Multivariate Correlation of the Physicochemical and Sensory Profile of Milk Quality from Small Producers in Barranca, Lima-Peru
The comprehensive quality assessment of raw milk from small-scale producers remains essential for improving dairy sector competitiveness. This study employed a multivariate approach to correlate the physicochemical, colorimetric, and sensory profiles of raw milk from eleven producers in the town of...
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| Lenguaje: | inglés |
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2026
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| author | Jose N. Jimenez-Bustamante José Cayetano Vergaray Huamán Carlos Enrique García Soto Tito Armando Jara Pajuelo Nil Edinson Mendoza Virhuez Thalia Alexandra Rivera-Ashqui Emmanuel Alexander Sessarego Angel Vásquez R. Reynaldo J. Silva-Paz |
| author_browse | Angel Vásquez R. Carlos Enrique García Soto Emmanuel Alexander Sessarego Jose N. Jimenez-Bustamante José Cayetano Vergaray Huamán Nil Edinson Mendoza Virhuez Reynaldo J. Silva-Paz Thalia Alexandra Rivera-Ashqui Tito Armando Jara Pajuelo |
| author_facet | Jose N. Jimenez-Bustamante José Cayetano Vergaray Huamán Carlos Enrique García Soto Tito Armando Jara Pajuelo Nil Edinson Mendoza Virhuez Thalia Alexandra Rivera-Ashqui Emmanuel Alexander Sessarego Angel Vásquez R. Reynaldo J. Silva-Paz |
| author_sort | Jose N. Jimenez-Bustamante |
| collection | Producción científica |
| description | The comprehensive quality assessment of raw milk from small-scale producers remains essential for improving dairy sector competitiveness. This study employed a multivariate approach to correlate the physicochemical, colorimetric, and sensory profiles of raw milk from eleven producers in the town of Supe, Barranca, Lima, Peru. Milk samples were analyzed using a Lactoscan MCC ultrasonic analyzer, CIEL*a*b* colorimetry, and the Flash Profile sensory method. Data integration and interpretation were performed using Analysis of Variance (ANOVA), Generalized Procrustes Analysis (GPA) and Hierarchical Multiple Factor Analysis (HMFA). The results revealed significant heterogeneity, identifying two distinct producer groups. A high-quality group (DF7, DF10, DF11) presented adequate physicochemical parameters: high fat content (>3.77%), total solids (>12.06%), normal freezing point (≈−0.53 °C), creamy color (high L* and b*), and positive sensory attributes (“fatty”, “creamy”). In contrast, a low-quality group (DF4, DF5, DF8, DF9) showed evidence of water adulteration (12–16%), reflected in an elevated freezing point (up to −0.44 °C), low solids-not-fat, and defective sensory profiles (“tasteless”, “salty”). The HMFA demonstrated a strong concordance between instrumental and sensory data sets, identifying water adulteration and fat content as the primary drivers of quality variation. This integrated methodology provides a robust diagnostic tool for quality-based payment systems and targeted technical assistance, offering a replicable model for enhancing quality control and valorizing raw milk in smallholder dairy systems. |
| format | Article |
| id | openalex:W7154186445 |
| institution | UPeU |
| language | English |
| publishDate | 2026 |
| publishDateRange | 2026 |
| publishDateSort | 2026 |
| record_format | dspace |
| spelling | openalex:W7154186445Multivariate Correlation of the Physicochemical and Sensory Profile of Milk Quality from Small Producers in Barranca, Lima-PeruJose N. Jimenez-BustamanteJosé Cayetano Vergaray HuamánCarlos Enrique García SotoTito Armando Jara PajueloNil Edinson Mendoza VirhuezThalia Alexandra Rivera-AshquiEmmanuel Alexander SessaregoAngel Vásquez R.Reynaldo J. Silva-Pazraw milk qualitysmallholder dairy producerswater adulterationmilk fat contentfreezing pointmilk colorsensory profilephysicochemical propertiesgeneralized Procrustes analysismilk quality controlMilk Quality and Mastitis in Dairy CowsFood Nutrient Composition and Product DevelopmentSensory Analysis and Statistical MethodsThe comprehensive quality assessment of raw milk from small-scale producers remains essential for improving