Optimization of near-infrared reflectance models in determining flavonoid composition of okra (Abelmoschus esculentus L.) pods.

Abstract

Okra pods have been utilized as a functional food due to their rich active ingredient composition, especially the high content of flavonoid compounds. This study conducted near-infrared spectroscopy (NIRS) modeling optimization and external validation based on the flavonoid components of 219 pod samples. Spectral correlation analyses identified two types of spectral response patterns classified as quercetin-3-O-xylose (1-2) glucoside (QOXG) and total flavonoid content (TFC), consisting of six different spectral regions. Different modeling effects were observed for QOXG and TFC with various spectral region combination analyses, where the lower wave-number region contributed more to both flavonoids calibration models. The combination of standard normal variate / "1, 9, 3" / partial least squares was found to be the most effective for developing calibration models for both flavonoids. The resulting models had small root mean square errors of prediction for external validation and high determination coefficients, indicating their usefulness for rapid prediction of flavonoid composition in okra pods.