Smart Agricultural Technology, Год журнала: 2024, Номер unknown, С. 100716 - 100716
Опубликована: Дек. 1, 2024
Язык: Английский
E3S Web of Conferences, Год журнала: 2025, Номер 601, С. 00078 - 00078
Опубликована: Янв. 1, 2025
Optimizing irrigation water usage is crucial for sustainable agriculture, especially in the context of increasing scarcity and climate variability. Accurate estimation evapotranspiration (ET), a key component determining requirements crops, essential effective management. Traditional methods measuring estimating ET, such as eddy-covariance systems lysimeters, provide valuable data but often face limitations scalability, cost, complexity. Recent advancements machine learning (ML) offer promising alternatives to enhance precision efficiency ET smart systems. This review explores integration techniques optimizing usage, with particular focus on prediction technologies. We examine various ML models, that have been employed predict using diverse datasets comprising meteorological, soil, remote sensing data. In addition estimation, highlights optimize schedules based real-time inputs. Through this review, we aim comprehensive overview state-of-the-art ML-based technologies, contributing development more resilient efficient agricultural management strategies.
Язык: Английский
Процитировано
0
Agricultural Water Management, Год журнала: 2025, Номер 309, С. 109347 - 109347
Опубликована: Фев. 2, 2025
Язык: Английский
Процитировано
0
LatIA, Год журнала: 2025, Номер 3, С. 88 - 88
Опубликована: Фев. 19, 2025
The introduction of a deep learning-based method for non-destructive leaf area index (LAI) assessment has enhanced rapid estimation wheat and similar crops, aiding crop growth monitoring, water, nutrient management. Convolutional Neural Network (CNN)-based algorithms enable accurate, quantification seedling areas assess LAI across diverse genotypes environments, demonstrating adaptability. Transfer learning, known efficiency in plant phenotyping, was tested as resource-saving approach training the model. These advancements support breeding, facilitate genotype selection varied accelerate genetic gains, enhance genomic LAI. By capturing this can improve resilience to climate change. Additionally, advances machine learning data science better prediction distribution mapping global rust pathogens, major agricultural challenge. Accurate risk identification allows timely effective control measures. Moreover, lodging models using CNNs lodging-prone varieties, influencing decisions yield stability. artificial intelligence-driven techniques contribute sustainable enhancement, especially context change increasing food demand.
Язык: Английский
Процитировано
0
Pure and Applied Geophysics, Год журнала: 2025, Номер unknown
Опубликована: Март 31, 2025
Язык: Английский
Процитировано
0
Production, Год журнала: 2025, Номер 35
Опубликована: Янв. 1, 2025
Abstract: Paper aims The research to investigating the impact of implementing Internet Things (IoT) using Bayesian networks in supply chain manufacturing Indian auto components enterprises achieve enhanced productivity and reduced failure rates. Originality research's originality lies exploring IoT's with Networks component manufacturing, showcasing Industry 4.0 applications. Research method utilizes Network analysis investigate chains, validating findings through 4.0-based IoT implementation a pilot study. Main Implementing industry performance, productivity, rates technologies. Implications for theory practice offers theoretical insights into 4.0's on automotive industries practical solutions practitioners
Язык: Английский
Процитировано
0
SN Computer Science, Год журнала: 2025, Номер 6(5)
Опубликована: Май 3, 2025
Язык: Английский
Процитировано
0
Advances in information security, privacy, and ethics book series, Год журнала: 2025, Номер unknown, С. 181 - 216
Опубликована: Март 28, 2025
Precision agriculture, which combines modern technology with conventional farming techniques, has significantly transformed the efficient use of water, soil and farm resources. This chapter examines dynamic relationship between security within this particular industry, a specific emphasis on emerging technologies such as IoT, IDS, authentication mechanisms, AI, cyber security. The integration IoT enables real-time environmental sensing, while Intrusion Detection Systems (IDS) provide protection for agricultural networks against threats. Authentication mechanisms play crucial role in safeguarding essential equipment control systems. purpose is to guidance researchers, practitioners, policymakers regarding complex connection context precision agriculture. article adds ongoing dialogue surrounding preservation practices, presenting vision sustainable future innovation resilience are complementary.
Язык: Английский
Процитировано
0
Frontiers in Plant Science, Год журнала: 2025, Номер 16
Опубликована: Май 14, 2025
Traditional farming methods, effective for generations, struggle to meet rising global food demands due limitations in productivity, efficiency, and sustainability amid climate change resource scarcity. Precision agriculture presents a viable solution by optimizing use, enhancing fostering sustainable practices through data-driven decision-making supported advanced sensors Internet of Things (IoT) technologies. This review examines various smart used precision agriculture, including soil moisture, pH, plant stress etc. These deliver real-time data that enables informed decision-making, facilitating targeted interventions like optimized irrigation, fertilization, pest management. Additionally, the highlights transformative role IoT agriculture. The integration sensor networks with platforms allows remote monitoring, analysis via artificial intelligence (AI) machine learning (ML), automated control systems, enabling predictive analytics address challenges such as disease outbreaks yield forecasting. However, while offers significant benefits, it faces high initial investment costs, complexities management, needs technical expertise, security privacy concerns, issues connectivity agricultural areas. Addressing these technological economic is essential maximizing potential sustainability. Therefore, this we explore latest trends, challenges, opportunities associated enabled
Язык: Английский
Процитировано
0
Frontiers in Agronomy, Год журнала: 2025, Номер 7
Опубликована: Май 30, 2025
Irrigation plays a key role in boosting crop yields, supporting diversity, and reducing the impact of climate variability, especially regions like Great Lakes region where seasonal water availability can be unpredictable. Improving irrigation use efficiency (WUE) is critical for ensuring long-term sustainability. This study explores southwest Michigan’s humid climate, focusing on improving management practices. Several different volumes frequencies (30%, 50%, 60% Maximum Allowable Depletion) were examined as experimental treatments to better understand their productivity. Despite testing an array treatments, we found no statistical differences but noted unequal averages data spreads. These trends suggest more samples, under typical climatic conditions, are needed distinguish which approaches enhance WUE. We also contrasted producers’ methods with highlighting challenges optimizing WUE region’s soil conditions even experience management. was conducted demonstration benefit producers, intention providing reference
Язык: Английский
Процитировано
0
Heliyon, Год журнала: 2024, Номер 10(10), С. e31600 - e31600
Опубликована: Май 1, 2024
Irrigation schemes across sub-Saharan Africa are constructed with the intention of increasing agricultural production to increase food security, reduce poverty and improve economic growth. However, most these not performing as expected. This study therefore, diagnosed performance gaps in pilot irrigation Mubuku Doho Uganda analysed sustainable improvement options. Data was collected through systematic review literature scheme data, direct measurements at schemes, field surveys, inspections, key informant interviews. For each scheme, data for climate, irrigation, flow measurements, crop yields farm gate prices were collected. Comparative indicators output, water supply, financial physical sustainability used assess using standard approaches by International Water Management Institute (IWMI). The findings showed that optimally being far below attainable potential. major contributing factors low use efficiency output. Poor control, poor distribution, on-farm application contributed efficiency. Low attributed resulting from agronomic practices, scheduling produce prices. self-sufficiency indicator pointed farmers' inability operate maintain effectively. Improving requires a multidisciplinary approach targeting
Язык: Английский
Процитировано
2