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Smart Agricultural Technology
Scopus
ISSN 2772-3755 · Elsevier · 1.614 artikel di indeks
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Artikel Jurnal
Automatic annotation and performance evaluation of orchard pear fruit using SAM-based zero-shot segmentation
High-quality annotated data are essential for training high-performance models; therefore, the automatic annotation of instance segmentation training datasets helps improve model development efficiency and reduce development costs. In this study, the Segment Anything Model (SAM) and its variants…
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Artikel Jurnal
Improved strawberry disease classification under class imbalance through in-backbone latent diffusion
Strawberry production suffers major yield losses from fungal diseases such as Powdery mildew, Fusarium wilt, and Gray mold. These yield losses make early and accurate classification essential for effective crop management. Achieving accurate classification, however, is challenging in greenhouse…
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Artikel Jurnal
FHA-MTT: A fish health assessment method based on multi-target tracking
In aquaculture, the health status of crucian carp directly impacts production efficiency, and swimming behavior is an important indicator reflecting its physiological state. Existing vision-based methods for analyzing fish behavior lack a systematic correlation with health status. Furthermore…
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Artikel Jurnal
SwinGhost-ClustNet: An explainable deep ensemble model for papaya leaf disease detection and field deployment in Bangladeshi agriculture
Early detection of papaya leaf disease is essential for Bangladeshi farmers who experience 39.9% post-harvest losses and pesticide misuse risks. The proposed research presents SwinGhost-ClustNet, which is an ensemble of Swin Transformer to capture the global context, GhostNet to capture the local…
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Artikel Jurnal
Machine learning–based optimization of site-specific NPK fertilizer recommendation
Efficient fertilizer use is important for sustainable intensification, yet uniform recommendations tend to ignore sharp spatial and seasonal variability in soils, climate, and crop response. This study develops a machine learning–based and constrained optimization framework to generate…
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Artikel Jurnal
Automated extraction of scientific statements for integrated assessment of animal welfare using language models
Animal welfare is a key concern in livestock farming, and a semantic modeling approach for welfare assessment is recognized as scientifically grounded. However, extracting supporting scientific evidence still relies heavily on manual review of the literature, limiting scalability and efficiency. To…
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Artikel Jurnal
Energy-autonomous IoT-based wireless sensor networking architecture for plant health monitoring and precision irrigation in sugarcane
Sugarcane farming demands precise irrigation and vigilant health monitoring to maximize productivity, yet conventional approaches often fall short in efficiency and scalability. This paper introduces a self-sustaining IoT framework that leverages a wireless sensor network to track critical…
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Artikel Jurnal
Attention-based pretrained deep learning framework for nutrient deficiency diagnosis in oilseed rape using UAV multispectral imagery
Timely and accurate diagnosis of crop nutrient deficiencies using imagery is essential for advancing precision agriculture. Conventional approaches relying on RGB imagery are limited by their narrow spectral range, whereas multispectral (MS) imagery offers richer spectral information for crop…
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Artikel Jurnal
Lameness detection in dairy cows using pose estimation and bidirectional LSTMs
Lameness is a prevalent health condition in dairy cattle that negatively impacts welfare and productivity. Automatic lameness detection would allow for timely detection and treatment with limited labor. This study presents a lameness detection approach that combines pose-estimation and…
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Artikel Jurnal
An intelligent multi-modal Q&A system for agriculture combining APGM, PBTCS, and RAG
This study addresses the growing need for efficient large-scale modeling techniques in agricultural production by introducing an intelligent multimodal question-answering system tailored to fruit tree cultivation. At its core is a lightweight multimodal prompt-generation model (APGM), which…
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Artikel Jurnal
Variations in pod detachment forces in Arachis hypogaea forecast the most suitable conditions for mechanical harvesting
Peanut cultivation is regaining interest in Italy due to its agronomic and nutritional value, but profitable production requires well-defined practices that ensure efficient harvesting. In this context, one of the most affordable approaches for mechanised harvesting involves a two-phase process…
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Artikel Jurnal
Soybean phenological stage identification based on multimodal data and a dynamic gating fusion model
Accurate, near real-time soybean phenology information is critical for crop management and breeding. Previous approaches relying on satellite remote sensing time-series data suffer from temporal delays, limiting their usefulness for in-season decision-making. To overcome this limitation, this study…
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Artikel Jurnal
Comparative evaluation of depth imaging and 3D point cloud sensing for automatic strawberry runner cutting
Excessive runners divert plant resources, reduce yield, and increase labor costs. This study presents the development and evaluation of an intelligent runner detection and cutting system to automate strawberry runner management, thereby improving operational efficiency and reducing labor demand in…
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Artikel Jurnal
Proximal sensing of horticultural crops with mobile device LiDAR
Robust, multipurpose 3D plant model datasets are critical for the development of phenotyping and structural characteristic estimation methods. This study details the construction of a multi-crop 3D point cloud dataset collected in-situ, tests the efficacy of HSV thresholding on colorized point…
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Artikel Jurnal
Digital transformation in Canadian crop production: A scoping review of technologies, adoption drivers, and systemic barriers
Digital agricultural technologies are widely promoted as pathways to improve productivity, profitability, and environmental performance in crop production. Yet their development, validation, and adoption vary significantly across contexts. This scoping review synthesizes evidence from 64 Canadian…
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Artikel Jurnal
Sow farrowing detection and farrowing duration analysis based on Rotated Bounding Box and improved YOLOv8
Sow farrowing represents a critical stage in porcine production, profoundly impacting farm profitability and the welfare of both sows and piglets. Timely monitoring of maternal behavior is essential for ensuring successful delivery outcomes. This study proposes a novel real-time detection framework…
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Autonomous mowing in agriculture: Current status, needs, and future opportunities
Autonomous mowing between rows in orchards, vineyards, berry farms, and other specialty crop systems can reduce labor costs, improve safety on uneven terrain, and increase farm productivity and profitability. Mowing is also central to haymaking, where timely cutting affects forage quality and…
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Artikel Jurnal
Classification of drought resistance wheat varieties based on hyperspectral remote sensing combined with machine learning
The screening of new drought resistance wheat varieties is the most economical and effective method for combating drought. In this study, hyperspectral data of the wheat canopy at different growth stages and drought resistance indices during the maturity period were acquired, and spectral…
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Artikel Jurnal
YOLOv9t-DyE: A lightweight detection framework with SAM-assisted segmentation for quantifying chilli leaf curl complex
For chilli leaf curl complex accurate field-scale assessment is challenging because both chilli leaf curl virus (ChiLCV) and mite infestation generate visually similar curling symptoms leading to frequent misdiagnosis during routine scouting. Such overlap, coupled with reliance on manual scoring…
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Artikel Jurnal
Point cloud feature optimization of dual-mechanism LiDAR with reflection and fluorescence spectra for plant classification
LiDAR lacks spectral information related to plant properties, limiting its ability to identify plant in complex environments using only three-dimensional spatial information and single-band spectral data. We designed a dual-mechanism LiDAR system that combines reflection and fluorescence, proposing…
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