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AgriEngineering
Scopus
ISSN 2624-7402 · MDPI AG · 1.453 artikel di indeks
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Artikel Jurnal Teks lengkap
Comparative Evaluation of Deep Learning Architectures for Non-Destructive Estimation of Carotenoid Content from Visible–Near-Infrared (400–850 nm) Spectral Reflectance Data
This study compared three deep learning architectures—one-dimensional convolutional neural network (1D-CNN), self-supervised learning (SSL), and Vision Transformer (ViT)—to evaluate their ability to predict carotenoid content from visible–near-infrared (VIS–NIR) spectral reflectance data (400–850…
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AgroLLM: Connecting Farmers and Agricultural Practices Through Large Language Models for Enhanced Knowledge Transfer and Practical Application
Large language models (LLMs) offer new opportunities for agricultural education and decision support, yet their adoption is limited by domain-specific terminology, ambiguous retrieval, and factual inconsistencies. This work presents AgroLLM, a domain-governed agricultural knowledge system that…
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Circular Reuse of Onshore Oil and Gas Produced Water for Bioenergy Crop: Phytoextraction Using Nopalea cochenillifera for Recovery of Degraded Semi-Arid Lands in Brazil
Facing water scarcity and environmental contamination, a sustainable approach combining bioeconomy and circular economy principles has emerged: the use of onshore oil and gas produced water (PW) to irrigate Nopalea cochenillifera. This study evaluated the ability of Nopalea cochenillifera to…
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A STEM-Based Methodology for Designing and Validating a Cannabinoid Extraction Device: Integrating Drying Kinetics and Quality Function Deployment
Projects integrating Science, Technology, Engineering, and Mathematics (STEM) are essential to interdisciplinary research. This study presents a STEM (Science, Technology, Engineering, and Mathematics) methodology with the primary objective of designing, constructing, and validating a functional…
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Non-Destructive Detection of Heat Stress in Tobacco Plants Using Visible-Near-Infrared Spectroscopy and Aquaphotomics Approach
Non-destructive estimation of high-temperature stress effects on tobacco plants is crucial for both scientific research and practical applications. Normalized difference vegetation index (NDVI), chlorophyll index, and spectra in the range of 900–1700 nm of Burley, Oriental, and Virginia tobacco…
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Integrating Artificial Intelligence and Machine Learning for Sustainable Development in Agriculture and Allied Sectors of the Temperate Himalayas
The temperate Himalayan states of Jammu and Kashmir, Himachal Pradesh, Uttarakhand, Ladakh, Sikkim, and Arunachal Pradesh in India face unique agro-ecological challenges across agriculture and allied sectors, including pest and disease pressures, inefficient resource use, post-harvest losses, and…
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Design and Experimental Testing of a Self-Propelled Overhead Rail Air-Assisted Sprayer for Greenhouse
Greenhouse pesticide application often suffers from low droplet deposition uniformity and health risks to operators. A self-propelled overhead rail air-assisted sprayer has been designed. The mathematical model based on droplet movement and the DPM are used to analyze the equipment’s working…
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Uncertainty-Aware Deep Learning for Sugarcane Leaf Disease Detection Using Monte Carlo Dropout and MobileNetV3
Sugarcane diseases cause estimated global annual losses of over $5 billion. While deep learning shows promise for disease detection, current approaches lack transparency and confidence estimates, limiting their adoption by agricultural stakeholders. We developed an uncertainty-aware detection…
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Nitrogen Dynamics and Environmental Sustainability in Rice–Crab Co-Culture System: Optimal Fertilization for Sustainable Productivity
Rice–crab co-culture systems (RC) represent promising sustainable intensification approaches, yet their nitrogen (N) cycling and optimal fertilization strategies remain poorly characterized. In this study, we compared RC with rice monoculture system (RM) across four N gradients (0, 150, 210, and…
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Artikel Jurnal Teks lengkap
Lightweight GAFNet Model for Robust Rice Pest Detection in Complex Agricultural Environments
To address challenges such as small target size, high density, severe occlusion, complex background interference, and edge device computational constraints, a lightweight model, GAFNet, is proposed based on YOLO11n, optimized for rice pest detection in field environments. To improve feature…
