Haploid identification in maize.

Doubled haploid (DH) line production through in vivo maternal haploid induction is widely adopted in maize breeding programs. The established protocol for DH production includes four steps namely in vivo maternal haploid induction, haploid identification, genome doubling of haploid, and self-fertilization of doubled haploids. Since modern haploid inducers still produce relatively small portion of haploids among undesirable hybrid kernels, haploid identification is typically laborious, costly, and time-consuming, making this step the second foremost in the DH technique. This manuscript reviews numerous methods for haploid identification from different approaches including the innate differences in haploids and diploids, biomarkers integrated in haploid inducers, and automated seed sorting. The phenotypic differentiation, genetic basis, advantages, and limitations of each biomarker system are highlighted. Several approaches of automated seed sorting from different research groups are also discussed regarding the platform or instrument used, sorting time, accuracy, advantages, limitations, and challenges before they go through commercialization. The past haploid selection was focusing on finding the distinguishable marker systems with the key to effectiveness. The current haploid selection is adopting multiple reliable biomarker systems with the key to efficiency while seeking the possibility for automation. Fully automated high-throughput haploid sorting would be promising in near future with the key to robustness with retaining the feasible level of accuracy. The system that can meet between three major constraints (time, workforce, and budget) and the sorting scale would be the best option.

Fine mapping of major QTL qshgd1 for spontaneous haploid genome doubling in maize (Zea mays L.).

KEY MESSAGE: A large-effect QTL was fine mapped, which revealed 79 gene models, with 10 promising candidate genes, along with a novel inversion. In commercial maize breeding, doubled haploid (DH) technology is arguably the most efficient resource for rapidly developing novel, completely homozygous lines. However, the DH strategy, using in vivo haploid induction, currently requires the use of mutagenic agents which can be not only hazardous, but laborious. This study focuses on an alternative approach to develop DH lines-spontaneous haploid genome duplication (SHGD) via naturally restored haploid male fertility (HMF). Inbred lines A427 and Wf9, the former with high HMF and the latter with low HMF, were selected to fine-map a large-effect QTL associated with SHGD-qshgd1. SHGD alleles were derived from A427, with novel haploid recombinant groups having varying levels of the A427 chromosomal region recovered. The chromosomal region of interest is composed of 45 megabases (Mb) of genetic information on chromosome 5. Significant differences between haploid recombinant groups for HMF were identified, signaling the possibility of mapping the QTL more closely. Due to suppression of recombination from the proximity of the centromere, and a newly discovered inversion region, the associated QTL was only confined to a 25 Mb region, within which only a single recombinant was observed among ca. 9,000 BC1 individuals. Nevertheless, 79 gene models were identified within this 25 Mb region. Additionally, 10 promising candidate genes, based on RNA-seq data, are described for future evaluation, while the narrowed down genome region is accessible for straightforward introgression into elite germplasm by BC methods.

Accelerating haploid induction rate and haploid validation through marker-assisted selection for qhir1 and qhir8 in maize.

Doubled haploid (DH) technology becomes more routinely applied in maize hybrid breeding. However, some issues in haploid induction and identification persist, requiring resolution to optimize DH production. Our objective was to implement simultaneous marker-assisted selection (MAS) for qhir1 (MTL/ZmPLA1/NLD) and qhir8 (ZmDMP) using TaqMan assay in F2 generation of four BHI306-derived tropical × temperate inducer families. We also aimed to assess their haploid induction rate (HIR) in the F3 generation as a phenotypic response to MAS. We highlighted remarkable increases in HIR of each inducer family. Genotypes carrying qhir1 and qhir8 exhibited 1 - 3-fold higher haploid frequency than those carrying only qhir1. Additionally, the qhir1 marker was employed for verifying putative haploid seedlings at 7 days after planting. Flow cytometric analysis served as the gold standard test to assess the accuracy of the R1-nj and the qhir1 marker. The qhir1 marker showed high accuracy and may be integrated in multiple haploid identifications at early seedling stage succeeding pre-haploid sorting via R1-nj marker.

Current challenges and future of agricultural genomes to phenomes in the USA.

