title: Applying Least Absolute Shrinkage Selection Operator and Akaike Information Criterion Analysis to Find the Best Multiple Linear Regression Models between Climate Indices and Components of Cow's Milk.
abstract: This study focuses on multiple linear regression models relating six climate indices (temperature humidity THI, environmental stress ESI, equivalent temperature index ETI, heat load HLI, modified HLI (HLInew), and respiratory rate predictor RRP) with three main components of cow's milk (yield, fat, and protein) for cows in Iran. The least absolute shrinkage selection operator (LASSO) and the Akaike information criterion (AIC) techniques are applied to select the best model for milk predictands with the smallest number of climate predictors. Uncertainty estimation is employed by applying bootstrapping through resampling. Cross validation is used to avoid over-fitting. Climatic parameters are calculated from the NASA-MERRA global atmospheric reanalysis. Milk data for the months from April to September, 2002 to 2010 are used. The best linear regression models are found in spring between milk yield as the predictand and THI, ESI, ETI, HLI, and RRP as predictors withp-value < 0.001 andR² (0.50, 0.49) respectively. In summer, milk yield with independent variables of THI, ETI, and ESI show the highest relation (p-value < 0.001) withR² (0.69). For fat and protein the results are only marginal. This method is suggested for the impact studies of climate variability/change on agriculture and food science fields when short-time series or data with large uncertainty are available.
authors.affiliation: Department of Organic Food Quality and Food Culture, University of Kassel, Nordbahnhofstr. 1a, 37213 Witzenhausen, Germany. marami@uni-kassel.de.
authors.forename: Mohammad Reza
authors.initials: MR
authors.lastname: Marami Milani
authors.affiliation: Meteorological Institute, University of Bonn, Auf dem Hügel 20, 53121 Bonn, Germany. ahense@uni-bonn.de.
authors.forename: Andreas
authors.initials: A
authors.lastname: Hense
authors.affiliation: Meteorological Institute, University of Bonn, Auf dem Hügel 20, 53121 Bonn, Germany. erahmani@uni-bonn.de.
authors.forename: Elham
authors.initials: E
authors.lastname: Rahmani
authors.affiliation: Department of Organic Food Quality and Food Culture, University of Kassel, Nordbahnhofstr. 1a, 37213 Witzenhausen, Germany. a.ploeger@uni-kassel.de.
authors.forename: Angelika
authors.initials: A
authors.lastname: Ploeger
keywords: AIC; ESI; ETI; HLI; LASSO; RRP; THI; climate indices; linear regression model; milk components