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Agronomy
Special Issues
Maize Germplasm Improvement and Innovation
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Maize Germplasm Improvement and Innovation

A special issue of Agronomy (ISSN 2073-4395). This special issue belongs to the section "Crop Breeding and Genetics".

Deadline for manuscript submissions: 30 September 2025 | Viewed by 3554

Special Issue Editor

Dr. Hongjun Yong

E-Mail Website
Guest Editor
State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
Interests: maize germplasm improvement and innovation; maize breeding; exotic germplasm evaluation

Special Issue Information

Dear Colleagues,

Almost all new maize varieties come from a commercial maize breeding program. The majority of parents were derived from a few elite inbred lines, which will lead to homogenization and low genetic diversity, making it difficult to cope with extreme global climate changes. Maize germplasm improvement and innovation refers to the use of elite exotic or domestic resources to enhance and develop new germplasm for maize varieties through traditional breeding, genetic selection, and biotechnological approaches. Based on the above, we initiated a Special Issue in Agronomy on “Maize Germplasm Improvement and Innovation”, which will focus on the following:

  1. Maize population improvement, evaluation, and innovation;
  2. Study of increasing genetic gain in maize breeding, e.g. increasing plant density;
  3. Use of new conventional and modern techniques for maize germplasm improvement and innovation.

The overall aim of this Special Issue is to increase the awareness of maize germplasm improvement and innovation in the maize breeding program.

Dr. Hongjun Yong
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Agronomy is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • maize
  • germplasm improvement
  • innovation

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Published Papers (4 papers)

