Maize Breeding Research Articles

Integration of GWAS models and GS reveals the genetic architecture of ear shank in maize.

Maize is one of the most important crops for human food, animal feed, and industrial raw materials. Ear shank length (ESL) and ear shank node number (ESNN) are crucial selection criteria in maize breeding, impacting grain yield and dehydration rate during mechanical harvesting. To unravel the genetic basis of ESL and ESNN in maize, an association panel consisting of 379 multi-parent doubled-haploid (DH) lines was developed for genome-wide association studies (GWAS) and genomic selection (GS). The heritabilities of ESL and ESNN were 0.68 and 0.55, respectively, which were controlled by genetic factors and genotype-environment interaction factors. Using five different models for GWAS, 11 significant single nucleotide polymorphisms (SNPs) located on chromosomes 1, 2, and 4 were identified for ESL, with the phenotypic variation explained (PVE) value of each single SNP ranging from 4.91% to 21.35%, and 11 significant SNPs located on chromosomes 1, 2, 4, and 5 were identified for ESNN, with the PVE value of each SNP ranging from 1.22% to 18.42%. Genetic regions in bins 1.06, 2.06, and 2.08 were significantly enriched in SNPs associated with ear shank-related traits. The GS prediction accuracy using all markers by the five-fold cross-validation method for ESL and ESNN was 0.39 and 0.37, respectively, which was significantly improved by using only 500-1000 significant SNPs with the lowest P-values. The optimal training population size (TPS) and marker density (MD) for ear shank-related traits were 50%-60% and 3000, respectively. Our results provide new insights into the GS of ear shank-related traits.

Maize yields could benefit from increased vapor pressure deficit in hot managed environments

Abstract Recent studies highlight the adverse effects of increasing vapor pressure deficit (VPD) due to climate change on maize yields. Maize breeders are utilizing available genetic diversity to address these challenges. However, contrasting ecophysiological properties and genotype by environment interactions (GEI) often hinder these efforts. This study by the Agricultural Institute Osijek, in collaboration with Turkish company Tarım Kredi Tohumculuk, explores the adaptation of maize germplasm to hot, managed environments in Türkiye, originally bred for Southeast and Central European rainfed conditions. Over an 11-year period (2009–2019), multi-environment trials (MET) were conducted in two stages. In cycle 0 (C0), 22 hybrids were evaluated across 17 environments in Croatia and Türkiye. In cycle 1 (C1), MET was conducted in 18 Turkish environments. Complete linkage hierarchical clustering based on hybrid performance and climatic variables revealed two distinct clusters with positive or negative responses to increasing VPD in C0. In C1, genetic variances increased with rising VPD, maintaining distinct responses. Our findings align with reports on the limited transpiration trait in maize and sorghum, suggesting that while such traits can reduce water loss, they may also limit yield potential in high-VPD environments.

ZmMYC2, selected during modern breeding, orchestrates growth and defense gene expression in maize

ZmMYC2, selected during modern breeding, orchestrates growth and defense gene expression in maize

Genome‐Wide Diversity in Lowland and Highland Maize Landraces From Southern South America: Population Genetics Insights to Assist Conservation

