Future Of Agriculture Research Articles

Combating food waste in the agricultural supply chain: A systematic review of supply chain optimization strategies and their sustainability benefits

Food waste represents a significant global challenge, with approximately one-third of all food produced for human consumption lost or wasted annually, leading to severe environmental, economic, and social consequences. The issue not only exacerbates food insecurity but also contributes to greenhouse gas emissions, waste of resources, and economic losses estimated at over $1 trillion each year. This paper aims to systematically review the causes of food waste across agricultural supply chains and explore effective supply chain optimization strategies to mitigate these losses. Through a comprehensive analysis, the paper identifies critical drivers of food waste, including post-harvest losses, inefficient processing, and aesthetic standards, while proposing technological innovations such as the Internet of Things (IoT), blockchain, and artificial intelligence (AI) as solutions to enhance supply chain efficiency. Furthermore, it evaluates policy frameworks that support waste reduction, highlighting the role of government incentives and regulations in promoting sustainable practices. The findings underscore the importance of reducing food waste not only for environmental sustainability but also for economic profitability, as optimizing supply chains can lead to substantial cost savings and increased revenue for businesses. Ultimately, the paper emphasizes the necessity for collaboration among stakeholders—including governments, industries, and non-profit organizations—to create systemic change and effectively combat food waste on a global scale. By fostering innovative practices and policies, we can pave the way for a more sustainable agricultural future, ultimately contributing to the alleviation of food insecurity and the enhancement of economic resilience.

Time-course analysis of the transcriptome of Arabidopsis thaliana leaves under high-concentration ammonium sulfate treatment

ABSTRACT Ammonium fertilization is of great interest for future agriculture, as unlike nitrate, ammonium use efficiency does not decrease in C3 plants, even in environments with elevated CO2 concentrations. However, excess ammonium often results in toxic effects such as growth suppression and chlorosis, i.e. ammonium toxicity. The addition of nitrate, a major source of nitrogen commonly found in soils, has been shown to alleviate these toxic effects. Understanding the mechanisms of ammonium toxicity in the presence of nitrate is crucial for the effective use of ammonium fertilizers in crop cultivation. To elucidate these responses, a time-course analysis of the transcriptome was performed on A. thaliana leaves treated with high concentrations of ammonium sulfate in the presence of sufficient nitrate. The expression of nitrate-inducible genes tended to be downregulated by the treatment. The expression of genes relating to abscisic acid (ABA), jasmonic acid (JA), salicylic acid (SA), and membrane trafficking was upregulated, whereas that of photosynthesis-, auxin-, and cytokinin-related genes involved in growth and development was downregulated. The induction of many osmotic stress-responsive genes and nitric oxide (NO)-inducible genes suggests the involvement of osmotic stress and NO signaling in the response. This study provides a novel and comprehensive overview of transcriptional changes occurring in response to high ammonium sulfate concentrations with sufficient nitrate, and sheds light on potential pathways involved in ammonium toxicity under these conditions.

Jivamrit as a Sustainable Approach: A Review of Natural Farming and Future Agriculture.

Green Revolution aims to boost food production and feed millions of Indians, but it also has negative effects on agriculture and society's health. Natural manures like cow dung and cow urine can counteract the adverse effects of inorganic fertilizer on soil along with improving physicochemical qualities, maintaining the soil quality, and increasing crop output. Zero Budget Natural Farming (ZBNF) formulations like Jivamrit promote soil health and microbial activities and are an excellent source of macronutrients, other micronutrients needed for plant growth, plus adds beneficial microbes, nitrogen (N2), phosphorus (P), potassium (K), and natural carbon (C). Further, conventional agricultural methods, like monocropping and heavy tillage, can damage soil bacteria which contributes to sustainable agriculture through nitrogen fixation, siderophore synthesis and nutrient absorption. A sustainable agricultural system is resource-efficient, socially and commercially competitive, ecologically sound, and supportive of society. Jivamrit, a natural organic manure, is gaining interest due to concerns about the sustainability of input-intensive agriculture systems. It promotes crop growth, quality, and yield, enhances soil pH, population, and activity of beneficial microorganisms, and helps with nitrogen fixation, phosphate solubili-zation, and easy decomposition. Long-term use of Jivamrit, may disrupt soil microbial balance, may leading to overpopulation of certain species. The current review on the Jivamrit emphasizes on the biological and chemical characterization and its significance to the agriculture.

