MethodsX最新文献_第3页

Grapevine disease detection using (q,τ)-nabla calculus quantum deformation with deep learning features 基于深度学习特征的(q,τ)-nabla微积分量子变形的葡萄病害检测

IF 1.9

MethodsX Pub Date : 2025-09-10 DOI: 10.1016/j.mex.2025.103619

Ahmad Sami Al-Shamayleh , Rabha W. Ibrahim

{"title":"Grapevine disease detection using (q,τ)-nabla calculus quantum deformation with deep learning features","authors":"Ahmad Sami Al-Shamayleh , Rabha W. Ibrahim","doi":"10.1016/j.mex.2025.103619","DOIUrl":"10.1016/j.mex.2025.103619","url":null,"abstract":"<div><div>Today, one of the most important first steps in attaining sustainable agriculture and guaranteeing food security is the detection of plant diseases. Quantitative analysis of plant physiology is now feasible thanks to developments in computer vision and imaging technologies. On the other hand, manual diagnosis requires a lot of work and in-depth plant pathology knowledge. Numerous innovative methods for identifying and classifying plant diseases have been widely used. In this study, we propose a novel hybrid classification method that combines (q,τ)-Nabla calculus quantum deformation-based features with deep learning feature representations to classify diseases in grapevine leaves. The methodology of this study relies on:<ul><li><span>•</span><span><div>Nabla calculus quantum deformation features are utilized to extract robust handcrafted features that capture local texture and structural variations associated with disease symptoms.</div></span></li><li><span>•</span><span><div>Deep features are extracted using a pre-trained convolutional neural network, which captures high-level semantic information from leaf images.</div></span></li></ul>The concatenated feature vectors are then fed into a machine learning classifier for final prediction. Test results on a dataset of grapevine leaf disease show that the proposed method outperforms individual approaches, in accuracy. The proposed method helps minimize financial losses and support effective plant disease management, thereby improving crop yield and contributing to food security.</div></div>","PeriodicalId":18446,"journal":{"name":"MethodsX","volume":"15 ","pages":"Article 103619"},"PeriodicalIF":1.9,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145094864","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A hybrid approach for real-time hand tracking using fiducial markers and inertial sensors 一种基于基准标记和惯性传感器的手部实时跟踪混合方法

IF 1.9

MethodsX Pub Date : 2025-09-08 DOI: 10.1016/j.mex.2025.103609

Ranjeet Bidwe , Shubhangi Deokar , Yash Parkhi , Tanisha Vyas , Nimita Jestin , Utkarsh Kumar , Satviki Budhia , Armaan Jeswani

{"title":"A hybrid approach for real-time hand tracking using fiducial markers and inertial sensors","authors":"Ranjeet Bidwe , Shubhangi Deokar , Yash Parkhi , Tanisha Vyas , Nimita Jestin , Utkarsh Kumar , Satviki Budhia , Armaan Jeswani","doi":"10.1016/j.mex.2025.103609","DOIUrl":"10.1016/j.mex.2025.103609","url":null,"abstract":"<div><div>This paper presents a cost-effective hybrid hand-tracking technique that integrates fiducial marker detection, capacitive touch sensing, and inertial measurement for real-time gesture recognition in immersive environments. The system is implemented on lightweight hardware comprising a Raspberry Pi Zero 2 W and an ESP32, with OpenCV’s ArUco marker detection enabling 3D hand pose estimation, capacitive sensors supporting finger-state recognition, and an Inertial Measurement Unit (IMU) providing orientation tracking. Optimizations such as exposure adjustment and region-of-interest processing ensure robust marker detection under variable illumination, while sensor data is transmitted via Bluetooth Low Energy (BLE) and WebSocket protocols for synchronization with external devices.</div><div>The methodological novelty of this work is highlighted as follows:</div><div>•High Accuracy Across Modalities: Achieved 3.4 mm localization accuracy, 85–91% orientation accuracy, and ∼2.9 mm hand pose keypoint accuracy, with trajectory fidelity maintained at 80–81%.</div><div>•Robust Finger-State Recognition: The capacitive sensing module consistently delivered 96.1% accuracy in detecting finger states across multiple runs.</div><div>•Validated Communication Trade-offs: Latency testing established complementary roles of Wi-Fi (high throughput, ∼467 msg/s) and BLE (low latency, ∼50 ms, >98% reliability) for real-time applications.</div><div>By fusing multiple sensing modalities, the method delivers enhanced accuracy, responsiveness, and stability while minimizing computational overhead. The system provides a reproducible, modular, and scalable solution suitable for VR/AR interaction, assistive technology, education, and human–computer interaction.</div></div>","PeriodicalId":18446,"journal":{"name":"MethodsX","volume":"15 ","pages":"Article 103609"},"PeriodicalIF":1.9,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145044248","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A combined modelling approach to predicting injury severity in rear-end collisions 一种预测追尾碰撞损伤严重程度的组合建模方法

