Soil Management Practices Research Articles

Comparative efficacy of wheat-straw biochar and chicken-waste compost on cadmium contaminated soil remediation, reducing cadmium bioavailability and enhancing wheat performance under cadmium stress

Cadmium (Cd) pollution of soil and food crops is a widespread environmental issue caused by excessive industrialization, unsustainable urbanization, and intensive farming practices. Cd, a hazardous element, poses significant risks to agro-environmental sustainability, food safety, and human health. Using organic materials such as biochar and compost to stabilize Cd in contaminated soil is an environmentally benign and cost-effective strategy for remediating moderately to highly polluted soil. However, in response to the scarcity of comparative studies on biochar and compost efficacy, this research explores the impact of wheat-straw biochar and chicken waste compost on Cd-contaminated soil remediation. A greenhouse experiment using two application rates (1.5 % and 2.5 %) of biochar and compost in 10 mg kg−1 Cd-contaminated soil revealed significant (p≤0.05) effects. The 2.5 % compost application increased soil organic carbon (SOC) from 0.45 % to 0.85 %, while 2.5 % biochar enhanced soil pH from 7.1 to 7.7 and electrical conductivity (EC) from 0.33 to 0.44 dSm−1. Notably, 2.5 % biochar significantly reduced Cd bioavailability from 9.49 to 4.90 mg kg−1, root accumulation from 29.8 to 16.4 mg kg−1 and shoot translocation from 16.8 to 8.4 mg kg−1. This reduction was confirmed through translocation factor (51.5 %) and immobilization efficiency (48.4 %). Furthermore, 2.5 % biochar improved chlorophyll content (a, b, and total) and wheat morphological attributes under Cd stress in soil. Overall, higher rates of biochar (2.5 %) and compost (2.5 %) effectively mitigate Cd uptake, improve soil properties, and enhance physiological and morphological responses, suggesting their promise for sustainable soil management practices.

Effects of Different Rates of Sugarcane Biochar on Amelioration of Adverse Salinity Effects in Calcareous Clay Soil

ABSTRACT Soil salinity is a major challenge in agriculture, particularly in calcareous soils with high calcium carbonate levels. Biochar, produced from biomass pyrolysis, is being considered as a potential solution for mitigating salinity effects. A greenhouse pot experiment was conducted using calcareous soil from a saline field to investigate the effects of sugarcane biochar applied at different rates (0.0%, 2.0%, and 5.0%) on soil properties and wheat (Triticum aestivum L.) growth. Results showed that both Low Rate (2.0% biochar) and High Rate (5.0% biochar) treatments significantly improved soil pH, reduced electrical conductivity (EC), and increased soil organic matter (SOM) content. Plant growth indicators such as plant height, stem diameter, and leaf chlorophyll content also showed significant improvement with biochar application. High Rate had more pronounced effects compared to Low Rate. The analysis confirmed the significant effects of biochar on soil properties and plant growth, indicating its potential as a beneficial soil amendment. Sugarcane biochar has the potential to mitigate salinity stress and enhance crop productivity in calcareous soils. Further research is needed to explore the long-term effects of sugarcane biochar application and its interactions with other soil management practices in different crop systems. These findings highlight the promising role of biochar as a sustainable approach for mitigating salinity stress in agriculture and improving soil quality for crop production.

Soil biological quality in rhizosphere, growth, and yield of upland rice grown on acid soil after amended biochar enriched sap of Kappaphycus alvarezii