ABSTRACTMaize (Zea mays ssp. mays L.) landraces are traditional American crops with high genetic variability that conform a source of original alleles for conventional maize breeding. Northern Argentina, one the southernmost regions of traditional maize cultivation in the Americas, harbours around 57 races traditionally grown in two regions with contrasting environmental conditions, namely, the Andean mountains in the Northwest and the tropical grasslands and Atlantic Forest in the Northeast. These races encounter diverse threats to their genetic diversity and persistence in their regions of origin, with climate change standing out as one of the major challenges. In this work, we use genome‐wide SNPs derived from ddRADseq to study the genetic diversity of individuals representing the five groups previously described for this area. This allowed us to distinguish two clearly differentiated gene pools, the highland northwestern maize (HNWA) and the floury northeastern maize (FNEA). Subsequently, we employed essential biodiversity variables at the genetic level, as proposed by the Group on Earth Observations Biodiversity Observation Network (GEO BON), to evaluate the conservation status of these two groups. This assessment encompassed genetic diversity (Pi), inbreeding coefficient (F) and effective population size (Ne). FNEA showed low Ne values and high F values, while HNWA showed low Ne values and low Pi values, indicating that further genetic erosion is imminent for these landraces. Outlier detection methods allowed identification of putative adaptive genomic regions, consistent with previously reported flowering‐time loci and chromosomal regions displaying introgression from the teosinte Zea mays ssp. mexicana. Finally, species distribution models were obtained for two future climate scenarios, showing a notable reduction in the potential planting area of HNWA and a shift in the cultivation areas of FNEA. These results suggest that maize landraces from Northern Argentina may be unable to cope with climate change. Therefore, active conservation policies are advisable.

SimpleMating: R-package for prediction and optimization of breeding crosses using genomic selection.

Selecting parents and crosses is a critical step for a successful breeding program. The ability to design crosses with high means that will maintain genetic variation in the population is the goal for long-term applications. Herein, we describe a new computational package for mate allocation in a breeding program. SimpleMating is a flexible and open-source R package originally designed to predict and optimize breeding crosses in crops with different reproductive systems and breeding designs. Divided into modules, SimpleMating first estimates the cross performance (criterion), such as mid-parental value, cross total genetic value, and/or usefulness of a set of crosses. The second module implements an optimization algorithm to maximize a target criterion while minimizing next-generation inbreeding. The software is flexible, enabling users to specify the desired number of crosses, set maximum and minimum crosses per parent, and define the maximum allowable parent relationship for creating crosses. As an outcome, SimpleMating generates a mating plan from the target parental population using single or multi-trait criteria. For example, we implemented and tested SimpleMating in a simulated maize breeding program obtained through stochastic simulations. The crosses designed via SimpleMating showed a large genetic mean over time (up to 22% more genetic gain than conventional genomic selection programs, with lesser loss of genetic diversity over time), supporting the use of this tool, as well as the use of data-driven decisions in breeding programs.

Single plant segmentation and growth parameters measurement of maize seedling stage based on point cloud intensity

Maize growth parameters are key pieces of information describing the growth, development and yield of plants, and they are of great significance for high quality and high yield maize breeding. Plants counting, row spacing, and plant spacing are closely related to maize sowing quality and yield. Plant height is closely related to maize photosynthetic rate and biomass. The main problem with measuring phenotypic parameters during the maize seedling stage is that maize plants are small, making it difficult to segment maize plant point clouds from ground point clouds, and there is a lack of automatic methods for measuring growth parameters. A point cloud intensity segmentation and improved Euclidean clustering method for single plant segmentation was proposed based on terrestrial laser scanning (TLS) technical, and an automatic measuring method of growth parameters of maize seedling stage was realized. First, TLS was used to scan maize plants at two planting densities at V1 (first leaf is fully expanded) and V2 (second leaf is fully expanded) stages. Second, the segmentation based on point cloud intensity method and the improved Euclidean clustering single plant segmentation method were used to achieve the segmentation of a single maize plant. Finally, the automatic measurement of maize plants counting, row spacing, plant spacing, and plant height were realized. When plants counting of maize, the percentage error was lower than 1.70%. In the measurement of row spacing, plant spacing and plant height of maize plants, the mean absolute percentage error (MAPE) were lower than 1.50%, 5.50% and 3.10%, respectively. These results demonstrate that the point cloud intensity segmentation and growth parameters measurement method is feasible for maize V1 and V2 stages and different planting densities. The automatic measurement values of the number of maize plants, row spacing, plant spacing and plant height has high measurement accuracy and small error. This study provides a rapid, automatic and accurate measurement method for researchers to measure maize growth parameters.

