Agricultural Strategies Research Articles

‘For the Farmers of the Country’: Indian Agricultural Universities at the Cusp of Nation-Building Plans and the Cold War, 1947–67

Agricultural universities are integral to the history of modern India. The aspiration of the Indian state to be economically and socially modern is coincident with the origin of agricultural universities. This paper explores the making of agricultural universities from the Radhakrishnan Committee to the New Agricultural Strategy and shows their connections to the political and economic needs of the nation. Also, the Cold War imperatives encouraged American involvement in India’s agricultural reforms. However, this paper argues that neither the Indian state nor the American experts determined the evolution of these institutes as per their developmental goals. Geopolitical events, like the Partition, the Union-state relationship and the history of marginalisation of agricultural scientists combined and produced varying dynamics. It is within these historical contexts that the paper has analysed the growth trajectory of agricultural institutions, with particular reference to the Punjab Agricultural University—the pivot of the agricultural modernisation programme.

LOSS OF BIODIVERSITY AND FOOD SECURITY IN NIGERIA

Nigeria is rich in biodiversity, boasting of diverse ecosystems and numerous species. The country's ecosystems range from semi-arid savannas to montane forests, floodplains, rainforests, freshwater swamps, and coastal vegetation. However, Nigeria's rich biodiversity, essential for agriculture and food security, is under severe threat, impacting adversely on food security. This study investigates the impact of oil pollution, deforestation, and desert encroachment on biodiversity loss within Nigeria's agricultural ecosystems. This study employed a comprehensive review of existing literature on the assessment of biodiversity loss in Nigeria's agricultural ecosystems due to pollution from oil spill, deforestation and desert encroachment. By analyzing the correlation between these environmental stressors and food security challenges, this study highlight the critical need for integrated conservation and agricultural strategies. The findings indicate that the loss of biodiversity has far-reaching implications, including malnutrition, food price volatility, and the erosion of rural livelihoods. The study emphasizes the pressing necessity of tackling these challenges in order to guarantee sustainable food security and ecological equilibrium in Nigeria. To address these interconnected issues, the study recommends a holistic approach that prioritizes sustainable practices, robust policies, and community engagement. By safeguarding Nigeria's biodiversity, we can ensure a sustainable food future for generations to come.

Exploring the synergy of enhanced weathering and Bacillus subtilis: A promising strategy for sustainable agriculture.

Climate change is one of the most urgent environmental challenges that humanity faces. In addition to the reduction of greenhouse gas emissions, safe and robust carbon dioxide removal (CDR) technologies that capture atmospheric CO2 and ensure long-term sequestration are required. Among CDR technologies, enhanced silicate weathering (ESW) has been suggested as a promising option. While ESW has been demonstrated to depend strongly on pH, water, and temperature, recent studies suggest that biota may accelerate mineral weathering rates. Bacillus subtilis is a plant growth-promoting rhizobacterium that can facilitate weathering to obtain mineral nutrients. It is a promising agricultural biofertilizer, as it helps plants acquire nutrients and protects them from environmental stresses. Given that croplands are optimal implementation fields for ESW, any synergy between ESW and B. subtilis can hold great potential for further practice. B. subtilis was reported to enhance weathering under laboratory conditions, but there is a lack of data for soil applications. In a soil-mesocosm experiment, we examined the effect of B. subtilis on basalt weathering. B. subtilis-basalt interaction stimulated basalt weathering and increased soil extractable Fe. The combined application displayed higher CDR potential compared to basalt-only application (3.7 vs. 2.3 tons CO2 ha-1) taking solid and liquid cation pools into account. However, the cumulative CO2 efflux decreased by approximately 2 tons CO2 ha-1 with basalt-only treatment, while the combined application did not affect the CO2 efflux. We found limited mobilization of cations to the liquid phase as most were retained in the soil. Additionally, we found substantial mobilization of basalt-originated Mg, Fe, and Al to oxide- and organic-bound soil fractions. We, therefore, conclude that basalt addition showed relatively low inorganic CDR potential but a high capacity for SOM stabilization. The outcomes indicated the importance of weathering rate-GHG emission integration and the high potential of SOM stabilization in ESW studies.