Dramatic improvements in measuring genetic variation across agriculturally relevant populations (genomics) must be matched by improvements in identifying and measuring relevant trait variation in such populations across many environments (phenomics). Identifying the most critical opportunities and challenges in genome to phenome (G2P) research is the focus of this paper. Previously (Genome Biol, 23(1):1-11, 2022), we laid out how Agricultural Genome to Phenome Initiative (AG2PI) will coordinate activities with USA federal government agencies expand public-private partnerships, and engage with external stakeholders to achieve a shared vision of future the AG2PI. Acting on this latter step, AG2PI organized the "Thinking Big: Visualizing the Future of AG2PI" two-day workshop held September 9-10, 2022, in Ames, Iowa, co-hosted with the United State Department of Agriculture's National Institute of Food and Agriculture (USDA NIFA). During the meeting, attendees were asked to use their experience and curiosity to review the current status of agricultural genome to phenome (AG2P) work and envision the future of the AG2P field. The topic summaries composing this paper are distilled from two 1.5-h small group discussions. Challenges and solutions identified across multiple topics at the workshop were explored. We end our discussion with a vision for the future of agricultural progress, identifying two areas of innovation needed: (1) innovate in genetic improvement methods development and evaluation and (2) innovate in agricultural research processes to solve societal problems. To address these needs, we then provide six specific goals that we recommend be implemented immediately in support of advancing AG2P research.

Assessing data analysis techniques in a high-throughput meiosis-like induction detection system.

BACKGROUND: Strategies to understand meiotic processes have relied on cytogenetic and mutant analysis. However, thus far in vitro meiosis induction is a bottleneck to laboratory-based plant breeding as factor(s) that switch cells in crops species from mitotic to meiotic divisions are unknown. A high-throughput system that allows researchers to screen multiple candidates for their meiotic induction role using low-cost microfluidic devices has the potential to facilitate the identification of factors with the ability to induce haploid cells that have undergone recombination (artificial gametes) in cell cultures. RESULTS: A data analysis pipeline and a detailed protocol are presented to screen for plant meiosis induction factors in a quantifiable and efficient manner. We assessed three data analysis techniques using spiked-in protoplast samples (simulated gametes mixed into somatic protoplast populations) of flow cytometry data. Polygonal gating, which was considered the "gold standard", was compared to two thresholding methods using open-source analysis software. Both thresholding techniques were able to identify significant differences with low spike-in concentrations while also being comparable to polygonal gating. CONCLUSION: Our study provides details to test and analyze candidate meiosis induction factors using available biological resources and open-source programs for thresholding. RFP (PE.CF594.A) and GFP (FITC.A) were the only channels required to make informed decisions on meiosis-like induction and resulted in detection of cell population changes as low as 0.3%, thus enabling this system to be scaled using microfluidic devices at low costs.

Phenotypic and genome-wide association analyses for nitrogen use efficiency related traits in maize (Zea mays L.) exotic introgression lines.

Nitrogen (N) limits crop production, yet more than half of N fertilizer inputs are lost to the environment. Developing maize hybrids with improved N use efficiency can help minimize N losses and in turn reduce adverse ecological, economical, and health consequences. This study aimed to identify single nucleotide polymorphisms (SNPs) associated with agronomic traits (plant height, grain yield, and anthesis to silking interval) under high and low N conditions. A genome-wide association study (GWAS) was conducted using 181 doubled haploid (DH) lines derived from crosses between landraces from the Germplasm Enhancement of Maize (BGEM lines) project and two inbreds, PHB47 and PHZ51. These DH lines were genotyped using 62,077 SNP markers. The same lines from the per se trials were used as parental lines for the testcross field trials. Plant height, anthesis to silking interval, and grain yield were collected from high and low N conditions in three environments for both per se and testcross trials. We used three GWAS models, namely, general linear model (GLM), mixed linear model (MLM), and Fixed and Random model Circulating Probability Unification (FarmCPU) model. We observed significant genetic variation among the DH lines and their derived testcrosses. Interestingly, some testcrosses of exotic introgression lines were superior under high and low N conditions compared to the check hybrid, PHB47/PHZ51. We detected multiple SNPs associated with agronomic traits under high and low N, some of which co-localized with gene models associated with stress response and N metabolism. The BGEM panel is, thus, a promising source of allelic diversity for genes controlling agronomic traits under different N conditions.

Genetic basis of maize maternal haploid induction beyond MATRILINEAL and ZmDMP.