Abstract. Rakian TC, Kilowasid LMH, Afa LO, Riskyana A, Nurazizah, Wijayanti Y, Bahrun A, Subair I, Rahni NM, Alam S, Sarawa, Karimuna L. 2023. Soil biological quality in rhizosphere, growth, and yield of upland rice grown on acid soil after amended biochar enriched sap of Kappaphycus alvarezii. Biodiversitas 24: 6780-6792. Biological soil quality is essential in evaluating soil management practices using biochar enriched for upland rice growth on acid soil. Therefore, the study aimed to (i) analyze the effect of biochar-enriched sap of Kappaphycus alvarezii (K-sap) on the abundance of Arbuscular Mycorrhizae Fungi (AMF), bacteria, and protozoa in rhizosphere soil, growth, and yield of upland rice, and (ii) the relationship between the abundance of soil biota and the growth and yield components, as well as straw N, P, and K content on acid soil. Four upland rice were grown on acid soil incubated with biochar-enriched sap for two weeks in pots. Nine treatments of the biochar-enriched sap were tested, namely control, 5% biochar-0% K-sap, 5% biochar-5% K-sap, 5% biochar -10% K-sap, 5% biochar-15% K-sap, 7.5% biochar-0% K-sap, 7.5% biochar-5% K-sap, 7.5% biochar-10% K-sap, and 7.5% biochar-15% K-sap. Each treatment was three replicates in a randomized block design. The results demonstrated that the AMF spores quantity decreased while flagellates increased in the soil rhizosphere. The P and K content increased, the N:P decreased, and P:K ratio varied in the straw of the upland rice. Plant height and total spikelets increased, while root dry weight and roots to shoots ratio (R:S) decreased with biochar enriched. The abundance of AMF spores and flagellates correlated positively and negatively with R:S. Furthermore, R:S was negatively correlated with plant height and total spikelets. Plant height and total spikelets showed a positive correlation, while root dry weight and R:S was negatively correlated with K content in shoot tissue. The P and K contents with N:P ratio and N:P with P:K were negatively correlated. In conclusion, biochar-enriched K-sap effectively regulated the activity and composition of soil biota in the rhizosphere, influencing upland rice's growth, yield, and nutrient balance uptake on acid soils.

Multiple potentially toxic elements in urban gardens from a Brazilian industrialized city.

Urban agriculture should be promoted as long as the food produced is safe for consumption. Located in the metropolitan region of São Paulo-Brazil, Santo André has intense industrial activities and more recently an increasing stimulus to urban gardening. One of the potential risks associated to this activity is the presence of potentially toxic elements (PTEs). In this study, the concentration of PTEs (As, Ba, Cd, Co, Cu, Cr, Ni, Mo, Pb, Sb, Se, V and Zn) was evaluated by soil (n = 85) and soil amendments (n = 19) in urban gardens from this municipality. Only barium was above regulatory limits in agricultural soil ranging from 20 to 112mgkg-1. Geochemical indexes (Igeo, Cf and Er) revealed moderate to severe pollution for As, Ba, Cr, Cu, Pb Se and Zn, especialy in Capuava petrochemical complex gardens. A multivariate statistical approach discriminated Capuava gardens from the others and correlated As, Cr and V as main factors of pollution. However, carcinogenic and non-carcinogenic risks were below the acceptable range for regulatory purposes of 10-6-10-4 for adults. Soil amendments were identified as a possible source of contamination for Ba, Zn and Pb which ranged from 37 to 4137mgkg-1, 20 to 701mgkg-1 and 0.7 to 73mgkg-1, respectively. The results also indicated the presence of six pathogenic bacteria in these amendments. Besides that, the occurrence of antimicrobial resistance for Shigella, Enterobacter and Citrobacter isolates suggests that soil management practices improvement is necessary.

Perspectives on the misconception of levitating soil aggregates

Abstract. Soil aggregation is an important process in nearly all soils across the globe. Aggregates develop over time through a series of abiotic and biotic processes and interactions, including plant growth and decay, microbial activity, plant and microbial exudation, bioturbation, and physicochemical stabilization processes, and are greatly influenced by soil management practices. Together, and through feedback with organic matter and primary soil particles, these processes form dynamic soil aggregates and pore spaces, which jointly constitute a soil's structure and contribute to overall soil functioning. Nevertheless, the concept of soil aggregates is hotly debated, leading to confusion about their function or relevancy to soil processes. We argue here that the opposition to the concept of soil aggregation likely stems from the fact that the methods for the characterization of soil aggregates have largely been developed in the context of arable soils, where tillage promotes the formation of distinct soil aggregates that are easily visible in the topsoil. We propose that the widespread use of conceptual figures showing detached and isolated aggregates can be misleading and has contributed to the skepticism towards soil aggregates. However, the fact that we do not always see discrete aggregates within soils in situ does not mean that aggregates do not exist or are not relevant to the study of soil processes. Given that, by definition, soil aggregates consist of any group of soil particles that cohere more strongly to each other than neighboring particles, aggregates may, but do not necessarily need to be, bordered by pore space. Here, we illustrate how aggregates can form and dissipate within the context of undisturbed, intact soils, highlighting the point that aggregates do not necessarily need to have a discrete physical boundary and can exist seamlessly embedded in the soil. We hope that our contribution helps the debate on soil aggregates and supports the foundation of a shared understanding on the characterization and function of soil structure.