IF 1.9

MethodsX Pub Date : 2025-09-08 DOI: 10.1016/j.mex.2025.103612

Shufeng Wang, Shixuan Jiang, Zhengli Wang, Lingyi Meng

{"title":"A combined modelling approach to predicting injury severity in rear-end collisions","authors":"Shufeng Wang, Shixuan Jiang, Zhengli Wang, Lingyi Meng","doi":"10.1016/j.mex.2025.103612","DOIUrl":"10.1016/j.mex.2025.103612","url":null,"abstract":"<div><div>Rear-end collisions constitute the most prevalent category of urban road traffic accidents, resulting in severe traffic congestion, casualties, and substantial economic losses. To mitigate the impact of such accidents effectively, this study proposes a severity prediction model that integrates Convolutional Neural Networks (CNN) and Extreme Gradient Boosting (XGBoost). The model employs the U.S. Department of Transportation's Fatality Analysis Reporting System (FARS) accident dataset, which undergoes preliminary preprocessing. Subsequently, Principal Component Analysis (PCA) is applied to reduce the dimensionality of the influencing factors prior to their input into the combined model for classification. CNN is utilized to extract features, while XGBoost is responsible for classification. Experimental results demonstrate that the combined model achieves a classification accuracy of 96.2 %, with superior AUC and F1 scores compared to traditional models, indicating excellent predictive performance.<ul><li><span>•</span><span><div>This paper proposes a hybrid CNN-XGBoost algorithm that combines the superior feature extraction capability of CNN with the powerful structured data processing and precise prediction ability of XGBoost, resulting in a significant performance improvement over traditional algorithms.</div></span></li></ul></div></div>","PeriodicalId":18446,"journal":{"name":"MethodsX","volume":"15 ","pages":"Article 103612"},"PeriodicalIF":1.9,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145117860","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

From scores to insights: Predicting MT errors using reliable metrics and linguistic typology in slavic languages 从分数到洞察力：使用可靠的度量和斯拉夫语言的语言类型学预测机器翻译错误

IF 1.9

MethodsX Pub Date : 2025-09-08 DOI: 10.1016/j.mex.2025.103613

Dasa Munkova , Lucia Benkova , Michal Munk , Ľubomír Benko , Petr Hajek

{"title":"From scores to insights: Predicting MT errors using reliable metrics and linguistic typology in slavic languages","authors":"Dasa Munkova , Lucia Benkova , Michal Munk , Ľubomír Benko , Petr Hajek","doi":"10.1016/j.mex.2025.103613","DOIUrl":"10.1016/j.mex.2025.103613","url":null,"abstract":"<div><div>Machine Translation (MT) evaluation plays a crucial role in advancing systems translating into morphologically rich, low-resource languages such as Slovak. Existing automatic evaluation methods typically offer a single quality score, lacking insight into specific error types. A novel linguistically informed methodology that predicts the probability of MT error categories by integrating manual annotation with automatic evaluation metrics is proposed. The method builds on a modified MQM framework adapted for Slovak and employs a dataset of English-to-Slovak translations, combining outputs from statistical and neural MT systems with human reference translations. Manual annotations identified five linguistically motivated error categories. Reliability of 68 automatic metrics was assessed using Cronbach’s alpha, correlation coefficients, coefficient of determination (R²), and entropy. Bootstrapped logistic regression models were then developed to predict error occurrence probabilities. The proposed methodology improves the explainability and reliability of automatic MT evaluation by bridging the gap between holistic scoring and detailed error categorization. It significantly reduces the human effort required for quality assessment while maintaining a high degree of linguistic relevance, particularly for complex target languages like Slovak.<ul><li><span>•</span><span><div>Predicts probabilities of specific MT error categories</div></span></li><li><span>•</span><span><div>Integrates linguistic expertise with statistical reliability analysis</div></span></li><li><span>•</span><span><div>Reduces human effort in MT evaluation while preserving linguistic precision</div></span></li></ul></div></div>","PeriodicalId":18446,"journal":{"name":"MethodsX","volume":"15 ","pages":"Article 103613"},"PeriodicalIF":1.9,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145044117","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A systematical procedure to extracting legal entities from Indonesian judicial decisions 将法律实体从印尼司法判决中分离出来的系统程序

