Dynamic algorithmic conversion of compressed sward height to dry matter yield by a rising plate meter

McSweeney, Diarmuid and Delaby, Luc and O'Brien, Bernadette and Ferard, Alexis and Byrne, Nicky and McDonagh, Justin and Ivanov, Stepan and Coughlan, Neil E. (2022) Dynamic algorithmic conversion of compressed sward height to dry matter yield by a rising plate meter. Computers and Electronics in Agriculture, 196. ISSN 0168-1699

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Abstract

The strategic allocation of pasture grazing area to dairy cows is essential for optimal management and increased outputs. Rising plate meters are frequently used to estimate pasture herbage mass, i.e. dry matter yield per hectare, by employing simple regression equations that relate compressed sward height to herbage mass. However, to improve the accuracy and precision of these equations, so that inherent variation of grasslands is captured, there is a need to incorporate differences in grass types and seasonal growth. Using a total of 308 grass plots, the variation of growth for both perennial ryegrass and hybrid ryegrass was recorded over the seven-month growing season, i.e. March–September. From these data three dynamic equations were derived. The models showed reduced levels of error in comparison to most other conventional equations. As such, the derived models represent a considerable advance for predictive assessment of herbage mass and will support more efficient grassland utilisation by farmers. Although all equations were found to be highly accurate and precise, only a single equation was considered the most effective (R2 = 0.7; RMSE = 248.05), allowing herbage mass to be predicted reliably from compressed sward height data in relation to ryegrass type and calendar month. Although further research will be required, the results presented allow farm operators to calculate herbage mass, as well as support the development of decision support tools to improve on-farm grassland management, particularly at the local paddock rather than national level.

Item Type:	Article
Additional Information:	Funding Information: The authors acknowledge support from FP7 Era-net of ICT GRAZINGTOOLS. In addition, we thank all staff at Teagasc Moorepark, Fermoy, particularly Caroline O′Sullivan. We also graciously thank two anonymous reviewers for helpful comments. Publisher Copyright: © 2022 The Authors
Uncontrolled Keywords:	/dk/atira/pure/subjectarea/asjc/1100/1107
Departments or Groups:
Depositing User:	Admin SSL
Date Deposited:	19 Oct 2022 23:13
Last Modified:	11 Aug 2023 08:00
URI:	http://repository-testing.wit.ie/id/eprint/4686

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