Location: Cotton Fiber Bioscience ResearchTitle: Feasibility assessment of phenotyping cotton fiber maturity using infrared spectroscopy and algorithms for genotyping analyses
Submitted to: Journal of Cotton Research
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 6/17/2019
Publication Date: 7/4/2019
Citation: Kim, H.J., Liu, Y., Fang, D.D., Delhom, C.D. 2019. Feasibility assessment of phenotyping cotton fiber maturity using infrared spectroscopy and algorithms for genotyping analyses. Journal of Cotton Research. 2:8. https://doi.org/10.1186/s42397-019-0027-0.
Interpretive Summary: Cotton fiber maturity or thickness is an important fiber property for determining commercial value of cotton fibers. Current methods of measuring cotton fiber thickness for biological and genetic analyses are expensive, laborious and time-consuming process. We have shown that a combination of an algorithm and Fourier transform infrared (FT-IR) spectroscopy can rapidly and efficiently estimate cotton fiber maturity that can classify immature fiber phenotype from mature fiber phenotype from a genetic population consisting of a large number of progeny plants. Thus, the new method provides an option for cotton breeders for genetic analyses and potentially helps them develop strategic plans to improve fiber maturity.
Technical Abstract: Background: Cotton fiber maturity is an important property that partially determines the processing and performance of cotton. Due to difficulties of obtaining fiber maturity values accurately from every plant of a genetic population, cotton geneticists often use micronaire (MIC) and/ or lint percentage for classifying immature phenotypes from mature fiber phenotypes although they are complex fiber traits. The recent development of an algorithm for determining cotton fiber maturity (MIR) from Fourier transform infrared (FT-IR) spectra explores a novel way to measure fiber maturity efficiently and accurately. However, the algorithm has not been tested with a genetic population consisting of a large number of progeny plants. Results: The merits and limits of the MIC- or lint percentage-based phenotyping method were demonstrated by comparing the observed phenotypes with the predicted phenotypes based on their DNA marker genotypes in a genetic population consisting of 708 F2 plants with various fiber maturity. The observed MIC-based fiber phenotypes matched to the predicted phenotypes better than the observed lint percentage-based fiber phenotypes. The lint percentage was obtained from each of F2 plants, whereas the MIC values were unable to be obtained from the entire population since certain F2 plants produced insufficient fiber mass for their measurements. To test the feasibility of cotton fiber infrared maturity (MIR) as a viable phenotyping tool for genetic analyses, we measured FT-IR spectra from the second population composed of 80 F2 plants with various fiber maturities, determined MIR values using the algorithms, and compared them with their genotypes in addition to other fiber phenotypes. The results showed that MIR values were successfully obtained from each of the F2 plants, and the observed MIR-based phenotypes fit well to the predicted phenotypes based on their DNA marker genotypes as well as the observed phenotypes based on a combination of MIC and lint percentage. Conclusions: The MIR value obtained from FT-IR spectra of cotton fibers is able to accurately assess fiber maturity of all plants of a population in a quantitative way. The technique provides an option for cotton geneticists to determine fiber maturity rapidly and efficiently.