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Federal
Data and Code from: Smart vision-based monitoring system for AI-driven moth population estimation using camera-equipped trap imaging
Department of Agriculture —
Real-time, image-based monitoring for stored product insect pests could increase timely treatments and protection for postharvest products throughout the supply... -
Federal
Data from: Avian Sentinels Neural Nest: AI-Powered Bird Monitoring System for Real-Time Detection and Species Identification
Department of Agriculture —
Traditional bird deterrent methods, such as scarecrows, loud noise emitters, and netting, can become less effective over time due to bird habituation. This study... -
Federal
Genome analysis of the ubiquitous boxwood pathogen Pseudonectria foliicola: A small fungal genome with an increased cohort of genes associated with loss of virulence
Department of Agriculture —
Boxwood plants are affected by many different diseases caused by fungi. Some boxwood diseases are deadly and quickly kill the infected plants, but with others, the... -
Federal
Data and code from: AI-based image profiling and detection for the beetle byte quintet using Vision Transformer (ViT) in advanced stored product infestation monitoring
Department of Agriculture —
Managing beetles that infest stored products is crucial for reducing losses in harvest supply chains and improving food security and safety. Successful pest... -
Federal
Data from: Visualizing Plant Responses: Novel Insights Possible through Affordable Imaging Techniques in the Greenhouse
Department of Agriculture —
Data of image calculation averages, coefficient of variations, and experimental measurements that were presented in the manuscript, Visualizing Plant Responses: Novel... -
Federal
The Bronson Files, Dataset 2, Field 17, 2013
Department of Agriculture —
Dr. Kevin Bronson provides this unique nitrogen and water management in cotton agricultural research dataset for compute, including notation of field events and... -
Federal
Data and Images from: Numerical Signature Dataset of Thoracic and Elytral Fragments from Curculionidae and Tenebrionidae Beetles for AI-Based Species Identification
Department of Agriculture —
This dataset presents curated and annotated 256×256 pixel image fragments of thoracic and elytral regions from six economically significant species within the beetle... -
Federal
The Bronson Files, Dataset 1, Field 17, 2012
Department of Agriculture —
Dr. Kevin Bronson provides this unique nitrogen and water management in cotton agricultural research dataset for compute, including notation of field events and... -
Federal
The Bronson Files, Dataset 7, Field 13, 2015
Department of Agriculture —
Dr. Kevin Bronson provides a second experiment year of Field 13 nitrogen and water management in cotton agricultural research data for compute, including notation of... -
Federal
The Bronson Files, Dataset 4, Field 105, 2013
Department of Agriculture —
Dr. Kevin Bronson provides this unique nitrogen and water management in wheat agricultural research dataset for compute. Ten irrigation treatments from a linear... -
Federal
The Bronson Files, Dataset 3, Field 107, 2013
Department of Agriculture —
Dr. Kevin Bronson provides a small area nitrogen and water management in Guayule agricultural research dataset for compute, including notation of field events and... -
Federal
The Bronson Files, Dataset 5, Field 105, 2014
Department of Agriculture —
Dr. Kevin Bronson provides a second year of nitrogen and water management in wheat agricultural research dataset for compute. Ten irrigation treatments from a linear... -
Federal
The Bronson Files, Dataset 6, Field 13, 2014
Department of Agriculture —
Dr. Kevin Bronson provides a unique nitrogen and water management in cotton agricultural research dataset for compute, including notation of field events and...