IF 1.9

MethodsX Pub Date : 2025-09-06 DOI: 10.1016/j.mex.2025.103610

Eka Qadri Nuranti , Naili Suri Intizhami , Evi Yulianti , A. Muh. Iqbal Latief , Osama Iyad Al Ghozy

{"title":"A systematical procedure to extracting legal entities from Indonesian judicial decisions","authors":"Eka Qadri Nuranti , Naili Suri Intizhami , Evi Yulianti , A. Muh. Iqbal Latief , Osama Iyad Al Ghozy","doi":"10.1016/j.mex.2025.103610","DOIUrl":"10.1016/j.mex.2025.103610","url":null,"abstract":"<div><div>This article presents a systematic method of extracting legal entities from Indonesian judicial decisions with a well-structured named entity recognition (NER) approach. The procedure was implemented by gathering and annotating court decisions for theft cases at three court levels: first instance (2478 files), appeal (147 files), and cassation (62 files), amounting to 2687 annotated files. The data were harvested from the official website of the Supreme Court of the Republic of Indonesia using automated web scraping, followed by manual filtering for relevance and completeness.</div><div>Manual annotation was performed with the Label Studio platform by three independent annotators. Annotation consistency was considered using Fleiss' Kappa, yielding an average agreement score of 0.705 across all levels, indicating good inter-annotator reliability. The method uses a hierarchical structure and a BIO tagging scheme to tag >50 types of legal entities, including defendants, judges, legal articles, charges, and verdict decisions.</div><div>This approach is proper for text processes such as legal information extraction, classification, and legal analysis. From a legal perspective, this process will improve legal transparency and research on Indonesian judicial data.<ul><li><span>•</span><span><div>Structured pipeline for gathering, filtering, and annotating Indonesian court judgments based on legal metadata and web scraping.</div></span></li><li><span>•</span><span><div>Manual annotation of 2687 court documents with annotation rules and inter-annotator agreement using Fleiss' Kappa.</div></span></li><li><span>•</span><span><div>Token-level translation and BIO tagging for >50 legal entities, enabling downstream NLP tasks such as named entity recognition.</div></span></li></ul></div></div>","PeriodicalId":18446,"journal":{"name":"MethodsX","volume":"15 ","pages":"Article 103610"},"PeriodicalIF":1.9,"publicationDate":"2025-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145044252","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Econometric methodology for selecting explanatory factors for power consumption 选择电力消耗解释因素的计量经济学方法

IF 1.9

MethodsX Pub Date : 2025-09-05 DOI: 10.1016/j.mex.2025.103601

Serge Guefano

{"title":"Econometric methodology for selecting explanatory factors for power consumption","authors":"Serge Guefano","doi":"10.1016/j.mex.2025.103601","DOIUrl":"10.1016/j.mex.2025.103601","url":null,"abstract":"<div><div>A thorough and careful choice of inputs is the bedrock of all successful energy demand modelling. However, the choice of inputs in most research into fluctuations in electricity demand and its potential determinants is very often made by establishing a simple correlation or by a short descriptive analysis of the specific characteristics of each selected input. As a result, this work proposes a new methodology for input selection based on the interaction between stationarity tests, the Johansen cointegration test, as well as ARDL and VECM modelling, in order to facilitate the highlighting of a real causal link between the inputs brought in the modelling of electricity consumption. Applying this new approach to the Cameroonian case, enables to establish the existence of a unidirectional causal relationship from GDP per capita, CO2 emissions, urbanization and the number of subscribers, respectively, to residential electricity consumption. These inputs are therefore the main factors explaining electricity consumption in this sector.<ul><li><span>•</span><span><div>A new methodology for selecting input variables in modelling power demand is outlined.</div></span></li><li><span>•</span><span><div>The stationarity and Johansen tests as well as the ARDL and VECM models are combined.</div></span></li><li><span>•</span><span><div>The choice of inputs for modelling and forecasting power demand is optimized.</div></span></li></ul></div></div>","PeriodicalId":18446,"journal":{"name":"MethodsX","volume":"15 ","pages":"Article 103601"},"PeriodicalIF":1.9,"publicationDate":"2025-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145044256","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Hybrid quantum-classical deep learning framework for balanced multiclass diabetic retinopathy classification 基于混合量子经典深度学习框架的糖尿病视网膜病变平衡分类