Research on the Application of Maize Genome Editing Technology in High-yield Breeding

With the continuous growth of global population, there is an increasing demand for high-yield crops, and how to improve the yield of maize, as an important food and feed crop, has become one of the important directions of agricultural research. Although traditional breeding techniques have made progress in improving high-yield traits in maize, their long cycle time and low efficiency make it difficult to meet the rapidly growing production demand. The emergence of genome editing technologies, especially the CRISPR/Cas9 system, has brought new opportunities for maize high-yield breeding. This paper systematically reviews the application of genome editing technology in maize breeding, focusing on the methods of target gene screening, optimization of editing tools and evaluation of high-yield traits, and describes the research results of the current technology in enhancing maize yield. The potential application value of novel editing tools in the maize genome editing process in future efficient breeding was analyzed. This study provides theoretical support and technical guidance for the use of genome editing technology to realize the precise improvement of high-yield traits in maize.

Molecular Mechanisms and Application Prospects for Breeding for Drought Tolerance in Maize

As a crop of critical global significance, maize requires substantial water throughout its growth cycle. However, with climate change intensifying and water resources becoming increasingly scarce, drought has emerged as a primary limitation on maize productivity. By delving into the molecular underpinnings of drought resistance in maize, researchers have pinpointed an array of drought-resilience genes, transcriptional regulators, and signal transduction pathways, offering a valuable genetic reservoir for enhancing maize’s drought resistance. Advanced molecular tools, including genome editing and marker-assisted selection, have streamlined the targeted optimization and transference of drought-resistance genes, thereby significantly strengthening drought resilience in maize varieties. This paper reviews the intricate molecular bases of drought tolerance and the regulatory frameworks surrounding essential genes in maize, while discussing the future potential of molecular breeding strategies tailored to enhance drought tolerance. Ultimately, this study aims to furnish both a theoretical foundation and technical guidance for advancing drought-resistant maize breeding initiatives.

Identification and segregation of two closely linked major QTLs for kernel row number in advanced maize-teosinte populations.

Two closely linked novel loci, qKRN2-1 and qKRN2-2, associated with kernel row number were fine-mapped on chromosome 2, and a key candidate gene for qKRN2-1 was identified through expression analysis. Kernel row number (KRN) is a crucial factor influencing maize yield and serves as a significant target for maize breeding. The use of wild progenitor species can aid in identifying the essential traits for domestication and breeding. In this study, teosinte (MT1) served as the donor parent, the inbred maize line of Mo17 was used as the recurrent parent, we identified a major quantitative trait locus (QTL) for KRN, designated qKRN2, into two closely linked loci, qKRN2-1 and qKRN2-2. Here, fine mapping was performed to investigate two QTLs, qKRN2-1 and qKRN2-2, within a genomic range of 272kb and 775kb, respectively. This was achieved using a progeny test strategy in an advanced backcross population, with the two QTLs explaining 33.49% and 35.30% of the phenotypic variance. Molecular marker-assisted selection resulted in the development of two nearly isogenic lines (NILs), qKRN2-1 and qKRN2-2, which differed only in the segment containing the QTL. Notably, the maize (Mo17) alleles increased the KRN relative to teosinte by approximately 1.4 and 1.2 rows for qKRN2-1 and qKRN2-2, respectively. Zm00001d002989 encodes a cytokinin oxidase/dehydrogenase and its expression in the immature ears exhibited significant differences among the qKRN2-1 NILs. In situ hybridization localized Zm00001d002989 to the primordia of the inflorescence meristem and spikelet pair meristems, is predicted to be the causal gene of qKRN2-1. The findings of this study deepen our understanding of the genetic basis of KRN and hold significant potential for improving maize grain yields.

