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Trend analysis and prediction of seasonal changes in milk composition from a pasture-based dairy research herd
Affiliation:1. Teagasc Food Research Centre, Moorepark, Fermoy, Co. Cork, Ireland, P61C996;2. School of Biosystems and Food Engineering, University College Dublin, Ireland, D04V1W8;3. School of Computer Science, University College Dublin, Ireland, D04V1W8;4. Teagasc Animal and Grassland Centre, Moorepark, Fermoy, Co. Cork, Ireland, P61C996
Abstract:The composition of seasonal pasture-produced milk is influenced by stage of lactation, animal genetics, and nutrition, which affects milk nutritional profile and processing characteristics. The objective was to study the effect of lactation stage (early, mid, and late lactation) and diet on milk composition in an Irish spring calving dairy research herd from 2012 to 2020 using principal component and predictive analytics. Crude protein, casein, fat, and solids increased from 2012 to 2020, whereas lactose concentration peaked in 2017, then decreased. Based on seasonal data from 2013 to 2016, forecasting models were successfully created to predict milk composition for 2017 to 2020. The diet of cows in this study is dependent upon grass growth rates across the milk production season, which in turn, are influenced by weather patterns, whereby extreme weather conditions (rainfall and temperature) were correlated with decreasing grass growth and increasing nonprotein nitrogen levels in milk. The study demonstrates a significant change in milk composition since 2012 and highlights the effect that seasonal changes such as weather and grass growth have on milk composition of pasture-based systems. The potential to forecast milk composition at different stages of lactation benefits processers by facilitating the optimization of in-process and supply logistics of dairy products.
Keywords:seasonality  milk trends  milk composition  lactation  forecasting
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