Data Analysis in Newly Developed Milk Sensor Platforms: Good Practices, Common Pitfalls, and Hard-Earned Lessons from Field Application

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Publicado en:Foods vol. 14, no. 10 (2025), p. 1724
Autor principal: Martelli, Francesco
Otros Autores: Giacomozzi Claudia, Dragone, Roberto, Frazzoli Chiara, Grasso, Gerardo
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MDPI AG
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100 1 |a Martelli, Francesco  |u Dipartimento Malattie Cardiovascolari ed Endocrino-Metaboliche, e Invecchiamento, Istituto Superiore di Sanità, Via Giano Della Bella, 34, 00162 Rome, Italy; francesco.martelli@iss.it (F.M.); claudia.giacomozzi@iss.it (C.G.); chiara.frazzoli@iss.it (C.F.) 
245 1 |a Data Analysis in Newly Developed Milk Sensor Platforms: Good Practices, Common Pitfalls, and Hard-Earned Lessons from Field Application 
260 |b MDPI AG  |c 2025 
513 |a Journal Article 
520 3 |a In the last decade, the demand for healthier and safer food has increased alongside greater consumer awareness of food consumption, particularly in developed countries. This trend has pushed the food industry to implement a wide range of food quality control measures and surveillance systems for detecting contaminants. While high-end laboratory techniques remain the gold standard detection techniques, there is a growing need for simpler, more robust diagnostic tools that can be applied in the early stages of the food production chain to promptly identify deviations that may compromise food safety or quality. A complementary approach using both techniques can result in an enhancement of the overall contaminant-detection effectiveness and a better balance between food safety decision-making and the preservation of production value. This need is particularly relevant in farming and in the dairy industry. Developing milk process analytics requires careful consideration of both the nature of the processed sample and the conditions under which it is collected. Moreover, newly introduced techniques require the development of sound methodologies for data collection, analysis, and statistical process control. For this reason, this paper presents a detailed analysis of our previous milk data-collection campaigns involving technological prototypes, aiming to identify and suggest ways to preventively minimize issues related to experimental data collection, interpretation, errors, and mishandling. This analysis resulted in a set of practical observations and recommendations reported in the paper. 
651 4 |a Italy 
653 |a Developed countries 
653 |a Food safety 
653 |a Dairy industry 
653 |a Gold 
653 |a Agricultural production 
653 |a Quality control 
653 |a Food contamination & poisoning 
653 |a Dairy farms 
653 |a Food consumption 
653 |a Statistical process control 
653 |a Laboratories 
653 |a Food quality 
653 |a Contaminants 
653 |a Food production 
653 |a Measurement techniques 
653 |a Data analysis 
653 |a Scientific imaging 
653 |a Chromatography 
653 |a Chemical contaminants 
653 |a Lipids 
653 |a Data collection 
653 |a Proteins 
653 |a Milk 
653 |a Food industry 
653 |a Mass spectrometry 
653 |a Quality standards 
653 |a Process control 
653 |a Food chains 
653 |a Sensors 
653 |a Process controls 
653 |a Surveillance systems 
653 |a Decision making 
653 |a Climate change 
653 |a Enzymes 
700 1 |a Giacomozzi Claudia  |u Dipartimento Malattie Cardiovascolari ed Endocrino-Metaboliche, e Invecchiamento, Istituto Superiore di Sanità, Via Giano Della Bella, 34, 00162 Rome, Italy; francesco.martelli@iss.it (F.M.); claudia.giacomozzi@iss.it (C.G.); chiara.frazzoli@iss.it (C.F.) 
700 1 |a Dragone, Roberto  |u Istituto per Lo Studio Dei Materiali Nanostrutturati Sede Sapienza, Consiglio Nazionale delle Ricerche, P. le Aldo Moro 5, 00185 Rome, Italy; roberto.dragone@cnr.it 
700 1 |a Frazzoli Chiara  |u Dipartimento Malattie Cardiovascolari ed Endocrino-Metaboliche, e Invecchiamento, Istituto Superiore di Sanità, Via Giano Della Bella, 34, 00162 Rome, Italy; francesco.martelli@iss.it (F.M.); claudia.giacomozzi@iss.it (C.G.); chiara.frazzoli@iss.it (C.F.) 
700 1 |a Grasso, Gerardo  |u Istituto per Lo Studio Dei Materiali Nanostrutturati Sede Sapienza, Consiglio Nazionale delle Ricerche, P. le Aldo Moro 5, 00185 Rome, Italy; roberto.dragone@cnr.it 
773 0 |t Foods  |g vol. 14, no. 10 (2025), p. 1724 
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