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Modelling Pasture-based Automatic Milking System Herds: Grazeable Forage Options

Overview of attention for article published in Animal Bioscience, February 2015
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Title
Modelling Pasture-based Automatic Milking System Herds: Grazeable Forage Options
Published in
Animal Bioscience, February 2015
DOI 10.5713/ajas.14.0384
Pubmed ID
Authors

M R Islam, S C Garcia, C E F Clark, K L Kerrisk

Abstract

One of the challenges to increase milk production in a large pasture-based herd with an automatic milking system (AMS) is to grow forages within a 1-km radius, as increases in walking distance increases milking interval and reduces yield. The main objective of this study was to explore sustainable forage option technologies that can supply high amount of grazeable forages for AMS herds using the Agricultural Production Systems Simulator (APSIM) model. Three different basic simulation scenarios (with irrigation) were carried out using forage crops (namely maize, soybean and sorghum) for the spring-summer period. Subsequent crops in the three scenarios were forage rape over-sown with ryegrass. Each individual simulation was run using actual climatic records for the period from 1900 to 2010. Simulated highest forage yields in maize, soybean and sorghum- (each followed by forage rape-ryegrass) based rotations were 28.2, 22.9, and 19.3 t dry matter/ha, respectively. The simulations suggested that the irrigation requirement could increase by up to 18%, 16%, and 17% respectively in those rotations in El-Niño years compared to neutral years. On the other hand, irrigation requirement could increase by up to 25%, 23%, and 32% in maize, soybean and sorghum based rotations in El-Nino years compared to La-Nina years. However, irrigation requirement could decrease by up to 8%, 7%, and 13% in maize, soybean and sorghum based rotations in La-Nina years compared to neutral years. The major implication of this study is that APSIM models have potentials in devising preferred forage options to maximise grazeable forage yield which may create the opportunity to grow more forage in small areas around the AMS which in turn will minimise walking distance and milking interval and thus increase milk production. Our analyses also suggest that simulation analysis may provide decision support during climatic uncertainty.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 18 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 18 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 4 22%
Student > Bachelor 4 22%
Student > Doctoral Student 2 11%
Student > Ph. D. Student 2 11%
Lecturer 1 6%
Other 1 6%
Unknown 4 22%
Readers by discipline Count As %
Agricultural and Biological Sciences 7 39%
Engineering 4 22%
Nursing and Health Professions 1 6%
Economics, Econometrics and Finance 1 6%
Computer Science 1 6%
Other 0 0%
Unknown 4 22%