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Research

19 pages, 1787 KiB  
Article
Genetic Trends in Seven Years of Maize Breeding at Mozambique’s Institute of Agricultural Research
by Pedro Fato, Pedro Chaúque, Constantino Senete, Egas Nhamucho, Clay Sneller, Samuel Mutiga, Lennin Musundire, Dagne Wegary, Biswanath Das and Boddupalli M. Prasanna
Agronomy 2025, 15(2), 449; https://doi.org/10.3390/agronomy15020449 - 12 Feb 2025
Viewed by 999
Abstract
Assessing genetic gains from historical data provides insights to improve breeding programs. This study evaluated the Mozambique National Maize Program’s (MNMP’s) genetic gains using data from advanced germplasm trials conducted at 21 locations between 2014 and 2020. Genetic gains were calculated by regressing [...] Read more.
Assessing genetic gains from historical data provides insights to improve breeding programs. This study evaluated the Mozambique National Maize Program’s (MNMP’s) genetic gains using data from advanced germplasm trials conducted at 21 locations between 2014 and 2020. Genetic gains were calculated by regressing the genotypic best linear unbiased estimates of grain yield and complementary agronomic traits against the initial year of genotype evaluation (n = 592). The annual genetic gain was expressed as a percentage of the trait mean. While grain yield, the primary breeding focus, showed no significant improvement, significant gains were observed for the plant height (0.67%), ear height (1.74%), ears per plant (1.31%), ear position coefficient (1.22%), and husk cover (4.7%). Negative genetic gains were detected for the days to anthesis (−0.5%), the anthesis–silking interval or ASI (−9.31%), and stalk lodging (−5.01%). These results indicate that while MNMP did not achieve the desired positive genetic gain for grain yield, progress was made for traits related to plant resilience, particularly the ASI and stalk lodging. MNMP should seek to incorporate new breeding technologies and human resources to enhance genetic gains for grain yield and other key traits in the maize breeding program, while developing and deploying high-yielding, climate-resilient maize varieties to address emerging food security challenges in Mozambique. Full article
(This article belongs to the Special Issue Maize Germplasm Improvement and Innovation)
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17 pages, 1377 KiB  
Article
Adaptation of Diverse Maize Germplasm to Spring Season Conditions in Northeast China
by Yi Li, Zhiyuan Yang, Yong Shao, Zhenguo Jin, Li Gao, Yang Yu, Fengyi Zhang, Yuxing Zhang, Yuantao Nan, Mingshun Li, Degui Zhang, Zhuanfang Hao, Jianfeng Weng, Xinhai Li and Hongjun Yong
Agronomy 2025, 15(1), 170; https://doi.org/10.3390/agronomy15010170 - 12 Jan 2025
Viewed by 623
Abstract
Northeast China (NEC) is a major spring maize (Zea mays L.) growing belt, and the outputs substantially influence national grain production. However, the maize grain yield per unit area has little changes in recent years, partially due to the lack of elite [...] Read more.
Northeast China (NEC) is a major spring maize (Zea mays L.) growing belt, and the outputs substantially influence national grain production. However, the maize grain yield per unit area has little changes in recent years, partially due to the lack of elite germplasm resources and innovation. Therefore, this study aimed to determine the performance of diverse populations in NEC to propose appropriate strategies for the utilization of elite germplasm to broaden the genetic base of Chinese germplasm. Fifteen diverse maize populations from the International Maize and Wheat Improvement Center (CIMMYT) and the U.S. were crossed to two local tester lines, representing Chinese heterotic groups Reid and Lancaster, for evaluating the combining ability and heterosis in three locations (Gongzhuling, Jilin Province, and Harbin and Suihua, Heilongjiang Province) in NEC over two years. The U.S. (BS13(S)C7 and BS31) and Chinese (Ji Syn A) populations exhibited more favorable alleles for high yield potential in all locations tested. Furthermore, the PH6WC × BS31 and PH6WC × Ji Syn A crosses had higher grain yields, and an appropriate number of days to silking, ear height, and resistance to lodging at Gongzhuling and Harbin in NEC. The best strategies for utilizing these diverse germplasms may be to develop new inbred lines from the existing elite populations or improve the grain yield and resistance to lodging of the elite line PH4CV for broadening the genetic base of the Chinese group Lancaster in NEC. Full article
(This article belongs to the Special Issue Maize Germplasm Improvement and Innovation)
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16 pages, 241 KiB  
Article
Research on the Genetic Improvement Effects of Lodging Resistance-Related Traits in Maize Core Germplasm
by Kaizhi Yang, Jian Tan, Qiyuan Zhang, Tianhang Bai, Shuna Zhou, Junheng Hao, Xinling Yu, Zhenyuan Zang and Dan Zhang
Agronomy 2025, 15(1), 17; https://doi.org/10.3390/agronomy15010017 - 26 Dec 2024
Cited by 2 | Viewed by 667
Abstract
Lodging is a key factor affecting maize yield and harvestability. This study utilized Reid population baselines and their improved lines as female parents and No-Reid population baselines and their improved lines as male parents to form 48 incomplete diallel crosses. The genetic improvement [...] Read more.
Lodging is a key factor affecting maize yield and harvestability. This study utilized Reid population baselines and their improved lines as female parents and No-Reid population baselines and their improved lines as male parents to form 48 incomplete diallel crosses. The genetic improvement effects, combining ability, and heterosis of three lodging resistance-related traits (stem tension, puncture strength, and crushing strength at the third internode) were analyzed. Regarding genetic improvement, the results indicated that all three traits were significantly improved in the improved lines compared to the baselines, with improvements increasing in each round. Combining ability analysis showed positive general combining ability (GCA) effects for the improved lines J133A, JM25, JM115, and JM1895 in all three traits, with higher GCA values than the baselines and first-round improved lines. Heterosis analysis revealed the highest advantages for the combinations J133A × JM115 (stem tension), JM25 × JM115 (crushing strength), and J133A × J1865 (puncture strength). These findings suggest that the improved female lines J133A and JM25, along with male lines JM115 and JM1895, not only possess strong lodging resistance but also exhibit high yield potential in the cross J133A × JM115, offering new materials and varieties for maize mechanization. Full article
(This article belongs to the Special Issue Maize Germplasm Improvement and Innovation)
16 pages, 1829 KiB  
Article
Genomic Prediction of Kernel Water Content in a Hybrid Population for Mechanized Harvesting in Maize in Northern China
by Ping Luo, Ruisi Yang, Lin Zhang, Jie Yang, Houwen Wang, Hongjun Yong, Runze Zhang, Wenzhe Li, Fei Wang, Mingshun Li, Jianfeng Weng, Degui Zhang, Zhiqiang Zhou, Jienan Han, Wenwei Gao, Xinlong Xu, Ke Yang, Xuecai Zhang, Junjie Fu, Xinhai Li, Zhuanfang Hao and Zhiyong Niadd Show full author list remove Hide full author list
Agronomy 2024, 14(12), 2795; https://doi.org/10.3390/agronomy14122795 - 25 Nov 2024
Cited by 1 | Viewed by 819
Abstract
Genomic prediction enables rapid selection of maize varieties with low kernel water content (KWC), facilitating the development of mechanized maize harvesting and reducing costs. This study evaluated and characterized the KWC and grain yield (GY) of hybrid maize in northern China and used [...] Read more.
Genomic prediction enables rapid selection of maize varieties with low kernel water content (KWC), facilitating the development of mechanized maize harvesting and reducing costs. This study evaluated and characterized the KWC and grain yield (GY) of hybrid maize in northern China and used genomic prediction to identify superior hybrid combinations with low kernel water content at maturity (MKWC) and high GY adapted to northern China. A total of 285 hybrids obtained from single crosses of 34 inbred lines from Stiff Stalk and Non-Stiff Stalk heterotic groups were used for genomic prediction of KWC and GY. We tested 20 different statistical prediction models considering additive effects and evaluating the impact of dominance and epistasis on prediction accuracy. Employing 10-fold cross-validation, it showed that the average prediction accuracy ranged drastically from 0.386 to 0.874 across traits and models. Eight linear statistical methods displayed a very similar prediction accuracy for each trait. The average prediction accuracy of machine learning methods was lower than that of linear statistical methods for KWC-related traits, but the random forest model had a high prediction accuracy of 0.510 for GY. When genetic effects were incorporated into the prediction model, the prediction accuracy for each trait was improved. Overall, the model with dominant and epistatic effects (G:AD(AA)) performed best. For the same number of markers, predictions using trait-specific markers resulted in higher prediction accuracy than randomly selected markers. When the number of trait-specific SNPs was set to 100, the prediction accuracy of GY increased by 33.27%, from 0.406 to 0.541. Out of all the 561 potential hybrids, the TOP 30 hybrids selected by genomic prediction would lead to a 1.44% decrease in MKWC compared with Xianyu335, a hybrid with a fast kernel water dry-down, and these hybrids also had higher GY simultaneously. Our results confirm the value of genomic prediction for hybrid breeding low MKWC suitable for maize mechanized harvesting in northern China. In conclusion, this study highlights the potential of genomic prediction to optimize maize hybrid breeding, enhancing efficiency and providing insights into genotype-accuracy relationships. The findings offer new strategies for hybrid design and advancing mechanized harvesting in northern China. Full article
(This article belongs to the Special Issue Maize Germplasm Improvement and Innovation)
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