Skip to main content
Log in

Mid-infrared and near-infrared spectroscopies to classify improper fermentation of pineapple wine

  • Original Paper
  • Published:
Chemical Papers Aims and scope Submit manuscript


Improper fermentation of pineapple wine owing to volatile acidity has been associated with excessive proliferation of acetic acid bacteria during fermentation and consequent increased acetic acid concentration. Mid-infrared (MIR) and near-infrared (NIR) spectroscopies were employed to classify improper pineapple wine fermentation. Two clusters of samples possessing within the limit and over-limit acetic acid content were obtained using low-grade pineapples and prepared accordingly. Spectral data were collected for all samples in the 4000–650 cm−1 region using attenuated total reflection (ATR) with an FT-MIR spectrophotometer and in the 11,536–5800 cm−1 using sample vials and 11,536–3952 cm−1 regions using a liquid probe and a liquid cup with an FT-NIR spectrophotometer. The classification models for pineapple wine fermentation based on acetic acid content were constructed using soft independent modeling of class analogy (SIMCA) and partial least squares discriminant analysis (PLSDA). Comparisons of MIR and NIR techniques, classification methods, and spectral pretreatments have been reported. The results demonstrated that MIR spectroscopy coupled with ATR and PLSDA is highly effective for the detection of improper pineapple wine fermentation as a function of acetic acid content. The best classification model was generated using the entire MIR spectra after second derivatives transformation, which provided the highest accuracy, sensitivity, specificity, and precision.

Graphical abstract

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

Data availability

All data generated or analyzed during this study are included in this published article.


Download references


S.K. thanks Yiping Du for his technical assistance. The authors gratefully thank the KURDI committee for valuable discussion and comments. This research was funded by the Kasetsart University Research and Development Institute (KURDI), grant number FF(KU)15.64.

Author information

Authors and Affiliations



SK contributed to conceptualization, funding acquisition, investigation, and writing—original draft preparation, KN contributed to experiment setup and validation, SJ contributed to review and editing original draft preparation, WA and PJ contributed to formal analysis and performed methodology, PV contributed to resource and visualization, and AB contributed to fermentation methodology, supervision and project administration.

Corresponding author

Correspondence to Sumaporn Kasemsumran.

Ethics declarations

Conflict of interest

Sumaporn Kasemsumran declares that she has no conflict of interest. Antika Boondaeng declares that she has no conflict of interest. Kraireuk Ngowsuwan declares that he has no conflict of interest. Sunee Jungtheerapanich declares that she has no conflict of interest. Waraporn Apiwatanapiwat declares that she has no conflict of interest. Phornphimon Janchai declares that she has no conflict of interest. Pilanee Vaithanomsat declares that she has no conflict of interest.

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 16 kb)

Rights and permissions

Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kasemsumran, S., Boondaeng, A., Ngowsuwan, K. et al. Mid-infrared and near-infrared spectroscopies to classify improper fermentation of pineapple wine. Chem. Pap. 77, 335–349 (2023).

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: