Effects of Selection–Evaluation Density Interaction on Genetic Gain and Optimization Pathways in Maize Recurrent Breeding Systems

Breaking the maize yield plateau necessitates the development of density-tolerant varieties, for which recurrent selection is a key breeding strategy. However, a systematic understanding of how the interaction between selection density (parental screening environment) and evaluation density (variety testing environment) modulates genetic gain remains a critical knowledge gap. This study aimed to systematically elucidate this interaction and its impact on genetic gain and combining ability. We established two F2 base populations from distinct heterotic groups: Zheng 58 × LH196 (Stiff Stalk, SS) and Chang 7-2 × MBUB (Non-Stiff Stalk, NSS). Through bulk selection, we advanced populations for three cycles (C0, C2, C4) under three selection densities: low (60,000 plants/ha), medium (90,000 plants/ha), and high (120,000 plants/ha). Hybrids were generated using a double tester design and evaluated in multi-environment trials at Shijiazhuang in Hebei province and Xinxiang in Henan province in 2023 across matching density gradients. We employed analysis of variance (ANOVA) and general combining-ability (GCA) estimates to assess the genetic gains for yield and combining ability across 14 parental materials and 28 hybrids. Our results demonstrate that density compatibility between selection and evaluation environments is paramount. Genetic gain decreased by 0.89–26.52% with a density discrepancy of >30,000 plants/ha and plummeted by 19.71–77.44% when the discrepancy exceeded 60,000 plants/ha, underscoring the necessity of aligning selection density with the target environment. Under matched densities, population yield increased significantly with escalating density, with the high-density selection regime showing a maximum yield improvement of 53.78% from C0 to C4. Materials selected under high density exhibited superior performance and significantly higher combining ability (averaging a 238.35% increase) and genetic gain (averaging a 263.39% improvement) in medium-to-high-density environments, confirming strong positive selection pressure. Conversely, materials from low-density selection processes were better adapted to environments of ≤60,000 plants/ha. This study provides a crucial theoretical and practical foundation for establishing density-optimized recurrent breeding systems to directionally enhance genetic gain in maize.

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Journal
Agronomy
Published
2025-10-21
DOI
https://doi.org/10.3390/agronomy15102435
Primary Topic
Genetics and Plant Breeding
Type
article
Field-Weighted Citation Impact
0.00

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Effects of Selection–Evaluation Density Interaction on Genetic Gain and Optimization Pathways in Maize Recurrent Breeding Systems

Jianfeng Weng, Jienan Han, Xinhai Li, Juying Wang et al.
Agronomy
Genetics and Plant Breeding
article

Effects of Selection–Evaluation Density Interaction on Genetic Gain and Optimization Pathways in Maize Recurrent Breeding Systems

Jianfeng Weng, Jienan Han, Xinhai Li, Juying Wang, Zhiqiang Zhou, Degui Zhang, Fengyi Zhang, Hongjun Yong, Mingshun Li, Rong Zhang, Yuxing Zhang, Zhuanfang Hao, Zhennan Xu, Zhiyuan Yang
article en

Abstract

Breaking the maize yield plateau necessitates the development of density-tolerant varieties, for which recurrent selection is a key breeding strategy. However, a systematic understanding of how the interaction between selection density (parental screening environment) and evaluation density (variety testing environment) modulates genetic gain remains a critical knowledge gap. This study aimed to systematically elucidate this interaction and its impact on genetic gain and combining ability. We established two F2 base populations from distinct heterotic groups: Zheng 58 × LH196 (Stiff Stalk, SS) and Chang 7-2 × MBUB (Non-Stiff Stalk, NSS). Through bulk selection, we advanced populations for three cycles (C0, C2, C4) under three selection densities: low (60,000 plants/ha), medium (90,000 plants/ha), and high (120,000 plants/ha). Hybrids were generated using a double tester design and evaluated in multi-environment trials at Shijiazhuang in Hebei province and Xinxiang in Henan province in 2023 across matching density gradients. We employed analysis of variance (ANOVA) and general combining-ability (GCA) estimates to assess the genetic gains for yield and combining ability across 14 parental materials and 28 hybrids. Our results demonstrate that density compatibility between selection and evaluation environments is paramount. Genetic gain decreased by 0.89–26.52% with a density discrepancy of >30,000 plants/ha and plummeted by 19.71–77.44% when the discrepancy exceeded 60,000 plants/ha, underscoring the necessity of aligning selection density with the target environment. Under matched densities, population yield increased significantly with escalating density, with the high-density selection regime showing a maximum yield improvement of 53.78% from C0 to C4. Materials selected under high density exhibited superior performance and significantly higher combining ability (averaging a 238.35% increase) and genetic gain (averaging a 263.39% improvement) in medium-to-high-density environments, confirming strong positive selection pressure. Conversely, materials from low-density selection processes were better adapted to environments of ≤60,000 plants/ha. This study provides a crucial theoretical and practical foundation for establishing density-optimized recurrent breeding systems to directionally enhance genetic gain in maize.

AgronomyVol. 15(10)
Heilongjiang Provincial Academy of Agricultural Sciences (CN), Hexi University (CN), Institute of Crop Sciences (CN)
National Natural Science Foundation of China, Key Technology Research and Development Program of Shandong, National Key Research and Development Program of China
Openalex Percentile: Top 78%
Genetics and Plant Breeding
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