Data-driven modeling of bio-oil yield in agricultural biomass pyrolysis with machine learning

Abundant amounts of solid waste are produced due to the processing of various agricultural goods, such as garbage incineration. This agricultural waste management strategy causes a significant increase in air pollution and environmental deterioration. Several methods are widely applied to treat agricultural waste; the pyrolysis process, which includes burning biomass feedstocks without oxygen, is one of the most recommended. Pyrolysis of agricultural waste can produce biochar, bio-oil, and syngas. Pyrolysis is a complicated procedure that depends on feedstock characteristics such as feed composition (i.e., carbon, hydrogen, and oxygen elemental composition), fixed carbon, and volatile matter. Investigation of the individual property of the feedstock on the overall product yield by experimental or computational study is laborious and time-consuming. Therefore, the machine learning technique is applied in this paper to develop a robust and accurate model to predict the agricultural waste bio-oil yield. A total of 387 data points are gathered from various literature sources. This paper utilizes the proximate analysis, ultimat analysis of the agricultural feedstock, and pyrolysis reaction conditions as input features. Eight different machine-learning algorithms, i.e. adaptive boosting, artificial neural network, categorical boosting, decision tree with bagging, k nearest neighbor, light gradient boosting, random forest, and extreme gradient boosting are deployed for this objective. In addition, a SHAP analysis with a bar plot and a beeswarm plot is built to identify the input variables that had the greatest impact on bio-oil production. The categorical boost model gave the lowest root mean squared error of 2.65 out of all the models and had the greatest R2 value of 93.2% on the testing dataset. The SHAP analysis of the developed model for identifying the feature importance and the beeswarm plot is also performed, which shows that for the pyrolysis of agricultural waste, the hydrogen content is one of the most crucial parameters for the maximization of bio-oil yield.

Discrete Homogeneous and Non-Homogeneous Markov Chains Enhance Predictive Modelling for Dairy Cow Diseases.

Modelling and predicting dairy cow diseases empowers farmers with valuable information for herd health management, thereby decreasing costs and increasing profits. For this purpose, predictive models were developed based on machine learning algorithms. However, machine-learning based approaches require the development of a specific model for each disease, and their consistency is limited by low farm data availability. To overcome this lack of complete and accurate data, we developed a predictive model based on discrete Homogeneous and Non-homogeneous Markov chains. After aggregating data into categories, we developed a method for defining the adequate number of Markov chain states. Subsequently, we selected the best prediction model through Chebyshev distance minimization. For 14 of 19 diseases, less than 15% maximum differences were measured between the last month of actual and predicted disease data. This model can be easily implemented in low-tech dairy farms to project costs with antibiotics and other treatments. Furthermore, the model's adaptability allows it to be extended to other disease types or conditions with minimal adjustments. Therefore, including this predictive model for dairy cow diseases in decision support systems may enhance herd health management and streamline the design of evidence-based farming strategies.

Apple pomace in feeding of dairy cattle as an element of sustainable agriculture strategy - a review

Abstract This work provides an overview of the knowledge about using apple pomace as milk cattle feed. Utilization of apple pomace as livestock feed is one of the possible alternatives to reduce environmental pollution and overcome the feed deficit. Apple pomace, rich in e.g. polyphenolic compounds, holds potential to be a valuable feed additive for enhancing the antioxidative capacity and overall quality of milk. The research on apple pomace as feed additive for livestock are important due to abundance of apples in Poland, the world’s second-largest apple producer. To promote sustainability in animal feed production the use of agro-food-by products as apple pomace as animal feed component should be considered.

A conceptual framework for landscape-based environmental risk assessment (ERA) of pesticides

While pesticide use is subject to strict regulatory oversight worldwide, it remains a main concern for environmental protection, including biodiversity conservation. This is partly due to the current regulatory approach that relies on separate assessments for each single pesticide, crop use, and non-target organism group at local scales. Such assessments tend to overlook the combined effects of overall pesticide usage at larger spatial scales. Integrative landscape-based approaches are emerging, enabling the consideration of agricultural management, the environmental characteristics, and the combined effects of pesticides applied in a same or in different crops within an area. These developments offer the opportunity to deliver informative risk predictions relevant for different decision contexts including their connection to larger spatial scales and to combine environmental risks of pesticides, with those from other environmental stressors. We discuss the needs, challenges, opportunities and available tools for implementing landscape-based approaches for prospective and retrospective pesticide Environmental Risk Assessments (ERA). A set of “building blocks” that emerged from the discussions have been integrated into a conceptual framework. The framework includes elements to facilitate its implementation, in particular: flexibility to address the needs of relevant users and stakeholders; means to address the inherent complexity of environmental systems; connections to make use of and integrate data derived from monitoring programs; and options for validation and approaches to facilitate future use in a regulatory context. The conceptual model can be applied to existing ERA methodologies, facilitating its comparability, and highlighting interoperability drivers at landscape level. The benefits of landscape-based pesticide ERA extend beyond regulation. Linking and validating risk predictions with relevant environmental impacts under a solid science-based approach will support the setting of protection goals and the formulation of sustainable agricultural strategies. Moreover, landscape ERA offers a communication tool on realistic pesticide impacts in a multistressors environment for stakeholders and citizens.

