TY - JOUR
T1 - Dynamic algorithmic conversion of compressed sward height to dry matter yield by a rising plate meter
AU - McSweeney, Diarmuid
AU - Delaby, Luc
AU - O'Brien, Bernadette
AU - Ferard, Alexis
AU - Byrne, Nicky
AU - McDonagh, Justin
AU - Ivanov, Stepan
AU - Coughlan, Neil E.
N1 - 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
PY - 2022/5/1
Y1 - 2022/5/1
N2 - 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.
AB - 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.
KW - Digital data capture
KW - Dry matter yield
KW - Grass measurement
KW - Grassland management
KW - Herbage mass
KW - Rising plate meter
UR - http://www.scopus.com/inward/record.url?scp=85127255149&partnerID=8YFLogxK
U2 - 10.1016/j.compag.2022.106919
DO - 10.1016/j.compag.2022.106919
M3 - Article
AN - SCOPUS:85127255149
SN - 0168-1699
VL - 196
JO - Computers and Electronics in Agriculture
JF - Computers and Electronics in Agriculture
M1 - 106919
ER -