Prieto, Jose Manuel
Preferred name
Prieto, Jose Manuel
Main Affiliation
Email
jose.prieto@upeu.edu.pe
ORCID
Scopus Author ID
9 resultados
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Item type:Publicación, Denaturation kinetics and processing of cream cheese substitute coagulated with lemon juice(2025-01-01); Abstract The objective of this study was to evaluate the kinetics of denaturation of milk proteins at different temperatures of 80 °C and 85 °C, using lemon juice as a coagulating agent. Subsequently, we develop a cream cheese substitute and analyze its rheological, physicochemical, and sensory properties in comparison with commercial cream cheese. The results indicated that a higher reaction rate constant (K) and a higher yield were obtained at 85 °C. For the preparation of the cream cheese substitute, three formulations were developed, differentiated by the type of hydrocolloids: M1 (0.11% guar gum, 0.11% xanthan gum, and 0.11% carob gum), M2 (0.165% guar gum and 0.165% xanthan gum), and M3 (0.165% guar gum and 0.165% carob gum). Samples M1, M2, and M3 presented a pseudoplastic fluid, while the Control sample presented a fluid closer to Newtonian, both with elastic behavior. At the physicochemical level, the M3 cream cheese substitute showed higher protein content and lower fat and moisture content than the commercial cream cheese. In the sensory analysis, the M3 sample showed greater perception of acidity, while the commercial cheese stood out in creaminess and spreadability, obtaining greater acceptance. The differences observed between the two products may be influenced by the composition of the milk used, affecting the structure and stability of the cream cheese. - Some of the metrics are blocked by yourconsent settings
Item type:Publicación, Sorption isotherms and physical properties of three quinoa varieties grown at two altitudes(2025-01-01); - Some of the metrics are blocked by yourconsent settings
Item type:Publicación, Cooking quality, color, and texture profile analysis of a quinoa and lentil pasta(2024-01-01); ABSTRACT Quinoa (Chenopodium quinoa willd) and lentils (Lens culinaris) are ingredients used to enrich or substitute gluten in pasta manufacture due to their high nutritional content. The objective of this work was to develop quinoa noodles with lentils that have similar or superior attributes compared to the product with gluten. Therefore, we evaluated the cooking properties (cooking quality, hydration, rheology), color, and texture profile of noodles developed with different concentrations (10%, 20%, and 30%) of lentil flour (LF) in comparison to commercial wheat pasta (control). ANOVA comparisons were performed on cooking and texture profile attributes, with the best treatment being the one with values that did not significantly differ from the control sample (T0). Thus, T3 (70% quinoa grits and 30% LF) is the formulation that presents better and/or similar attributes to those of the control sample. - Some of the metrics are blocked by yourconsent settings
Item type:Publicación, Study of the puffing process of amaranth seeds by dielectric spectroscopy(2011-04-22); - Some of the metrics are blocked by yourconsent settings
Item type:Publicación, Discrimination of foreign bodies in quinoa <i>(Chenopodium quinoa</i> Willd.) grains using convolutional neural networks with a transfer learning approach(2023-01-30); Willd.) is due to its high protein content and gluten-free condition; nonetheless, the presence of foreign bodies in quinoa processing facilities is an issue that must be addressed. As a result, convolutional neural networks have been adopted, mostly because of their data extraction capabilities, which had not been utilized before for this purpose. Consequently, the main objective of this work is to evaluate convolutional neural networks with a learning transfer for foreign bodies identification in quinoa samples. For experimentation, quinoa samples were collected and manually split into 17 classes: quinoa grains and 16 foreign bodies. Then, one thousand images were obtained from each class in RGB space and transformed into four different color spaces (L*a*b*, HSV, YCbCr, and Gray). Three convolutional neural networks (AlexNet, MobileNetv2, and DenseNet-201) were trained using the five color spaces, and the evaluation results were expressed in terms of accuracy and F-score. All the CNN approaches compared showed an F-score ranging from 98% to 99%; both color space and CNN structure were found to have significant effects on the F-score. Also, DenseNet-201 was the most robust architecture and, at the same time, the most time-consuming. These results evidence the capacity of CNN architectures to be used for the discrimination of foreign bodies in quinoa processing facilities. - Some of the metrics are blocked by yourconsent settings
Item type:Publicación, EFECTO DE LA RELACIÓN DE AGUA Y TIEMPO DE PROCESO TÉRMICO SOBRE EL VOLUMEN DE EXPANSIÓN Y ATRIBUTOS SENSORIALES DE Chenopodium quinoa Willd.(2019-04-30) - Some of the metrics are blocked by yourconsent settings
Item type:Publicación, Feasibility of using spectral profiles for modeling water activity in five varieties of white quinoa grains(2018-06-13); - Some of the metrics are blocked by yourconsent settings
Item type:Patent, SECADOR DE LECHO FLUIDIZADO DE AIRE FRÍO CONVECTIVO CON MONITORIZACIÓN EN TIEMPO REAL DE TEMPERATURA Y HUMEDAD(Instituto Nacional de Defensa de la Competencia y de la Proteccion de la Propiedad Intelectual, 2022-10-13); ; - Some of the metrics are blocked by yourconsent settings
Item type:Publicación, Low doses of insulin-like growth factor-I improve nitrogen retention and food efficiency in rats with early cirrhosis(2017-05-03)