A Multi‐Objective Optimization for Determination of Sustainable Crop Pattern Using Game Theory

ABSTRACTAmid growing concerns about environmental sustainability in agriculture, this study explores the potential of a game‐theoretic approach to identify and implement sustainable crop patterns in the Marvdasht–Kherameh sub‐basin, Iran. Employing a cooperative game‐theoretic framework, the study considers farmers, environmental advocates and policymakers as stakeholders with distinct objectives: maximising profit, minimising environmental pollution and optimising water consumption. This research aims to develop and apply a comprehensive model that effectively integrates these diverse objectives, proposing practical, sustainable agricultural strategies for the region. The game‐theoretic model is integrated with data analysis and optimization techniques to identify Pareto‐optimal solutions that balance the competing objectives of stakeholders with vested interest. The advantage of this approach is its ability to produce a robust, spatially visualised solution using GIS‐based mapping, which improves communication and aids in implementing sustainable crop patterns. Using regression models, an equilibrium point, defined as the intersection of the three polynomial regression models representing profit, nitrate fertiliser amount and water consumption objectives is identified. The optimised crop pattern corresponding to this equilibrium point is determined using a single‐objective optimization model. Key findings include a 40% reduction in wheat cultivation and significant increases in barley (143%) and paddy rice (113%), leading to enhanced resource efficiency and sustainability by optimising water and nitrate fertiliser use. The results offer significant benefits, including detailed spatial visualisation and stakeholder‐specific optimization for sustainable crop patterns, which can be adapted to other agricultural regions facing similar challenges.

Developing Energy Conservation Strategies in Agricultural Enterprises

The article emphasizes that agriculture has specific aspects, particularly regarding energy consumption. The research reveals that some agricultural enterprises are capable of generating their own energy. These characteristics are associated with various types of energy used in the production process: fossil energy, solar energy, and soil energy. The authors highlight the need for special attention to the development of energy-saving strategies in agriculture, as these enterprises often face high energy costs and have significant potential for enhancing energy efficiency. It has been established that reducing the use of fossil energy sources and maximizing the use of renewable sources, such as solar energy and soil energy potential, can substantially contribute to energy conservation in the agricultural sector. The considerable dispersion of agricultural enterprises leads to high costs and differences in energy consumption principles: fossil energy is primary for industry, while in agriculture, it serves a supplementary role, where natural energy forms biological mass (crops, livestock). The importance of management aspects in developing an effective energy-saving strategy, which promotes sustainable development and economic benefit in the agricultural sector, is highlighted. The authors propose key steps for ensuring energy conservation, which should form the basis for creating a comprehensive energy-saving strategy in agriculture.

Technician assignment in multi-shift maintenance schedules in an offshore wind farm

Offshore wind farms are becoming more and more important to sustainable energy strategies, yet their maintenance presents unique logistical challenges. The focus of this research is the Technician Assignment Problem (TAP) which involves a complicated and fluctuating scheduling problem. The key objective is to determine the most effective assignment of technicians to maintenance tasks to maximize operational efficiency and ensure reliable service. This study introduces a mathematical optimization model that processes numerous variables—technician availability, skill sets, and temporal constraints—to minimize unmet maintenance needs and ensure equitable workload distribution. The model is based on assumptions derived from actual operational conditions and human resource practices, guaranteeing that its results are not only theoretically valid but also practically feasible. TAP adheres to labor regulations, employs human resource capabilities, and aims for a smart assignment of workforce. It complies with restrictions that prevent excessive work, require breaks, and ensure that technicians are assigned tasks that match their skills, thus promoting the well-being of the workforce and the efficiency of operations. The computational investigation of the model shows that it has a remarkable ability to improve scheduling decisions which effectively reduce unassigned positions and uniformly distribute work hours. In essence, this research contributes a methodologically robust framework to the field of workforce scheduling, with the potential to inform the maintenance strategies of offshore wind farms and similar complex service systems.