Tailoring convolutional neural networks for custom botanical data

AbstractPremiseAutomated disease, weed, and crop classification with computer vision will be invaluable in the future of agriculture. However, existing model architectures like ResNet, EfficientNet, and ConvNeXt often underperform on smaller, specialised datasets typical of such projects.MethodsWe address this gap with informed data collection and the development of a new convolutional neural network architecture, PhytNet. Utilising a novel dataset of infrared cocoa tree images, we demonstrate PhytNet's development and compare its performance with existing architectures. Data collection was informed by spectroscopy data, which provided useful insights into the spectral characteristics of cocoa trees. Cocoa was chosen as a focal species due to the diverse pathology of its diseases, which pose significant challenges for detection.ResultsResNet18 showed some signs of overfitting, while EfficientNet variants showed distinct signs of overfitting. By contrast, PhytNet displayed excellent attention to relevant features, almost no overfitting, and an exceptionally low computation cost of 1.19 GFLOPS.ConclusionsWe show that PhytNet is a promising candidate for rapid disease or plant classification and for precise localisation of disease symptoms for autonomous systems. We also show that the most informative light spectra for detecting cocoa disease are outside the visible spectrum and that efforts to detect disease in cocoa should be focused on local symptoms, rather than the systemic effects of disease.

The Use of Anaerobic Digestate for Greenhouse Horticulture

Agricultural crop production practices are being developed for organic, sustainable, and environmentally friendly farming systems. Developing efficient and resourceful crop fertilizers is significantly important for future agriculture. Various biofertilizers, such as animal manures, composts, and vegetable byproducts, have been successfully applied in agriculture. Anaerobic digestate, organic matter obtained from animal or plant waste processing during anaerobic digestion into biomass, has become popular due to its versatility, multiple purposes, and facile application methods. Digestate has recently been widely used in agriculture to enrich the soil with nutrients and thus increase crop yields. Several studies have shown that anaerobic digestate is a valuable fertilizer that can be used as a biofertilizer in field and greenhouse horticulture. Also, research has been carried out on the use of digestate in hydroponic horticulture. This review presents the research results and discusses the possibilities of using anaerobic digestate in greenhouse horticulture. Its objective is to provide a comprehensive understanding of the application of digestate from various sources and its impact on the growth, progress, yield, and quality of greenhouse-grown vegetables.

Designated market makers and agricultural futures market quality: Evidence from China's Dalian commodity exchange

AbstractMany financial markets use designated market makers (DMMs), but the impacts of DMMs on agricultural futures markets – and in particular, how to arrange DMMs among contracts expiring in different months – are largely neglected. In 2017, Chinese exchanges started recruiting DMMs for inactive contracts when they become nearby contracts to address the discontinuous trading activity of nearest‐to‐maturity contracts, which enables us to study the benefit and cost of recruiting DMMs for inactive contracts using a quasi‐experimental framework. Leveraging tick‐by‐tick data on corn and soybean meal futures, we find that DMMs improve the market quality of inactive contracts without disrupting the market quality of dominant contracts. Heterogeneity analysis in policy settings suggests that more DMMs are conducive to improving market quality for corn and soybean meal futures. We demonstrate that DMM policy is a feasible measure to facilitate continuous activeness in Chinese agricultural futures markets. Our results are important for exchanges and regulators seeking to better design and implement designated market‐making programs in agricultural futures markets.

Agriculture and Automation: Potential Benefits, Difficulties and Economic Impacts

In contemporary agriculture, automation and robotics are the main players. They present viable answers to issues with the world's expanding population, changing demographics, and economic standing. This analysis examines the potential and difficulties of utilizing new technologies as well as the frequently overlooked connection between automation technology and agricultural economics. This study examines the potential of automation and robots in farming techniques, as well as their socio-economic impacts, through a methodical analysis of the literature. It also offers practical advice for those involved. For this reason, a variety of robot types used in diverse agricultural fields have been examined, along with the difficulties and technical viability of adopting automation. Additional significant aspects have been examined, such as changes in the labour market, economic conditions, and demographic trends. This study also looks into the social effects of automation, specifically with regard to worker adaption and employment. It discovers that although automation increases sustainability and efficiency, it also results in labour displacement and necessitates significant technological investment. This in-depth analysis closes a significant gap by evaluating precision agriculture's future, labour market change, and economic viability. Along with outlining a future roadmap for research and policy, it also plots a course for future studies and policy-making at the nexus of agricultural technology and socioeconomic domains.