MADS-box encoding gene Tunicate1 positively controls maize yield by increasing leaf number above the ear

The leaves above the ear serve as a major source of carbohydrates for grain filling in maize. However, increasing the number of leaves above the ear to strengthen the source and improve maize yield remains challenging in modern maize breeding. Here, we clone the causative gene of the quantitative trait locus (QTL) associated with the number of leaves above the ear. The causative gene is the previously reported MADS-box domain-encoding gene Tunicate1 (Tu1), which is responsible for the phenotype of pod corn or Tunicate maize. We show that Tu1 can substantially increase the leaf number above the ear while maintaining the source‒sink balance. A distal upstream 5-base pair (bp) insertion of Tu1 originating from a popcorn landrace enhances its transcription, coregulates its plastochron activators and repressors, and increases the number of leaves above the ear. Field tests demonstrate that the 5-bp insertion of Tu1 can increase grain yields by 11.4% and 9.5% under regular and dense planting conditions, respectively. The discovery of this favorable Tu1 allele from landraces suggests that landraces represent a valuable resource for high-yield breeding of maize.

Assessment of genetic diversity and heterotic alignment of CIMMYT and IITA maize inbred lines adapted to sub‐Saharan Africa

AbstractDespite the breeding efforts by many institutions, maize (Zea mays L.) productivity in sub‐Saharan Africa is still low. A limited number of productive maize hybrids have been developed partly due to a lack of knowledge on the diversity and heterotic relationship of the germplasm, especially in public breeding programs. Understanding the extent of diversity, structure, and heterotic grouping of available maize germplasm originating from different breeding programs is important to enhance long‐term genetic gain in hybrid maize breeding programs by optimizing heterotic pools using modern breeding tools. Information about the genetic structure of the available germplasm could help breeders design effective breeding strategies to improve yield. This study was conducted to determine the genetic diversity, population structure, and heterotic alignment among 187 elite maize inbred lines from the IITA (International Institute of Tropical Agriculture) and CIMMYT (International Maize and Wheat Improvement Center) maize breeding programs. The inbred lines were genotyped with 9857 Diversity Array Technology sequencing based single nucleotide polymorphism markers. Hierarchical clustering revealed three major groups, with some subgroups consistent with the selection history, and pedigree of the inbred lines. Three broad groups were detected: two consisting of CIMMYT lines and a mixed group consisting of both CIMMYT and IITA inbred lines. The STRUCTURE analysis revealed six subpopulations (fixation index value = 0.58), which depicts a moderate genetic diversity among the materials. Population 2 comprises the highest number of genotypes (102) from both programs. More than 89% of the elite lines had homozygosity exceeding 95%, with the remaining lines requiring further inbreeding through repeated self‐pollination. There was inconsistency in the predetermined heterotic groups' alignment between CIMMYT and IITA elite inbred lines. Analysis of molecular variance revealed that 96% of the total variation was accounted for by differences within groups, with the remaining 4% representing the variation between groups. This suggests that the two programs can benefit from germplasm exchange for the improvement of maize productivity.

Effect of the B chromosome-located long non-coding RNAs on gene expression in maize

Using artificial chromosomes in maize breeding allows for site-specific integration of multigene stacks, effectively overcoming the limitations of conventional transgenic approaches. The maize B chromosome, which is dispensable and highly heterochromatic, has minimal impact on phenotypes at low copy numbers, making it a promising platform for engineering artificial chromosomes. However, recent studies have demonstrated that the maize B chromosome can impact gene expression and recombination on the A chromosome. Understanding the genic characteristics of the B chromosomes and their impact on gene expression is essential for their application in artificial chromosome construction. Despite advancements in elucidating how the B chromosome affects A chromosome expression, the role of long non-coding RNAs (lncRNAs) in this context remains unclear. In this study, we analyzed the RNA-seq data from leaf tissue of plants with 0 to 7 B chromosomes, identifying a total of 1614 lncRNAs, including 1516 A chromosome-located and 98 B chromosome-located lncRNAs, 72 of which are specific to the B chromosome. While A-located lncRNAs show greater dependence on the mere presence of the B chromosome, the expression of B-located lncRNAs is significantly affected by the number of B chromosomes present. Regulatory networks constructed in this study suggest that B-located lncRNAs may drive the differential expression of A chromosome-located transcription factors and genes associated with circadian rhythm regulation, indicating their regulatory role in A chromosome gene expression.