Biochar mitigates the stimulatory effects of straw incorporation on N2O emission and N2O/(N2O + N2) ratio in upland soil

Straw incorporation, a common agricultural strategy designed to enhance soil organic carbon (SOC), often leads to increased nitrous oxide (N2O) emission, potentially offsetting benefits of SOC sequestration. However, the mechanism and mitigation options for the enhanced N2O emission following straw incorporation remain unclear. Here, N2 and N2O emission rate, as well as N2O/(N2O + N2) ratio under four different fertilization treatments [i.e., non-fertilization (Control), conventional chemical fertilization (CF), conventional chemical fertilization plus straw incorporation (SWCF), and conventional chemical fertilization plus straw and biochar incorporation (SWBCF)] were investigated by a robotized sampling and analysis system. High-throughput sequencing was also employed to assess the variation of bacterial community across different treatments. The results showed CF, SWCF, and SWBCF fertilization treatments significantly increased N2O emission rate by 1.04, 2.01, and 1.29 folds, respectively, relative to Control treatment. Albeit no significant enhancements in N2 emission rate, the N2O/(N2O + N2) ratio significantly increased by 65.53%, 1.10 folds, and 69.49% in CF, SWCF, and SWBCF treatments, respectively. The partial least squares path modeling analysis further revealed that fertilization treatments slightly increased N2 emission rate by increasing DOC content and keystone OTUs abundance. While the enhanced N2O emission rate and N2O/(N2O + N2) ratio in the fertilization treatments was primarily determined by reducing DOC/NO3− ratio and specific bacteria module abundance dominated by Gaiellales, Solirubrobacterales, and Micrococcales. Furthermore, SWBCF treatment alleviated the increase in net global warming potential due to straw incorporation, as indicated by the higher SOC sequestration and lower N2O/(N2O + N2) ratio therein. Collectively, these findings suggest that simultaneous application of straw and biochar has the potential to mitigate the risk of increased N2O emission from straw incorporation. This study provides valuable insights for developing targeted strategies in C sequestration and greenhouse gas mitigation, tackling the challenge presented by global climate change.

Compost tea enhances volatile content in tomato fruits via SlERF.E4-activated SlLOX expression.

Aroma volatiles, essential for tomato fruit flavor, were previously reported to accumulate more abundantly in fruits cultivated with compost tea. However, the underlying molecular mechanisms by which compost tea regulates aroma volatile synthesis in tomato fruit remains elusive. Here, we found that compost tea treatment significantly increased the content of volatiles derived from fatty acids in tomato fruit. Transcriptional analysis revealed that compost tea application upregulated the expression of linolenic acid metabolic pathway gene LOXs (SlLOXD and SlLOXE). Furthermore, overexpression of SlLOXD and SlLOXE enhanced the volatiles in fruit, while compost tea treatment failed to increase volatiles content in loxd and loxe mutants. Interestingly, compost tea application increased the level of ACC, a precursor of ethylene. Treatment with an ethylene signaling inhibitor 1-methylcyclopropene (1-MCP) negated the aroma enhancement effect of compost tea on tomato fruits. SlERF.E4, a transcription factor responsive to ethylene signaling, bound to the promoters of SlLOXD and SlLOXE. Overexpression of SlERF.E4 led to increased expression of SlLOXD and SlLOXE, as well as elevated fruit volatile content. Indeed, aroma enhancement in the SlERF.E4-overexpressed tomatoes was not affected by 1-MCP. These findings shed light on the molecular mechanisms underlying the improvement of flavor in organic fruits and provide valuable insights for the development of strategies in organic agriculture.

Development Strategy of Arabica Coffee in Conto Village, Bulukerto District, Wonogiri Regency

This study aims to identify developing arabica coffee farming strategy in Conto Village, Bulukerto District, Wonogiri Regency. This study uses the descriptive analysis method to determine SWOT analysis (Strengths, Weaknesses, Opportunities, and Threats) to see internal factors, namely strengths and weaknesses, and external factors, namely opportunities and threats. The results showed that the analysis of the strategy owned by arabica coffee farming in Conto Village, Bulukerto District, Wonogiri Regency was in the position of cell or quadrant I (growth), which used incentive strategies including market penetration, market development, and product development. Alternative strategies for developing arabica coffee farming in Conto Village, Bulukerto District, Wonogiri Regency are the development of integrated coffee-based arabica coffee in each main area of arabica coffee production; the development of an arabica coffee agribusiness system on local resources and culture; the use of environmentally friendly and market-oriented technology, and the development of an arabica coffee agribusiness system directed at increasing the ability of farmers in cultivating coffee plants through increased counselling and demonstrating plot implementation. The priorities of the arabica coffee development strategy in Conto Village, Bulukerto District, Wonogiri Regency are as follows: increased counselling carried out by the government. Keywords: developing, coffee, strategy, farming

