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Maize stalk rot reduces grain yield and quality. Information about the genetics of resistance to maize stalk rot could help breeders design effective breeding strategies for the trait. Genomic prediction may be a more effective breeding strategy for stalk-rot resistance than marker-assisted selection. We performed a genome-wide association study (GWAS) and genomic prediction of resistance in testcross hybrids of 677 inbred lines from the Tuxpeño and non-Tuxpeño heterotic pools grown in three environments and genotyped with 200,681 single-nucleotide polymorphisms (SNPs). Eighteen SNPs associated with stalk rot shared genomic regions with gene families previously associated with plant biotic and abiotic responses. More favorable SNP haplotypes traced to tropical than to temperate progenitors of the inbred lines. Incorporating genotype-by-environment (G x E) interaction increased genomic prediction accuracy. [ABSTRACT FROM AUTHOR]

Heat and drought stresses negatively affect maize (Zea mays L.) productivity. We aimed to identify the genetic basis of tolerance to heat stress (HS) and combined heat and drought stress (HS+DS) and compare how QTL and whole genome selection (GS) could be leveraged to improve tolerance to both stresses. A set of 97 testcross hybrids derived from a maize bi-parental doubled-haploid population was evaluated during the summer seasons of 2014, 2015, and 2016 in Ciudad Obregon, Sonora, Mexico, under HS and HS+DS. Grain yield (GY) reached 5.7 t ha−1 under HS and 3.0 t ha−1 under HS+DS. Twenty-six QTL were detected across six environments, with LOD scores ranging from 2.03 to 3.86; the QTL explained 8.6% to 18.6% of the observed phenotypic variation. Hyperspectral biomass and structural index (HBSI) had higher genetic correlation with GY for HS (r = 0.97) and HS+DS (r = 0.74), relative to the correlation with crop water mass or greenness indices. Genetic correlations between GY and canopy temperature for HS (r = −0.89) and HS+DS (r = −0.75) or vegetation indices, along with clusters of QTL in bins 1.02, 1.05, and 2.05, underline the importance of these genomic areas for secondary traits associated with general vigor and greenness. Prediction accuracy of the model used for GS had values below those found in previous studies. We found a high-yielding hybrid that was tolerant to HS and HS+DS. [ABSTRACT FROM AUTHOR]

Most maize production across the globe is rain‐fed, and production is set to be negatively impacted as duration and occurrence of droughts increases due to climate change. Development of water‐deficit tolerant maize germplasm has been a major focus for most breeding programmes. Here, we sought to assess the genetic gain for grain yield in two maize populations developed for drought tolerance at CIMMYT by evaluating their cycle progeny through hybrid performance. Inbreds derived from different cycles of the Drought Tolerant Population (DTP) and La Posta Sequia (LPS) were mated to a tester (CML550), and resulting hybrids were evaluated under managed water‐deficit stress and well‐watered conditions. The difference in yield between water‐deficit and well‐watered treatments was 27% and 36% for the DTP and LPS, respectively. Genetic gain for grain yield across cycles for the two populations was confirmed in the study. Genetic gain was observed for both treatments indicating that selection for water‐deficit stress tolerance simultaneously improves grain yield in well‐watered conditions. The DTP population had a genetic gain of 0.07 t ha−1 cycle−1, while the LPS had 0.16 t ha−1 cycle−1 under water‐deficit conditions. Significant genetic gain was also observed in the well‐watered treatments for both populations. Anthesis to silking interval was significantly reduced under water‐deficit stress conditions in both populations. Plant and ear height were reduced in the LPS population in both treatments, while no reductions were observed for the trait in the DTP population. Potential water‐deficit stress tolerance donor lines with yields comparable to commercial check varieties were identified. [ABSTRACT FROM AUTHOR]

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CIMMYT maize lines (CMLs), which represent the tropical maize germplasm, are freely available worldwide. All currently released 615 CMLs and fourteen temperate maize inbred lines were genotyped with 180 kompetitive allele-specific PCR single nucleotide polymorphisms to develop a reference fingerprinting SNP dataset that can be used to perform quality control (QC) and genetic diversity analyses. The QC analysis identified 25 CMLs with purity, identity, or mislabeling issues. Further field observation, purification, and re-genotyping of these CMLs are required. The reference fingerprinting SNP dataset was developed for all of the currently released CMLs with 152 high-quality SNPs. The results of principal component analysis and average genetic distances between subgroups showed a clear genetic divergence between temperate and tropical maize, whereas the three tropical subgroups partially overlapped with one another. More than 99% of the pairs of CMLs had genetic distances greater than 0.30, showing their high genetic diversity, and most CMLs are distantly related. The heterotic patterns, estimated with the molecular markers, are consistent with those estimated using pedigree information in two major maize breeding programs at CIMMYT. These research findings are helpful for ensuring the regeneration and distribution of the true CMLs, via QC analysis, and for facilitating the effective utilization of the CMLs, globally. [ABSTRACT FROM AUTHOR]

