Quantification of Photosynthetic Pigments in Neopyropia yezoensis Using Hyperspectral Imagery

Phycobilisomes and chlorophyll-a ( ) play important roles in the photosynthetic physiology of red macroalgae and serve as the primary light-harvesting antennae and reaction center for photosystem II. is an economically important red macroalga widely cultivated in East Asian countries. The contents and ratios of 3 main phycobiliproteins and are visible traits to evaluate its commercial quality. The traditional analytical methods used for measuring these components have several limitations. Therefore, a high-throughput, nondestructive, optical method based on hyperspectral imaging technology was developed for phenotyping the pigments phycoerythrin (PE), phycocyanin (PC), allophycocyanin (APC), and in thalli in this study. The average spectra from the region of interest were collected at wavelengths ranging from 400 to 1000 nm using a hyperspectral camera. Following different preprocessing methods, 2 machine learning methods, partial least squares regression (PLSR) and support vector machine regression (SVR), were performed to establish the best prediction models for PE, PC, APC, and contents. The prediction results showed that the PLSR model performed the best for PE ( = 0.96, MAPE = 8.31%, RPD = 5.21) and the SVR model performed the best for PC ( = 0.94, MAPE = 7.18%, RPD = 4.16) and APC ( = 0.84, MAPE = 18.25%, RPD = 2.53). Two models (PLSR and SVR) performed almost the same for (PLSR: = 0.92, MAPE = 12.77%, RPD = 3.61; SVR: = 0.93, MAPE = 13.51%, RPD =3.60). Further validation of the optimal models was performed using field-collected samples, and the result demonstrated satisfactory robustness and accuracy. The distribution of PE, PC, APC, and contents within a thallus was visualized according to the optimal prediction models. The results showed that hyperspectral imaging technology was effective for fast, accurate, and noninvasive phenotyping of the PE, PC, APC, and contents of in situ. This could benefit the efficiency of macroalgae breeding, phenomics research, and other related applications.