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dc.contributor.authorHanrahan, Liam
dc.contributor.authorGeoghegan, Anne
dc.contributor.authorO'Donovan, Michael
dc.contributor.authorGriffith, Vincent
dc.contributor.authorRuelle, Elodie
dc.contributor.authorWallace, Michael
dc.contributor.authorShalloo, Laurence
dc.date.accessioned2020-06-17T15:48:42Z
dc.date.available2020-06-17T15:48:42Z
dc.date.issued2017-03-22
dc.identifier.citationHanrahan, L., Geoghegan, A., O'Donovan, M., Griffith, V., Ruelle, E., Wallace, M. and Shalloo, L. PastureBase Ireland: A grassland decision support system and national database. Computers and Electronics in Agriculture, 2017, 136, 193-201. doi: https://dx.doi.org/10.1016/j.compag.2017.01.029en_US
dc.identifier.urihttp://hdl.handle.net/11019/2012
dc.descriptionpeer-revieweden_US
dc.description.abstractPastureBase Ireland (PBI) is a web-based grassland management application incorporating a dual function of grassland decision support and a centralized national database to collate commercial farm grassland data. This database facilitates the collection and storage of vast quantities of grassland data from grassland farmers. The database spans across ruminant grassland enterprises – dairy, beef and sheep. To help farmers determine appropriate actions around grassland management, we have developed this data informed decision support tool to function at the paddock level. Individual farmers enter data through the completion of regular pasture cover estimations across the farm, allowing the performance of individual paddocks to be evaluated within and across years. To evaluate the PBI system, we compared actual pasture cut experimental data (Etesia cuts) to PBI calculated outputs. We examined three comparisons, comparing PBI outputs to actual pasture cut data, for individual DM yields at defoliation (Comparison 1), for cumulative annual DM yields including silage data (Comparison 2) and, for cumulative annual DM yields excluding silage data (Comparison 3). We found an acceptable accuracy between PBI outputs and pasture cut data when statistically analyzed using relative prediction error and concordance correlation coefficients for the measurement of total annual DM yield (Comparison 2), with a relative prediction error of 15.4% and a concordance correlation coefficient of 0.85. We demonstrated an application of the PBI system through analysis of commercial farm data across two years (2014–2015) for 75 commercial farms who actively use the system. The analysis showed there was a significant increase in DM yield from 2014 to 2015. The results indicated a greater variation in pasture growth across paddocks within farms than across farms.en_US
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.relation.ispartofseriesComputers and Electronics in Agriculture;Vol. 136
dc.rightsAttribution-NonCommercial-ShareAlike 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/3.0/us/*
dc.subjectPastureBase Irelanden_US
dc.subjectGrassland farmingen_US
dc.subjectDry matter productionen_US
dc.subjectDecision supporten_US
dc.subjectCentralized databaseen_US
dc.titlePastureBase Ireland: A grassland decision support system and national databaseen_US
dc.typeArticleen_US
dc.embargo.terms2018-03-22en_US
dc.identifier.doihttps://dx.doi.org/10.1016/j.compag.2017.01.029
refterms.dateFOA2018-03-22T00:00:00Z


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