Curasi Rafael, Nancy

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Curasi Rafael, Nancy
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  • Publicacion
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    Development of a Hybrid System Based on the CIELAB Colour Space and Artificial Neural Networks for Monitoring pH and Acidity During Yogurt Fermentation
    (Multidisciplinary Digital Publishing Institute (MDPI), 2025-08-01)
    Alvarado, Ulises
    ;
    Tacuri, Jhon
    ;
    Coloma, Alejandro
    ;
    Gallegos Rojas, Edgar
    ;
    Callo, Herbert
    Monitoring pH and acidity during yoghurt fermentation is essential for product quality and process efficiency. Conventional measurement methods, however, are invasive and labour-intensive. This study developed artificial neural network (ANN) models to predict pH and titratable acidity during yoghurt fermentation using CIELAB colour parameters (L, a*, b*). Reconstituted milk powder with 12% total solids was prepared with varying protein levels (4.2–4.8%), inoculum concentrations (1–3%), and fermentation temperatures (36–44 °C). Data were collected every 10 min until pH 4.6 was reached. Forty models were trained for each output variable, using 90% of the data for training and 10% for validation. The first two phases of the fermentation process were clearly distinguishable, lasting between 4.5 and 7 h and exceeding 0.6% lactic acid in all treatments evaluated. The best pH model used two hidden layers with 28 neurons (R2 = 0.969; RMSE = 0.007), while the optimal acidity model had four hidden layers with 32 neurons (R2 = 0.868; RMSE = 0.002). The strong correlation between colour and physicochemical changes confirms the feasibility of this non-destructive approach. Integrating ANN models and colourimetry offers a practical solution for real-time monitoring, helping improve process control in industrial yoghurt production.
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    Ultrasound-Assisted Kinetics of Alcoholic Fermentation at Varying Power Levels for the Production of Isaño Wine (Tropaeolum tuberosum)
    (Multidisciplinary Digital Publishing Institute (MDPI), 2025-05-08)
    Coloma, Alejandro
    ;
    Mamani-Mamani, Maria
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    Valencia-Sullca, Cristina
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    Mamani Paredes, Javier
    ;
    Callo, Herbert
    Ultrasound is considered a physical technology that can be applied at various stages of food processing to optimise resources and reduce production time. In this study, the influence of ultrasonic treatments at different power levels (0 W, 100 W, 200 W, and 300 W) on three Isaño genotypes (yellow, yellow with purple eyes, and purple) during alcoholic fermentation was investigated. The main parameters assessed were yeast growth kinetics, ethanol production, and substrate consumption in an ultrasonic bath operating at a frequency of 50 kHz. The findings demonstrated enhanced yeast growth, accelerated substrate consumption, and increased ethanol production compared to the control (untreated sample). However, the impact of ultrasound on fermentation decreased as the power level increased. Notably, an ultrasonic power of 100 W applied over 84 h of fermentation resulted in the highest ethanol yield (10.36% v/v) in the purple Isaño genotype. In conclusion, ultrasonic treatment is a promising approach to improve the fermentation process of Isaño, potentially enabling its development as a functional beverage with both nutritional and therapeutic properties.
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    Estimation of arsenic contents in rice purchased on Peruvian markets and estimation of dietary intake by Peruvians through rice consumption
    (2021-04-29)
    Zhunaula Guaman, Sonia Tatiana
    ;
    Coaquira Ccahua, Washington
    ;
    Curasi Rafael, Nancy  
    ;
    Unchupaico Payano, Ide
    ;
    Angeles Suazo, Julio Miguel
    Rice (Oryza sativa L) is an important source of essential elements but also can contain high As concentrations, which may be consumed and causes health effects. This work aimed to contribute to the lack of information quantifying the total arsenic (tAs) in 31 domestic rice (white rice, n=19; brown rice, n=7; parboiled rice, n=5) of different brands purchased in Peruvian markets. The tAs content was conducted by ICP-MS. The tAs concentration was compared to the maximum limits prescribed by regulatory agencies. Dietary intake (DI), dietary exposure (DE), and margin of exposure (MOE) were estimated. tAs concentration in white, brown and parboiled rice were 0.292 ± 0.106 mg/kg, 0.401 ± 0.081 mg/kg, 0.229 ± 0.03 mg/kg, respectively. Arsenic concentration in white rice exceeded limits recommended by FAO/WHO (0.20 mg kg-1), and European legislation (0.25 mg kg-1), but no Mercosul limits (0.3 mg kg-1). The DE showed that, on average, Peruvians consume 5.60 μg As kg-1 BW weekly. The MOE value was higher than 1 at the mean dietary exposure level. Our findings suggest that the health risk from dietary arsenic exposure is low for the Peruvian population. However, more studies are needed to reduce dietary arsenic exposure in Peru.
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    Biomonitoring of Potentially Toxic Elements in Two Polluted Areas from Lurigancho-Chosica Using the genus Tillandsia latifolia and T. purpurea as Biomonitor
    (2021-03-05)
    Huaman de la Cruz, Alex Ruben  
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    Yauri Molina, Hérica
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    Vilca Monrroy, Xiomara Rosa
    ;
    Beringui, Karmel
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    Camargo Caysahuana, Andres
    In the present study, an urban and industrial area were evaluated through a biomonitoring study employing the Tillandsia purpurea and T. latifolia species as a biomonitor. Plants were collected from a non-contaminated area and transplanted and exposed for three months into study areas to determine metal accumulation. Sixteen elements (Al, As, Ba, Ca, Cd, Co, Cr, Cu, Fe, K, Mg, Mn, Ni, Pb, Rb, Sb, V, and Zn) were measured using ICP-MS analysis. Datasets were assessed by one-way ANOVA, exposed-to-baseline (EB) ratio, and principal component analysis. Results showed significant differences among study areas for most elements, but no differences were found between species. According to EB ratios, As, Cd, Cr, Cu, Fe, Ni, Pb, Sb, V, and Zn showed EB ratios > 1.75 for both Tillandsia species around the industrial area, indicating influence from the Smelter plant. Ba, Sb, and Zn showed EB ratios > .1.75 in the urban area for both plants, indicating the releasing of pollutants from vehicular sources. PCA showed that most elements are derived from vehicular sources, industrial activities, and dust resuspension.
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