Short communication: Mid-infrared spectroscopy prediction of fine milk composition and technological properties in Italian Simmental

Bonfatti, V.; Degano, L.; Menegoz, A.; Carnier, Paolo

doi:10.3168/jds.2016-10953

Cited by 37 publications

(48 citation statements)

References 21 publications

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“…Values of RMSEP and R 2 in cross-validation calculated for SFA, SCFA, and C18:0 calibration models are reported in Table 2, and are in agreement with those obtained in previous studies (Soyeurt et al, 2006;Bonfatti et al, 2016).…”

Section: Validation Of the Standardization Proceduressupporting

confidence: 89%

Standardization of milk infrared spectra for the retroactive application of calibration models

Bonfatti

Fleming

Koeck

et al. 2017

Journal of Dairy Science

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The objective of this study was to standardize the infrared spectra obtained over time and across 2 milk laboratories of Canada to create a uniform historical database and allow (1) the retroactive application of calibration models for prediction of fine milk composition; and (2) the direct use of spectral information for the development of indicators of animal health and efficiency. Spectral variation across laboratories and over time was inspected by principal components analysis (PCA). Shifts in the PCA scores were detected over time, leading to the definition of different subsets of spectra having homogeneous infrared signal. To evaluate the possibility of using common equations on spectra collected by the 2 instruments and over time, we developed a standardization (STD) method. For each subset of data having homogeneous infrared signal, a total of 99 spectra corresponding to the percentiles of the distribution of the absorbance at each wavenumber were created and used to build the STD matrices. Equations predicting contents of saturated fatty acids, short-chain fatty acids, and C18:0 were created and applied on different subsets of spectra, before and after STD. After STD, bias and root mean squared error of prediction decreased by 66% and 32%, respectively. When calibration equations were applied to the historical nonstandardized database of spectra, shifts in the predictions could be observed over time for all investigated traits. Shifts in the distribution of the predictions over time corresponded to the shifts identified by the inspection of the PCA scores. After STD, shifts in the predicted fatty acid contents were greatly reduced. Standardization reduced spectral variability between instruments and over time, allowing the merging of milk spectra data from different instruments into a common database, the retroactive use of calibrations equations, or the direct use of the spectral data without restrictions.

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Section: Validation Of the Standardization Proceduressupporting

confidence: 89%

Standardization of milk infrared spectra for the retroactive application of calibration models

Bonfatti

Fleming

Koeck

et al. 2017

Journal of Dairy Science

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“…The DP method has some benefits over the IP method: there is no need to predict phenotypes from the spectra to estimate the EBV for the traits, and EBV are predicted once (only for the spectra) and then used to derive the EBV of traits. This is particularly relevant when considering the high number of traits for which FTIR calibration equation are being developed (Bonfatti et al, 2016;Gengler et al, 2016). In addition, direct analysis of the spectral variables may increase the precision of the estimated genetic parameters and the accuracy of EBV predictions and genetic gains, particularly for low-heritability traits, as a consequence of exploiting the genetic relationships among many spectral variables (Dagnachew et al, 2013b).…”

Section: Comparison Between Direct and Indirect Methods For Exploitingmentioning

confidence: 99%

“…Calibration equations used in this study were the outcome of a research project (MilCo project, CPDA122982; University of Padova, Padova, Italy), which started in 2013 with the aim of developing proce-dures to estimate EBV for the Italian Simmental cattle population for FTIR predictions of detailed protein and FA composition, minerals, lactoferrin, coagulation properties, cheese yield, and curd composition. Reference data for the development of calibration equations were obtained for milk protein composition by reversed phase HPLC (Bonfatti et al, 2008), for FA composition by accelerated extraction (Dionex application note 345; Thermo Scientific Dionex, 2016) followed by 2-dimensional gas chromatography separation (Pellattiero et al, 2015), for minerals by inductively coupled plasma atomic emission spectroscopy (Soyeurt et al, 2009), for lactoferrin by ELISA (Soyeurt et al, 2007), for milk coagulation properties by lactodynamography (Bonfatti et al, 2016), and for cheese yield and curd composition by micro-cheese making (Bonfatti et al, 2016). In total, 92 traits were measured and calibration equations were developed using more than 1,000 samples for each of the investigated traits, with the exception of minerals (n = 689) and lactoferrin (n = 558).…”

Section: Ftir Spectra and Calibration Modelsmentioning

confidence: 99%

“…In total, 92 traits were measured and calibration equations were developed using more than 1,000 samples for each of the investigated traits, with the exception of minerals (n = 689) and lactoferrin (n = 558). Details on procedures providing reference data for the traits investigated in this study can be found in Bonfatti et al (2016).…”

