Literature DB >> 26956366

Selection of promising sweet potato clones using projective mapping.

Esteban Vicente1, Gastón Ares2, Gustavo Rodríguez1, Pablo Varela1, Franco Bologna1, Joanna Lado1.   

Abstract

BACKGROUND: Increasing demand for sweet potato in regions with temperate climates has triggered interest in the development of new cultivars. Breeding of this crop should consider sensory characteristics in order to meet consumers' expectations. This requires the application of simple and cost-effective methodologies that allow quality evaluation from a sensory perspective.
RESULTS: With the objective of identifying the key sensory characteristics of different sweet potato genotypes, two commercial cultivars and seven clones were evaluated during three consecutive years using projective mapping by an untrained consumer panel. This methodology allowed the discrimination of the genotypes, identifying similarities and differences among groups based on sensory terms selected by the assessors. Genotypes were differentiated in terms of texture and flavor characteristics (firmness, moisture, smoothness, creaminess, flavor intensity, sweetness and bitterness). Materials for future crossings were identified.
CONCLUSIONS: The evaluation of the sensory characteristics of sweet potato clones and cultivars using projective mapping is a quick, cost-effective and reliable tool for the selection of new advanced sweet potato clones with superior sensory characteristics compared to the reference cultivars INIA Arapey and Cuarí.
© 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

Entities:  

Keywords:  breeding; projective mapping; sensory analysis; sweet potato

Mesh:

Year:  2016        PMID: 26956366     DOI: 10.1002/jsfa.7704

Source DB:  PubMed          Journal:  J Sci Food Agric        ISSN: 0022-5142            Impact factor:   3.638


  1 in total

1.  Consumer Description by Check-All-That-Apply Questions (CATA) of the Sensory Profiles of Commercial and New Mandarins. Identification of Preference Patterns and Drivers of Liking.

Authors:  Paula Tarancón; Amparo Tárrega; Pablo Aleza; Cristina Besada
Journal:  Foods       Date:  2020-04-09
  1 in total

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