Molecular Diversity and Combining Ability in Newly Developed Maize Inbred Lines under Low-Nitrogen Conditions

Abstract

Nitrogen is an essential element for maize growth, but excessive application can lead to various environmental and ecological issues, including water pollution, air pollution, greenhouse gas emissions, and biodiversity loss. Hence, developing maize hybrids resilient to low-N conditions is vital for sustainable agriculture, particularly in nitrogen-deficient soils. Combining ability and genetic relationships among parental lines is crucial for breeding superior hybrids under diverse nitrogen levels. This study aimed to assess the genetic diversity of maize inbred lines using simple sequence repeat (SSR) markers and evaluate their combining ability to identify superior hybrids under low-N and recommended conditions. Local and exotic inbred lines were genotyped using SSR markers, revealing substantial genetic variation with high gene diversity (He = 0.60), moderate polymorphism information content (PIC = 0.54), and an average of 3.64 alleles per locus. Twenty-one F1 hybrids were generated through a diallel mating design using these diverse lines. These hybrids and a high yielding commercial check (SC-131) were field-tested under low-N and recommended N conditions. Significant variations (p < 0.01) were observed among nitrogen levels, hybrids, and their interaction for all recorded traits. Additive genetic variances predominated over non-additive genetic variances for grain yield and most traits. Inbred IL3 emerged as an effective combiner for developing early maturing genotypes with lower ear placement. Additionally, inbreds IL1, IL2, and IL3 showed promise as superior combiners for enhancing grain yield and related traits under both low-N and recommended conditions. Notably, hybrids IL1×IL4, IL2×IL5, IL2×IL6, and IL5×IL7 exhibited specific combining abilities for increasing grain yield and associated traits under low-N stress conditions. Furthermore, strong positive associations were identified between grain yield and specific traits like plant height, ear length, number of rows per ear, and number of kernels per row. Due to their straightforward measurability, these relationships underscore the potential of using these traits as proxies for indirect selection in early breeding generations, particularly under low-N stress. This research contributes to breeding nitrogen-efficient maize hybrids and advances our understanding of the genetic foundations for tolerance to nitrogen limitations.

Keywords: genetic diversity; hybrid breeding; microsatellite markers; nitrogen deficiency; sustainable agriculture.

Figure 1

The minimum and maximum temperatures along with solar radiation levels, were recorded across the growing seasons.

Figure 2

(A) depicts gene diversity and Polymorphic Information Content (PIC) for each marker, and (B) illustrates the number of alleles per locus.

Figure 3

Dendrogram of the assessed inbreds based on applied SSR markers. The evaluated inbred lines were grouped into four primary clusters, each with varying levels of genetic diversity.

Figure 4

Comparative performance of developed 21 F1 hybrids and check hybrid (SC-131): 1 days to silking (A), plant height (B), ear height (C), and ear length (D). The bars on the tops of the columns represent the SE, and different letters on the columns show the significant difference using the Least Significant Difference (LSD) (p < 0.05). The uppercase letters belong to low N while the lowercase letters belong to the recommended conditions.

Figure 5

Comparative performance of developed 21 F1 hybrids and check hybrid (SC-131): number of rows per ear (A), number of kernels per row (B), 1000-kernel weight (C), and grain yield (D). The bars on the tops of the columns represent the SE, and different letters on the columns show the significant difference using the Least Significant Difference (LSD) (p < 0.05). The uppercase letters belong to low N while the lowercase letters belong to the recommended conditions.

Figure 6

Dendrogram of phenotypic distances among twenty-one hybrids and commercial check SC-131 based on the yield traits. The evaluated twenty-one F1 maize hybrids and the commercial check SC-131 were clustered based on yield characteristics into six groups. Group A exhibited the highest yield and related traits while group F showed the lowest agronomic performance.

Figure 7

PC-biplot (A) and heatmap and hierarchical clustering (B) were used to study the association between agronomic traits and develop maize hybrids. PH: plant height; DS: days to silking; EL: ear length; NRE: number of rows/ear; NKR: number of kernels/row; GY: grain yield; and TKW: 1000-kernel weight.