Consumer Perception of Beef Quality and How to Control, Improve and Predict It? Focus on Eating Quality

Foods. 2022 Jun 13;11(12):1732. doi: 10.3390/foods11121732.

Abstract

Quality refers to the characteristics of products that meet the demands and expectations of the end users. Beef quality is a convergence between product characteristics on one hand and consumers' experiences and demands on the other. This paper reviews the formation of consumer beef quality perception, the main factors determining beef sensory quality, and how to measure and predict beef eating quality at scientific and industrial levels. Beef quality is of paramount importance to consumers since consumer perception of quality determines the decision to purchase and repeat the purchase. Consumer perception of beef quality undergoes a multi-step process at the time of purchase and consumption in order to achieve an overall value assessment. Beef quality perception is determined by a set of quality attributes, including intrinsic (appearance, safety, technological, sensory and nutritional characteristics, convenience) and extrinsic (price, image, livestock farming systems, commercial strategy, etc.) quality traits. The beef eating qualities that are the most valued by consumers are highly variable and depend mainly on the composition and characteristics of the original muscle and the post-mortem processes involved in the conversion of muscle into meat, the mechanisms of which are summarized in this review. Furthermore, in order to guarantee good quality beef for consumers in advance, the prediction of beef quality by combining different traits in scenarios where the animal, carcass, and muscle cuts can be evaluated is also discussed in the current review.

Keywords: beef eating quality; beef grading scheme; beef quality attributes; consumer perception; pre- and post-mortem determinisms.

Publication types

  • Review

Grants and funding

This work was supported by the Bulgarian Ministry of Education and Science under the project GREENANIMO (contract No Д01-287/07.10.2020 and Trakia University’s reference number M004/7.10.2020), part of the National Program “European Scientific Networks”.