Vitamin A deficiency (VAD) is a public health issue worldwide. Provitamin A (PVA) biofortified maize serves as an alternative to help combat VAD. Breeding efforts to develop maize varieties with high PVA carotenoid content combine molecular and phenotypic selection strategies. The phenotypic assessment of carotenoids is currently done using liquid chromatography, a precise but time- and resource-consuming methodology. Using near-infrared spectroscopy (NIRS) could increase the breeding efficiency. This study used ultra-performance liquid chromatography (UPLC) data from 1857 tropical maize genotypes as a training set and NIRS data to do an independent test of a set of 650 genotypes to predict PVA carotenoids using Bayesian and modified partial least square (MPLS) regression models. Both regression methods produced similar prediction accuracies for the total carotenoids (r2 = 0.75), lutein (r2 = 0.55), zeaxanthin (r2= 0.61), β-carotene (r2 = 0.22) and β-cryptoxanthin (BCX) (r2 = 0.57). These results demonstrate that Bayesian and MPLS regression of BCX on NIRS data can be used to predict BCX content, the current focus on PVA enhancement, and thus offers opportunities for high-throughput phenotyping at a low cost, especially in the early stages of PVA maize breeding pipeline when many genotypes must be screened. [ABSTRACT FROM AUTHOR]

Common rust is one of the major foliar diseases in maize, leading to significant grain yield losses and poor grain quality. To dissect the genetic architecture of common rust resistance, a genome-wide association study (GWAS) panel and a bi-parental doubled haploid (DH) population, DH1, were used to perform GWAS and linkage mapping analyses. The GWAS results revealed six single-nucleotide polymorphisms (SNPs) significantly associated with quantitative resistance of common rust at a very stringent threshold of P- value 3.70 × 10–6 at bins 1.05, 1.10, 3.04, 3.05, 4.08, and 10.04. Linkage mapping identified five quantitative trait loci (QTL) at bins 1.03, 2.06, 4.08, 7.03, and 9.00. The phenotypic variation explained (PVE) value of each QTL ranged from 5.40 to 12.45%, accounting for the total PVE value of 40.67%. Joint GWAS and linkage mapping analyses identified a stable genomic region located at bin 4.08. Five significant SNPs were only identified by GWAS, and four QTL were only detected by linkage mapping. The significantly associated SNP of S10_95231291 detected in the GWAS analysis was first reported. The linkage mapping analysis detected two new QTL on chromosomes 7 and 10. The major QTL on chromosome 7 in the region between 144,567,253 and 149,717,562 bp had the largest PVE value of 12.45%. Four candidate genes of GRMZM2G328500 , GRMZM2G162250 , GRMZM2G114893 , and GRMZM2G138949 were identified, which played important roles in the response of stress resilience and the regulation of plant growth and development. Genomic prediction (GP) accuracies observed in the GWAS panel and DH1 population were 0.61 and 0.51, respectively. This study provided new insight into the genetic architecture of quantitative resistance of common rust. In tropical maize, common rust could be improved by pyramiding the new sources of quantitative resistance through marker-assisted selection (MAS) or genomic selection (GS), rather than the implementation of MAS for the single dominant race-specific resistance gene. [ABSTRACT FROM AUTHOR]

Key message: Intensive public sector breeding efforts and public-private partnerships have led to the increase in genetic gains, and deployment of elite climate-resilient maize cultivars for the stress-prone environments in the tropics. Maize (Zea mays L.) plays a critical role in ensuring food and nutritional security, and livelihoods of millions of resource-constrained smallholders. However, maize yields in the tropical rainfed environments are now increasingly vulnerable to various climate-induced stresses, especially drought, heat, waterlogging, salinity, cold, diseases, and insect pests, which often come in combinations to severely impact maize crops. The International Maize and Wheat Improvement Center (CIMMYT), in partnership with several public and private sector institutions, has been intensively engaged over the last four decades in breeding elite tropical maize germplasm with tolerance to key abiotic and biotic stresses, using an extensive managed stress screening network and on-farm testing system. This has led to the successful development and deployment of an array of elite stress-tolerant maize cultivars across sub-Saharan Africa, Asia, and Latin America. Further increasing genetic gains in the tropical maize breeding programs demands judicious integration of doubled haploidy, high-throughput and precise phenotyping, genomics-assisted breeding, breeding data management, and more effective decision support tools. Multi-institutional efforts, especially public–private alliances, are key to ensure that the improved maize varieties effectively reach the climate-vulnerable farming communities in the tropics, including accelerated replacement of old/obsolete varieties. [ABSTRACT FROM AUTHOR]

