Discrimination of Camellia japonica cultivars and chemometric models: An interlaboratory study

Abstract

Camellia japonica is a valued plant since ancient times throughout the world mostly due to their ornamental flowers. It has a high number of cultivars, with very similar phenotypic and genotypic characteristics which are difficult to discriminate, being some of them often rare and with a high price at the market. Their discrimination is mostly done through visual inspection of the morphologic characteristics which is a hard and inefficient task. Spectroscopic techniques had already been used for taxonomic purposes at species and sub-species level with success and could be an alternative for accurate C. japonica cultivars discrimination. Despite the already recognized success of such techniques, most of the studies arises from a single laboratory and little is known about the robustness of these techniques regarding interlaboratory data transferability. In this context, the work developed herein presents a double aim: (I) to explore the ability of near infrared (NIR) spectroscopy and partial least square-discriminant analysis (PLS-DA) to discriminate C. japonica cultivars and (II) to evaluate data transferability between two independent laboratories (Lab A and Lab B). Air-dried leaves NIR spectra of 43 C. japonica plants (15 distinct cultivars) were acquired in both laboratories using two similar NIR instruments (same manufacturer and model). Spectra were further modelled by PLS-DA after exploratory analysis using principal component analysis (PCA): (I) individually for Lab A and Lab B; (II) using Lab A as calibration and Lab B as validation set and vice-versa and (III) with using Lab A and Lab B data together. The percentage of C. japonica cultivars discrimination for both laboratories was nearly the same (around 83%) indicating no significant differences between Lab A and Lab B analysis. However, the results were quite poor when spectra were modelled with data from a single laboratory and validated with the other (65.5 and 63.8%). When data were merged, 85.9% of correct cultivars assignments were obtained. The results herein obtained could benefit of including additional cultivars and plants; but demonstrated the ability of NIR spectroscopy for C. japonica cultivars discrimination. Regarding data transferability, even when dealing with a similar instrument, some issues arisen preventing easy and efficient spectral library transfers.

Discrimination of Gentiana and Its Related Species Using IR Spectroscopy Combined with Feature Selection and Stacked Generalization

“…Among them, near-infrared (NIR) and mid-infrared (MIR) spectroscopy are probably the most publicized technologies [27][28][29][30]. These two technologies can provide detailed structural information on sample properties and composition at the molecular level [31][32][33][34]. Like human fingerprints, the infrared spectrum of any substance has to be unique [31].…”

“…Like human fingerprints, the infrared spectrum of any substance has to be unique [31]. This is the reason for NIR and MIR spectral fingerprints can be applied to identify or classify different samples [31][32][33][34]. In the case of medicinal plants, chemical constituents and their ratios of biochemicals of different species can vary substantially [35,36].…”

Oxidatively Modified Proteins Level in the Muscle Tissue of the Rainbow Trout (Oncorhynchus Mykiss Walbaum) as a Biomarker of Antioxidant Properties of Leaf Extracts of Camellia Japonica L. Cultivars (Theaceae D. Don)

“…tries [30,33]. These plants present vast phenotypic differences, more than 32,000 known cultivars [39], and possess a great economical value due to its beautiful flowers [30].…”

“…The study of its genetic structure revealed that these plants maintain high levels of genetic diversity and a high evolutionary potential which makes them less susceptible to environmental stresses [28]. This could explain with these species are also well adapted in many other countries [33].…”