Attenuated Total Reflection Fourier Transform Infrared Spectroscopy with Soft Independent Modeling of Class Analogy–Principal Component Analysis for Classifying Cotton Fiber Maturity Phenotypes of Cotton Population Composed of Various Genotypes

Abstract

Maturity is a major fiber trait that affects the processing and performance of cotton fiber. Rapid and accurate identification of fiber maturity phenotypes and genotypes is of importance to breeders. Previous studies showed that either conventional fiber measurements or attenuated total reflection Fourier transform infrared spectroscopy (ATR FT-IR) analysis discriminated the immature fiber ( im) phenotype from the wild type (WT) mature fiber phenotype in a segregating F2 population from a cross between two upland cotton lines differing in fiber maturity. However, both conventional fiber property measurement methods and FT-IR analyses with current algorithms could not detect the subtle differences among the WT fibers composed of two different genotypes, WT homozygosity (WT-homo) and WT heterozygosity (WT-hetero). This research explored the FT-IR method, in combination with soft independent modeling of class analogy of principal component analysis (SIMCA–PCA), for the discrimination of WT fiber phenotypes consisting of two different genotypes (WT-homo and WT-hetero). The new approach enabled the detection of IR spectral intensity differences between WT-homo and WT-hetero fibers. Successful classification originated from a distinctive spectral difference in the low-wavenumber region (<700 cm–1) between WT-hetero fibers and WT-homo fibers. This observation emphasized that ATR FT-IR with a SIMCA–PCA approach would be a sensitive tool for classifying the WT fibers demonstrating minor phenotypic differences. The improved sensitivity of the infrared method may provide a way of dissecting genotype–phenotype interactions of cotton fibers rapidly and efficiently.