Evidence map›Paper›PMID 33776246›Full record

ArticleInternational journal of food science & technology2021

End-user preferences for pounded yam and implications for food product profile development.

Bolanle Otegbayo, Tessy Madu, Oluyinka Oroniran, Ugo Chijioke, Olabisi Fawehinmi, Benjamin Okoye, Abiola Tanimola, Patrick Adebola, Jude Obidiegwu

Abstract read
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Article in International journal of food science & technology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 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

9 authors.

Bolanle OtegbayoDepartment of Food Science and Technology Bowen University Iwo 232101 Nigeria.ORCID https://orcid.org/0000-0002-8672-1479
Tessy MaduNational Root Crop Research Institute Umudike 440110 Nigeria.
Oluyinka OroniranDepartment of Food Science and Technology Bowen University Iwo 232101 Nigeria.
Ugo ChijiokeNational Root Crop Research Institute Umudike 440110 Nigeria.ORCID https://orcid.org/0000-0001-6983-5215
Olabisi FawehinmiDepartment of Food Science and Technology Bowen University Iwo 232101 Nigeria.
Benjamin OkoyeNational Root Crop Research Institute Umudike 440110 Nigeria.
Abiola TanimolaDepartment of Food Science and Technology Bowen University Iwo 232101 Nigeria.
Patrick AdebolaInternational institute of Tropical Agriculture Ibadan 200132 Nigeria.
Jude ObidiegwuNational Root Crop Research Institute Umudike 440110 Nigeria.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pounded yam is a popular food in Nigeria. This study reports end-user preferences for pounded yam and implications for trait evaluation by breeding programme. The study was carried out in two pounded yam-consuming regions in Nigeria: south-east and south-west. Multistage sampling technique was used to collect information from users along food chain. This involved market, individual, key informant interviews and focus group discussions. Responses of participants were used to develop product profile of pounded yam from raw material (yam) to final product. Key user-preferred quality traits for pounded yam in both regions were colour and textural quality followed by taste and aroma which are lesser attributes. There were regional differences in ranking of these quality attributes but no gender difference. This information will be useful in determining food quality indicators that can be used to select breeding lines for preferred quality traits in pounded yam.

Indexed as

Appearanceend‐user preferencesfood product profileNigeriapounded yamquality traitregiontextural quality gender

Identifiers

PMID33776246
PMCPMC7984093

What OpenQuestion holds

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Registered trials

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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.