In maize, doubled haploid (DH) lines are created in vivo through crosses with maternal haploid inducers. Their induction ability, usually expressed as haploid induction rate (HIR), is known to be under polygenic control. Although two major genes (MTL and ZmDMP) affecting this trait were recently described, many others remain unknown. To identify them, we designed and performed a SNP based (~9007) genome-wide association study using a large and diverse panel of 159 maternal haploid inducers. Our analyses identified a major gene near MTL, which is present in all inducers and necessary to disrupt haploid induction. We also found a significant quantitative trait loci (QTL) on chromosome 10 using a case-control mapping approach, in which 793 noninducers were used as controls. This QTL harbors a kokopelli ortholog, whose role in maternal haploid induction was recently described in Arabidopsis. QTL with smaller effects were identified on six of the ten maize chromosomes, confirming the polygenic nature of this trait. These QTL could be incorporated into inducer breeding programs through marker-assisted selection approaches. Further improving HIR is important to reduce the cost of DH line production.

Molecular characterization of doubled haploid lines derived from different cycles of the Iowa Stiff Stalk Synthetic (BSSS) maize population.

Molecular characterization of a given set of maize germplasm could be useful for understanding the use of the assembled germplasm for further improvement in a breeding program, such as analyzing genetic diversity, selecting a parental line, assigning heterotic groups, creating a core set of germplasm and/or performing association analysis for traits of interest. In this study, we used single nucleotide polymorphism (SNP) markers to assess the genetic variability in a set of doubled haploid (DH) lines derived from the unselected Iowa Stiff Stalk Synthetic (BSSS) maize population, denoted as C0 (BSSS(R)C0), the seventeenth cycle of reciprocal recurrent selection in BSSS (BSSS(R)C17), denoted as C17 and the cross between BSSS(R)C0 and BSSS(R)C17 denoted as C0/C17. With the aim to explore if we have potentially lost diversity from C0 to C17 derived DH lines and observe whether useful genetic variation in C0 was left behind during the selection process since C0 could be a reservoir of genetic diversity that could be untapped using DH technology. Additionally, we quantify the contribution of the BSSS progenitors in each set of DH lines. The molecular characterization analysis confirmed the apparent separation and the loss of genetic variability from C0 to C17 through the recurrent selection process. Which was observed by the degree of differentiation between the C0_DHL versus C17_DHL groups by Wright's F-statistics (FST). Similarly for the population structure based on principal component analysis (PCA) revealed a clear separation among groups of DH lines. Some of the progenitors had a higher genetic contribution in C0 compared with C0/C17 and C17 derived DH lines. Although genetic drift can explain most of the genetic structure genome-wide, phenotypic data provide evidence that selection has altered favorable allele frequencies in the BSSS maize population through the reciprocal recurrent selection program.

Overcoming roadblocks for in vitro nurseries in plants: induction of meiosis.

Efforts to increase genetic gains in breeding programs of flowering plants depend on making genetic crosses. Time to flowering, which can take months to decades depending on the species, can be a limiting factor in such breeding programs. It has been proposed that the rate of genetic gain can be increased by reducing the time between generations by circumventing flowering through the in vitro induction of meiosis. In this review, we assess technologies and approaches that may offer a path towards meiosis induction, the largest current bottleneck for in vitro plant breeding. Studies in non-plant, eukaryotic organisms indicate that the in vitro switch from mitotic cell division to meiosis is inefficient and occurs at very low rates. Yet, this has been achieved with mammalian cells by the manipulation of a limited number of genes. Therefore, to experimentally identify factors that switch mitosis to meiosis in plants, it is necessary to develop a high-throughput system to evaluate a large number of candidate genes and treatments, each using large numbers of cells, few of which may gain the ability to induce meiosis.

Self-supervised maize kernel classification and segmentation for embryo identification.

Introduction: Computer vision and deep learning (DL) techniques have succeeded in a wide range of diverse fields. Recently, these techniques have been successfully deployed in plant science applications to address food security, productivity, and environmental sustainability problems for a growing global population. However, training these DL models often necessitates the large-scale manual annotation of data which frequently becomes a tedious and time-and-resource- intensive process. Recent advances in self-supervised learning (SSL) methods have proven instrumental in overcoming these obstacles, using purely unlabeled datasets to pre-train DL models. Methods: Here, we implement the popular self-supervised contrastive learning methods of NNCLR Nearest neighbor Contrastive Learning of visual Representations) and SimCLR (Simple framework for Contrastive Learning of visual Representations) for the classification of spatial orientation and segmentation of embryos of maize kernels. Maize kernels are imaged using a commercial high-throughput imaging system. This image data is often used in multiple downstream applications across both production and breeding applications, for instance, sorting for oil content based on segmenting and quantifying the scutellum's size and for classifying haploid and diploid kernels. Results and discussion: We show that in both classification and segmentation problems, SSL techniques outperform their purely supervised transfer learning-based counterparts and are significantly more annotation efficient. Additionally, we show that a single SSL pre-trained model can be efficiently finetuned for both classification and segmentation, indicating good transferability across multiple downstream applications. Segmentation models with SSL-pretrained backbones produce DICE similarity coefficients of 0.81, higher than the 0.78 and 0.73 of those with ImageNet-pretrained and randomly initialized backbones, respectively. We observe that finetuning classification and segmentation models on as little as 1% annotation produces competitive results. These results show SSL provides a meaningful step forward in data efficiency with agricultural deep learning and computer vision.

