Evidence map›Paper›PMID 29225662›Full record

ArticlePlant methods2017

Increased accuracy of starch granule type quantification using mixture distributions.

Emi Tanaka, Jean-Phillippe F Ral, Sean Li, Raj Gaire, Colin R Cavanagh, Brian R Cullis, Alex Whan

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Article in Plant methods, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Emi TanakaSchool of Mathematics and Applied Statistics, University of Wollongong, Northfields Ave, Wollongong, 2522 Australia.ORCID 0000-0002-1455-259X
Jean-Phillippe F RalCSIRO Agriculture and Food, 1600 Clunies Ross Street, Canberra, 2601 Australia.
Sean LiCSIRO Agriculture and Food, 1600 Clunies Ross Street, Canberra, 2601 Australia.
Raj GaireCSIRO Agriculture and Food, 1600 Clunies Ross Street, Canberra, 2601 Australia.
Colin R CavanaghBayer CropScience Pty Ltd, Seeds, Technologiepark 38, 9052 Zwijnaarde (Gent), Belgium.
Brian R CullisSchool of Mathematics and Applied Statistics, University of Wollongong, Northfields Ave, Wollongong, 2522 Australia.
Alex WhanCSIRO Agriculture and Food, 1600 Clunies Ross Street, Canberra, 2601 Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe proportion of granule types in wheat starch is an important characteristic that can affect its functionality. It is widely accepted that granule types are either large, disc-shaped A-type granules or small, spherical B-type granules. Additionally, there are some reports of the tiny C-type granules. The differences between these granule types are due to its carbohydrate composition and crystallinity which is highly, but not perfectly, correlated with the granule size. A majority of the studies that have considered granule types analyse them based on a size threshold rather than chemical composition. This is understandable due to the expense of separating starch into different types. While the use of a size threshold to classify granule type is a low-cost measure, this results in misclassification. We present an alternative, statistical method to quantify the proportion of granule types by a fit of the mixture distribution, along with an R package, a web based app and a video tutorial for how to use the web app to enable its straightforward application.

resultsOur results show that the reliability of the genotypic effects increase approximately 60% using the proportions of the A-type and B-type granule estimated by the mixture distribution over the standard size-threshold measure. Although there was a marginal drop in reliability for C-type granules. The latter is likely due to the low observed genetic variance for C-type granules.

conclusionsThe determination of the proportion of granule types from size-distribution is better achieved by using the mixing probabilities from the fit of the mixture distribution rather than using a size-threshold.

Indexed as

Granule typeMastersizerMixture distributionStarch

Identifiers

PMID29225662
PMCPMC5718142

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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.