Standardization of milk mid-infrared spectra from a European dairy network

Grelet, Clément; Pierna, Juan Antonio Fernández; Dardenne, Pierre; Baeten, Vincent; Dehareng, Frédéric

doi:10.3168/jds.2014-8764

Cited by 117 publications

(122 citation statements)

References 17 publications

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“…A previous study (Grelet et al, 2015) demonstrated that until now it was possible to transfer only high-quality models (fat). The results confirm the first conclusions obtained with the fat model: without the use of a standardization step, the transfer of models leads to considerable errors in the predictions, reducing the value of information from FT-MIR milk spectra for Figure 4.…”

Section: Discussionmentioning

confidence: 99%

“…Plots representing the link between the quality of the model (coefficient of determination of cross-validation; R 2 cv) and the performance of the transfer by piecewise direct standardization [relative root mean squared error (RMSE) between slaves and master predictions after standardization] from the 5 interlaboratory study samples analyzed on 66 instruments. CH 4 = methane emitted by dairy cows; PUFA = PUFA in milk; FCY = fresh cheese yield; Fat = fat model used in Grelet et al (2015). reproducibility of wave number areas selected within the models.…”

Section: Discussionmentioning

confidence: 99%

“…A set of standardization samples were measured on a reference instrument (the "master" instrument) and on each instrument that needs to be aligned (the "slave" instruments), leading to different response matrices. As reported by Grelet et al (2015) and Wang et al (2016), individual FT-MIR spectrometers suffer from instability over time. To cope with this instability, the master cannot be a single instrument.…”

Section: Standardizationmentioning

confidence: 99%

“…The standardization procedure, based on the PDS method, is described in Grelet et al (2015). A set of standardization samples were measured on a reference instrument (the "master" instrument) and on each instrument that needs to be aligned (the "slave" instruments), leading to different response matrices.…”

Section: Standardizationmentioning

confidence: 99%

“…Over the years the network size has increased, and as many as 127 instruments of 3 different brands coming from 14 countries on 4 continents (North America, Asia, Europe, and Oceania) have been standardized. Recently, it has been shown that using the piecewise direct standardization (PDS) method it is possible to transfer a high-quality fat model from one instrument to more than 20 different instruments in the network (Grelet et al, 2015). However, there is no information about the possibility of transferring models with lower accuracy or predicting fine milk composition or indirect variables, which are not milk components and consequently are predicted indirectly, despite the fact that these models are of great interest to the dairy sector.…”

Section: Introductionmentioning

confidence: 99%

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Standardization of milk mid-infrared spectrometers for the transfer and use of multiple models

Grelet

Pierna

Dardenne

et al. 2017

Journal of Dairy Science

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An increasing number of models are being developed to provide information from milk Fourier transform mid-infrared (FT-MIR) spectra on fine milk composition, technological properties of milk, or even cows' physiological status. In this context, and to take advantage of these existing models, the purpose of this work was to evaluate whether a spectral standardization method can enable the use of multiple equations within a network of different FT-MIR spectrometers. The piecewise direct standardization method was used, matching "slave" instruments to a common reference, the "master." The effect of standardization on network reproducibility was assessed on 66 instruments from 3 different brands by comparing the spectral variability of the slaves and the master with and without standardization. With standardization, the global Mahalanobis distance from the slave spectra to the master spectra was reduced on average from 2,655.9 to 14.3, representing a significant reduction of noninformative spectral variability. The transfer of models from instrument to instrument was tested using 3 FT-MIR models predicting (1) the quantity of daily methane emitted by dairy cows, (2) the concentration of polyunsaturated fatty acids in milk, and (3) the fresh cheese yield. The differences, in terms of root mean squared error, between master predictions and slave predictions were reduced after standardization on average from 103 to 17 g/d, from 0.0315 to 0.0045 g/100 mL of milk, and from 2.55 to 0.49 g of curd/100 g of milk, respectively. For all the models, standard deviations of predictions among all the instruments were also reduced by 5.11 times for methane, 5.01 times for polyunsaturated fatty acids, and 7.05 times for fresh cheese yield, showing an improvement of prediction reproducibility within the network. Regarding the results obtained, spectral standardization allows the transfer and use of multiple models on all instruments as well as the improvement of spectral and prediction reproducibility within the network. The method makes the models universal, thereby offering opportunities for data exchange and the creation and use of common robust models at an international level to provide more information to the dairy sector from direct analysis of milk.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Standardizationmentioning

confidence: 99%

Section: Standardizationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Standardization of milk mid-infrared spectrometers for the transfer and use of multiple models

Grelet

Pierna

Dardenne

et al. 2017

Journal of Dairy Science

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Data augmentation in food science: Synthesising spectroscopic data of vegetable oils for performance enhancement

Georgouli

Osório

Rincón

et al. 2018

Journal of Chemometrics

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Generating more accurate, efficient, and robust classification models in chemometrics, able to address real‐world problems in food analysis, is intrinsically related with the amount of available calibration samples. In this paper, we propose a data augmentation solution to increase the performance of a classification model by generating realistic data augmented samples. The feasibility of this solution has been evaluated on 3 main different experiments where Fourier transform mid infrared (FT‐IR) spectroscopic data of vegetable oils were used for the identification of vegetable oil species in oil admixtures. Results demonstrate that data augmented samples improved the classification rate by around 19% in a single instrument validation and provided a significant 38% improvement in classification when testing in more than 10 different spectroscopic instruments to the calibration one.

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Perspective of vibrational spectroscopy analytical methods in on‐field/official control of olives and virgin olive oil

Nenadis

Tsimidou

2016

Euro J Lipid Sci & Tech

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Vibrational spectroscopic techniques, infrared (near, mid, far) and Raman that are based on the continuous vibrational motion of the atoms in the corresponding bonds of the compounds correlate in a unique way the physical properties of materials in the gaseous, solid, or liquid state with the molecular structure. Olive industry and olive oil official control may benefit from the introduction of these powerful techniques to address quality and authenticity issues. This review focuses on evidence obtained from comparative studies among different vibrational techniques for the same set/s of samples or from the same instrumentation. It also assists the forum of discussion on what is needed for their standardization in order to find their place in the official control of the end product. The need for validation guidelines regarding the management of the instrument as well as the construction of the calibration model is highlighted. The latter depends heavily on the reference method employed. An extended list of references covering the characteristics of the techniques, advancements in instrumentation, general applications to oils and fats, and those useful for on‐field and official control of olive and olive oil is also given. Practical application: Vibrational spectroscopic techniques coupled to chemometrics can modernize olive and olive oil analysis from the field to the official control at the borders and in the market. As it occurs already for many decades in the field of other high added value commodities, i.e., milk, meat, wine, the value of the multiple type of information acquired with little sample manipulation should be recognized by all interested parties in the olive sector (stakeholders, authorities, researchers). Qualitative and quantitative information from field to the table (quality, adulteration, authentication).

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Standardization of milk mid-infrared spectra from a European dairy network

Cited by 117 publications

References 17 publications

Standardization of milk mid-infrared spectrometers for the transfer and use of multiple models

Standardization of milk mid-infrared spectrometers for the transfer and use of multiple models

Data augmentation in food science: Synthesising spectroscopic data of vegetable oils for performance enhancement

Perspective of vibrational spectroscopy analytical methods in on‐field/official control of olives and virgin olive oil

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