Quinoa growth and yield, soil water dynamics, root growth, and water use indicators in response to deficit irrigation and planting methods

To address the growing issue of scarce water in the arid and semi-arid areas, it is essential to investigate the potential of drought tolerant crops and implement promising farm management strategies to improve water productivity and yield production. Therefore, a split plot experiment to investigate how different irrigation levels (I-1:100% water requirement (WR), I-2:75%WR, and I-3: 50%WR) and planting methods (P-1: basin, P-2: on-ridge, and, P-3: in-furrow) interact and affect quinoa water use, yield, root growth, and water productivity in southern Iran over two growing seasons. The results showed high seasonal crop evapotranspiration (993–1030 mm) in I-1 as a result of the high advection ratio (α), which ranged from 1.02 to 1.46 from the early vegetative to the seed filling stages. The P-3 increased transpiration rate by 4.5% and 7.7%, and decreased soil evaporation by 17% and 29% compared to P-1 and P-2, respectively. Single (Kc) and dual (Kcb + Ke) crop coefficients varied between 0.41 and 1.38 over the two growing seasons. Grain yield in P-3 were 25%, 34%, and 44% higher compared to P-1 and P-2 under I-1, I-2 and I-3, respectively. The study revealed that nearly 67% and 80% of the total root dry matter was in the 0–30 cm and 0–60 cm of the soil profile in all experimental treatments, respectively. Regardless of irrigation treatment, root length density (RLD) and root mass density (RMD) were found to be 18.9% and 15.7% lower in P-1’s top 0–20 cm of the soil profile than those obtained in P-2 and P-3, respectively. Analyses showed that the increased root length in deeper soil layers contributed to higher soil water uptake, and consequently higher crop water productivity. In addition, root-to-shoot ratio increased as the amount of the applied irrigation water was decreased. Quinoa exhibited the highest acclimation to water stress in P-3 based on water stress sensitivity coefficients (λi) and yield response factor (Ky) values. Crop water productivity (WPC) and irrigation water productivity (WPI) for grain yield varied between 0.17 and 0.28 kg m−3. In conclusion, in terms of grain yield, shoot and root dry matter and water productivity, I-2 and P-3 (75% WR irrigation level and in-furrow planting method treatment) is recommended as the optimum water and planting management strategy for quinoa cultivation in the study area as a measure to address water scarcity and food sustainability. Still, to improve yield and irrigation water efficiency, the effect of soil management practices such as mulching and organic amendments on soil water retention and nutrient availability for quinoa should be investigated.

ARMOSA Model Parametrization for Winter Durum Wheat Cultivation under Diverse Cropping Management Practices in a Mediterranean Environment

In anticipation of climate changes, strategic soil management, encompassing reduced tillage and optimized crop residue utilization, emerges as a pivotal strategy for climate impact mitigation. Evaluating the transition from conventional to conservative cropping systems, especially the equilibrium shift in the medium to long term, is essential. ARMOSA, a robust crop simulation model, adeptly responds to varied soil management practices such as no tillage, minimum tillage, and specific straw management options such as chopping and incorporating crop residue into the soil (with or without prior nitrogen and water addition before ploughing). It effectively captures dynamic fluctuations in total organic carbon over an extended period. While challenges persist in precisely predicting grain yield due to climatic intricacies, ARMOSA stands out as a valuable and versatile tool. The model excels in comprehending and simulating wheat cultivar responses in dynamic agricultural ecosystems, shedding light on phenological patterns, biomass accumulation, and soil organic carbon dynamics. This research significantly advances our understanding of the intricate complexities associated with past wheat cultivation in diverse environmental conditions. ARMOSA’s ability to inform decisions on conservation practices positions it as a valuable asset for researchers, agronomists, and policymakers navigating the challenges of sustainable agriculture amidst climate change. Its real-world significance lies in its potential to guide informed decisions, contributing to global efforts in sustainable agriculture and climate resilience.