Crop Rotation and Diversification in China: Enhancing Sustainable Agriculture and Resilience

Crop rotation and diversification (CRD) are crucial strategies in sustainable agriculture, offering multiple benefits to both farmers and the environment. By alternating crops or introducing diverse plant species, CRD practices improve soil fertility, reduce pest populations, and enhance nutrient availability. For example, legume-based rotations increase soil nitrogen levels through biological nitrogen fixation, reducing the need for synthetic fertilizers. Moreover, these practices promote more efficient water and nutrient use, reducing the reliance on synthetic fertilizers and minimizing the risk of pests and diseases. This review synthesizes findings from recent research on the role of CRD in enhancing sustainable agriculture and resilience, highlighting the potential contributions of these practices towards climate change mitigation and adaptation. Specific crop rotation systems, such as the cereal–legume rotation in temperate regions and the intercropping of maize with beans in tropical environments, are reviewed to provide a comprehensive understanding of their applicability in different agroecological contexts. The review also addresses the challenges related to implementing CRD practices, such as market demand and knowledge transfer, and suggests potential solutions to encourage broader adoption. Lastly, the potential environmental benefits, including carbon sequestration and reduced greenhouse gas emissions, are discussed, highlighting the role of CRD in building resilient agricultural systems. Collectively, this review paper emphasizes the importance of CRD methods as sustainable agricultural practices and provides key insights for researchers and farmers to effectively integrate these practices into farming systems.

Influence of Climatic Factors on Rust Severity in Sorghum in Dharwad, Karnataka, India

Sorghum rust, caused by Puccinia purpurea, significantly reduces crop yield, affecting plant growth and grain quality. Understanding the impact of weather parameters on disease incidence is crucial for timely disease management, to enhance crop resilience and yield stability. This study aims to identify and quantify the relationship between weather parameters and the incidence of sorghum rust, to inform decision-making on disease management strategies. A comprehensive analysis was conducted utilizing 17 years of secondary data (2006-2022) sourced from the All India Coordinated Research Project (AICRP) on Sorghum and the Department of Agrometeorology at the Climate Model Intercomparison Project (CMIP), University of Agricultural Sciences (UAS), Dharwad. The study employed statistical methods, including Multiple Linear Regression (MLR) and Step-wise Regression, to model the dependence of rust disease incidence on independent variables such as precipitation, temperature, relative humidity, wind speed, radiation, and heat flux. The results revealed the MLR model explains 65.45% of the variation and the Step-wise Regression model identifies four critical parameters- relative humidity, heat flux, wind speed, and radiation that together accounted for 65.09% of the variation without exhibiting multicollinearity (Variance Inflation Factor values below 10). These findings enhance the understanding of environmental impacts on sorghum rust and can inform future agricultural management strategies for disease prediction and control.

Impact of projected climate variability on agricultural water demand of key crops in drought-prone central India region

ABSTRACT Water scarcity predominantly affects agriculture production. It is mandatory to save future water to prevent its shortage due to variations in climate. Variation in climate is a significant factor responsible for frequent droughts over the Bundelkhand region in central India. It is necessary to obtain early warning studies in this region to manage and arrange future agricultural water. Out of best Regional Climate Models (RCMs) under the Coordinated Regional Downscaling Experiment (CORDEX) and their driving Coupled Model Intercomparison Project Phase 5 (CMIP5), General Circulation Models (GCMs) for India, the most effective model has been found based on the observed multiscale data for the region. The daily projected data (2021–2100) of best GCM, Earth System Model, ESM-2M have been used to evaluate the future water requirements for major rabi and hot weather crops grown in the region. The climate change effect is seen in the majority, especially in the upper Bundelkhand part. Most of the crops will need more water than the present condition, especially from 2071 to 2100. The findings will also help researchers and policymakers to utilize the future projected data to propose suitable water management strategies for agriculture.

