Rapid Determination of Crocin‐I in Gardenia Fruits (Gardenia jasminoides Ellis) by Combining Spectral and Image Data Through Hyperspectral Imaging

ABSTRACT Introduction Crocin‐I, a water‐soluble carotenoid pigment, is an important coloring constituent in gardenia fruit. It has wide application in various industries such as food, medicine, chemical industry, and so on. So the content of crocin‐I plays a key role in evaluating the quality of gardenia. Objective We assessed crocin‐I content in gardenia with a rapid, nondestructive, and convenient method. Method The data of gardenia samples were scanned under a portable visible–near‐infrared (Vis–NIR) hyperspectral imaging (HSI) in the spectral range of 400–1000 nm. Afterward, the spectral data along with image‐related information, encompassing color and texture, were extracted from the HSI. Based on a single information and its fusion at different fusion levels (low‐level, traditional mid‐level fusion, and an improved mid‐level fusion), partial least squares regression (PLSR) prediction models were established and compared. Result The results demonstrated the superiority of data fusion, which ingeniously combined spectra and image data. Compared with individual information sources, the traditional mid‐level fusion model showed a robust predictive ability. The correlation coefficient of the prediction set (R p ), the root mean square error of prediction (RMSEP), and the ratios of performance to deviation (RPDP) of the model were 0.901, 0.962, and 2.262, respectively. Conclusion This study highlights the effectiveness of the data fusion method, showcasing its capacity to significantly enhance the prediction accuracy of crocin‐I content in gardenia through the integration of hyperspectral mapping data. The findings of this research are anticipated to serve as a valuable reference for predicting the active ingredients of other Chinese herbal medicines.