A global dataset of biochar application effects on crop yield, soil properties, and greenhouse gas emissions

Biochar application is widely studied to mitigate the threats of soil degradation to food security and climate change. However, there are big variations in the effects of biochar application on crops, soils, and the atmosphere during crop production. This study provides a global dataset of biochar application effects on crop yield, soil properties, and greenhouse emissions. The dataset is extracted and integrated from 367 peer-reviewed studies with 891 independent field, laboratory, and incubation experiments across 37 countries. This dataset includes 21 variables before and after biochar application (including soil properties, crop yield, greenhouse gas emissions, etc.) of 2438 items, focusing on two main biochar application types: biochar application alone and combined with fertilizers. Background information on climate conditions, initial soil properties, management practices, and characteristics of biochar sources and production is also contained in the dataset. This dataset facilitates a comprehensive understanding of the impact of biochar application, supports the utilization of agricultural wastes for biochar production, and assists researchers in refining experimental protocols for further studies.

Mobility of Nitrates and Phosphates from Animal Manure-Amended Soil to Runoff and Seepage Water from a Sweet Potato Field

Ammonia, nitrate, and phosphate in animal manure used as fertilizer reduce environmental quality by running off agricultural fields into natural water resources. Runoff and seepage water from five soil management practices (chicken manure CM, sewage sludge SS, chitin CH, biochar Bio, and no-amendment NA control plots), were investigated for their potential nutrient catching down the field slope of a sweet potato, Ipomoea balata field. The results revealed that CM-amended soil released the greatest runoff water volume (172.6 L plot −1) compared to the control treatment (98.6 L plot −1), indicating a 75% increase in the runoff water volume. CM also increased the percolated water into the rhizosphere of the growing plants by 55% compared to the control, whereas SS reduced the runoff water volume and increased the leaching water by 36% and 82%, respectively (a desirable attribute of water conservation), compared to the control plots. The concentration of PO4−3 ions in the percolated water from the biochar treatment was significantly greater compared to the other treatments, indicating there was no impact of biochar on binding PO4−3 ions. SS reduced the nitrate concentrations in the runoff and increased the seepage water volume percolated towards the roots of the growing plants; a desired attribute for preventing surface water contamination by nitrates. Observing the precipitation pattern and improving the N application rate are recommended.

New empirical-point pedotransfer functions for water retention data for a wide range of soil texture and climates

Knowing soil hydraulic properties is essential to support soil use and management practices; however, their measuring is commonly expensive and time-consuming. Thus, pedotransfer functions (PTFs) have been used to quantify physical properties such as the soil water retention curve (SWRC). SWRC relates the volumetric soil water content (θ) as a function of the matric potential (h) and plays a vital role in soil hydraulic modeling. Point-PTFs estimate key-points of the SWRC, often from measured texture, bulk density, and organic matter. This study aimed to formulate new point-PTFs to estimate θ(h) data ranging from θ(-0.1 m) to θ(-150 m) to be applied in subtropical, tropical and temperate soils. The PTF equations were derived from linear and non-linear regressions of measured soil physical properties against to the water retention data. The prediction performance of the new-formulated PTFs overcame the performance of already existing and widely-known PTFs recognized in the literature and can be, therefore, applied in soil water retention topics under a wider textural range.

Soil hydrostructural parameters under various soil management practices

Hydrostructural parameters are driven by the characterization of the soil aggregates structure using a set of thermodynamic equations. Soil aggregates structure is unique for each soil type and can be affected by its physical, chemical, and biological properties. Because it so completely represents those properties, tracking the changes in soil aggregates structure can be used to develop quantitative indicators of soil quality. This study involves a field experiment to examine pedostructure-based soil characterization under different soil management practices. It investigates the feasibility of defining a new soil quality indicator. Three organic amendments (chicken manure, dairy manure, and milorganite) were applied at 0, 168, 336, 672 kgN/ha (rate 0, 1, 2, and 3) for 36 plots of 3 m. × 1.5 m. After extracting 12 hydro-structural parameters from TypoSoil™ measurements, statistical analysis was used to evaluate the sensitivity of these parameters to management practices. Results showed that increasing the application rate from 1 to 3 showed no significant effect on hydrostructural parameters for all treatments. However, treatments significantly enhanced water content and available water in the A horizon. In the B horizon, only rate 3 affected available water for chicken and dairy manure. Comparing the three treatments, dairy manure’s significance was prominent and promising for improving soil aggregates structure in rates greater than 1. The best application rate to improve soil aggregates structure for chicken manure seems to be 1, for dairy manure rate 2, and milorganite rate 3.