Pengelolaan limbah rumah kemas sayur melalui produksi pupuk organik cair

Background: The growth of the agricultural sector in Cipanas District, Cianjur Regency, West Java has increased the production of organic waste from vegetable packaging houses. This study aims to explore the method of converting vegetable waste into Liquid Organic Fertilizer (POC) for waste management and sustainable agriculture. Methods: This descriptive study evaluated the process of converting vegetable waste into POC in Cipanas District. The process includes soaking rice grits, mixing ingredients (rice soaking water, brown sugar solution, coconut water, vegetable waste), anaerobic fermentation for three weeks with periodic stirring, and harvesting. Findings: The study resulted in a description of the process of making POC from vegetable waste. POC has the potential to improve soil fertility holistically (physically, chemically, biologically) and has been proven effective in increasing the productivity of various types of vegetables. Conclusion: Utilization of vegetable waste as POC offers a sustainable solution for waste management and environmentally friendly agriculture. Although there are challenges in quality standardization and infrastructure, its economic potential and long-term benefits make this approach worthy of consideration in future agricultural strategies. Novelty: This study highlights the potential use of vegetable waste from packaging houses in Cipanas for POC production, integrating the concept of circular economy in agricultural waste management and the development of sustainable agricultural practices.

The Fremont Frontier: Living at the Margins of Maize Farming

Abstract The Fremont provide an important case study to examine the resilience of ancient farmers to climatic downturns, because they lived at the far northern margin of intensive maize agriculture in the American West, where the constraints on maize production are made abundantly clear. Using a tree-ring and simulation-based reconstruction of average annual precipitation and maize growing degree days, along with cost-distance to perennial streams, we model spatial variability in Fremont site density in the eastern Great Basin. The results of our analysis have implications for defining the ecological envelope in which farming is a viable strategy across this arid region and can be used to predict where and why maize farming strategies might evolve and eventually collapse as climate changes over time.

Urban air quality affects the apple microbiome assembly

Exposure to air pollution affects health of all organisms on earth but the impact on the plant microbiome is less understood. Here, we link the Air Quality Index with the dust and apple epiphytic and endophytic microbiome across the city of Graz (Austria). The microbiome of the apple episphere, peel endosphere and pulp endosphere, and surrounding dust was analyzed. Our results show that the fungal communities were more influenced by air quality than bacterial communities. Bacterial communities, instead, were more specific for the individual sample types, especially noticeable in the pulp endosphere. The microbiome of each sample type was comprised of distinct microbial communities. Overall, the bacterial communities were highly dominated by Proteobacteria followed by Bacteroidota and Actinobacteriota, and the fungal communities were dominated by Ascomycota followed by Basidiomycota. With lower air quality, the relative abundance of the fungal orders Hypocreales and Pleosporales decreased in the apple episphere and the peel endosphere, respectively. Interestingly, an unexpectedly high level of similarity was observed between the bacterial communities of dust and peel endosphere, while the epiphytic bacterial community was significantly different compared to the other samples. We suggested that dust served as a potential microbial colonization route for the fruit microbiome as most bacteria (55%) colonizing the peel endosphere originated from dust. In conclusion, air quality affects the microbiome of edible plants, which can cause health consequences in humans. Therefore, this knowledge should be considered in urban and horticultural farming strategies.

Monitoring of Herbicide Residues in Agricultural Soils in Vojvodina Province (Northern Serbia)

Pesticides in soils raise concerns about the biodiversity, food safety, and contamination of watercourses, contributing to unsustainable land management practices. Monitoring the residue levels in agricultural soils is essential, as this offers valuable insights into the current extent of soil contamination and potential environmental risks attributed to their application. This study aimed to address the occurrence of the currently used herbicides in soil under intensive crop production, comparing the results of monitoring at two depths (0–30 and 30–60 cm) in 2013 and 2023. The research concerned the main agricultural area in Vojvodina Province (Serbia) and evaluated the presence of 41 herbicides in 128 localities. Pesticides were found in all samples, finding even more than six different herbicides per sample. The significant concentrations of s-metolachlor, etofumesate, clomazone, diflufenican, pendimethalin, and terbuthylazine found can be attributed to application practices, as they are typically applied pre-emergence, either through direct soil treatment with or without incorporation. Moreover, the correlation between different depths, herbicide residues, and soil properties was not significant. The decrease in the herbicide residues found in 2023 compared to the residues found in 2013 can be attributed to the implementation of good agricultural practices, which promote sustainable agricultural strategies through controlled pesticide application.