GWAS across multiple environments and WGCNA suggest the involvement of ZmARF23 in embryonic callus induction from immature maize embryos.

KEY MESSAGE: Combined GWAS, WGCNA, and gene-based association studies identified the co-expression network and hub genes for maize EC induction. ZmARF23 bound to ZmSAUR15 promoter and regulated its expression, affecting EC induction. Embryonic callus (EC) induction in immature maize embryos shows high genotype dependence, which limits the application of genetic transformation in transgenic breeding and gene function elucidation in maize. Herein, we conducted a genome-wide association mapping (GWAS) for four EC induction-related traits, namely rate of embryonic callus induction (REC), increased callus diameter (ICD), ratio of shoot formation (RSF), and length of shoot (LS) across different environments. A total of 77 SNPs were significantly associated these traits under three environments and using the averages (across environments). Among these significant SNPs, five were simultaneously detected under multiple environments and 11 had respective phenotypic variation explained > 10%. A total of 257 genes were located in the linkage disequilibrium decay of these REC- and ICD-associated SNPs, of which 178 were responsive to EC induction. According to the expression values of the 178 genes, we performed a weighted gene co-expression network analysis (WGCNA) and revealed an EC induction-associated module and five hub genes. Hub gene-based association studies uncovered that the intragenic variations in GRMZM2G105473 and ZmARF23 influenced EC induction efficiency among different maize lines. Dual-luciferase reporter assay indicated that ZmARF23 bound to the promoter of a known causal gene (ZmSAUR15) for EC induction and positively regulated its expression on the transcription level. Our study will deepen the understanding of genetic and molecular mechanisms underlying EC induction and contribute to the use of genetic transformation in maize.

Combining ability of tropical × temperate maize inducers for haploid induction rate, R1-nj seed set, and agronomic traits.

In vivo maternal haploid induction in isolation fields is proposed to bypass the workload and resource constraints existing in haploid induction nurseries. A better understanding of combining ability and gene action conditioning traits related to hybrid inducers is necessary to set the breeding strategy including to what extent parent-based hybrid prediction is feasible. This study aimed to evaluate the following in tropical savanna in the rainy and dry seasons for haploid induction rate (HIR), R1-nj seed set, and agronomic traits: 1) combining ability, line per se, and hybrid performance of three genetic pools; 2) genetic parameters, the modes of gene action, and heterosis; and 3) the relationships of inbred-general combining ability (GCA) and inbred-hybrid performance. Fifty-six diallel crosses derived from eight maize genotypes were evaluated in the rainy season of 2021 and the dry season of 2021/2022. Reciprocal cross effects including the maternal effect barely contributed to the genotypic variance for each trait observed. HIR, R1-nj seed set, flowering dates, and ear position were highly heritable and additive inherited, while ear length showed dominant inheritance. The equal importance of additive and dominance effects was found for yield-related traits. Temperate inducer BHI306 was the best general combiner for the HIR and R1-nj seed set, followed by two tropical inducers, KHI47 and KHI54. The ranges of heterosis were trait-dependent and slightly influenced by the environment, where hybrids in the rainy season consistently had higher heterosis than those in the dry season for each trait observed. Both hybrid groups derived from tropical × tropical and tropical × temperate inducers showed taller plants, larger ear size, and higher seed sets than the corresponding parents. However, their HIRs were still below the standard check of BHI306. The implications of genetic information, combining ability, and inbred-GCA and inbred-hybrid relationships on breeding strategies are discussed.

A Comparison between Inbred and Hybrid Maize Haploid Inducers.

