@prefix dcat: <http://www.w3.org/ns/dcat#> .
@prefix dct: <http://purl.org/dc/terms/> .
@prefix foaf: <http://xmlns.com/foaf/0.1/> .
@prefix xsd: <http://www.w3.org/2001/XMLSchema#> .

<https://opendata.teagasc.ie/dataset/1faf34f8-810d-4ba3-8366-dad0c6ad5680> a dcat:Dataset ;
    dct:identifier "1faf34f8-810d-4ba3-8366-dad0c6ad5680" ;
    dct:issued "2026-10-07T13:48:36"^^xsd:dateTime ;
    dct:language "en" ;
    dct:modified "2026-10-08T08:28:24"^^xsd:dateTime ;
    dct:provenance "Camera and phone subset (2020): images were taken over 0.5 x 0.5 m quadrats on 26 grass-clover plots at Moorepark Farm (Teagasc), using a tripod-mounted Canon EOS 90D and a handheld iPhone 6. For labelled quadrats, herbage was cut at 2-4 cm above ground with Gardena Accu 60 hand shears immediately after imaging. Fresh weight was recorded, and the herbage separated into grass, clover and weeds, oven-dried for 16 h and weighed for dry matter. Further unlabelled images were taken at random locations in the same plots.   Drone subset (late autumn 2021): 7-36 images per paddock were taken over 23 paddocks with a DJI Mavic 2 Pro at 6-12 m. Paddock-level dry herbage mass came from (a) visual estimation by two experts at the time of imaging and (b) the protocol of Egan et al. (2018): two 1.2 x 8 m strips per paddock cut at 4 cm with an Etesia mower, and a 100 g subsample dried at 95 C for 16 h.  " ;
    dct:publisher <https://opendata.teagasc.ie/organization/b16b4c0b-15bd-4654-b227-792210c7076b> ;
    dct:relation "Albert, P., Saadeldin, M., Narayanan, B., Mac Namee, B., Hennessy, D., O'Connor, A. H., O'Connor, N. E. & McGuinness, K. (2022). Utilizing unsupervised learning to improve sward content prediction and herbage mass estimation. arXiv:2204.09343",
        "Albert, P., Saadeldin, M., Narayanan, B., Mac Namee, B., Hennessy, D., O'Connor, A., O'Connor, N. & McGuinness, K. (2021). Semi-supervised dry herbage mass estimation using automatic data and synthetic images. Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) Workshops, pp. 1284-1293",
        "Albert, P., Saadeldin, M., Narayanan, B., Mac Namee, B., Hennessy, D., O'Connor, N. E. & McGuinness, K. (2022). Unsupervised domain adaptation and super resolution on drone images for autonomous dry herbage biomass estimation. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, pp. 1636-1646" ;
    dct:title "Irish Grass Clover Dataset (VistaMilk)" ;
    dcat:keyword "Dry matter",
        "Grass",
        "Herbage mass",
        "Perennial ryegrass",
        "White clover" ;
    dcat:landingPage <https://zenodo.org/records/14191859> ;
    dcat:theme <animal_and_grassland> .

<https://opendata.teagasc.ie/organization/b16b4c0b-15bd-4654-b227-792210c7076b> a foaf:Organization ;
    foaf:name "Animal and Bioscience Research" .