Open Access

Correction to: Meta-barcoding in combination with palynological inference is a potent diagnostic marker for honey floral composition

  • Rama Chandra Laha1Email author,
  • Surajit De Mandal1,
  • Lalhmanghai Ralte1,
  • Laldinfeli Ralte1,
  • Nachimuthu Senthil Kumar1,
  • Guruswami Gurusubramanian1,
  • Ramalingam Satishkumar2,
  • Raja Mugasimangalam3 and
  • Nagesh Aswathnarayana Kuravadi4
AMB Express20177:189

https://doi.org/10.1186/s13568-017-0489-8

Received: 3 October 2017

Accepted: 3 October 2017

Published: 11 October 2017

The original article was published in AMB Express 2017 7:132

In the version of this article that was originally published (Laha et al. 2017) the authors did not properly reference one paragraph in the Introduction section.

Correction to: AMB Expr (2017) 7:132 DOI 10.1186/s13568-017-0429-7

In the version of this article that was originally published (Laha et al. 2017) the authors did not properly reference one paragraph in the Introduction section.

“While some efforts have been made to develop protocols to ascertain the entomological sources of honey (Schnell et al. 2010), most have focused on identifying its plant origin. Past studies have often relied upon diagnostic phytochemicals (Cotte et al. 2004; Tosun 2013) or the study of pollen in honey (melissopalynology) (Alves and Santos 2014). Although the latter approach requires considerable expertise and cannot distinguish many plant species (Kaškonienė and Venskutonis 2010), yet it is a powerful diagnostic tool, especially when used with other methods (Hawkins et al. 2015). However, melissopalynology is ineffective in cases where low value honey is filtered to remove its source pollen and spiked with pollen from the desired monoflora (Kaškonienė and Venskutonis 2010).”

The authors wish to acknowledge the article “Rapid identification of the botanical and entomological sources of honey using DNA metabarcoding” by Sean W.J. Prosser and Paul D.N. Hebert as reference for this paragraph (Prosser and Hebert 2017). The authors wish to apologize for this omission.

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Authors’ Affiliations

(1)
Departments of Botany, Biotechnology and Zoology, School of Life Sciences, Mizoram University
(2)
Department of Biotechnology, Bharathiar University
(3)
Genotypic Technologies
(4)
QTLomics Technologies

References

  1. Laha RC, De Mandal S, Ralte L, Ralte L, Kumar NS, Gurusubramanian G, Satishkumar R, Mugasimangalam R, Kuravadi NA (2017) Meta-barcoding in combination with palynological inference is a potent diagnostic marker for honey floral composition. AMB Expr 7:132. doi:10.1186/s13568-017-0429-7 View ArticleGoogle Scholar
  2. Prosser SW, Hebert PD (2017) Rapid identification of the botanical and entomological sources of honey using DNA metabarcoding. Food Chem 214:183–191View ArticlePubMedGoogle Scholar

Copyright

© The Author(s) 2017