Diagnosing pregnancy status using infrared spectra and milk composition in dairy cows

被引:42
作者
Toledo-Alvarado, Hugo [1 ]
Vazquez, Ana I. [2 ]
de los Campos, Gustavo [2 ]
Tempelman, Robert J. [3 ]
Bittante, Giovanni [1 ]
Cecchinato, Alessio [1 ]
机构
[1] Univ Padua, Dept Agron Food Nat Resources Anim & Environm DAF, I-35020 Legnaro, PD, Italy
[2] Michigan State Univ, Dept Epidemiol & Biostat, E Lansing, MI 48824 USA
[3] Michigan State Univ, Dept Anim Sci, E Lansing, MI 48824 USA
基金
美国国家卫生研究院; 美国食品与农业研究所;
关键词
Fourier transform infrared spectroscopy; milk; milk component; pregnancy; BROWN SWISS; MIDINFRARED SPECTROSCOPY; HERD PRODUCTIVITY; GENETIC-ANALYSIS; BOVINE-MILK; PREDICTION; FERTILITY; HOLSTEIN; SYSTEMS; REGRESSION;
D O I
10.3168/jds.2017-13647
中图分类号
S8 [畜牧、 动物医学、狩猎、蚕、蜂];
学科分类号
0905 ;
摘要
Data on Holstein (16,890), Brown Swiss (31,441), Simmental (25,845), and Alpine Grey (12,535) cows reared in northeastern Italy were used to assess the ability of milk components (fat, protein, casein, and lactose) and Fourier transform infrared (FTIR) spectral data to diagnose pregnancy. Pregnancy status was defined as whether a pregnancy was confirmed by a subsequent calving and no other subsequent inseminations within 90 d of the breeding of specific interest. Milk samples were analyzed for components and FTIR full-spectrum data using a MilkoScan FT+ 6000 (Foss Electric, Hillerod, Denmark). The spectrum covered 1,060 wavenumbers (wn) from 5,010 to 925 cm(-1). Pregnancy status was predicted using generalized linear models with fat, protein, lactose, casein, and individual FTIR spectral bands or wavelengths as predictors. We also fitted a generalized linear model as a simultaneous function of all wavelengths (1,060 wn) with a Bayesian variable selection model using the BGLR R-package (https://r-forge.r-project.org/projects/bglr/). Prediction accuracy was determined using the area under a receiver operating characteristic curve based on a 10-fold cross-validation (CV-AUC) assessment based on sensitivities and specificities of phenotypic predictions. Overall, the best prediction accuracies were obtained for the model that included the complete FTIR spectral data. We observed similar patterns across breeds with small differences in prediction accuracy. The highest CV-AUC value was obtained for Alpine Grey cows (CV-AUC = 0.645), whereas Brown Swiss and Simmental cows had similar performance (CV-AUC = 0.630 and 0.628, respectively), followed by Holsteins (CV-AUC = 0.607). For single-wavelength analyses, important peaks were detected at wn 2,973 to 2,872 cm(-1) where Fat-B (C-H stretch) is usually filtered, wn 1,773 cm(-1) where Fat-A (C=O stretch) is filtered, wn 1,546 cm(-1) where protein is filtered, wn 1,468 cm(-1) associated with urea and fat, wn 1,399 and 1,245 cm(-1) associated with acetone, and wn 1,025 to 1,013 cm(-1) where lactose is filtered. In conclusion, this research provides new insight into alternative strategies for pregnancy screening of dairy cows.
引用
收藏
页码:2496 / 2505
页数:10
相关论文
共 33 条
[1]   On the role of mid-infrared predicted phenotypes in fertility and health dairy breeding programs [J].
Bastin, C. ;
Theron, L. ;
Laine, A. ;
Gengler, N. .
JOURNAL OF DAIRY SCIENCE, 2016, 99 (05) :4080-4094
[2]   Genetic analysis of the Fourier-transform infrared spectra of bovine milk with emphasis on individual wavelengths related to specific chemical bonds [J].
Bittante, G. ;
Cecchinato, A. .
JOURNAL OF DAIRY SCIENCE, 2013, 96 (09) :5991-6006
[3]   Effect of pregnancy on production traits of Canadian Holstein cows [J].
Bohmanova, J. ;
Jamrozik, J. ;
Miglior, F. .
JOURNAL OF DAIRY SCIENCE, 2009, 92 (06) :2947-2959
[4]   Invited review: Mid-infrared spectroscopy as phenotyping tool for milk traits [J].
De Marchi, M. ;
Toffanin, V. ;
Cassandro, M. ;
Penasa, M. .
JOURNAL OF DAIRY SCIENCE, 2014, 97 (03) :1171-1186
[5]   An introduction to ROC analysis [J].
Fawcett, Tom .
PATTERN RECOGNITION LETTERS, 2006, 27 (08) :861-874
[6]   Bayesian regression models outperform partial least squares methods for predicting milk components and technological properties using infrared spectral data [J].
Ferragina, A. ;
de los Campos, G. ;
Vazquez, A. I. ;
Cecchinato, A. ;
Bittante, G. .
JOURNAL OF DAIRY SCIENCE, 2015, 98 (11) :8133-8151
[7]   Methods for and Implementation of Pregnancy Diagnosis in Dairy Cows [J].
Fricke, Paul M. ;
Ricci, Alessandro ;
Giordano, Julio O. ;
Carvalho, Paulo D. .
VETERINARY CLINICS OF NORTH AMERICA-FOOD ANIMAL PRACTICE, 2016, 32 (01) :165-+
[8]   Screening of dairy cows for ketosis by use of infrared spectroscopy and multivariate calibration [J].
Hansen, PW .
JOURNAL OF DAIRY SCIENCE, 1999, 82 (09) :2005-2010
[9]  
Hansen PW, 1998, MILCHWISSENSCHAFT, V53, P251
[10]  
ICAR (International Committee for Animal Recording), 2016, INT AGR REC PRACT RE