Survival analysis model to estimate sensory shelf life with temperature and illumination as accelerating factors

Garitta, Lorena; Langohr, Klaus; Elizagoyen, Eliana; Ottaviano, Fernanda Gugole; Gómez, Guadalupe; Hough, Guillermo

doi:10.1016/j.foodqual.2018.03.014

Cited by 13 publications

(5 citation statements)

References 24 publications

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“…The information obtained from consumers using survival method is related to their everyday eating/buying routine and, thus, is relevant for product marketing or development. In survival analysis, only responses related to consumption, limited to the answers yes or no, are requested (Hough et al., 2003; Hough et al., 2006; Garitta et al, 2018). Unlike in sensory profiling method, no pressure is exerted on consumers to assess the intensity of an attribute.…”

Section: Resultsmentioning

confidence: 99%

Determination of optimum ripening time in hard cooked cheeses (Reggianito type) using survival analysis statistics: Modified versus traditional cheese making technology

Garitta

Ayelén

Rodriguez

et al. 2021

Journal of Food Science

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In this work, we determined optimum ripening time of hard cooked cheeses made by traditional technology or by an innovative process aimed at accelerating flavor formation. For that purpose, we applied survival analysis statistics. Experimental cheese making (E) included homogenization of milk fat, unpasteurized cheese milk, changes in cooking temperature, and a curd‐washing step, while traditional cheese making (T) followed a classic hard‐cooked cheese making. Cheeses were ripened for 215 days and samples were analyzed at 76, 112, 128, 152, and 215 days. Consumers (250) were recruited and divided into five groups of 50 consumers for each stage. At each sampling time, consumers assessed whether the sample was “under‐ripe,” “ok,” or “over‐ripe.” Optimum ripening time could be estimated only for E cheeses, with a high percentage of rejection. For T cheeses, it was not possible to determine the optimum ripening time because the rejection by over‐ripening was never reported. We verified consumer segmentation: a small percentage found E cheese under‐ripe and a high percentage found it over‐ripe. Many consumers qualified E cheeses as too spicy, especially at the end of ripening. Spicy flavor is usually perceived before than the texture and evidenced an acceleration of the flavor formation. We concluded that the innovative intervention in cheese making technology was successful in accelerating cheese ripening. It also had potential to develop a new cheese product targeted at consumers who chose/prefer good spicy flavor. Practical Application Survival analysis is a useful methodology to determine the optimum ripening time of foods based on consumer data. In this work, it evidenced that the proposed innovative cheese making was successful in accelerating the formation of cheese flavor, and had the potential to develop a new cheese product targeted at consumers who chose/prefer good spicy flavor.

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Section: Resultsmentioning

confidence: 99%

Determination of optimum ripening time in hard cooked cheeses (Reggianito type) using survival analysis statistics: Modified versus traditional cheese making technology

Garitta

Ayelén

Rodriguez

et al. 2021

Journal of Food Science

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“…e survival model is mainly used in the food and finance industry and is not applied much in the machinery industry. A survival model is introduced to contemplate two simultaneous accelerating factors affecting a food product's shelf life: temperature and illumination [31]. e empirical analysis is based on an extension of the discrete-time survival analysis model, which allows for a structural break in its baseline hazard function and a unique set of individual loan accounts in [32].…”

Section: Survival Modelmentioning

confidence: 99%

Predicting Remaining Useful Life Based on Hilbert–Huang Entropy with Degradation Model

Zheng

2019

Journal of Electrical and Computer Engineering

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Prognostics health management (PHM) of rotating machinery has become an important process for increasing reliability and reducing machine malfunctions in industry. Bearings are one of the most important equipment parts and are also one of the most common failure points. To assess the degradation of a machine, this paper presents a bearing remaining useful life (RUL) prediction method. The method relies on a novel health indicator and a linear degradation model to predict bearing RUL. The health indicator is extracted by using Hilbert–Huang entropy to process horizontal vibration signals obtained from bearings. We present a linear degradation model to estimate RUL using this health indicator. In the training phase, the degradation detection threshold and the failure threshold of this model are estimated by the distribution of 600 bootstrapped samples. These bootstrapped samples are taken from the six training sets. In the test phase, the health indicator and the model are used to estimate the bearing’s current health state and predict its RUL. This method is suitable for the degradation of bearings. The experimental results show that this method can effectively monitor bearing degradation and predict its RUL.

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“…El número de consumidores que evaluaron la aceptabilidad en ambas etapas estuvieron entre 50 y 80, tal como lo indica Hough (2010) para este tipo de estudio. Se consideró un 50 % como porcentaje de rechazo de los consumidores para las estimaciones (Garitta et al, 2018).…”

Section: Aceptabilidad Del Nivel De Sólidos Solubles (°Brix)unclassified

Optimización sensorial de un néctar mixto de papaya y maracuyá aplicando el análisis de supervivencia a la respuesta de los consumidores

Quispe¹,

Ticlayauri²

2019

Peruv. Agric. Res.

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Objetivos: Determinar el óptimo sensorial de un néctar mixto de papaya y maracuyá aplicando el análisis de supervivencia a la respuesta de los consumidores. Metodología: Se encuestaron a 55 consumidores para evaluar el grado de aceptabilidad de un néctar mixto de papaya y maracuyá con concentraciones de jugo de maracuyá de 2,5; 5,0; 7,5; 10,0; 12,5 y 15,0 %, solicitándoles su aceptación o rechazo para cada concentración. Para evaluar la aceptabilidad del nivel de sólidos solubles en el néctar mixto con 12, 14, 16 y 18 °Brix, se encuestaron a 65 consumidores, solicitándoles su aceptación o rechazo para cada grado. Se utilizó la metodología del análisis de supervivencia con el modelo Weibull para realizar la optimización sensorial de la concentración del jugo de maracuyá y el nivel de sólidos solubles en el néctar mixto. Resultados: Se estimó la concentración del jugo de maracuyá y el nivel de sólidos solubles en el néctar mixto, 9,18 ± 0,54 % y 15,41 ± 0,18 oBrix, respectivamente. Conclusiones: El análisis de supervivencia con el modelo Weibull, utilizando la respuesta de los consumidores, permitió estimar la concentración óptima de maracuyá y el nivel de sólidos solubles en un néctar mixto de papayay maracuyá.Palabras clave: Optimización sensorial, análisis de supervivencia, néctar mixto, Weibull.

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Survival analysis model to estimate sensory shelf life with temperature and illumination as accelerating factors

Cited by 13 publications

References 24 publications

Determination of optimum ripening time in hard cooked cheeses (Reggianito type) using survival analysis statistics: Modified versus traditional cheese making technology

Determination of optimum ripening time in hard cooked cheeses (Reggianito type) using survival analysis statistics: Modified versus traditional cheese making technology

Predicting Remaining Useful Life Based on Hilbert–Huang Entropy with Degradation Model

Optimización sensorial de un néctar mixto de papaya y maracuyá aplicando el análisis de supervivencia a la respuesta de los consumidores

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