A novel statistical approach to assess the quality and commercial viability of a retail branded perishable fruit

Abstract

Few studies have investigated sensory quality in multi-varietal fruit brands due to challenges in making comparisons between varieties harvested sequentially throughout the season. Sensory data are collected in crisp form and analysed using a great amount of numerical data. However, human perception is vague and an assessor's opinion comes in linguistic form. The purpose was to assess the sensory quality of branded apricot using a novel statistical approach. Physicochemical and sensory attributes were determined for two consecutive commercial seasons. Univariate and multivariate models were applied in order to assess quality stability and to create a prediction model. The brand was affected by the presence of different cultivars and the multiple factor analysis demonstrated aroma and juiciness as the most differentiated parameters, while univariate analysis highlighted hardness and mealiness. Use of expert knowledge mixed with information from sample data enabled the development of a fuzzy model. Investigation with consumer test is needed.Novedoso enfoque estadístico para evaluar la calidad y la viabilidad comercial de una fruta perecedera de marca minorista RESUMEN Pocos estudios han investigado la calidad sensorial en marcas de frutas de múltiples variedades debido a las dificultades para realizar comparaciones entre variedades cosechadas de forma secuencial a lo largo de una temporada. Generalmente, los datos sensoriales se recopilan de forma precisa y se analizan utilizando una gran cantidad de datos numéricos. Sin embargo, la percepción humana suele ser vaga y la opinión del evaluador se presenta en forma lingüística. El propósito del presente estudio fue evaluar la calidad sensorial del albaricoque [durazno] de marca empleando un enfoque estadístico novedoso. Así, durante dos temporadas comerciales consecutivas se determinaron los atributos fisicoquímicos y sensoriales de los albaricoques. Para ello se aplicaron modelos univariados y multivariados con el fin de evaluar la estabilidad de la calidad y crear un modelo de predicción. Se constató que la marca se vio afectada por el uso de diferentes cultivares; en este sentido el análisis factorial múltiple demostró que el aroma y la jugosidad son los parámetros de la fruta que más se diferencian, mientras que el análisis univariado destacó la dureza y la consistencia harinosa de la fruta. El uso de conocimiento experto combinado con la información proveniente de los datos de muestra permitió desarrollar un modelo difuso. Es necesario realizar investigaciones que incluyan pruebas entre consumidores.

A New Sensory Approach Combined with a Text-Mining Tool to Create a Sensory Lexicon and Profile of Monovarietal Apple Juices

“…L*, b*, Chroma (C*), and hue angle (h*) As stated in the previous literature[35], the lower levels of anthocyanins of Pinova juice contribute to a less-red color and a lighter appearance of the sample. Thus, in this assessment, the level of anthocyanins of the Pinova sample could have contributed to its more yellowish color compared to the Jonagold juice, as indicated by the h* index measured in this work.…”

“…Assessing the complex index h*, along with the classic colorimetric values, enables the detection of different color patterns behind the term "lighter", which were previously used indistinctly for both Jonagold and Pinova juices in other authors' work [4]. As stated in the previous literature [35], the lower levels of anthocyanins of Pinova juice contribute to a less-red color and a lighter appearance of the sample. Thus, in this assessment, the level of anthocyanins of the Pinova sample could have Assessing the complex index h*, along with the classic colorimetric values, enables the detection of different color patterns behind the term "lighter", which were previously used indistinctly for both Jonagold and Pinova juices in other authors' work [4].…”

“…This index takes into account differences in ratios of acids and sugars in different species by introducing a k-coefficient [33]. The main idea is that the human tongue perceives sugar and acids with differing sensitivities; thus, this index allows smaller amounts of acid to make the same numerical change to BrimA, as well as sugar [33][34][35]. Although different articles describe the sensory profile of the fresh-apple samples used in this work [36][37][38], no information is available regarding comparisons among Rubinette, Gravensteiner, Pinova, and Jonagold sweetness perceptions.…”

Multivariate factor analysis (MFA) approach to evaluate the quality of stored Cavendish banana sourced from different geographical areas

“…In particular TSS (represented by "brix") displayed a different pattern if compared to weight loss and dry matter. TSS followed a non-linear trend during shelf life for all samples and the interaction of this parameter with weight loss and dry matter is only partially described due to the fact that the MFA common space is based on linear combinations of parameters (Mendes da Silva et al, 2019). Considering the distribution of single variables divided between negative and positive loadings in dimension 1, it can be concluded that all samples at the overripe stage (positive loadings) presented increased adhesiveness and springiness values, while fresh bananas (negative loadings) presented firm texture and higher gumminess values.…”

“…Currently, MFA is mainly used in sensory studies due to its property of handling different types of data such as continuous or categoric variables (Pagès, 2005). However, it has been suggested as a proper approach to many types of quality assessment that involves multi-structured parameters in pre-harvest and postharvest longitudinal studies (Mendes da Silva et al, 2019;Mendes da Silva et al, 2020).…”