A Two-tiered system of analysis to tackle rice fraud: The Indian Basmati study

Maeve Shannon*, Terry McGrath, Christopher Elliott, Ratnasekhar Ch

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)
30 Downloads (Pure)

Abstract

Demand for high quality Basmati rice has increased significantly in the last decade. This commodity is highly vulnerable to fraud, especially in the post COVID-19 era. A unique two-tiered analytical system comprised of rapid on-site screening of samples using handheld portable Near-infrared NIR and laboratory confirmatory technique using a Head space gas chromatography mass spectrometry (HS-GC-MS) strategy for untargeted analysis was developed. Chemometric models built using NIR data correctly predicted nearly 100% of Pusa 1121 and Taraori, two high value types of Basmati, from potential adulterants. Furthermore, rice VOC profile fingerprints showed very good classification (R2 >0.9, Q2 > 0.9, Accuracy > 0.99) for these high quality Basmati varieties from potential adulterant varieties with aldehydes identified as key VOC marker compounds. Using a two-tiered system of a rapid method for on-site screening of many samples alongside a laboratory-based confirmatory method can classify Basmati rice varieties, protecting the supply chain from fraud.
Original languageEnglish
Article numberTAL_122038
JournalTalanta
Early online date19 Dec 2020
DOIs
Publication statusEarly online date - 19 Dec 2020

Fingerprint

Dive into the research topics of 'A Two-tiered system of analysis to tackle rice fraud: The Indian Basmati study'. Together they form a unique fingerprint.

Cite this