Response of soil microbiota to various soil management practices in 100-year-old agriculture field and identification of potential bacterial ecological indicator

The study aimed to comprehensively investigate the structural dynamics of a soil microbial community within a 100-year agricultural field experiment. The experimental design encompasses three distinct soil management practices, namely monoculture, five–year rotation, and random rotation, each with or without the incorporation of legumes and manure. Soil microbial communities were determined by the Next-Generation Sequencing (Illumina MiSeq analysis) of both the V3 and V4 hypervariable regions of the 16S rRNA gene for bacteria and Archaea, as well as ITS1 for fungi. In all soils, dominant bacterial phyla were Proteobacteria, Actinobacteria, Acidobacteria, and Chloroflexi, and dominant orders were Actinomycetales, Rhizobiales, Acidimicrobiales, and Sphingomonadales. However, dominant fungal phyla were Ascomycota, Basidiomycota, and Zygomycota, and dominant fungal orders were Pleosporales, Eurotiales, Hypocreales, or Mortierellales. Compared to fallow land, agricultural soil management affected the microbial community of the soil, reducing the ratio of oligotrophs (e.g. Acidobacteria and Armatimonadetes) to copiotrophs (Actinobacteria or Gemmatimonadetes). Moreover, agricultural soil management contributed to an increased number of plant growth-promoting bacterial groups (PGPB), antagonistic to many fungal (e.g., Fusarium spp.) and bacterial pathogens (e.g., Bukholderiales, Xanthomonadales). However, generally in the study, there were no significant differences in microbial communities between monoculture and crop rotations. Moreover, two taxa can be considered as potential indicators of “healthy soil”: the nitrifying bacteria Nitrospira spp. whose abundance was strongly dependent on nitrogen, potassium, phosphorus, organic carbon, and soil pH, and the PGP fungi of the genus Mortierellla which depended mainly on nitrogen and pH. Finally, the genus Mortierellla was generally the most abundant in agricultural soils, especially in the five–year rotation with legumes, while fallow soils did not favour these microorganisms. In conclusion, various soil management practices strongly affect the soil microbiota and thus their ability to support land productivity.

Phosphorus speciation under long‐term crop rotation management in a tropical soil

AbstractCrop rotation and soil management practices after native tropical forest conversion may impact the dynamics of inorganic and organic phosphorus (Pi and Po) species in the soil. By combining the state‐of‐the‐art spectroscopic methods P K‐edge X‐ray absorption near edge structure (XANES), 31P liquid nuclear magnetic resonance (31P‐NMR) and chemical P fractionation, this study provides important insights on soil P speciation after conversion of native forest to cropland under distinct managements. A field trial was conducted in a weathered tropical soil to assess Pi and Po changes after conversion of native forest to cropland. The crop rotations were managed under no‐tillage (NT) or minimum tillage (MT) since 2003, and repeated annually until 2015, cropped in the fall–winter and spring seasons, followed by soybean in the summer. Soil XANES analysis in the end revealed that P was predominantly associated with ferrihydrite and hematite, suggesting that P speciation was more strongly influenced by the presence of iron(oxyhydr)oxide than by crop rotations and/or soil management. The conversion of native forest to cropland promoted the mineralization of Po species, leading to re‐adsorption in non‐labile forms and consequently worsening the P cycling in the system. To increase the labile P pools and supply crop P demand, inputs of inorganic fertilizers were required owing to the strong soil P sorption. Our results show that even conservation practices such as MT or NT and complex crop rotations are not sufficient to inhibit the impact of cropland conversion on soil P forms.

Responses of soil microbial metabolic limitations to erosion under contrasting soil types and management practices

AbstractSoil microbial metabolism plays an important role in supporting soil services and functionalities but is usually restricted by the availability of soil nutrients. Although soil microbial metabolism limitation (SMML) has been widely addressed with regard to various driving factors, its response to erosion has not been examined but is urgently needed given the important influence of erosion on global environments. To understand how erosion affects SMML and whether erosion's effect varies with tillage practices and soil types, we conducted a simulated erosion experiment to compare eroded and noneroded plots with contrasting soil types (Mollisol vs. loess soils) and managements (conventional tillage versus no‐tillage in plots with crops versus without crops). We measured soil extracellular enzymatic activities and quantified SMML with extracellular enzymatic stoichiometry models. In both soils, the microbes were limited by carbon (C) and phosphorus (P), but not by nitrogen, and microbial C and P limitations were greater in Mollisol than loess soils. For the Mollisol, erosion significantly increased the relative C limitation, whereas the presence of crops eliminated this increase. For the loess soils, erosion enhanced the relative C limitation regardless of crop presence and tillage management. Erosion consistently increased microbial P limitation in plots with crops, with greater effects under no‐tillage (+2.9%) compared to conventional tillage (+0.7%) conditions regardless of soil type (p < 0.05). In plots without crops, microbial P limitation was increased by erosion under no‐tillage (+2.1%) but was decreased under conventional tillage (−5.6%) (p < 0.05). Additionally, conventional tillage exacerbated microbial C limitation but alleviated microbial P limitation. These results indicated that erosion shifted microbial C and P limitations depending on soil type, tillage practice and the presence of plants, highlighting the importance of considering all these factors when assessing soil microbial metabolic limitation at various spatial scales.

The Biochar Amendment Improves Tomato Growth and Yield under Deficit Irrigation in Sandy Loam Soil in Senegal.

Poor agricultural soil management practices and water use optimisation in irrigation are major challenges facing crop production in Senegal. To address these problems, a factorial experiment was conducted in 2021 and 2022 to investigate the effects of biochar on tomato growth and yield in sandy loam soil under different irrigation levels. Treatments included three biochar treatments (B2 = 30 t·ha-1, B1 = 15 t·ha-1, and B0 = 0 t·ha-1) and three irrigation levels (full irrigation, W0 = 8 L·m-2·day-1; medium deficit irrigation, W1 = 6 L·m-2·day-1, which is 75% of W0; and deficit irrigation, W2 = 4 L·m-2·day-1, 50% of W0). The results showed that using biochar at 30 t·ha-1 significantly (P < 0.05) reduced the bulk density of the soil by up to 8.3% under W1. In addition, biochar at 15 t·ha-1 and 30 t·ha-1 enhanced, regardless of the amount of water applied, the growth of tomato plants by at least 14% compared to that in the B0 treatment. Furthermore, the tomatoes' yields in biochar treatments B1 (12.58 t·ha-1) and B2 (12.45 t·ha-1) under W2 were greater than those under B0 (9.27 t·ha-1) under full irrigation. The combinations of biochar and the lowest irrigation water level (W2 and B1 or W2 and B2) can therefore allow a water economy of up to 50% of full irrigation without compromising yield. Our study concluded that biochar could sustainably reduce agricultural water consumption while increasing yields. To further understand the influence of biochar on sandy loam soil, more research is needed on its effects on soil moisture content at permanent wilting points and field capacity.

Applying machine learning to soil analysis for accurate farming

A crucial component of agriculture is soil. Soil analysis is critical for optimizing agricultural practices and ensuring sustainable crop production. Traditional methods are often time-consuming and labor intensive, limiting their scalability and real-time applicability. The application of machine learning techniques in soil nutrient analysis has emerged as a promising solution. There is a lot of complicated soil data, but algorithms that use machine learning can handle it all, enabling accurate prediction and assessment of soil nutrient content. Integration with remote sensing technologies enhances the capabilities of soil nutrient analysis, allowing for rapid assessment at different scales. Machine learning facilitates personalized recommendations for fertilizer application, irrigation strategies, and soil amendments, tailored to the specific needs of learning and adaptive individual fields or crops. The continuous capabilities of machine learning models ensure up-to-date nutrient management recommendations. Challenges include the availability of representative interpretability of models. Nevertheless, the integration of machine learning in soil nutrient analysis offers improved resource utilization, enhanced crop productivity, and sustainable soil management practices. Ongoing research and collaboration with domain experts will further advance the application of machine learning in this field.

Agricultural advantages in soil management practices generated from the use of precision agriculture techniques. Literature review

The growing demand for food production, the economic importance of agricultural activities, and the concern with preserving natural resources justify the use of new technologies intended to increase productivity per unit area, reduce production costs, and minimize environmental impacts. Given this, in recent decades, the use of technologies related to Precision Agriculture (AP) became a viable alternative, spreading frantically in the various agricultural activities, encompassing, above all, the great cultures of agribusiness crops such as sugar cane, soy, corn, and cotton highlighting the tools and input application techniques at variable rates on the ground. Therefore, this work aimed to carry out a literature review of the last ten years' main technical/scientific publications related to soil fertility management from application techniques of input at variable rates, emphasizing agronomic results from the use of AP tools.

