Evidence map›Paper›PMID 34646524›Full record

ArticleFood science & nutrition2021

Optimization of novel multigrain pasta and evaluation of physicochemical properties: using D-optimal mixture design.

Leila Kamali Rousta, Amir Pouya Ghandehari Yazdi, Sepideh Khorasani, Mohammad Tavakoli, Zahra Ahmadi, Mahdi Amini

Abstract read
In one paragraph

Article in Food science & nutrition, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

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0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Leila Kamali RoustaDepartment of Food Research and Development Zar Research and Industrial Development Group Alborz Iran.ORCID https://orcid.org/0000-0001-7848-6897
Amir Pouya Ghandehari YazdiDepartment of Food Research and Development Zar Research and Industrial Development Group Alborz Iran.ORCID https://orcid.org/0000-0002-7647-3512
Sepideh KhorasaniDepartment of Food Science and Technology Faculty of Agriculture, Research and Technology Institute of Plant Production (RTIPP) Shahid Bahonar University of Kerman Kerman Iran.ORCID https://orcid.org/0000-0002-5454-5837
Mohammad TavakoliDepartment of Food Research and Development Zar Research and Industrial Development Group Alborz Iran.
Zahra AhmadiDepartment of Food Science and Technology Ferdowsi University of Mashhad Mashhad Iran.
Mahdi AminiDepartment of Food Research and Development Zar Research and Industrial Development Group Alborz Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

D-optimal mixture design looked to be a priceless tool for optimizing the influences of semolina flour (SF), defatted soy flour (DSF), whole quinoa flour (WQF), whole rye flour (WRF), whole oat flour (WOF), whole barley flour (WBF), and rice flour (RF) on the quality attributes of multigrain pasta (MP). Multigrain flours were considered as the independent variables evaluated with respect to three response variables containing hardness and the amount of protein and fiber. Quadratic, linear, and linear models were chosen to explain the hardness and the amount of protein and fiber of the MPs, respectively. In optimal formulation of MP, that is, SF (57.34%,), DSF (14%), WQF (11%), WRF (7.54%), WOF (5.61%), WBF (2.51%), and RF (2%), the content of fiber and protein enhanced more than 4.12 and 1.34 times compared with SP, respectively. Therefore, according to the European Union law, it can be claimed that this pasta is a source of fiber. As the amount of protein and fiber increased, the hardness and optimal cooking time decreased, while the cooking loss increased. After cooking, MP was murkier and less yellow in color. The 2, 2- diphenyl- 1- picrylhydrazyl (DPPH) inhibition activity of the MP was about 2.5 times higher than the SP. Analysis of the antioxidant properties of the samples after cooking showed that the DPPH inhibition activity of the SP and MP reduced. The results indicated that the overall acceptability of MP was higher than SP. Based on our findings, these multigrain flours are probable to be applied as nutritious complements in the pasta industry to improve the functional characteristics.

Indexed as

D‐optimalenrichmentmixture designmultigrainpasta

Identifiers

PMID34646524
PMCPMC8498078

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.