Molecular Plant Breeding 2025, Vol.16, No.1, 93-104 http://genbreedpublisher.com/index.php/mpb 95 Figure 1 Nutritional quality of different components of a maize kernel (Adopted from Prasanna et al., 2020) 3 Comprehensive Methodological Framework 3.1 Strategic selection of diverse genetic maize varieties The strategic selection of diverse genetic maize varieties is fundamental to breeding programs aimed at enhancing protein content. This process involves identifying and utilizing a wide range of genetic resources to ensure a broad genetic base. For instance, the study by Jaradat and Goldstein (2013) utilized multivariate statistical procedures to quantify total diversity and its components across 31 traits in 1348 maize accessions. This approach allowed for the identification of physical and color traits useful for selecting accessions with high protein and nutrient contents. Similarly, the research conducted by Okporie et al. (2013) sourced genetic materials from a gene bank and developed high-protein maize populations through three cycles of reciprocal recurrent selection. Moreover, understanding the genetic diversity and population structure is crucial for predicting hybrid performance. Abu et al. (2021)’s study on tropical extra-early maturing quality protein maize (QPM) inbred lines under low soil nitrogen stress, assessed 110 inbred lines using SNP markers, revealing significant genetic distances and clustering based on endosperm color, pedigree, and selection history. This genetic variability is essential for breeding programs aiming to enhance protein content while maintaining other agronomic traits. 3.2 Detailed description of crossbreeding and selection methodologies Crossbreeding and selection methodologies are pivotal in developing high-protein maize varieties. Mass selection, as described in the study by the Crop Science Society of America (Bletsos and Goulas, 1999), involves a two-step selection procedure. Plants with grain yield higher than 80% of the check-plant mean and protein concentration greater than the check-plant mean were selected. The four plants within each selection grid with the highest protein concentration were chosen, resulting in a final selection intensity of 5%. This method, although not particularly effective after three cycles, highlights the iterative nature of selection in breeding programs. Reciprocal recurrent selection is another effective methodology. Okporie et al. (2013)’s study at Ebonyi State University demonstrated the development of high-protein maize populations through three cycles of this method. This approach involves selecting and intercrossing the best individuals from two populations to combine desirable traits. Additionally, the use of genomic selection (GS) can accelerate the breeding cycle by facilitating the rapid selection of superior genotypes. GS integrates genomic-enabled prediction models to enhance the efficiency of breeding programs, as discussed in a review on genomic selection in plant breeding (Crossa et al., 2017).
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