Cited by 35Probiotics and Fermented FoodsFermentation and Sensory AnalysisAdvanced Scientific Research Methods

Assessment of wild non-dairy lactococcal strains for flavour diversification in a mini-Gouda type cheese model

Cavanagh, Daniel, Kilcawley, Kieran N., O'Sullivan, Maurice G., Fitzgerald, Gerald F., McAuliffe, Olivia·2014·Food Research International

Abstract

Wild lactococci possess enhanced metabolic capabilities in comparison to industrial dairy strains, including increased amino acid-converting enzyme activities. A bank of Lactococcus lactis strains isolated from different non-dairy environments exhibited wider carbohydrate fermentation profiles in comparison to dairy lactococcal strains. In addition, these non-dairy lactococci had the ability to ferment lactose and produce diverse aroma profiles when grown in milk. Based on volatile analysis, five of these non-dairy strains were selected and investigated as adjuncts to diversify cheese flavour using a mini-Gouda cheesemaking process model and compared to a cheese manufactured with a commercial adjunct. In total, 8 different cheeses were evaluated in duplicate and ripened for 14days at 12°C, followed by 8°C for 84days thereafter. Physicochemical analysis of cheeses was performed at day 14 and sensory evaluation at day 84. Viable counts, intracellular enzyme activity and indices of proteolysis were monitored over ripening. The ability of the non-dairy strains to survive, lyse, and release intracellular enzymes and alter proteolysis was strain dependent. Some strains performed as well as the commercial adjunct in terms of secondary proteolysis although others were associated with bitterness and development of off-flavours and off-aromas. Attenuation of DPC6853 positively reduced its association with bitterness during ripening. It is evident that non-dairy strains have potential as adjuncts in semi-hard type cheeses, and could be harnessed to diversify flavour profiles in semi-hard cheese varieties.

Integrity signals

Registry

Crossref · 10.1016/j.foodres.2014.03.043

Cites

43 of 43 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Authors
Cavanagh, D., Kilcawley, K. N., O'Sullivan, M. G., Fitzgerald, G. F., & McAuliffe, O.
Affiliations
  • Teagasc - The Irish Agriculture and Food Development Authority (IE)
  • University College Cork (IE)
Corresponding author
Kilcawley, Kieran N.
Venue
Food Research International
Publisher
Elsevier BV
Published
2014-08
Volume
62
Pages
432-440
ISSN
0963-9969 (ISSN-L)
OpenAlex
W1969721405
Cited by
35
References
43
Citations by year
2025: 1 · 2024: 3 · 2023: 3 · 2021: 4 · 2020: 3 · 2019: 1 · 2018: 9 · 2017: 3 · 2016: 5 · 2015: 2 · 2014: 1
FWCI
5.25
Type
journal article
Language
en
Open access
closed
Locations
Food Research International (publishedVersion)
Topics
  • Life Sciences › Agricultural and Biological Sciences › Food Science › Probiotics and Fermented Foods
  • Life Sciences › Agricultural and Biological Sciences › Food Science › Fermentation and Sensory Analysis
  • Life Sciences › Agricultural and Biological Sciences › Food Science › Advanced Scientific Research Methods
Keywords
Lactococcus lactis, cheese flavor, semi-hard cheese, proteolysis, intracellular enzymes, off-flavor, bitterness, volatile compounds, carbohydrate fermentation, lactic acid bacteria, cheese ripening, strain selection

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review