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Ms. Mar Ariza-Sentís | Precision Agriculture Award | Young Scientist Award

Ms. Mar Ariza-Sentís, Wageningen Univresity & Research, Netherlands

Maria del Mar Ariza-Sentís, a Ph.D. candidate at Wageningen University, specializes in Geo-Information Science and is an AI expert for the FlexiGroBots project. 🤖 With a background in Agricultural and Food Engineering, she’s dedicated to reducing pesticide use through AI models detecting Botrytis cinerea in vineyards. Maria’s expertise spans UAV technology, Big Data, and geospatial analysis. 🌱 As an educator, she has taught courses and moderated MOOCs, contributing significantly to agricultural innovation. Maria’s research publications and conference presentations underscore her commitment to advancing precision agriculture. Beyond academia, she enjoys figure skating, martial arts, and playing the piano. 🎿🥋🎹


Publication Profile

Professional Background

Maria del Mar Ariza-Sentís is a Ph.D. candidate at Wageningen University, specializing in Geo-Information Science. 🎓 With a master’s degree from Wageningen and a bachelor’s from the University of Lleida, she’s earned recognition for her academic achievements. Maria’s expertise extends to AI and UAV technology, evident through her role as an AI expert for the FlexiGroBots project, aiming to reduce pesticide use in agriculture. 🌿 Her diverse professional experience includes internships, teaching positions, and contributions to academic research, highlighting her commitment to advancing agricultural innovation.

Education and Awards

Maria’s dedication to continuous learning is evident through her complementary education, including a EU Drone license and qualifications in phytosanitary product handling. 🛩️ Her academic excellence has been recognized through numerous honors and awards, reflecting her commitment to excellence in research and academia.

Research Focus

Maria del Mar Ariza-Sentís’s research primarily focuses on the application of unmanned aerial vehicles (UAVs) and AI technologies in precision agriculture, with a specific emphasis on vineyard management. 🌱 Her work spans various areas, including object detection and tracking in precision farming, mapping spatial variability of diseases like Botrytis bunch rot, and optimizing crop management practices through UAV-based data analysis. 🚜 Maria’s innovative research contributes to sustainable agriculture by providing insights into crop health, yield prediction, and resource optimization, ultimately enhancing agricultural efficiency and minimizing environmental impact. 🌾


Publication Top Notes

🌿 Analysis of Vegetation Indices to Determine Nitrogen Application and Yield Prediction in Maize (Zea mays L.) from a Standard UAV Service
📄 Cited by: 221
📅 Year: 2016

🍇 Mapping the spatial variability of Botrytis bunch rot risk in vineyards using UAV multispectral imagery
📄 Cited by: 40
📅 Year: 2023

🔍 Object detection and tracking on UAV RGB videos for early extraction of grape phenotypic traits
📄 Cited by: 17
📅 Year: 2023

📸 Dataset on unmanned aerial vehicle multispectral images acquired over a vineyard affected by Botrytis cinerea in northern Spain
📄 Cited by: 11
📅 Year: 2023

🌱 Estimation of spinach (Spinacia oleracea) seed yield with 2D UAV data and deep learning
📄 Cited by: 11
📅 Year: 2023

🌾 Mapping of Rumex obtusifolius in nature conservation areas using very high resolution UAV imagery and deep learning
📄 Cited by: 11
📅 Year: 2022

🍇 Dataset on UAV RGB videos acquired over a vineyard including bunch labels for object detection and tracking
📄 Cited by: 10
📅 Year: 2023

🔄 BBR: An open-source standard workflow based on biophysical crop parameters for automatic Botrytis cinerea assessment in vineyards
📄 Cited by: 3
📅 Year: 2023

🌡️ Comparing Nadir and Oblique Thermal Imagery in UAV-Based 3D Crop Water Stress Index Applications for Precision Viticulture with LiDAR Validation
📄 Cited by: 2
📅 Year: 2023

🌽 Vegetation indices from unmanned aerial vehicles–mounted sensors to monitor the development of maize (Zea mays L.) under different N rates
📄 Cited by: 2
📅 Year: 2015

🔍 Object detection and tracking in Precision Farming: a systematic review
📄 Cited by: 1
📅 Year: 2024

Mar Ariza-Sentís | Precision Agriculture Award | Young Scientist Award

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