IF 1.9

MethodsX Pub Date : 2025-09-04 DOI: 10.1016/j.mex.2025.103605

Tabassum Ara , Ved Prakash Mishra , Manish Bali , Anuradha Yenkikar

{"title":"Hybrid quantum-classical deep learning framework for balanced multiclass diabetic retinopathy classification","authors":"Tabassum Ara , Ved Prakash Mishra , Manish Bali , Anuradha Yenkikar","doi":"10.1016/j.mex.2025.103605","DOIUrl":"10.1016/j.mex.2025.103605","url":null,"abstract":"<div><div>Diabetic Retinopathy (DR) is a progressive eye disease and a leading cause of preventable blindness among diabetic patients. Early and accurate classification of its severity stages is crucial for effective treatment but remains challenging due to class imbalance, high-resolution data, and limited scalability of existing models. This study presents a novel hybrid quantum-classical deep learning framework to address these limitations in five-class DR classification. The model achieves a balanced accuracy of 80.96 % on the APTOS 2019 dataset, outperforming several classical baselines across all DR stages. It is optimized for computational efficiency and class-balanced learning, making it suitable for deployment in telemedicine platforms and low-resource clinical settings. This work contributes a scalable AI-based diagnostic approach that fuses deep learning with emerging quantum computing techniques. The methodology, results, and publicly shared codebase provide a replicable framework for researchers and practitioners working in AI for medical imaging and early disease screening. This method is well-suited for low-resource clinical environments and tele-ophthalmology applications. The method involves an:<ul><li><span>•</span><span><div>ResNet-50 feature extractor with a 4-stage dense projection (2048→8) for quantum-ready compression</div></span></li><li><span>•</span><span><div>8-qubit VQC with parameterized RY–RZ gates and ring-style entanglement for high expressiveness</div></span></li><li><span>•</span><span><div>Stratified sampling + mixed-precision training for efficiency and class-balanced generalization</div></span></li></ul></div></div>","PeriodicalId":18446,"journal":{"name":"MethodsX","volume":"15 ","pages":"Article 103605"},"PeriodicalIF":1.9,"publicationDate":"2025-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145044241","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

EyeMap: A fusion-based method for eye movement-based visual attention maps as predictive markers of parkinsonism EyeMap：一种基于融合的方法，以眼动为基础的视觉注意图作为帕金森病的预测标记

IF 1.9

MethodsX Pub Date : 2025-09-03 DOI: 10.1016/j.mex.2025.103607

Akshay S , Amudha J , Amitabh Bhattacharya , Nitish Kamble , Pramod Kumar Pal

{"title":"EyeMap: A fusion-based method for eye movement-based visual attention maps as predictive markers of parkinsonism","authors":"Akshay S , Amudha J , Amitabh Bhattacharya , Nitish Kamble , Pramod Kumar Pal","doi":"10.1016/j.mex.2025.103607","DOIUrl":"10.1016/j.mex.2025.103607","url":null,"abstract":"<div><div>EyeMap is a method for visualizing and classifying eye movement patterns using scanpaths, fixation heatmaps, and gridded Areas of Interest (AOIs). EyeMap combines predictions from modality-specific machine learning and deep learning models using a late-fusion technique to produce interpretable gaze representations. By collecting spatial, temporal, and regional elements of gaze data, the method enhances diagnostic interpretability and enables the detection of Parkinsonian symptoms. This method provides complementary perspectives on gaze behavior, encompassing spatial focus, temporal scan order, and attention allocation across regions of interest. A dataset consisting of visualizations of organized visual tasks completed by both PD patients and healthy controls is created to support the development and validation of this method. EyeMap shows that vision-driven models may detect PD-specific gaze anomalies without the need for manual feature engineering. All implementation steps, from data acquisition to model fusion, are fully described to enable reproducibility and potential adaptation to other gaze-based analysis contexts.<ul><li><span>1.</span><span><div>A structured method was developed to visualize eye-tracking data in three distinct formats</div></span></li><li><span>2.</span><span><div>Classification outputs from separate gaze visualizations were combined using softmax-level fusion</div></span></li><li><span>3.</span><span><div>A new eye-tracking dataset was generated to support method development and reproducibility</div></span></li></ul></div></div>","PeriodicalId":18446,"journal":{"name":"MethodsX","volume":"15 ","pages":"Article 103607"},"PeriodicalIF":1.9,"publicationDate":"2025-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145019085","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimization and validation of a consolidated Set of TaqMan qPCR assays for the surveillance of clinically relevant antibiotic resistance genes in environmental matrices 环境基质中临床相关抗生素耐药基因的TaqMan qPCR检测方法的优化和验证

IF 1.9

MethodsX Pub Date : 2025-09-03 DOI: 10.1016/j.mex.2025.103600

Sasikaladevi Rathinavelu, Karin Beck, Denise Lea Wälchli, Helmut Bürgmann

{"title":"Optimization and validation of a consolidated Set of TaqMan qPCR assays for the surveillance of clinically relevant antibiotic resistance genes in environmental matrices","authors":"Sasikaladevi Rathinavelu, Karin Beck, Denise Lea Wälchli, Helmut Bürgmann","doi":"10.1016/j.mex.2025.103600","DOIUrl":"10.1016/j.mex.2025.103600","url":null,"abstract":"<div><div>The continued rise of antibiotic resistance and adoption of the One Health approach necessitates reliable methods for detection and quantification of antibiotic resistance genes (ARGs) in complex environmental matrices. Here we present a consolidated set of TaqMan quantitative PCR assays for quantification of clinically relevant and emerging ARGs in complex environmental matrices.<ul><li><span>•</span><span><div>We systematically designed five new primer sets, six TaqMan probes and verified and adapted four previously published relevant primer/probe sets from literature and evaluated their specificity <em>in silico</em> against current database.</div></span></li><li><span>•</span><span><div>For external quantification, two sets of gBlock standard libraries were designed. We experimentally validated the specificity, sensitivity, and efficiency of the assays with positive strain control DNA, negative strain control DNA, general no target controls, extraction blank controls, negative controls, and environmental test samples (i.e., metagenomic DNA from complex environmental matrices) to comprehensively assess each assays’ performance.</div></span></li><li><span>•</span><span><div>Optimization included iterative testing of both primer and probe concentration, annealing temperature, and annealing time. Results demonstrated robust and reliable detection and quantification of ARGs in clinical isolates and wastewater effluents with high sensitivity, specificity, and efficiency.</div></span></li></ul>This makes the assays suitable for surveillance in wastewater or various environmental matrices, in support of efforts to mitigate dissemination of antibiotic resistance<em>.</em></div></div>","PeriodicalId":18446,"journal":{"name":"MethodsX","volume":"15 ","pages":"Article 103600"},"PeriodicalIF":1.9,"publicationDate":"2025-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145019084","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Frag-n-Fly gardening method for coral restoration - Pitching to the industry level the methods for coral fragmentation and outplanting in coral reef restoration 珊瑚恢复用蝇蝇园艺法。向工业水平推广珊瑚礁恢复中珊瑚破碎和外植的方法

IF 1.9

MethodsX Pub Date : 2025-09-02 DOI: 10.1016/j.mex.2025.103602

Bruno Welter Giraldes , Caroline Donahue , Eduardo Santos Mello , Hamad S. Al-Mohannadi , Syed Faisal Mustafa , Maryam Abdulla , Pedro Range

{"title":"Frag-n-Fly gardening method for coral restoration - Pitching to the industry level the methods for coral fragmentation and outplanting in coral reef restoration","authors":"Bruno Welter Giraldes , Caroline Donahue , Eduardo Santos Mello , Hamad S. Al-Mohannadi , Syed Faisal Mustafa , Maryam Abdulla , Pedro Range","doi":"10.1016/j.mex.2025.103602","DOIUrl":"10.1016/j.mex.2025.103602","url":null,"abstract":"<div><div>This study introduces the Frag-n-Fly method, an innovative approach to large-scale coral gardening designed to improve the efficiency of fragmentation and outplanting while meeting maritime industry standards. The method follows a six-step workflow implemented during two maritime expeditions and centers on a cache area adjacent to the restoration site, where scientifically validated artificial reef structures replace traditional land-based husbandry facilities. By eliminating terrestrial transport and aquaria-based acclimation, Frag-n-Fly reduces coral stress and provides a stable in situ environment for acclimation and fragmentation. Validation was achieved by processing 2000 colonies, producing over 20,000 fragments. The method demonstrated a fivefold increase in fragmentation throughput (∼50 vs. 10 colonies per hour), a ∼30–50% reduction in project costs, and early survivorship rates comparable or superior to traditional husbandry (0.11% vs. 0.69% mortality at 75 days). While Frag-n-Fly provides substantial gains in scalability and efficiency, it requires validated artificial reef technologies, specialized vessels, and trained personnel. The method is therefore best suited for industrial-scale, offshore restoration projects, while complementing traditional nursery-based approaches. Methodological advances:<ul><li><span>•</span><span><div>Coral gardening conducted entirely at sea, eliminating land-based logistics.</div></span></li><li><span>•</span><span><div>Permanent cache areas with validated artificial reef modules ensure coral acclimation and survival.</div></span></li><li><span>•</span><span><div>Industrial tools enable high-throughput fragmentation and large-scale cost-efficient outplanting.</div></span></li></ul></div></div>","PeriodicalId":18446,"journal":{"name":"MethodsX","volume":"15 ","pages":"Article 103602"},"PeriodicalIF":1.9,"publicationDate":"2025-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145044112","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0