on species richness of invertebrates using structural equation modelling. Additionally, we assessed variation in community composition within and among wetlands in different land use management types using a direct gradient analysis and variance partitioning. The direct effects of land management type were not supported but we found strong supportive evidence that effects of land management on richness were significantly mediated through cropland cover, nutrient levels, and turbidity. After controlling for these indirect effects, aquatic invertebrate richness decreased along a gradient from the lowest to the highest farming intensity, i.e., richness decreased from perennial cover sites to organic to minimum tillage to conventional sites. Support was also found for negative effects of nutrient levels and turbidity on richness. We did not find significant support for differences in gamma diversity or a simple test (homogeneity of multivariate dispersions) of differences in turnover among land management types; however, land management had a significant effect in distance-based redundancy analysis. Taken together, these results suggest that focusing conservation efforts on reducing cropland erosion and nutrient inputs to wetlands and creating more permanent cover may be effective strategies for conserving richness of aquatic invertebrates in agricultural landscapes in this region.