Literature DB >> 34174303

Infrared heating under optimized conditions enhanced the pasting and swelling behaviour of cowpea starch.

Samson A Oyeyinka1, Ajibola B Oyedeji2, Opeolu M Ogundele2, Oluwafemi A Adebo3, Patrick B Njobeh2, Eugénie Kayitesi4.   

Abstract

Native starches are not suitable for industrial use and must be modified for improved functionality. In this study, the effect of moisture preconditioning and infrared heating time on physicochemical properties of cowpea starch was investigated using a two-factor central composite rotatable design. Factors (moisture levels:10-40 g/100 g starch and infrared heating time:10-60 min) with their corresponding α mid-point values resulted in 13 experimental runs. Selected functional and pasting properties were determined as response variables. Starch samples produced under optimized conditions were compared with corn starch and their physicochemical properties determined. Except for pasting temperature, cowpea starch prepared using the optimal conditions (moisture: 46.21 g/100 g starch, dry basis and heating time of 32.88 min) had higher functional and pasting properties compared with the native cowpea starch. Infrared heating significantly reduced the gelatinization temperatures of cowpea starch but did not significantly change that of the corn starch. The crystallinity and double-helical order structure of moisture conditioned cowpea starch also reduced after modification. Cowpea starch showed a bigger granule size, higher swelling power but lower water absorption capacities and pasting properties compared with the control. The infrared heating process is a novel and promising modification method for improving the swelling properties of starch.
Copyright © 2018. Published by Elsevier B.V.

Entities:  

Keywords:  Cowpea starch; Infrared heating; Moisture preconditioning; Pasting properties; Thermal properties

Year:  2021        PMID: 34174303     DOI: 10.1016/j.ijbiomac.2021.06.129

Source DB:  PubMed          Journal:  Int J Biol Macromol        ISSN: 0141-8130            Impact factor:   6.953


  1 in total

1.  Machine learning predictive model for evaluating the cooking characteristics of moisture conditioned and infrared heated cowpea.

Authors:  Opeolu M Ogundele; Ayooluwa T Akintola; Beatrice M Fasogbon; Oluwafemi A Adebo
Journal:  Sci Rep       Date:  2022-06-02       Impact factor: 4.996

  1 in total

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