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ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.26180/14531892&rft.title=Monitoring insect pollination in strawberry and raspberry crop polytunnels&rft.identifier=https://doi.org/10.26180/14531892&rft.publisher=Monash University&rft.description=Over one third of crops are animal pollinated, with insects being the largest group. In some crops, including strawberries, yield, fruit weight, quality, aesthetics and shelf life increase with insect pollination. Many crops are protected from extreme weather in polytunnels, but the impacts of polytunnels on insects are poorly understood. Polytunnels could reduce pollination services, especially if insects have access issues. Here we examine the distribution and activity of honeybees and non-honeybee wild insects on a commercial fruit farm. We evaluated whether insect distributions are impacted by flower type (strawberry; raspberry; weed), or distance from polytunnel edges. We compared passive pan-trapping and active quadrat observations to establish their suitability for monitoring insect distribution and behaviour on a farm. To understand the relative value of honeybees compared to other insects for strawberry pollination, the primary crop at the site, we enhanced our observations with video data analysed using insect tracking software to document the time spent by insects on flowers. This dataset includes pan-trap and quadrat insect counts, and camera observations of honeybees foraging in strawberry polytunnels. The dataset also contains annotated images, pre-trained YOLOv2 object detection model for honeybees, tracks of honeybees extracted using software, and the results of the validation study for software performance.&rft.creator=Adrian G. Dyer&rft.creator=Alan Dorin&rft.creator=Jair Garcia&rft.creator=Malika Nisal Ratnayake&rft.creator=Scarlett R. Howard&rft.date=2021&rft_rights=CC-BY-4.0&rft_subject=Pollination&rft_subject=insect monitoring&rft_subject=Deep Learning Applications&rft_subject=computer vision algorithms&rft_subject=Agriculture&rft_subject=Artificial Intelligence and Image Processing&rft_subject=Agricultural Systems Analysis and Modelling&rft_subject=Sustainable Agricultural Development&rft.type=dataset&rft.language=English Access the data

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Over one third of crops are animal pollinated, with insects being the largest group. In some crops, including strawberries, yield, fruit weight, quality, aesthetics and shelf life increase with insect pollination. Many crops are protected from extreme weather in polytunnels, but the impacts of polytunnels on insects are poorly understood. Polytunnels could reduce pollination services, especially if insects have access issues. Here we examine the distribution and activity of honeybees and non-honeybee wild insects on a commercial fruit farm. We evaluated whether insect distributions are impacted by flower type (strawberry; raspberry; weed), or distance from polytunnel edges. We compared passive pan-trapping and active quadrat observations to establish their suitability for monitoring insect distribution and behaviour on a farm. To understand the relative value of honeybees compared to other insects for strawberry pollination, the primary crop at the site, we enhanced our observations with video data analysed using insect tracking software to document the time spent by insects on flowers.

This dataset includes pan-trap and quadrat insect counts, and camera observations of honeybees foraging in strawberry polytunnels. The dataset also contains annotated images, pre-trained YOLOv2 object detection model for honeybees, tracks of honeybees extracted using software, and the results of the validation study for software performance.

Issued: 2021-05-04

Created: 2021-05-04

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