dairy sector competitiveness. This study employed a multivariate approach to correlate the physicochemical, colorimetric, and sensory profiles of raw milk from eleven producers in the town of Supe, Barranca, Lima, Peru. Milk samples were analyzed using a Lactoscan MCC ultrasonic analyzer, CIEL*a*b* colorimetry, and the Flash Profile sensory method. Data integration and interpretation were performed using Analysis of Variance (ANOVA), Generalized Procrustes Analysis (GPA) and Hierarchical Multiple Factor Analysis (HMFA). The results revealed significant heterogeneity, identifying two distinct producer groups. A high-quality group (DF7, DF10, DF11) presented adequate physicochemical parameters: high fat content (>3.77%), total solids (>12.06%), normal freezing point (≈−0.53 °C), creamy color (high L* and b*), and positive sensory attributes (“fatty”, “creamy”). In contrast, a low-quality group (DF4, DF5, DF8, DF9) showed evidence of water adulteration (12–16%), reflected in an elevated freezing point (up to −0.44 °C), low solids-not-fat, and defective sensory profiles (“tasteless”, “salty”). The HMFA demonstrated a strong concordance between instrumental and sensory data sets, identifying water adulteration and fat content as the primary drivers of quality variation. This integrated methodology provides a robust diagnostic tool for quality-based payment systems and targeted technical assistance, offering a replicable model for enhancing quality control and valorizing raw milk in smallholder dairy systems.Articlehttps://doi.org/10.3390/app16083796https://www.mdpi.com/2076-3417/16/8/3796/pdf?version=1776085100W7154186445enApplied Sciences2076-34172026-04-13 |
| spellingShingle | raw milk quality smallholder dairy producers water adulteration milk fat content freezing point milk color sensory profile physicochemical properties generalized Procrustes analysis milk quality control Milk Quality and Mastitis in Dairy Cows Food Nutrient Composition and Product Development Sensory Analysis and Statistical Methods Jose N. Jimenez-Bustamante José Cayetano Vergaray Huamán Carlos Enrique García Soto Tito Armando Jara Pajuelo Nil Edinson Mendoza Virhuez Thalia Alexandra Rivera-Ashqui Emmanuel Alexander Sessarego Angel Vásquez R. Reynaldo J. Silva-Paz Multivariate Correlation of the Physicochemical and Sensory Profile of Milk Quality from Small Producers in Barranca, Lima-Peru |
| title | Multivariate Correlation of the Physicochemical and Sensory Profile of Milk Quality from Small Producers in Barranca, Lima-Peru |
| title_full | Multivariate Correlation of the Physicochemical and Sensory Profile of Milk Quality from Small Producers in Barranca, Lima-Peru |
| title_fullStr | Multivariate Correlation of the Physicochemical and Sensory Profile of Milk Quality from Small Producers in Barranca, Lima-Peru |
| title_full_unstemmed | Multivariate Correlation of the Physicochemical and Sensory Profile of Milk Quality from Small Producers in Barranca, Lima-Peru |
| title_short | Multivariate Correlation of the Physicochemical and Sensory Profile of Milk Quality from Small Producers in Barranca, Lima-Peru |
| title_sort | multivariate correlation of the physicochemical and sensory profile of milk quality from small producers in barranca lima peru |
| topic | raw milk quality smallholder dairy producers water adulteration milk fat content freezing point milk color sensory profile physicochemical properties generalized Procrustes analysis milk quality control Milk Quality and Mastitis in Dairy Cows Food Nutrient Composition and Product Development Sensory Analysis and Statistical Methods |
| topic_facet | raw milk quality smallholder dairy producers water adulteration milk fat content freezing point milk color sensory profile physicochemical properties generalized Procrustes analysis milk quality control Milk Quality and Mastitis in Dairy Cows Food Nutrient Composition and Product Development Sensory Analysis and Statistical Methods |
| url | https://doi.org/10.3390/app16083796 https://www.mdpi.com/2076-3417/16/8/3796/pdf?version=1776085100 |
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