Sizing Up the Farm Bill Safety Net

Lower commodity prices and higher production costs over the past couple of years have crop producers concerned about tighter margins and cash flow for their operations. The federal farm income safety net provides substantial support to producers through commodity programs, crop insurance programs, and disaster assistance. Crop insurance has been the primary safety net tool for producers in recent years as commodity prices generally fluctuated at levels above commodity program support levels. Even declining markets in the past couple years left prices that remained above Price Loss Coverage (PLC) support levels and revenue calculations above Agriculture Risk Coverage (ARC) guarantees unless there were significant yield losses at the county level for ARC-CO or the individual farm level for ARC-IC. The outlook is changing however as declining prices run into support levels that are increasing based on the past few years of higher prices. The ARC program provides a revenue guarantee tied to 86% of a benchmark revenue calculated from a five-year moving average price and a five-year moving average trend-adjusted yield. The PLC program provides support if prices fall below the higher of a legislated reference price or 85% of a five-year moving average price. With the higher prices experienced during the past few years, the five-year moving average price has increased and both ARC and PLC support levels have gotten stronger. A look at ARC and PLC protection and payment levels provides a picture of what current support and cash flow may look like and what future support could be under current or future farm legislation.

Genome Editing for Grass Improvement and Future Agriculture

Abstract Grasses, including turf and forage, cover most of the earth’s surface; predominantly important for land, water, livestock feed, soil and water conservation, as well as carbon sequestration. Improved production and quality of grasses by modern molecular breeding is gaining more research attention. Recent advances in genome-editing technologies are helping to revolutionize plant breeding and also offering smart and efficient acceleration on grass improvement. Here, we reviewed all recent researches using (CRISPR)/CRISPR-associated protein (Cas)-mediated genome editing tools to enhance the growth and quality of forage and turf grasses. Furthermore, we highlighted emerging approaches aimed at advancing grass breeding program. We assessed the CRISPR-Cas effectiveness, discussed the challenges associated with its application, and explored future perspectives primarily focusing on turf and forage grasses. Despite the promising potential of genome editing in grasses, its current efficiency remains limited due to several bottlenecks, such as the absence of comprehensive reference genomes, the lack of efficient gene delivery tools, unavailability of suitable vector and delivery for grass species, high polyploidization, multiple homoeoalleles, etc. Despite these challenges, the CRISPR-Cas system holds great potential to fully harness its benefits in grass breeding and genetics, aiming to improve and sustain the quantity and quality of turf and forage grasses.

Depth-dependent Effects of Leguminous Crops on Soil Nitrogen-Fixing Microbial Communities Correlated with Carbon Degradation

Abstract Legumes play critical roles in agroecosystems by modulating nitrogen-fixing microorganisms to enhance soil fertility and promote crop productivity. Current research on the effects of legumes predominantly focuses on surface soil, lacking a comprehensive analysis of their overall impact across multiple soil layers and an in-depth understanding of associated microbial mechanisms. Here, the community structure of soil nitrogen-fixing microorganisms in three soil layers (0-20, 20-50, and 50-100 cm) under legume and non-legume cultivation was investigated through metagenomic sequencing. We found that only in topsoil (0-20 cm) legume treatment exhibited a significantly higher relative abundance of nitrogen-fixing genes than non-legume treatment. Under legume cultivation, the relative abundance of nitrogen-fixing genes was significantly higher in the topsoil layer than in deeper layers, whereas non-legume treatment displayed an inverse depth-dependent pattern. Combining soil physicochemical properties, the relative abundance of nitrogen-fixing genes correlated significantly with soil moisture, total carbon (TC), and dissolved organic carbon (DOC) content. Both TC and DOC were identified as key drivers of these genes. Subsequently, a similar depth-dependent pattern within the relative abundance of soil carbon degradation genes was found in response to the cultivation of both crops. The relative abundances of soil carbon degradation genes were negatively correlated with nitrogen-fixing genes under legume treatment individually, distinct from non-legume treatment. Our findings highlight the depth-dependent impact of legumes on nitrogen fixation and the critical interaction between soil carbon degradation and nitrogen fixation, providing insights into carbon management in legume cultivation practices to enhance nitrogen fixation in future agriculture.