The effectiveness of haploid induction systems is regarded not only for high haploid induction rate (HIR) but also resource savings. Isolation fields are proposed for hybrid induction. However, efficient haploid production depends on inducer traits such as high HIR, abundant pollen production, and tall plants. Seven hybrid inducers and their respective parents were evaluated over three years for HIR, seeds set in cross-pollinations, plant and ear height, tassel size, and tassel branching. Mid-parent heterosis was estimated to quantify how much inducer traits improve in hybrids in comparison to their parents. Heterosis benefits hybrid inducers for plant height, ear height, and tassel size. Two hybrid inducers, BH201/LH82-Ped126 and BH201/LH82-Ped128, are promising for haploid induction in isolation fields. Hybrid inducers offer convenience and resource-effectiveness for haploid induction by means of improving plant vigor without compromising HIR.

Haploid male fertility is restored by parallel spindle genes in Arabidopsis thaliana.

Doubled haploid technology can accelerate plant breeding and its two main steps are haploid induction and subsequent doubled haploid production from fertile haploid plants. Although haploid female fertility is present to some extent in plants, the lack of haploid male fertility is a bottleneck. Herein, we demonstrate that mutations in the parallel spindle genes are sufficient to restore haploid male fertility in Arabidopsis with no impact on haploid female fertility.

ZmbZIP54 and ZmFDX5 cooperatively regulate maize seedling tolerance to lead by mediating ZmPRP1 transcription.

Extensive lead (Pb) accumulation in plants exerts toxic effects on plant growth and development and enters the human food chain. Combining linkage mapping, transcriptome analysis, and association studies, we cloned the ZmbZIP54 transcription factor, which confers maize tolerance to Pb. Combined overexpression and knockdown confirmed that ZmbZIP54 mitigates Pb toxicity in maize by alleviating Pb absorption into the roots. Yeast one-hybrid and dual-luciferase assays revealed that ZmbZIP54 binds to the ZmPRP1 promoter and promotes its transcription. Yeast two-hybrid and bimolecular fluorescence complementation assays indicated that ZmFdx5 interacts with ZmbZIP54 in the nucleus. ZmFdx5 acts as a switch that controls the regulation of ZmPRP1 expression by ZmbZIP54 when maize encounters Pb stress. Furthermore, we revealed that variation in the 5'-UTR of ZmbZIP54 affects its expression level under Pb stress and contributes to the difference in Pb tolerance among maize lines. Finally, we proposed a model to summarize the role of ZmbZIP54 in Pb tolerance, which involves the cooperative effect of ZmbZIP54 and ZmFdx5 on the ZmPRP1 transcription in maize response to Pb. This study provides novel insights into the development of Pb-tolerant maize varieties and bioremediation of Pb-contaminated soils.

Fine-Mapping and Comparative Genomic Analysis Reveal the Gene Composition at the S and Z Self-incompatibility Loci in Grasses.

Self-incompatibility (SI) is a genetic mechanism of hermaphroditic plants to prevent inbreeding after self-pollination. Allogamous Poaceae species exhibit a unique gametophytic SI system controlled by two multi-allelic and independent loci, S and Z. Despite intense research efforts in the last decades, the genes that determine the initial recognition mechanism are yet to be identified. Here, we report the fine-mapping of the Z-locus in perennial ryegrass (Lolium perenne L.) and provide evidence that the pollen and stigma components are determined by two genes encoding DUF247 domain proteins (ZDUF247-I and ZDUF247-II) and the gene sZ, respectively. The pollen and stigma determinants are located side-by-side and were genetically linked in 10,245 individuals of two independent mapping populations segregating for Z. Moreover, they exhibited high allelic diversity as well as tissue-specific gene expression, matching the expected characteristics of SI determinants known from other systems. Revisiting the S-locus using the latest high-quality whole-genome assemblies revealed a similar gene composition and structure as found for Z, supporting the hypothesis of a duplicated origin of the two-locus SI system of grasses. Ultimately, comparative genomic analyses across a wide range of self-compatible and self-incompatible Poaceae species revealed that the absence of a functional copy of at least one of the six putative SI determinants is accompanied by a self-compatible phenotype. Our study provides new insights into the origin and evolution of the unique gametophytic SI system in one of the largest and economically most important plant families.

Genome-wide association analysis of plant architecture traits using doubled haploid lines derived from different cycles of the Iowa Stiff Stalk Synthetic maize population.

