A New Tool for Interpretation of Thermal Stability of Raw Milk by Means of the Alizarol Test Using a PLS Model on a Mobile Device
- 12 Downloads
This article describes the development of a new tool for interpreting the thermal stability of raw milk by means of the alizarol test, using a multivariate calibration model on a mobile device. The alizarol test is a semiquantitative test that uses an alcoholic solution containing a pH indicator (alizarin). Color judgment and correlation with pH are done visually and may involve several errors and differences between one analyst and another. Therefore, a pH scale (3 to 12) was constructed with raw milk for the alizarol test using a mobile device for image acquisition for each pH point (in triplicate). For quantitative pH determination, a new version of the PhotoMetrix® app was developed (named PhotoMetrix Pro®), including partial least square (PLS) regression tools, choosing RGB histograms and mean center preprocessing. The alizarol stability test was performed using 2 mL of sample and 2 mL of alizarol. To verify the performance of the PLS model, seven samples from different milk producers were analyzed. The results indicate that the root mean square error of calibration (RMSEC) was 0.25, and the root mean square error of prediction (RMSEP) was 0.30, very satisfactory. The results obtained by the proposed method were compared to those obtained using the potentiometric method (reference method); agreement between 95.0 and 100.9% was obtained, without statistical difference (p > 0.05). This application using PhotoMetrix Pro® could be an alternative for fast and reliable interpretation of the alizarol test.
KeywordsRaw milk Smartphone Digital image analysis pH Alizarol test
The authors would like to thank Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), Fundação de Amparo à Pesquisa do Estado do Rio Grande do Sul (FAPERGS), and Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES).
Compliance with Ethical Standards
Conflict of Interest
Gilson Augusto Helfer declares that he has no conflict of interest. Bruna Tischer declares that she has no conflict of interest. Paula Freitas Filoda declares that she has no conflict of interest. Alessandra Betina Parckert declares that she has no conflict of interest. Ronaldo Bastos dos Santos declares that he has no conflict of interest. Layane Lenardon Vinciguerra declares that she has no conflict of interest. Marco Flôres Ferrão declares that he has no conflict of interest. Juliano Smanioto Barin declares that he has no conflict of interest. Adilson Ben da Costa declares that he has no conflict of interest.
This article does not contain any studies with human participants or animals performed by any of the authors.
- Brasil (2011) Instrução Normativa n° 62, de 29 de dezembro de 2011. Diário Oficial da República Federativa do Brasil, Brasília, 30 dez. 2011Google Scholar
- Chavan RS, Sehrawat R, Mishra V, Bhatt S (2016) Milk: processing of milk. In: Encyclopedia of Food and Health Academic Press, Oxford, pp 729–735. https://doi.org/10.1016/B978-0-12-384947-2.00464-5
- Claeys WL, Cardoen S, Daube G, de Block J, Dewettinck K, Dierick K, de Zutter L, Huyghebaert A, Imberechts H, Thiange P, Vandenplas Y, Herman L (2013) Raw or heated cow milk consumption: review of risks and benefits. Food Control 31:251–262. https://doi.org/10.1016/j.foodcont.2012.09.035 CrossRefGoogle Scholar
- Claeys WL, Verraes C, Cardoen S, de Block J, Huyghebaert A, Raes K, Dewettinck K, Herman L (2014) Consumption of raw or heated milk from different species: an evaluation of the nutritional and potential health benefits. Food Control 42:188–201. https://doi.org/10.1016/j.foodcont.2014.01.045 CrossRefGoogle Scholar
- FAO (1996) Milk testing and quality control, Training Programme for Small Scale Dairy Sector and Dairy Training Institute - Naivasha vol 2. http://www.fao.org/ag/againfo/resources/documents/MPGuide/mpguide2.htm
- Helfer GA (2015) PhotoMetrix.http://www.photometrix.com.br/
- Helfer GA, Magnus VS, Böck FC, Teichmann A, Ferrão MF, Costa ABD (2017) PhotoMetrix: an application for univariate calibration and principal components analysis using colorimetry on mobile devices. J Braz Chem Soc 28:328–335. https://doi.org/10.5935/0103-5053.20160182
- Kim S, Kim KC, Yeom E (2017) Microfluidic method for measuring viscosity using images from smartphone. Opt Lasers Eng. https://doi.org/10.1016/j.optlaseng.2017.05.016
- Le TT, Phan TTQ, Van Camp J, Dewettinck K (2015) 5—milk and dairy polar lipids: occurrence, purification, and nutritional and technological properties. In: Polar lipids. Elsevier, pp 91–143. https://doi.org/10.1016/B978-1-63067-044-3.50009-1
- O’Sullivan O, Cotter PD (2017) Chapter 12- Microbiota of raw milk and raw milk cheeses. In: Cheese (fourth edition). Academic Press, San Diego, pp 301–316. https://doi.org/10.1016/B978-0-12-417012-4.00012-0
- Rateni G, Dario P, Cavallo F (2017) Smartphone-based food diagnostic technologies: a review. Sensors 17:1453. https://doi.org/10.3390/s17061453
- Roda A, Calabretta MM, Calabria D, Caliceti C, Cevenini L, Lopreside A, Zangheri M (2017) Smartphone-based biosensors for bioanalytics: a critical review. Comprehensive Analytical Chemistry. https://doi.org/10.1016/bs.coac.2017.05.007
- Suñé RW (2010) A Incidência de Amostras de Leite com Reação Positiva ao Teste do Álcool em Diferentes Concentrações na Região da Campanha do Rio Grande do Sul e a Relação com a Acidez Titulável no Acidímetro de Dornic. Bagé, RS. Documentos/Embrapa Pecuária Sul, 113:1982-5390Google Scholar