Insects as Sustainable Feed: Enhancing Animal Nutrition and Reducing Livestock Environmental Impression.

Insects are emerging as a promising alternative source in animal nutrition, offering high protein content and a low environmental impression compared to traditional feed sources. This abstract explores the potential role of insects in reducing the environmental impact of livestock production. Insects such as black soldier fly larvae, mealworms, and crickets are rich in essential nutrients, including proteins, amino acids, fatty acids and so on. They can be efficiently farmed on organic waste streams, contributing to resource efficiency and waste lessening. Additionally, insect farming needs a small quantity of water, less land, and emits fewer greenhouse gases than conventional animal feed production. Despite these benefits, several challenges must be addressed to realize their potential, including regulatory approval, consumer acceptance, production scalability, and ensuring consistent nutritional quality. By overcoming these challenges through research, innovation, and policy support, insects can be integrated into mainstream animal feed systems, significantly reducing the environmental impact of livestock farming and contributing to a more sustainable agricultural future.

Towards a comprehensive analysis of agricultural land systems in the EU and US: A critical view on publicly available datasets

Understanding agricultural land systems is paramount to preparing for future transitions under climate change. Systematic quantitative, multi-context analyses of agricultural land systems are a promising way of increasing our understanding but rely on the availability of large-scale and commensurable data. The available data, however, are outcomes of political priorities and processes and thus not neutral windows into agricultural realities. We map, describe, and compare publicly available and publicly curated data describing agricultural land systems—those devoted to the production of food, fuel, and fiber—in the United States (US) and European Union (EU) to identify underlying data collection norms and political priorities. We discuss how these priorities shape what we can(not) see in each region and articulate future data needs to support an in-depth understanding of agricultural land systems dynamics. This comprehensive understanding of how and why agricultural land systems change is imperative to promoting sustainable, resilient, and just agriculture futures.

Sustainable Development of Agro-Based Industries and Agricultural Practices: An Analytical Study of Rajasthan

Background: Agriculture plays a pivotal role in Rajasthan's economy, supporting a significant portion of the population. However, the sector faces numerous challenges, including water scarcity, soil degradation, and climate change impacts. This study investigates the sustainable development of agro-based industries and agricultural practices in Rajasthan, analyzing current practices, challenges, and potential solutions. Materials and Methods: The research employed a mixed-methods approach, combining qualitative interviews and focus group discussions with a quantitative survey of 500 participants across various districts of Rajasthan. Data were collected on agricultural practices, challenges faced by farmers, and perspectives on sustainable development. Statistical analysis was performed using SPSS, while qualitative data were analyzed through thematic analysis. Results: The study revealed a blend of traditional (68% using rainwater harvesting) and modern (42% adopting precision farming) agricultural practices. Water scarcity emerged as the most critical challenge, reported by 85% of farmers. Sustainable strategies showed promising results, with organic farming increasing income by 20% and water-efficient irrigation reducing water usage by 40%. Agro-based industries, particularly food processing and textiles, contributed significantly to the state's economy. Conclusion: The findings underscore the need for integrated approaches to address water scarcity, promote sustainable farming practices, strengthen agro-based industries, and enhance farmers' access to markets and credit facilities. Policy recommendations include prioritizing water management, climate change adaptation, and farmer education to ensure a sustainable and resilient agricultural future for Rajasthan

Power positions in the farm family, marrying in, and negative peer pressure: the social relations that impact agricultural practice

AbstractIn this article, we wish to consider relationships internal and external to the farm household, and how these enable and/or mitigate the adoption of better farm practices. We find that internally, members of the farm household (successors or spouses ‘marrying in’), can influence the future direction of agricultural practice in a positive way, that is more profitable and sustainable. It is not a straightforward process though. Interpersonal household relations play a role; status and standing within the family can impact on how decisions about change are made. This relates to both people marrying in and the position of the successor in an inter-generational household. We found that the power of the farming peer group to influence change is underestimated. Our data shows that farming is an occupation subject to strong cultural norms regarding acceptable farming practice. Sometimes farm family decisions to change agricultural practice falter under the weight of sanctions and derision encountered when trying to make adjustments. This paper draws from two data sets in Germany and England. We conclude that understanding internal farm household interactions, and their external relations with farming peer groups is critical to supporting the future of agriculture.

