This study aimed to evaluate the feasibility of mid-infrared (MIR; 5000–900 cm−1) and visible/near-infrared (Vis/NIR; 400–2500 nm) spectroscopy to discriminate organic (ORG) from conventional (CONV) bulk milk. Samples (n = 225) from 24 farms (ORG, n = 12; CONV, n = 12) located in the same area, mainly rearing Holstein-Friesian cows, under similar management conditions, except for ORG livestock spending a period of time on pasture, were collected from September 2019 to August 2020. Chemical composition of the lactation ration was similar between groups. Mid-infrared and Vis/NIR spectrum of each sample were collected. Principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) were done using R software. For the PLS-DA, records were divided in a train set (8 farms/group) and a test set (4 farms/group), and only wavelengths with VIP >1 were retained. The PCA was not able to discriminate both groups. The PLS-DA revealed an accuracy of the model in the test set of 54.1% and 62.9%, for MIR and Vis/NIR, respectively. In conclusion, both infrared regions performed similarly, and the moderate accuracy of the PLS-DA could be related to the similarity of the selected farms between both categories.

MIR and Vis/NIR spectroscopy cannot authenticate organic bulk milk

Burbi, Sara;
2021-01-01

Abstract

This study aimed to evaluate the feasibility of mid-infrared (MIR; 5000–900 cm−1) and visible/near-infrared (Vis/NIR; 400–2500 nm) spectroscopy to discriminate organic (ORG) from conventional (CONV) bulk milk. Samples (n = 225) from 24 farms (ORG, n = 12; CONV, n = 12) located in the same area, mainly rearing Holstein-Friesian cows, under similar management conditions, except for ORG livestock spending a period of time on pasture, were collected from September 2019 to August 2020. Chemical composition of the lactation ration was similar between groups. Mid-infrared and Vis/NIR spectrum of each sample were collected. Principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) were done using R software. For the PLS-DA, records were divided in a train set (8 farms/group) and a test set (4 farms/group), and only wavelengths with VIP >1 were retained. The PCA was not able to discriminate both groups. The PLS-DA revealed an accuracy of the model in the test set of 54.1% and 62.9%, for MIR and Vis/NIR, respectively. In conclusion, both infrared regions performed similarly, and the moderate accuracy of the PLS-DA could be related to the similarity of the selected farms between both categories.
2021
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11382/559814
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