Erosion Modeling in Overburden Excavation in Mining Areas with the Approach of Rain Intensity and Duration

This study investigates erosion modeling in overburden excavation in mining areas with the approach of rain intensity and duration. The main variables considered included rainfall erosion as well as slope length and slope, which were identified as key factors in predicting soil management. The linear regression method evaluated the relationship between independent variables (rainfall erosion, length, and slope) and dependent variables (soil management). The analysis showed that in Model 1, not all independent variables significantly influenced soil management. However, Model 2 revealed that precipitation erosion and slope length and slope significantly affected the dependent variables. These results provide an in-depth understanding of how weather and topographic factors affect soil management practices in mining environments. These findings can be used as a basis for environmental conservation and mitigation decision-making, especially in minimizing soil erosion due to mining activities. By paying attention to these factors, it is hoped that soil management practices can be improved to achieve better environmental sustainability. Further research is recommended to expand this understanding in various geographical conditions and mining environments

SOIL EROSION AND IMPACT ON RECREATIONAL RESOURCES IN THE SHYNGYRLAU BASIN, WESTERN KAZAKHSTAN: A MULTI-ANALYTICAL ASSESSMENT

Over the past decades, water erosion has increased significantly in the Shyngyrlau River basin. Recreational development, haphazard construction and operation of roads have led to increased water erosion and the formation of numerous linear erosion forms. Erosion reduces the natural resource status of the region. Water erosion develops in most cases along roads laid along the thalwegs of the ravine-hollow network. The light substrate along with sparse vegetation cover (the sparseness is aggravated by intensive grazing) predetermine its rapid development. Water erosion is an acute problem arising from the present climate change, agricultural intensification and diverse forms of anthropogenic land degradation. Assessment of present and potential soil erosion is useful for landscape preservation as well as development planning. Multi-analytical modeling can provide a quantitative and consistent estimation of soil erosion and sediment yield under locally specific environmental conditions. The soil loss model, Revised Universal Soil Loss Equation (RUSLE), integrated with GIS, has been used to estimate soil loss in the Shyngyrlau Basin (a left-bank tributary of the Ural River, NW Kazakhstan). The RUSLE model is based on remote sensing and field data; erosion probabilities were determined using GIS. The percentage ratio of the soil loss in the Shyngyrlau River basin shows erosion variation of 0.001–2.47 t/ha/yr. The degree of erosion increases with the length of the slope. A new factor Chip curvature (Cu factor), defining the accuracy of the soil loss results, was defined. According to this factor, soil erosion in the study area is 0.007–2.48 t/ha/yr within the low erosion class. The lowest indicator of the K factor is 0.2 in sandy clay soils used as pasturelands. The highest K factor (0.3) relates to clayey arable soils. The research results add to implementation of new strategies in soil management and conservation practices reducing soil erosion in the Shyngyrlau Basin. Both climate and anthropogenic factors are seen behind the activated ground erosion. The development of forms of water erosion leads to a violation of the integrity of modern natural complexes of the West Kazakhstan region, which significantly reduces their stability and recreational potential.

Critical Period of Weed Control in Maize as Influenced by Soil Tillage Practices and Glyphosate Application

Increasing evidence on environmental and economic benefits has raised farmers’ interest in adopting alternative, less intensive soil management practices. To evaluate the influence of weed-competitive ability in response to a different tillage regime, a field study was conducted in maize under humid Central European climatic conditions in Slovenia. This study was established as a split-plot arrangement with three tillage practices (TPs) as the main plot: conventional (CN), conservation (CS), and no tillage (NT); this was combined with glyphosate application and the weed removal timing as the subplot. The weed removal timings were at the V3, V6, V9, V15, and R1 maize stages, with weed-free and weed season-long monitoring. The beginning and the end of the critical period of weed control (CPWC), based on a 5% maize yield loss rate, were determined by fitting the four-parameter log-logistic equations to the relative maize dry grain yield. The weed dry biomass from maize germination until the R1 growth stage in the NT TP was consistently lower than that in the CN and CS TP. Moreover, the NT TP resulted in a shorter CPWC (39 days after emergence (DAE)) compared to the CN (57 DAE) and CS (58 DAE). The results of CTWR (critical timing of weed removal) showed that less intensive tillage operations in the CS resulted in an earlier need for weed control (V2 and 23 DAE) compared to the CN (V3 and 39 DAE) and NT (V3 and 40 DAE). Our study suggests that the intensive tillage operations performed in the CN TP and the pre-sowing use of non-selective burndown herbicide in the NT delay the CTWR by more than 2 weeks, thus reducing the need for early post-emergence herbicide application in maize.