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Computers and Electronics in Agriculture
Article . 2022 . Peer-reviewed
License: CC BY
Data sources: Crossref
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T-Stór
Article . 2022 . Peer-reviewed
Data sources: T-Stór
DBLP
Article . 2022
Data sources: DBLP
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Dynamic algorithmic conversion of compressed sward height to dry matter yield by a rising plate meter

Authors: Mc Sweeney, Diarmuid; Delaby, Luc; O'Brien, Bernadette; Ferard, Alexis; Byrne, Nicky; Mc Donagh, Justin; Ivanov, Stepan; +1 Authors

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

Abstract

peer-reviewed 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.

Countries
France, Ireland
Keywords

[SDV.SA]Life Sciences [q-bio]/Agricultural sciences, [SDV.SA] Life Sciences [q-bio]/Agricultural sciences, Grass measurement, Herbage mass, Dry matter yield, 630, Rising plate meter, Grassland management, Digital data capture

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    influence
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
7
Top 10%
Average
Top 10%
Green
hybrid