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Strategies for Wine, Orange Processing and Olive Oil By-Product Valorisation Based on GIS Spatial Analysis
Waste valorisation has become a key strategy for applying circular economy principles in the agro-industrial field. This study investigated the territorial implementation of the waste composting on a territorial scale. The wastes considered were the post-processing orange waste, spent olive oil…
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Ambrosia artemisiifolia in Hungary: A Review of Challenges, Impacts, and Precision Agriculture Approaches for Sustainable Site-Specific Weed Management Using UAV Technologies
Weed management has become a critical agricultural practice, as weeds compete with crops for nutrients, host pests and diseases, and cause major economic losses. The invasive weed Ambrosia artemisiifolia (common ragweed) is particularly problematic in Hungary, endangering crop productivity and…
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RGB Image Processing Allows Differentiation of the Effects of Water Deficit and Bacillusaryabhattai on Wheat
This study aimed to develop a methodology to evaluate, through RGB image processing, the wheat cultivar TRIO Calibre under three irrigation levels (100, 50, and 25%), with or without the application of Bacillus aryabhattai, in Brazilian Cerrado soil. The experimental scheme was a 3×2 factorial…
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RF-Driven Adaptive Surrogate Models for LoRaDisC Network Performance Prediction in Smart Agriculture and Field Sensing Environments
LoRa-based IoT systems are increasingly used in smart farming, greenhouse monitoring, and large-scale agricultural sensing, where long-range, energy-efficient communication is essential. However, estimating link quality metrics such as PRR, RSSI, and SNR typically requires continuous packet…
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Ontology-Enhanced Deep Learning for Early Detection of Date Palm Diseases in Smart Farming Systems
Early and accurate date palm disease detection is the key to successful smart farming ecosystem sustainability. In this paper, we introduce DoST-DPD, a new Dual-Stream Transformer architecture for multimodal disease diagnosis utilizing RGB, thermal and NIR imaging. In contrast with standard deep…
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A Novel Nonthermal Plasma System for Continuous On-Site Production of Nitrogen Fertilizer
Plasma-assisted nitrogen fixation is emerging as a promising alternative to the dominant industrial method of the Haber–Bosch (H–B) process, which is energy-intensive and environmentally detrimental. Nonthermal plasma technology represents a cutting-edge innovation with the potential to…
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Web-Based Explainable AI System Integrating Color-Rule and Deep Models for Smart Durian Orchard Management
This study presents a field-oriented AI web system for durian orchard management that recognizes leaf health from on-orchard images under variable illumination. Two complementary pipelines are employed: (1) a rule-based module operating in HSV and CIE Lab color spaces that suppresses sun-induced…
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Identification of the Geographical Origins of Matcha Using Three Spectroscopic Methods and Machine Learning
For high-value-added products such as matcha, scientific confirmation of the origin is essential for quality assurance and fraud prevention. In this study, three nondestructive analytical techniques, specifically fluorescence (FF), near-infrared (NIR), and Fourier transform infrared (FT-IR)…
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Artikel Jurnal Teks lengkap
Optimized Evolving Fuzzy Inference System for Humidity Forecasting in Greenhouse Under Extreme Weather Conditions
Precision agriculture has increasingly adopted controlled agricultural microclimates, particularly smart greenhouses, as a strategy to enhance crop yields while maintaining environmental conditions within suitable ranges for each crop. Among the variables that govern the water balance in these…
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Artikel Jurnal Teks lengkap
Remote Sensing of Nematode Stress in Coffee: UAV-Based Multispectral and Thermal Imaging Approaches
Early and non-destructive detection of plant-parasitic nematodes is critical for implementing site-specific management in coffee production systems. This study evaluated the potential of unmanned aerial vehicle (UAV) multispectral and thermal imaging, combined with textural analysis, to detect…
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