Laser-induced Fluorescence Spectroscopy (LIFS) for Discrimination of Genetically Close Sweet Orange Accessions (Citrus sinensis L. Osbeck)

Abstract

Although there is substantial diversity among cultivated sweet oranges genotypes with respect to morphological, physiological, and agronomic traits, very little variation at DNA level has been observed. It is possible that this low DNA molecular variability is due to a narrow genetic basis commonly observed in this citrus group. The most different morphological characters observed were originated through mutations, which are maintained by vegetative propagation. Despite all molecular tools available for discrimination between these different accessions, in general, low polymorphism has been observed in all groups of sweet oranges and they may not be identified by molecular markers. In this context, this paper describes the results obtained by using laser-induced fluorescent spectroscopy (LIFS) as a tool to discriminate sweet orange accessions ( Citrus sinensis L. Osbeck) including common, low acidity, pigmented, and navel orange groups, with very little variation at DNA level. The findings showed that LIFS combined with statistical methods is capable to discriminate different accessions. The basic idea is that citrus leaves have multiple fluorophores and concentration depends on their genetics and metabolism. Thus, we consider that the optical properties of citrus leaves may be different, depending on variety. The results have shown that the developed method, for the best classification rate, reaches an average sensitivity and specificity of 95% and 97.5%, respectively. An interesting application of this study is the development of an economically viable tool for early identification in seedling certification, in citrus breeding programs, in cultivar protection, or in germplasm core collection.

Discrimination of Genetically Very Close Accessions of Sweet Orange (Citrus sinensis L. Osbeck) by Laser-Induced Breakdown Spectroscopy (LIBS)

“…The LIBS analysis was performed within 24 h after collection. During this time, the leaves were maintained in bags and refrigerated at 4 °C to avoid degradation and drying [ 7 ].…”

“…For each leaf sample, ten measurements were performed and averages were calculated to minimize uncertainties due to the biological heterogeneity of samples. Accessions from the same variety were not measured in sequence to avoid interference [ 7 ]. The software OOIBase32 developed by Ocean Optics was used for data acquisition.…”

“…To achieve the differentiation between classes, 13,560 spectral points in the average broadband spectrum of each sample were used as input variables in the classifier model. The two data sets consisting of either the 23 selected elemental peak areas or the whole LIBS emission spectra were exported to the open-source software Weka to yield the classifiers obtained by combining CVR and the regression function via PLSR [ 7 , 22 , 23 , 24 ].…”

“…The performance of the CVR associated with the PLSR classifier was calculated using two parameters, sensitivity, and specificity, which are described in terms of True Positive ( TP ), True Negative ( TN ), False Positive ( FP ), and False Negative ( FN ) according to Equations (1) and (2) below [ 7 , 25 ]: …”

“…To assist citrus breeding programs and advance the research on the discrimination of orange variety accessions in Brazil, the Optic and Photonic Laboratory of Embrapa Instrumentation and the Agronomic Institute of Campinas (IAC) joined efforts to establish and validate a rapid and efficient method for the identification and discrimination of orange accessions. To this purpose, laser-induced fluorescence spectroscopy (LIFS) showed to be a promising suitable certification tool able to discriminate orange accessions [ 5 , 6 , 7 ].…”