Environmental impact of modern agricultural practices: Strategies for reducing carbon footprint and promoting conservation

Modern agricultural practices have significantly transformed food production, leading to increased efficiency and productivity. However, these advancements have also had notable environmental impacts, particularly concerning carbon emissions and resource depletion. This study explores the environmental impact of contemporary agricultural practices, emphasizing the need for strategies to mitigate carbon footprints and enhance conservation efforts. Agriculture contributes substantially to greenhouse gas emissions through sources such as livestock, synthetic fertilizers, and fossil fuel consumption. These emissions contribute to climate change and global warming. Additionally, modern farming practices often lead to deforestation, habitat loss, and soil degradation, exacerbating biodiversity loss and reducing soil health. Water usage in agriculture also poses significant challenges, with high water consumption and pollution from runoff affecting water resources and aquatic ecosystems. To address these issues, several strategies can be employed to reduce the carbon footprint of agriculture. Adoption of sustainable farming practices such as conservation tillage and no-till farming can enhance soil carbon sequestration, improving soil health and reducing emissions. Agroforestry and cover cropping further contribute by capturing atmospheric carbon and improving soil structure. The integration of renewable energy sources like solar and wind power in farming operations, along with energy-efficient technologies, can also reduce reliance on fossil fuels and lower overall greenhouse gas emissions. Promoting conservation involves implementing practices that protect and restore natural resources. Soil conservation methods, including erosion control techniques like terracing and contour plowing, help maintain soil health and prevent degradation. Efficient water management strategies, such as drip irrigation and rainwater harvesting, reduce water consumption and mitigate pollution from runoff. Biodiversity conservation can be supported through the preservation of natural habitats and the promotion of biodiverse farming systems, which enhance ecosystem resilience and stability. Effective policy frameworks and support mechanisms are crucial for driving the adoption of these strategies. Government policies, including environmental regulations and incentives, play a pivotal role in encouraging sustainable practices. Research and innovation are essential for developing new technologies and practices, while education and extension services ensure the dissemination of knowledge and best practices to farmers. Modern agricultural practices have significant environmental impacts, but through the adoption of sustainable practices and innovative strategies, it is possible to reduce carbon footprints and promote conservation. Continued research, supportive policies, and effective implementation of conservation strategies are essential for achieving a more sustainable agricultural future. Keywords: Environmental Impact, Agricultural Practices, Carbon Footprint.

A Review on Integrating Bioinformatics Tools in Modern Plant Breeding

Bioinformatics has become integral to modern plant breeding, facilitating the analysis of large-scale genomic data, identifying key genetic markers, and enabling precision breeding techniques such as genomic selection. Advances in sequencing technologies and computational tools have accelerated the pace of crop improvement, allowing for the rapid identification of genes associated with important agronomic traits, including yield, stress tolerance, and disease resistance. The integration of bioinformatics in plant breeding also presents significant challenges, particularly in terms of data management, multi-omics integration, and the interpretation and validation of complex datasets. The role of emerging trends such as pangenomics, metagenomics, and epigenomics in expanding the scope of plant breeding, as well as the increasing importance of artificial intelligence and machine learning in enhancing predictive accuracy and optimizing breeding strategies. Personalized plant breeding and precision agriculture are identified as promising approaches for tailoring crop varieties to specific environments and farming practices, driven by bioinformatics tools that enable detailed analysis of genomic and phenotypic data. Ethical considerations and data privacy issues are also addressed, emphasizing the need for transparent and equitable practices in the collection, sharing, and use of genomic data. The importance of collaborative efforts and global initiatives in advancing bioinformatics-driven plant breeding, with a focus on fostering international cooperation, building capacity in developing regions, and ensuring open access to bioinformatics resources. As the field continues to evolve, bioinformatics will play a Important role in developing sustainable agricultural systems capable of meeting the demands of a growing global population while mitigating the impacts of climate change. The current applications, challenges, and future prospects of bioinformatics in plant breeding, offering insights into the critical role of this field in shaping the future of agriculture.

