Are stomatal area and stomatal density reliable traits for identification of doubled haploids in maize?

Abstract

To meet the demands of the production chain, breeding programs need to reduce the time for selection and development of higher yielding maize genotypes. This involves application of new strategies, such as the use of the doubled haploid lines. We evaluated the use of stomatal area and density in distinguishing doubled haploids (DH) from false positive (FP) plants derived from nine tropical source populations. We selected four DH plants and two FP plants for identification of DH through leaf anatomy in the populations, in each group. Data on stomatal area and density were considered in a completely randomized model in a factorial scheme (populations and genotypes) and analyzed by restricted maximum likelihood. There were statistically significant effects of populations and genotypes for both traits. For stomatal density, the population by genotype interaction was not verified. Stomatal density proved to be efficient for distinguishing DH and FP for use in selection of doubled haploids.

Use of machine learning models-based image analysis for classification of haploid and diploid maize

“…Jones et al (2012) achieved haploid discrimination with a success rate of 87.5% using NIR spectroscopy. Ribeiro et al (2022) suggested that stomata density is an efficient parameter for distinguishing doubled haploids from false positives in in vivo haploid technique. The prediction model created in our study achieved similar success to these methods.…”

“…For this reason, alternative methods that can perform seed discrimination in a more practical way are emphasized. There are numerous approaches to separate haploid and diploid seeds such as stomata measurements (Ribeiro et al 2022), flow cytometry (Baleroni et al 2021), near infrared reflectance (NIR) spectroscopy (Jones et al 2012, Liu et al 2017, Cui et al 2019, near infrared transmittance (NIT) spectroscopy (Lin et al 2017) and image analysis (Veeramani et al 2018). Among these methods, image analysis is one of the alternatives with significant advantages.…”

Early haploid identification by stomatal guard cell length in tropical supersweet corn using different inducers

“…Other strategies such as flow cytometry (Couto et al 2013, Baleroni et al, 2021, chromosome counts (Sekiya et al 2020), and molecular markers (Ribeiro et al 2018) can be used, but are less efficient, expensive and laborious. Therefore, the use of morphological traits of seedlings and plants (Chaikam et al 2017), such as first-leaf-sheath color (Sekiya et al 2020) associated with stomatal guard cell length or area (Choe et al 2012, Ribeiro et al 2022, are important alternatives for haploid identification in corn. The green first-leaf-sheath is a recessive characteristic and can be observed in some corn genotypes, such as the supersweet genotypes studied by Sekiya et al (2020), which allows 100% accuracy in the early haploid seedling selection, as the diploid inducers and F1's have a purple first-leaf-sheath.…”