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Novais, W
Ammar, K
Rehman, T
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Authors
Rodrigues Junior, F.A
Ortiz-Monasterio, I
Zarco-Tejada, P.J
Ammar, K
Gérard, B.G
Villalobos, J.E
Perret, J.S
Abdalla, K
Fuentes, C.L
Rodriguez, J.C
Novais, W
Syed, H.H
Rehman, T
Rahman, M
Busby, S
Sanz-Saez, A
Ru, S
Rehman, T
Rehman, T
Rahman, M
Ayipio, E
Lukwesa, D
Zheng, J
Wells, D
Syed, H.H
Topics
Sensor Application in Managing In-season CropVariability
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Robotics and Automation with Row and Horticultural Crops
Artificial Intelligence (AI) in Agriculture
Type
Oral
Year
2014
2018
2024
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1. Using Precision Agriculture And Remote Sensing Techniques To Improve Genotype Selection In A Breeding Program

Precision Agriculture (PA) and Remote Sensing (RS) technologies are increasingly being used as tools to assess crop and soil properties by breeders and physiologists.  These technologies are showing potential to improve genotype selections over their traditional field measurements, by providing quick access to crop properties throughout the crop cycle and yield estimation. The objective of this work was to use vegetation indices (VIs) and soil apparent electrical conductivity... F.A. Rodrigues junior, I. Ortiz-monasterio, P.J. Zarco-tejada, K. Ammar, B.G. Gérard

2. Delineation of Site-Specific Nutrient Management Zones to Optimize Rice Production Using Proximal Soil Sensing and Multispectral Imaging

Evaluating nutrient uptake and site-specific nutrient management zones in rice in Costa Rica from plant tissue and soil sampling is expensive because of the time and labor involved.  In this project, a range of measurement techniques were implemented at different vintage points (soil, plant and UAVs) in order to generate and compare nutrient management information.  More precisely, delineation of site-specific nutrient management zones were determined using 1) georeferenced soil/tissue... J.E. Villalobos, J.S. Perret, K. Abdalla, C.L. Fuentes, J.C. Rodriguez, W. Novais

3. Automated In-field Ornamental Nursery Plant Counting and Quality Assessment with End-to-end Deep Learning for Inventory Management

Efficient inventory management and rigorous quality evaluation play crucial roles for monitoring sales, yield, space utilization, production schedules, and quality enhancements in the ornamental nursery sector. The current method for conducting inventory and quality assessments is through manual plant counting, even when dealing with thousands of plants. The prevailing approach is inefficient, time consuming, labor intensive, potential inaccuracies, and high expenses. Given the continuous decrease... H.H. Syed, T. Rehman

4. Drought Tolerance Assessment with Statistical and Deep Learning Models on Hyperspectral Images for High-throughput Plant Phenotyping

Drought is an important factor that severely restricts blueberry growth, output and adversely impacts the desirable physiologic quality. Considering the challenges posed by climate change and erratic weather patterns, evaluating the drought tolerance of blueberry plants is not only vital for the agricultural industry but also for ensuring a consistent supply of these nutritious berries to consumers. Blueberry plants have a relatively ineffective water regulation mechanism due to their shallow... M. Rahman, S. Busby, A. Sanz-saez, S. Ru, T. Rehman

5. A High-throughput Phenotyping System Evaluating Salt Stress Tolerance in Kale Plants Cultivated in Aquaponics Environments

Monitoring plant growth in a controlled environment is crucial to make informed decisions for various management practices such as fertilization, weed control, and harvesting. Agronomic, physiological, and architectural traits in kale plants (Brassica oleracea) are important to producers, breeders, and researchers for assessing the performance of the plants under biotic and abiotic stresses.  Traditionally, architectural, and morphological traits have been used to monitor plant growth. However,... T. Rehman, M. Rahman, E. Ayipio, D. Lukwesa, J. Zheng, D. Wells, H.H. Syed