Abstract

The objective of this study was carried out to evaluating the productive performance, the physical-chemical quality of the milk, the physical-chemical and sensorial quality of rennet cheeses obtained from the milk of goats submitted to diets with diferente levels of guava agroindustrial waste (GAW). The goats were randomly distributed in a Latin square (4x4) according to the substitution levels (0, 14, 28, and 42%) of inclusion GAW in the diet. The consumption of natural and dry matter increased with the increase in hay substitution. However, the physical-chemical requirements of milk and cheese were not altered.

Highlights

  • Goat rearing is a low cost alternative for dairy production in underdeveloped and developing countries (Schwarz et al, 2017)

  • The increase in goat milk production and processing that has occurred in recent years is mainly due to new food trends (Barlowska et al, 2018)

  • The objective of this research was to evaluate the productive performance, the physicochemical quality of milk, and the physicochemical and sensory quality of curd type cheese obtained from goat milk submitted to diets with different levels of substitution tifton grass hay by guava agroindustrial waste (GAW)

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Summary

Introduction

Goat rearing is a low cost alternative for dairy production in underdeveloped and developing countries (Schwarz et al, 2017). The increase in goat milk production and processing that has occurred in recent years is mainly due to new food trends (Barlowska et al, 2018). There is a demand from the consumer to buy cheese made by traditional methods. The sensory qualities of cheese produced by traditional methods are differentiated from cheese produced on an industrial scale (Kuźnicka & Łapinska, 2014). An analytical sensory evaluation and consumer testing provide reliable, valuable and the most meaningful information on the quality and acceptability of food. During the development of an innovative product process, information is always urgent. A quantitative descriptive analysis (QDA) is one of the most sophisticated tools that provides a multidimensional sensory ‘image’ of a product and could be useful during the comparison of samples (Mituniewicz-Malek et al, 2019)

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