Identifying and quantifying the contribution of maize plant traits to nitrogen uptake and use through plant modelling

Abstract Breeding for high nitrogen use efficient crops can contribute to maintaining or even increasing yield with less nitrogen. Nitrogen use is co-determined by N uptake and physiological use efficiency (PE, biomass per unit of N taken up), to which soil processes as well as plant architectural, physiological and developmental traits contribute. The relative contribution of these crop traits to N use is not well known but relevant to identify breeding targets in important crop species like maize. To quantify the contribution of component plant traits to maize N uptake and use, we used a functional-structural plant model. We evaluated the effect of varying both shoot and root traits on crop N uptake across a range of nitrogen levels. Root architectural traits were found to play a more important role in root N uptake than physiological traits. Phyllochron determined the structure of the shoot through changes in source: sink ratio over time which, in interaction with light and temperature, resulted in a significant effect on PE and N uptake. Photosynthesis traits were more relevant to biomass accumulation rather than yield, especially under high nitrogen conditions. The traits identified in this study are potential targets in maize breeding for improved crop N uptake and use.

Identification of SNP and SilicoDArT Markers and Characterization of Their Linked Candidate Genes Associated with Maize Smut Resistance.

The implementation of biological advancements in agricultural production is the response to the needs of the agricultural sector in the 21st century, enabling increased production and improved food quality. Biological progress in the maize breeding and seed industries is unique in terms of their social and ecological innovation aspects. It affects agricultural productivity and the adaptation of cultivated maize varieties to market demands and changing climate conditions without compromising the environment. Modern maize resistance breeding relies on a wide range of molecular genetic research techniques. These technologies enable the identification of genomic regions associated with maize smut resistance, which is crucial for characterizing and manipulating these regions. Therefore, the aim of this study was to identify molecular markers (SilicoDArT and SNP) linked to candidate genes responsible for maize smut resistance, utilizing next-generation sequencing, as well as association and physical mapping. By using next-generation sequencing (NGS) and statistical tools, the analyzed maize genotypes were divided into heterotic groups, which enabled the prediction of the hybrid formula in heterosis crosses. In addition, Illumina sequencing identified 60,436 SilicoDArT markers and 32,178 SNP markers (92,614 in total). For association mapping, 32,900 markers (26,234 SilicoDArT and 6666 SNP) meeting the criteria (MAF > 0.25 and the number of missing observations < 10%) were used. Among the selected markers, 61 were highly statistically significant (LOD > 2.3). Among the selected 61 highly statistically significant markers (LOD > 2.3), 10 were significantly associated with plant resistance to maize smut in two locations (Smolice and Kobierzyce). Of the 10 selected markers, 3 SilicoDArT (24016548, 2504588, 4578578) and 3 SNP (4779579, 2467511, 4584208) markers were located within genes. According to literature reports, of these six genes, three (ATAD3, EDM2, and CYP97A3) are characterized proteins that may play a role in the immune response that develops in response to corn smut infection. In the case of genotypes belonging to the same origin groups, markers linked to these genes can be used to select varieties resistant to corn smut. These markers will also be tested on genotypes belonging to other maize origin groups to demonstrate their universality.

Validation of QTLs associated with corn borer resistance and grain yield: implications in maize breeding.

