Non-destructive determination of the oil content in peach palm (<i>Bactris gasipaes</i>) flour using NMR and NIR spectroscopies

SANTOS, Yves José de Souza; CAMPOS, Natalia Alves; BICCA, Gerson Balbueno; SORA, Gisele Teixeira de Souza; POLESI, Luis Fernando; ALBERTE, Tania Maria; SANTOS, Poliana M.; GARCIA, Rodrigo Henrique dos Santos; COLNAGO, Luiz Alberto; OLIVEIRA-FOLADOR, Gabrieli

doi:10.1590/fst.112322

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Original Article • Food Sci. Technol 43 • 2023 • https://doi.org/10.1590/fst.112322 linkcopy

Non-destructive determination of the oil content in peach palm (Bactris gasipaes) flour using NMR and NIR spectroscopies

Authorship SCIMAGO INSTITUTIONS RANKINGS

The oil from the fruit of peach palm or Pupunha (Bactris gasipaes) is an example of a material with low-cost and good antioxidant capacity. However, Conventional methods for measuring oil content are time-consuming, labor-intensive and use toxic chemicals. In this sense, the aim of this study was evaluated fast and non-destructive spectroscopy methods, such as Near Infrared (NIR) and Time-Domain Nuclear Magnetic Resonance (TD-NMR) (CPMG and ROSE pulse sequences), to quantify the oil content in pupunha flours collected in the amazon forest. For this, 93 samples were used and the results showed three distinct levels of oil in the samples: high, medium and low oil content. Furthermore, the determination coefficient (R²) reached values of 0.92, 0.92 and 0.70 for NIR, TD-NMR (ROSE) and TD-NMR (CPMG), respectively. Therefore, the NIR and TD-NMR (ROSE) methods demonstrate a higher prediction efficiency, with the NIR achieving 100% classification of the samples.

Keywords:
pupunha; Amazonian fruit; oil content; NIR; TD-RMN

Technique	LV	Correct classification (%)
Technique	LV	Class 1	Class 2	Class 3	Average
NIR	3	83.3	60.0	100.0	81.1
TD-NMR (ROSE)	2	66.7	100.0	53.8	73.5
TD-NMR(CPMG)	2	0.0	40.0	83.3	41.1

Technique	LV	% Correct classification
Technique	LV	Class 1	Class 2	Average
NIR	3	100.0	100.0	100.0
TD-NMR (ROSE)	3	81.8	84.6	83.2
TD-NMR(CPMG)	3	72.7	84.6	78.7

REGRESSION PARAMETERS	NIR	TD-NMR (ROSE)	TD-NMR (CPMG)
Number of LV	4	2	2
RMSEC	0.96	1.00	1.39
RMSECV	1.11	1.19	1.54
RMSEP	1.39	1.54	1.88
R²cal	0.92	0.92	0.70
R²val	0.70	0.71	0.58
RPDcal	3.17	2.96	1.72
RDPval	1.97	1.78	1.46

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[1] RMSEC: Root Mean Square Error of Calibration; RMSECV: Root Mean Square Error of Cross validation; REMSEP: Root Mean Square Error of Prediction; RPD: Residual Prediction Deviation; cal: calibration group; val: validation group; R²: determination coefficient.