Effectiveness of two different at-line instruments for the assessment of cheese composition, major minerals and fatty acids content

Franzoi, Marco; Ghetti, Matteo; Lorenzi, Claudia De; Marchi, Massimo De

doi:10.1016/j.idairyj.2021.105184

Cited by 4 publications

(1 citation statement)

References 44 publications

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“…Similar to the local methods, cluster methods also use subgroups of samples in the dataset to develop multiple prediction equations [ 18 , 19 , 20 ]. However, in the local approach, different neighbours are identified for each predictand, whereas cluster methods identify a fixed number of groups (or clusters) in the dataset, where each cluster is characterised by similar samples.…”

Section: Introductionmentioning

confidence: 99%

Selecting Milk Spectra to Develop Equations to Predict Milk Technological Traits

Frizzarin

Gormley

Casa

et al. 2021

Foods

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Including all available data when developing equations to relate midinfrared spectra to a phenotype may be suboptimal for poorly represented spectra. Here, an alternative local changepoint approach was developed to predict six milk technological traits from midinfrared spectra. Neighbours were objectively identified for each predictand as those most similar to the predictand using the Mahalanobis distances between the spectral principal components, and subsequently used in partial least square regression (PLSR) analyses. The performance of the local changepoint approach was compared to that of PLSR using all spectra (global PLSR) and another LOCAL approach, whereby a fixed number of neighbours was used in the prediction according to the correlation between the predictand and the available spectra. Global PLSR had the lowest RMSEV for five traits. The local changepoint approach had the lowest RMSEV for one trait; however, it outperformed the LOCAL approach for four traits. When the 5% of the spectra with the greatest Mahalanobis distance from the centre of the global principal component space were analysed, the local changepoint approach outperformed the global PLSR and the LOCAL approach in two and five traits, respectively. The objective selection of neighbours improved the prediction performance compared to utilising a fixed number of neighbours; however, it generally did not outperform the global PLSR.

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Section: Introductionmentioning

confidence: 99%

Selecting Milk Spectra to Develop Equations to Predict Milk Technological Traits

Frizzarin

Gormley

Casa

et al. 2021

Foods

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Feasibility of pocket-sized near-infrared spectrometer for the prediction of cheese quality traits

Manuelian

Ghetti

Lorenzi

et al. 2022

Journal of Food Composition and Analysis

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Change of Spectral Photoluminescent Properties of Milk during Souring

Belyakov

Samarin

Kudryavtsev

et al. 2022

Engineering Technologies and Systems

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Introduction. The use of digital technologies will increase the efficiency of animal husbandry. These technologies include optical monitoring of product quality. The aim of the research is to study the dependence of the spectral characteristics and parameters of excitation and luminescence of milk during souring. Materials and Methods. The milk with a fat content of 3.2% was used for measurements. The acidity was controlled by the titrimetric method. The excitation and luminescence registration spectra were measured on a Fluorat-02-Panorama spectrofluorimeter in the range of 200–500 nm. Spectra parameters were calculated in the PanoramaPro and Microcal Origin programs. Results. When milk sours, excitation spectra shift downwards, while a qualitative change in characteristics is observed with the range of 350–500 nm, although the photoelectric signal absolute level is almost an order of magnitude less than with a range of 220?340 nm. The photoluminescence flux when excited by the radiation with wavelength of 262 nm decreases during the souring process. The flux excited by the radiation with wavelength of 385 nm increases especially in the first three days. The flux at wavelength of 442 nm decreases slightly. Statistical parameters and energy of photoluminescence spectra are not informative for the milk souring control. The dependence of the ratio of photoluminescence fluxes excited by the radiation of 385 and 442 nm on acidity is linearly approximated with a determination coefficient of 0.99. Discussion and Conclusion. The change in the milk luminescent properties can be used as a marker of its souring with acidity control. To create a method for monitoring milk quality indicators during souring, the most informative is the use of excitation wavelengths of 385 and 442 nm with subsequent registration of photoluminescence in the ranges 440–490 and 490–600 nm respectively.

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Effectiveness of two different at-line instruments for the assessment of cheese composition, major minerals and fatty acids content

Cited by 4 publications

References 44 publications

Selecting Milk Spectra to Develop Equations to Predict Milk Technological Traits

Selecting Milk Spectra to Develop Equations to Predict Milk Technological Traits

Feasibility of pocket-sized near-infrared spectrometer for the prediction of cheese quality traits

Change of Spectral Photoluminescent Properties of Milk during Souring

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