Validations of previously detected quantitative trait loci (QTLs) to assess their reliability are crucial before implementing breeding programs. The objective of this study was to determine the reliability and practical usefulness of previously reported QTLs for resistance to stem tunneling by the Mediterranean stem borer (MSB) and yield. These authors used approximately 600 recombinant inbred lines (RILs) from a multiparent advanced generation intercross (MAGIC) population to map QTL using a genome-wide association study (GWAS) approach. We identified RILs situated at the extremes of resistance and yield distributions within the whole MAGIC, and those QTLs were evaluated per se and crossed to a tester (A638) using lattice designs. In each set, a significant single-nucleotide polymorphism (SNP) was considered validated if (1) the same SNP was associated with the trait with a p-value < 0.02, or (2) within a ±2-Mbp interval, an SNP associated with the trait exhibited a p-value < 0.02 and demonstrated linkage disequilibrium (r2 > 0.2) with the SNPs previously reported. The novel QTL validation approach was implemented using improved experimental designs that led to higher heritability estimates for both traits compared to those estimated with the whole MAGIC population. The procedure used allowed us to jointly validate several QTL and to ascertain their possible contribution to hybrid improvement. Specifically, nearly three-quarters of the QTLs for tunnel length were confirmed. Notably, QTLs located in the genomic region 6.05-6.07 were consistently validated across different sets and have been previously linked to resistance against stalk tunneling in various mapping populations. For grain yield, approximately 10 out of 16 QTLs were validated. The validation rate for yield was lower than for tunnel length, likely due to the influence of dominance and/or epistatic effects. Overall, 9 out of 21 QTLs for tunnel length and 6 out of 17 QTLs for grain yield identified in our previous research were validated across both validation sets, indicating a moderate genetic correlation between per se and testcross performance of inbred lines. These findings offer insights into the reliability of QTL and genomic predictions, both derived from assessments conducted on the entire MAGIC population. Genomic predictions for tunnel length based on inbred line evaluations could be useful to develop more resistant hybrids; meanwhile, genomic prediction for yield could only be valid in a homozygous background.

Phenotypic characterization and genetic mapping of the semi-dwarf mutant sdw9 in maize.

In summary, we characterized a maize semi-dwarf mutant, sdw9, and successfully isolated the responsible gene, which encodes a GRAS protein, through a combination of map-based cloning and Re-sequencing (Re-seq). Our findings demonstrate that the candidate gene ZmGRAS42 regulates BR signaling genes, thereby influencing internode development. This regulatory function likely involves processes such as cell division, cell cycle regulation and cell wall synthesis. Favorable variations of ZmGRAS42 identified in this study may hold promise for the development of lodging-resistant maize cultivars suitable for high-density planting, contributing to the improvement of maize breeding programs. Plant height and lateral root angle are crucial determinants of plant architecture in maize (Zea mays) which are closely related to lodging resistance at high planting density. These traits are intricately regulated by various phytohormones. Mutations affecting hormone biosynthesis and signaling often lead to reduced yield alongside diminished plant height, posing challenges in breeding dwarf maize varieties. In this study, the maize mutant sdw9 was characterized, which displays shorter stature and altered lateral root angle compared to WT, while showing potential to increase planting density and improve overall yield despite a slight reduction in single-ear yield. Employing positional cloning coupled with Re-seq techniques, we pinpointed a transposon insertion in the candidate gene ZmGRAS42, which encodes a GRAS transcription factor involved in BR signaling in maize. Transcriptome analysis revealed that ZmGRAS42 orchestrates the expression of several known dwarfing genes such as D8, Br2, and Na2, along with genes associated with cell wall organization, cell division, and cell cycle regulation, notably Cesa4, Cesa7, and Cyc11. Furthermore, identification of favorable ZmGRAS42 haplotypes linked to reduced plant height offers novel avenues for maize breeding strategies. These findings not only hold the potential for enhancing maize lodging resistance but also for optimizing land utilization through high-density planting practices.