Selection in the Iowa Stiff Stalk Synthetic (BSSS) maize population for high yield, grain moisture, and root and stalk lodging has indirectly modified plant architecture traits that are important for adaptation to high plant density. In this study, we developed doubled haploid (DH) lines from the BSSS maize population in the earliest cycle of recurrent selection (BSSS), cycle 17 of reciprocal recurrent selection, [BSSS(R)17] and the cross between the two cycles [BSSS/BSSS(R)C17]. We aimed to determine the phenotypic variation and changes in agronomic traits that have occurred through the recurrent selection program in this population and to identify genes or regions in the genome associated with the plant architecture changes observed in the different cycles of selection. We conducted a per se evaluation of DH lines focusing on high heritability traits important for adaptation to high planting density and grain yield. Trends for reducing flowering time, anthesis-silking interval, ear height, and the number of primary tassel branches in BSSS(R)17 DH lines compared to BSSS and BSSS/BSSS(R)C17 DH lines were observed. Additionally, the BSSS(R)C17 DH lines showed more upright flag leaf angles. Using the entire panel of DH lines increased the number of SNP markers identified within candidate genes associated with plant architecture traits. The genomic regions identified for plant architecture traits in this study may help to elucidate the genetic basis of these traits and facilitate future work about marker-assisted selection or map-based cloning in maize breeding programs.

Development of doubled haploid inducer lines facilitates selection of superior haploid inducers in maize.

Haploid inducers are key components of doubled haploid (DH) technology in maize. Robust agronomic performance and better haploid induction ability of inducers are persistently sought through genetic improvement. We herein developed C1-I inducers enabling large-scale in vivo haploid induction of inducers and discovered superior inducers from the DH progenies. The haploid induction rate (HIR) of C1-I inducers ranged between 5.8% and 12.0%. Overall, the success rate of DH production was 13% on average across the 23 different inducer crosses. The anthesis-silking interval and days to flowering of inducer F1s are significantly correlated with the success rate of DH production (r = -0.48 and 0.47, respectively). Transgressive segregants in DH inducers (DHIs) were found for the traits (days to flowering, HIR, plant height, and total primary branch length). Moreover, the best HIR in DHIs exceeded 23%. Parental genome contributions to DHI progenies ranged between 0.40 and 0.55, respectively, in 25 and 75 percentage quantiles, and the mean and median were 0.48. The allele frequency of the four traits from inducer parents to DHI progenies did not correspond with the phenotypic difference between superior and inferior individuals in the DH populations by genome-wide Fst analysis. This study demonstrated that the recombinant DHIs can be accessed on a large scale and used as materials to facilitate the genetic improvement of maternal haploid inducers by in vivo DH technology.

Improving drought tolerance in maize: Tools and techniques.

Drought is an important constraint to agricultural productivity worldwide and is expected to worsen with climate change. To assist farmers, especially in sub-Saharan Africa (SSA), to adapt to climate change, continuous generation of stress-tolerant and farmer-preferred crop varieties, and their adoption by farmers, is critical to curb food insecurity. Maize is the most widely grown staple crop in SSA and plays a significant role in food security. The aim of this review is to present an overview of a broad range of tools and techniques used to improve drought tolerance in maize. We also present a summary of progress in breeding for maize drought tolerance, while incorporating research findings from disciplines such as physiology, molecular biology, and systems modeling. The review is expected to complement existing knowledge about breeding maize for climate resilience. Collaborative maize drought tolerance breeding projects in SSA emphasize the value of public-private partnerships in increasing access to genomic techniques and useful transgenes. To sustain the impact of maize drought tolerance projects in SSA, there must be complementary efforts to train the next generation of plant breeders and crop scientists.

Seasonal Variation of Tropical Savanna Altered Agronomic Adaptation of Stock-6-Derived Inducer Lines.

Tropicalization is one of the major objectives in breeding haploid inducers to address the poor adaptation of temperate haploid inducers in doubled haploid production in tropical maize. Gaining a better understanding of weather profiles in targeted agroecology is important. This study aimed to investigate the seasonal variation of tropical savanna climate and its impact on agronomic traits and haploid induction rate (HIR) of Stock-6-derived haploid inducer lines. A total of 14 haploid inducers were evaluated across two typical growing seasons between 2020 and 2021. Weather data were collected on daily minimum and maximum temperatures, relative humidity, precipitation, and solar radiation whereas phenotypic data were recorded on plant phenology, tassel attributes, plant stature, ear components, inducer seed rate (ISR), and HIR. The effects of season, genotype, and genotype by season were significant for all traits except season factor on ISR. Seasonal variation existed where the dry season was more suitable for haploid induction and inducer maintenance, as haploid inducers revealed better agronomic performance and seed set, delayed flowering dates, and higher HIR. Since the crossover performance of haploid inducers over seasons was detected, further implications on genotype selection in each season are discussed.