Section: Ftir Spectra and Calibration Modelsmentioning

confidence: 99%

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Comparison between direct and indirect methods for exploiting Fourier transform spectral information in estimation of breeding values for fine composition and technological properties of milk

Bonfatti

Vicario²,

Degano³

et al. 2017

Journal of Dairy Science

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The aim of this study was to compare the common method of exploiting infrared spectral data in animal breeding; that is, estimating the breeding values for the traits predicted by infrared spectroscopy, and an alternative approach based on the direct use of spectral information (direct prediction, DP) to predict the estimated breeding values (EBV). Traits were pH, milk coagulation properties, contents of the main casein and whey protein fractions, cheese yield measured by micro-cheese making, lactoferrin, Ca, and fat composition. For the DP method, the number of spectral variables was reduced by principal components analysis to 8 latent traits that explained 99% of the original spectral variation. Restricted maximum likelihood was used to estimate variance components of the latent traits. (Co)variance components of the original spectral traits were obtained by back-transformation and EBV of all derived milk traits were then predicted as traits correlated with the genetic information of the spectra. The rank correlation between the EBV obtained for the infrared-predicted traits and those obtained from the DP method was variable across traits. Rank correlations ranged from 0.07 (for the content of saturated fatty acids expressed as g/100 g of fat) to 0.96 (for dry matter cheese yield, %) and, for most traits, was <0.5. This result can be explained by the nature of the principal components analysis: it does not take into account the covariance between the spectral variables and the reference traits but produces latent traits that maximize the spectral variance explained. Thus, the direct approach is more likely to be effective for traits more related to the main sources of spectral variation (i.e., protein and fat). More research is required to study spectral genetic variation and to determine the best way to choose spectral regions and the type and number of considered latent traits for potential applications.

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“…Oleic acid (18:1n-9, 35.70%) which belongs to VLCFAs is the most abundant fatty acid in beef, followed by palmitic acid (16:0, 31.07%) [4]. With the help of mid-infrared predictions tools, milk was detected to possess more palmitic acid (33.44%) than oleic acid (17.31%) [5]. Lately researches showed that diets high in oleic acid improved the health condition for individuals through the effect on reducing central obesity and cardiovascular disease risk [6, 7].…”

Section: Introductionmentioning

confidence: 99%

Tissue expression profiles and transcriptional regulation of elongase of very long chain fatty acid 6 in bovine mammary epithelial cells

Chen

Liu

2017

PLoS ONE

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In mammals, very long chain fatty acids (VLCFAs) perform pleiotropic roles in a wide range of biological processes, such as cell membrane formation, cell signal transduction, and endocrine regulation. Beef and milk are abundant of palmitic acid which can be further elongated into stearic acid for synthesizing VLCFAs. Elongase of very long chain fatty acid 6 (ELOVL6) is a rate-limiting enzyme for converting palmitic acid to stearic acid. Consequently, investigating the tissue expression patterns and transcriptional regulation of bovine ELOVL6 can provide new insights into improving the composition of beneficial fats in cattle and expanding the knowledge of transcriptional regulation mechanism among domestic animals. In the current study, we found that bovine ELOVL6 expressed ubiquitously. Dual-luciferase reporter assay identified that the core promoter region (-130/-41 bp) was located in the second CpG island. In addition, the deletion mutation of binding sites demonstrated that sterol regulatory element binding transcription factor 1 (SREBF1) and specific protein 1 (SP1) both were able to stimulate bovine ELOVL6 promoter activity independently, while resulting the similar effect. To confirm these findings, further RNA interference assays were executed in bovine mammary epithelial cells (BMECs). In summary, these data suggest that bovine ELOVL6 expressed ubiquitously and is activated by SREBF1 and SP1, via two binding sites present in the ELOVL6 promoter region between -130 bp to -41bp.

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Short communication: Mid-infrared spectroscopy prediction of fine milk composition and technological properties in Italian Simmental

Cited by 37 publications

References 21 publications

Standardization of milk infrared spectra for the retroactive application of calibration models

Standardization of milk infrared spectra for the retroactive application of calibration models

Comparison between direct and indirect methods for exploiting Fourier transform spectral information in estimation of breeding values for fine composition and technological properties of milk

Tissue expression profiles and transcriptional regulation of elongase of very long chain fatty acid 6 in bovine mammary epithelial cells

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