Risk spillovers and diversification benefits between crude oil and agricultural commodity futures markets

This study examines the dependence structure and risk spillovers between crude oil and eight major agricultural futures (wheat, corn, soybean coffee, cotton, lumber, cocoa, and live cattle) markets. It also analyzes the potential conditional diversification benefits using a variety of copula functions and Conditional Value at Risk (CoVaR) measure. The results show significant crisis-sensitive and temporal dependence between oil and agricultural markets. Moreover, crude oil shows a symmetric tail dependence with both wheat, corn, soybeans, and cotton futures, whereas oil exhibits an average dependence with coffee. A strong dependence is observed between oil and cocoa (lumber) during bearish (bullish) market conditions. Oil and Live cattle have a symmetric dependence during bearish and bullish market conditions. On the other hand, we find asymmetric and bidirectional risk spillovers from oil to agricultural markets. Furthermore, the wheat futures contract appears to be the most dominating and vulnerable asset to oil price shocks, followed by lumber and corn futures, respectively, while the live cattle contracts are the least. Finally, an equally weighted portfolio offers the highest diversification benefits at a 5 % expected shortfall.

Zinc oxide nanoparticles mediated salinity stress mitigation in Pisum sativum: a physio-biochemical perspective

Salinity is the major abiotic stress among others that determines crop productivity. The primary goal is to examine the impact of Zinc Oxide Nanoparticles (ZnO NPs) on the growth, metabolism, and defense systems of pea plants in simulated stress conditions. The ZnO NPs were synthesized via a chemical process and characterized by UV, XRD, and SEM. The ZnO NPs application (50 and 100) ppm and salt (50 mM and 100 mM) concentrations were carried out individually and in combination. At 50 ppm ZnO NPs the results revealed both positive and negative effects, demonstrating an increase in the root length and other growth parameters, along with a decrease in Malondialdehyde (MDA) and hydrogen peroxide concentrations. However, different concentrations of salt (50 mM and 100 mM) had an overall negative impact on all assessed parameters. In exploring the combined effects of ZnO NPs and salt, various concentrations yielded different outcomes. Significantly, only 50 mM NaCl combined with 50 ppm ZnO NPs demonstrated positive effects on pea physiology, leading to a substantial increase in root length and improvement in other physiological parameters. Moreover, this treatment resulted in decreased levels of MAD, Glycine betaine, and hydrogen peroxide. Conversely, all other treatments exhibited negative effects on the assessed parameters, possibly due to the high concentrations of both stressors. The findings offered valuble reference data for research on the impact of salinity on growth parameters of future agriculture crop.

Price spillovers and interdependences in China's agricultural commodity futures market: Evidence from the US-China trade dispute

We examine the effects of the US-China trade dispute on price spillovers and interdependencies among the ten most liquid agricultural futures contracts traded on China's commodity exchanges by employing the time-varying connectedness framework modified by Antonakakis, Chatziantoniou, and Gabauer (2020). We find that the overall market frictions increase modestly due to the clustering of mixed informational disturbances caused by the trade dispute. This lowers the gross spillovers in the entire asset system by reducing the efficiency of general price signal transmission. Notably, subsidiary products of rapeseed and soybean contribute the most to the total and net directional spillovers in the whole market, acting as shock transmitters before the trade dispute. The RBD palm market gains a dominant role as a shock transmitter during the trade dispute and its role strengthens further after the trade agreement was reached. Additionally, the average intensity of pairwise spillovers declines considerably during the trade dispute, suggesting weakening asset interconnectedness. The responsiveness of shock transmission channels to the trade dispute impacts is found to vary across industrial chains and the presence of delayed economic effects is detected in the structural changes of market interdependences.

Insights on the Optimization of Short- and Long-Term Maintenance Decisions for Floating Offshore Wind Using Nested Genetic Algorithms

The present research explores the optimization of maintenance strategies for floating offshore wind (FOW) farms using nested genetic algorithms. The primary goal is to provide insights on the decision-making processes required for both immediate and strategic maintenance planning, crucial for the viability and efficiency of FOW operations. A nested genetic algorithm was coupled with discrete-event simulations in order to simulate and optimize maintenance scenarios influenced by various operational and environmental parameters. The study revealed that short-term maintenance timing is significantly influenced by wind conditions, with higher electricity prices justifying on-site spare parts storage to mitigate operational disruptions, suggesting economic incentives for maintaining on-site inventory of spare parts. Long-term strategic findings emphasized the impact of planned intervals between inspections on financial outcomes, identifying optimal strategies that balance operational costs with energy production efficiency. Ultimately, this study highlights the importance of integrating sophisticated predictive models for failure detection with real-time operational data to enhance maintenance decision-making in the evolving landscape of offshore wind energy, where future farms are likely to operate farther from onshore facilities and under potentially highly varying market conditions in terms of electricity prices.