Zobrazeno 1 - 10
of 52
pro vyhledávání: '"Brett Whelan"'
Publikováno v:
Geoderma, Vol 446, Iss , Pp 116899- (2024)
This study investigates the complexity of spatial soil modelling, particularly focusing on the challenge of variable vertical support in traditional soil data collection. Traditional soil sampling, described in terms of horizons, often fails to accur
Externí odkaz:
https://doaj.org/article/f7c33414a37b4ba99a5717c91430eb62
Autor:
Brett Whelan, James Taylor
Precision Agriculture (PA) is an approach to managing the variability in production agriculture in a more economic and environmentally efficient manner. It has been pioneered as a management tool in the grains industry, and while its development and
Publikováno v:
Precision Agriculture. 23:578-601
There is considerable interest and value in identifying the gap between crop yields that have actually been achieved, and yields that could have potentially been achieved. A suite of methods currently exist to estimate the yield potential of a crop,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ca22458c025b4416b528c97d3efb776e
https://doi.org/10.1007/s11119-021-09850-7
https://doi.org/10.1007/s11119-021-09850-7
Autor:
Kanika Singh, Brett Whelan
Publikováno v:
Soil Use and Management. 36:616-632
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::adc583919071ab53c7f904ed9e798702
https://doi.org/10.1111/sum.12590
https://doi.org/10.1111/sum.12590
A high‐resolution, multimodal data set for agricultural robotics: A Ladybird 's‐eye view of Brassica
Publikováno v:
Journal of Field Robotics. 37:73-96
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::36d800474ce45be098d859967c93a4e5
https://doi.org/10.1002/rob.21877
https://doi.org/10.1002/rob.21877
Autor:
L. E. Pozza, Sabastine U. Ugbaje, Niranjan S. Wimalathunge, Brett Whelan, Patrick Filippi, Thomas F. A. Bishop, Stacey Paterson, Thomas G. Jephcott, Edward Jones, Pallegedara D. S. N. Somarathna
Publikováno v:
Precision Agriculture. 20:1015-1029
Many broadacre farmers have a time series of crop yield monitor data for their fields which are often augmented with additional data, such as soil apparent electrical conductivity surveys and soil test results. In addition there are now readily avail
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1771fbcb8e2802c024784ae3781d3674
https://doi.org/10.1007/s11119-018-09628-4
https://doi.org/10.1007/s11119-018-09628-4
Farmer’s management decisions and environmental factors are the main drivers for field spatial and temporal yield variability. In this study, a 22 ha field cultivated with corn for more than ten years using different prescription maps of nitrogen a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::037ee7cee9227edd9bc1c529c01e9e5c
http://hdl.handle.net/11577/3391222
http://hdl.handle.net/11577/3391222
Autor:
Dhahi Al-Shammari, James P. Moloney, Niranjan S. Wimalathunge, Thomas F. A. Bishop, Brett Whelan, Patrick Filippi
Publikováno v:
Burleigh Dodds Series in Agricultural Science ISBN: 9781786763402
Burleigh Dodds Series in Agricultural Science
Burleigh Dodds Series in Agricultural Science
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::76674b28cede3b252f049f8f6ed5a14e
https://doi.org/10.19103/as.2020.0069.13
https://doi.org/10.19103/as.2020.0069.13
Publikováno v:
Precision Agriculture. 20:767-787
Variations in water absorption across lettuce leaves (Latuca sativa L. var. longifolia) were quantified from hyperspectral imagery acquired in the laboratory using selected spectral indices, specifically, the Moisture Stress Index (MSI), the Normalis
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d2f76b8ebc8671136e6e245034d12a72
https://doi.org/10.1007/s11119-018-9610-5
https://doi.org/10.1007/s11119-018-9610-5
Publikováno v:
Computers and Electronics in Agriculture. 151:61-69
Accurate yield estimation and optimised nitrogen management is essential in agriculture. Remote sensing (RS) systems are being more widely used in building decision support tools for contemporary farming systems to improve yield production and nitrog
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ebb10933dc32a637fae880834e00e5ca
https://doi.org/10.1016/j.compag.2018.05.012
https://doi.org/10.1016/j.compag.2018.05.012