Murphy, Darren J. and O'Brien, Bernadette and Askaril, Mohammad Sadegh and McCarthy, Tim and Magee, Aidan and Burke, Rebekah and Murphy, Michael D.
(2019)
GrassQ - A holistic precision grass measurement and analysis system to optimize pasture based livestock production.
In:
2019 ASABE Annual International Meeting, Boston, Massachusetts July 7–10, 2019.
ASABE.
Abstract
GrassQ is a holistic grassland decision support system (DSS) that encapsulates a range of measurement
technologies to provide yield and quality data to a cloud based platform, which can provide users with real time management
information in the field. GrassQ aims to promote precision agricultural concepts within the pasture based livestock industry.
Accurate measurement and allocation of fresh pasture to grazing herds on a daily basis is essential in increasing efficiency.
Novel systems of measuring grass yield and quality were developed at the Moorepark Animal and Grassland Research
Centre in Cork, Ireland, over the grass growing seasons of 2017 and 2018. Measurement systems included ground based
and remote sensing techniques. The prototype GrassQ DSS was designed to process datasets uploaded from all proposed
measurement systems. Measurement parameters were compressed sward height (CSH) (mm), herbage mass (HM)
(kgDM/ha), dry matter (DM) (g/kg) and crude protein (CP) (g/kg). Ground based measurements were recorded using a
smart rising plate meter (RPM) and lab based near infrared spectroscopy (NIRS). Multispectral remote sensing was carried
out using an unmanned aerial vehicle (UAV), and data from the European Union’s Sentinel-2 satellite (S2). Reference
analyses for all prediction models were carried out at Moorpark’s Grassland Laboratory and all sample locations were geotagged to enable spatial mapping of all parameters. The GrassQ prototype DSS is currently operational, including a number
of preliminary grass quantity and quality prediction models. The complete Grass DSS will be is launched upon final
validation.
| Item Type: |
Book Section
|
| Keywords: |
Decision Support System; Grassland Management; Precision Grazing; Rising Plate Meter; Remote Sensing; Near
Infrared Spectroscopy; |
| Academic Unit: |
Faculty of Science and Engineering > Computer Science |
| Item ID: |
12793 |
| Identification Number: |
https://doi.org/10.13031/aim.201900769 |
| Depositing User: |
Tim McCarthy
|
| Date Deposited: |
14 Apr 2020 15:05 |
| Publisher: |
ASABE |
| Refereed: |
No |
| URI: |
|
| Use Licence: |
This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available
here |
Repository Staff Only(login required)
 |
Item control page |
Downloads per month over past year
Origin of downloads
Altmetric
Altmetric