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Wardle, E
Worthington, M
Wells, D
Weinhold, B
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Authors
Rehman, T
Rahman, M
Ayipio, E
Lukwesa, D
Zheng, J
Wells, D
Syed, H.H
Vail, B
Oster, Z
Weinhold, B
Brown, A.J
Deleon, E
Wardle, E
Tagoe, A
Koparan, C
Poncet, A
Johnson, D.M
Worthington, M
Wang, D
Topics
Artificial Intelligence (AI) in Agriculture
Big Data, Data Mining and Deep Learning
Wireless Sensor Networks and Farm Connectivity
Scouting and Field Data collection with Unmanned Aerial Systems
Type
Oral
Poster
Year
2024
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1. 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

2. Generative Modeling Method Comparison for Class Imbalance Correction

An image dataset, for use in object detection of hay bales, with over 6000 images of both good and bad hay bales was collected.  Unfortunately, the dataset developed a class imbalance, with more good bale images than bad bales.  This dataset class imbalance caused the bad bale class to over train and the good bale class to under train, severely impacting precision, and recall.  To correct this imbalance and provide a comparison of differing generative modeling methods; three different... B. Vail, Z. Oster, B. Weinhold

3. Crop and Water Monitoring Networks with Low-cost, Internet of Things Technology

Making meaningful changes in agroecosystems often requires the ability to monitor many environmental parameters to accurately identify potential areas for improvement in water quality and crop production. Increasingly, research questions are requiring larger and larger monitoring networks to draw applicable insights for both researchers and producers. However, acquiring enough sensors to address a particular research question is often cost-prohibitive, making it harder to draw meaningful conclusions... A.J. Brown, E. Deleon, E. Wardle

4. Vegetation Coverage Specific Flower Density Estimation in Blackberry Using Unmanned Aerial Vehicle (UAV) Remote Sensing

The effective management of agricultural systems relies on the utilization of accurate data collection techniques to analyze essential crop attributes to enhance productivity and ensure profits. Data collection procedures for specialty horticultural crops are mostly subjective, time consuming and may not be accurate for management decisions in both phenotypic studies and crop production. Reliable and repeatable standard methods are therefore needed to capture and calculate attributes of horticultural... A. Tagoe, C. Koparan, A. Poncet, D.M. Johnson, M. Worthington, D. Wang