Historical increases of maize leaf area index in the US Corn Belt due primarily to plant density increases

ContextLeaf area index (LAI) and leaf area distribution within the maize plant are important traits used to explain and predict light interception and thus crop productivity. ObjectivesHere we investigate breeding and plant density effects of leaf area traits. Our objectives are to 1) quantify maize breeding impacts on leaf area distribution and determine bell-shape coefficients used in crop modeling, 2) dissect the contribution of breeding from plant density, and 3) explore the relationship between LAI and crop yields. MethodsWe studied 18 hybrids released between 1983 and 2017 at two density treatments: current (8.5 pl m−2) and historical increasing density (from 4.6 to 8.5 pl m−2) in Iowa, USA. ResultsResults indicated that concurrent changes in hybrids and increases in plant density have increased LAI from 3.4 (in 1983) to 5.9 m2 m−2 (in 2017), with the highest LAI increases (>50 %) to be realized in the middle canopy. At historical increasing in plant density treatment, the LAI increased by 1.6 % year−1, but the individual plant leaf area decreased by 0.33 % year−1 from 1983 to 2017. This trade-off indicates that new hybrids are more tolerant to higher plant populations than old hybrids. At current plant density treatment, the year of hybrid release did not affect LAI or individual plant leaf area. New hybrids had 5 % narrower leaf area distributions, 23 % higher optimum LAI values (5.2 vs 4.2 m2 m−2) and 19 % higher grain yields compared to old hybrids. ConclusionsThe main reason for the increase in maize LAI in the US Corn Belt is plant density. However, an increase in LAI does not necessarily translate to higher grain yields as new hybrids had significantly higher grain yields than older hybrids at similar LAI values. Present results contribute to our understanding of maize canopy architecture and allow us to better calibrate crop models to accurately estimate LAI and grain yield.

Doubled Haploid Technology: Generation of Doubled Haploid Maize Lines Using Haploid Inducers.

Doubled haploid (DH) technology allows for the development of completely homozygous lines from heterozygous plants in only two generations. This approach has been widely adopted in maize breeding programs, as it expedites the generation of inbred lines compared to traditional methods. The DH approach is based on the use of maize genotypes that have the ability to induce haploid seeds when used as the pollen parent. The most common method for producing maize haploid plants for the generation of DH lines is in vivo maternal haploid induction. The process involves pollination with a haploid inducer maize line to generate haploid seeds. Then, haploids are screened for and identified (typically via the expression of a particular marker gene), germinated, treated with an exogenous doubling agent to induce genome duplication, and transplanted to the field. Following successful self-pollination, seeds harvested from the ear represent fully homozygous lines. The seed set at this stage, however, is often low, necessitating one or two additional rounds of self-pollination to increase the number of fully homozygous inbred lines. Here, we describe a protocol for the generation of maize DH lines using maternal haploid-inducing maize lines. We outline the steps for setting up the donor material, performing induction crosses, selecting haploids based on two different marker alleles, treating seedlings with colchicine to double the genome, transplanting the treated seedlings to the field, and self-pollinating the treated plants.

Study of Pollen Traits, Production, and Artificial Pollination Methods in Zea mays L.

The optimization of artificial pollination is crucial in breeding programs for allogamous plants. In maize, achieving a balance between the labor-intensive nature of controlled pollinations and the need for large-scale production of hybrid seeds, along with considerations of germinability and pollen production, determines the success of genetic improvement programs. Breeding programs in maize have resulted in a reduction in the number of tassel branches to increase light interception and plant density in production fields. However, despite this genetic improvement, the decreased pollen production per plant has raised critical concerns regarding pollination and subsequent ear filling, especially under adverse environmental conditions. The aim of this work was the analysis of factors that can contribute to increasing the efficiency of controlled pollination in maize. The data obtained showed that pollen diameter, flavonoid, and phenolic acid content do not influence the percentage of germination and therefore the efficiency of pollination. The quantity of pollen is a central factor in ensuring the efficiency of controlled pollinations, and the data obtained by comparing traditional varieties with modern hybrids of maize showed that an increase in pollen production is determined by the increase in branching of the male inflorescence. Furthermore, we propose the use of a “smart” pollination method to make this step in maize breeding programs easier and faster.

Maize breeding for smaller tassels threatens yield under a warming climate

Maize breeding for smaller tassels threatens yield under a warming climate