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Food and Bioprocess Technology

, Volume 11, Issue 4, pp 785–796 | Cite as

FTNIR-A Robust Diagnostic Tool for the Rapid Detection of Rhyzopertha dominica and Sitophilus oryzae Infestation and Quality Changes in Stored Rice Grains

  • Shubhangi Srivastava
  • Gayatri Mishra
  • Hari Niwas Mishra
Original Paper

Abstract

Fourier transform infrared spectroscopy (FTNIR) is an excellent mode for evaluation of grain-quality attributes. It enables the nonperturbative molecular information to be diagnosed and allows the explication of images of grains by the passage of the spectral data through an array of computational algorithms. The images are contrived from fingerprint spectra so the conception is that the reflection can conceal the status of the analyzed sample. Rhyzopertha dominica F.- and Sitophilus oryzae-infested and fresh rice grains analyzed with FTNIR within a range of 12,000–4000 cm−1 were proffered to mathematical processing. Partial least squares regression (PLSR) was used for the estimation of physicochemical parameters of rice grains. Outstanding predictive results were acquired denoting that infested rice grains could be convincingly quantified. The coefficient of correlation, root mean square error of validation, and cross validation for the FTNIR model developed to quantify the quality attribute changes with infestation in rice grains were in the range of 99.85–99.01% (R2), 0.2–1.14% (RMSEE), and 0.3–1.25% (RMSECV). Excellent prediction results of various physico-chemical attributes were obtained for rice grains indicating the fresh and infested samples can be uniquely identified. Also, a paired t test was performed to compare the analytical methods with FTNIR-developed method; no significant difference was found (tcal 0.025 < tcri 2.12; α = 0.05, RPD > 6) between the two methods. Thus, the results further confirmed the developed FTNIR system to be inherently rapid, clean, and capable of preventing hazardous chemicals which originates from traditional analytical processes and has the potential for monitoring and sorting of rice grains.

Keywords

FTNIR method Preprocessing Spectra Absorbance Analytical 

Notes

Compliance with Ethical Standards

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

Conflict of Interest

The authors declare that they have no conflict of interest.

Ethical Approval

Not applicable.

Informed Consent

Not applicable

Supplementary material

11947_2017_2048_MOESM1_ESM.doc (1.6 mb)
ESM 1 (DOC 1620 kb)

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Agricultural and Food Engineering DepartmentIndian Institute of TechnologyKharagpurIndia

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