A5062287855- Smart Agriculture and AI
- Remote Sensing in Agriculture
- Plant Surface Properties and Treatments
- Leaf Properties and Growth Measurement
- Plant and soil sciences
- Greenhouse Technology and Climate Control
- Soil Mechanics and Vehicle Dynamics
- Remote Sensing and LiDAR Applications
- Agricultural and Food Production Studies
- Plant Water Relations and Carbon Dynamics
- Irrigation Practices and Water Management
- Business, Innovation, and Economy
- Spectroscopy and Chemometric Analyses
- Weed Control and Herbicide Applications
- Plant Disease Management Techniques
- Date Palm Research Studies
- Regional Development and Innovation
- Knowledge Societies in the 21st Century
- Historical and socio-economic studies of Spain and related regions
- Entomopathogenic Microorganisms in Pest Control
- Plant Pathogens and Fungal Diseases
- Soil Management and Crop Yield
- Pesticide and Herbicide Environmental Studies
- Environmental and Ecological Studies
- Business, Education, Mathematics Research
Universidad de Sevilla
2016-2025
Ghent University
2023
Universidad Nacional de Ucayali
2021
University Hospital of Lausanne
2017
University of California, Davis
2012
Feeding the growing global population requires an annual increase in food production. This requirement suggests use of pesticides, which represents unsustainable chemical load for environment. To reduce pesticide input and preserve environment while maintaining necessary level production, efficiency relevant processes must be drastically improved. Within this context, research strived to design, develop, test assess a new generation automatic robotic systems effective weed pest control aimed...
Farmers require accurate yield estimates, since they are key to predicting the volume of stock needed at supermarkets and organizing harvesting operations. In many cases, is visually estimated by crop producer, but this approach not or time efficient. This study presents a rapid sensing estimation scheme using off-the-shelf aerial imagery deep learning. A Region-Convolutional Neural Network was trained detect count number apple fruit on individual trees located orthomosaic built from images...
The advancement of computer vision technology has allowed for the easy detection weeds and other stressors in turfgrasses agriculture. This study aimed to evaluate feasibility single shot object detectors weed lawns, which represents a difficult task. In this study, four different YOLO (You Only Look Once) version, along with all their various scales, were trained on public ‘Weeds’ dataset 4203 digital images growing lawns total 11,385 annotations tested turfgrasses. Different species...
Mechatronics and Robotics (MaR) have recently gained importance in product development manufacturing settings applications. Therefore, the Center for Space Emerging Technologies (C-SET) has managed an international multi-disciplinary study to present, historically, first Latin American general review of industrial, collaborative, mobile robotics, with support North European researchers institutions. The methodology is developed by considering literature extracted from Scopus, Web Science,...
Abstract The leaf area index (LAI) is a biophysical crop parameter of great interest for agronomists and plant breeders. Direct methods measuring LAI are normally destructive, while indirect either costly or require long pre- post-processing times. In this study, novel deep learning-based (DL) model was developed using RGB nadir-view images taken from high-throughput phenotyping platform estimation maize. study took place in commercial maize breeding trial during two consecutive growing...
The increasing demand for optimizing the use of agricultural resources will require adoption cutting-edge technologies and precision farming management. Unmanned Aerial Vehicle (UAV) sprayers seem promising due to their potential perform or spot spraying, particularly in woody crop environments where total surface spraying is unnecessary. However, incorporating this technology limited by lack scientific knowledge about environmental risks associated with UAV strict legal framework....
Leaf rust and yellow are globally significant fungal diseases that severely impact wheat production, causing yield losses of up to 60% in highly susceptible cultivars. Early accurate detection is crucial for integrating precision crop protection strategies mitigate these losses. This study investigates the potential 3D LiDAR technology monitoring rust-induced physiological changes by analyzing variations plant height, biomass, light reflectance intensity. Results showed grain decreased...
Homeostatic turnover of the extracellular matrix conditions structure and function healthy lung. In lung transplantation, long-term management remains limited by chronic allograft dysfunction, an umbrella term used for a heterogeneous entity ultimately associated with pathological airway and/or parenchyma remodeling.This study assessed whether local cross-talk between pulmonary microbiota host cells is key determinant in control lower remodeling posttransplantation.Microbiota DNA total RNA...
Remote and non-destructive estimation of leaf area index (LAI) has been a challenge in the last few decades as direct indirect methods available are laborious time-consuming. The recent emergence high-throughput plant phenotyping platforms increased need to develop new tools for better decision-making by breeders. In this paper, novel model based on artificial intelligence algorithms nadir-view red green blue (RGB) images taken from terrestrial high throughput platform is presented. mixes...
The demands of a growing population and developing global economy will require an increase in agricultural yield 70% over the next 30 years. However, achieving this goal is only possible with sustainable intensification systems. Spraying drones are one available technologies that could help meet goal. Presently, use spraying limited by both legal framework lack scientific knowledge about drift they generate compared to conventional terrestrial platforms. flexibility provide, their...
Plant modeling can provide a more detailed overview regarding the basis of plant development throughout life cycle. Three-dimensional processing algorithms are rapidly expanding in phenotyping programmes and decision-making for agronomic management. Several methods have already been tested, but practical implementations trade-off between equipment cost, computational resources needed fidelity accuracy reconstruction end-details needs to be assessed quantified. This study examined suitability...