The use of temperate maize (Zea mays L.) inbreds with expired Plant Variety Protection in tropical maize breeding programs could enhance the combining ability for grain yield among tropical heterotic groups. We used DNA markers from the DArTseq genotyping‐by‐sequencing platform to investigate the genetic structure of lines with expired U.S. Plant Variety Protection (ex‐PVP) relative to the International Maize and Wheat Improvement Center's (CIMMYT's) maize heterotic groups. Neighbor‐joining cluster analysis revealed two major groups: CIMMYT and ex‐PVP. The CIMMYT lines clustered according to their pedigree relationships and adaptation, but not according to their heterotic groups. In contrast, ex‐PVP lines clustered according to the Stiff Stalk Synthetic (BSSS) and non‐Stiff Stalk Synthetic (NSSS) heterotic groups, except for a few lines that were considered to be mixed. The genetic divergence, estimated as Wright's fixation index (FST), between BSSS and NSSS (FST =.053, P <.01) was four times as large as the divergence between CIMMYT Tuxpeño and non‐Tuxpeño heterotic groups (FST =.013, P =.068). Estimates of genetic divergence marginally favored breeding with BSSS in Tuxpeño and NSSS in non‐Tuxpeño. However, CIMMYT breeders may still exploit the ex‐PVP heterotic structure fully only by ensuring that the temperate heterotic groups are placed on opposite sides of the Tuxpeño and non‐Tuxpeño heterotic pattern. We also showed how estimates of admixture from model‐based clustering could be used to avoid ex‐PVP lines of mixed heterotic background when selecting lines to maximize the genetic divergence and combining ability of CIMMYT heterotic groups. [ABSTRACT FROM AUTHOR]

Enriching of kernel zinc (Zn) concentration in maize is one of the most effective ways to solve the problem of Zn deficiency in low and middle income countries where maize is the major staple food, and 17% of the global population is affected with Zn deficiency. Genomic selection (GS) has shown to be an effective approach to accelerate genetic gains in plant breeding. In the present study, an association-mapping panel and two maize double-haploid (DH) populations, both genotyped with genotyping-by-sequencing (GBS) and repeat amplification sequencing (rAmpSeq) markers, were used to estimate the genomic prediction accuracy of kernel Zn concentration in maize. Results showed that the prediction accuracy of two DH populations was higher than that of the association mapping population using the same set of markers. The prediction accuracy estimated with the GBS markers was significantly higher than that estimated with the rAmpSeq markers in the same population. The maximum prediction accuracy with minimum standard error was observed when half of the genotypes were included in the training set and 3,000 and 500 markers were used for prediction in the association mapping panel and the DH populations, respectively. Appropriate levels of minor allele frequency and missing rate should be considered and selected to achieve good prediction accuracy and reduce the computation burden by balancing the number of markers and marker quality. Training set development with broad phenotypic variation is possible to improve prediction accuracy. The transferability of the GS models across populations was assessed, the prediction accuracies in a few pairwise populations were above or close to 0.20, which indicates the prediction accuracies across years and populations have to be assessed in a larger breeding dataset with closer relationship between the training and prediction sets in further studies. GS outperformed MAS (marker-assisted-selection) on predicting the kernel Zn concentration in maize, the decision of a breeding strategy to implement GS individually or to implement MAS and GS stepwise for improving kernel Zn concentration in maize requires further research. Results of this study provide valuable information for understanding how to implement GS for improving kernel Zn concentration in maize. [ABSTRACT FROM AUTHOR]

Maize (Zea mays L.) inbred lines with expired U.S. Plant Variety Protection Act certificates (ex-PVPA) can be an important source of favorable alleles to improve grain yield, root and stalk lodging, drydown, plant architecture, and reduced time to maturity of tropical hybrids. Understanding the heterotic patterns and combining ability of ex-PVPA lines with tropical lines is necessary to design effective breeding strategies using this germplasm. This study evaluated 10 Iowa Stiff Stalk Synthetic (BSSS) and 11 Non-Stiff Stalk Synthetic (NSSS) inbred lines in hybrid combinations with tropical mid-altitude testers in five mid-altitude environments (900–2000 masl) in Mexico and identified six hybrids with grain yield equal or superior to that of the check hybrids. Two NSSS inbred lines: PHR03 and PHN82 had significant (P < 0.01) and positive general combining ability (GCA) effects with inbred lines from CIMMYT's Tuxpeño heterotic group. Similarly, the BSSS line PHG39 had a significant positive GCA effect (P < 0.05) with non-Tuxpeño lines. The lines PHN82 and PHK29 had positive GCA effects (P < 0.01) under drought stress and could be used as sources of drought tolerance in CIMMYT breeding programs. The mid-altitude lines CML537 and CML539 had positive GCA effects (1.45 and 0.69 t/ha, respectively; P < 0.01) with NSSS lines whereas hybrids of CML384 with BSSS lines yielded 0.64 t/ha (P < 0.01) more than the average of the testcrosses. These results showed that U.S. ex-PVPA lines can increase grain yield of CIMMYT's tropical mid-altitude hybrids. [ABSTRACT FROM AUTHOR]

Maize is a major source of food security and economic development in sub-Saharan Africa (SSA), Latin America, and the Caribbean, and is among the top three cereal crops in Asia. Yet, maize is deficient in certain essential amino acids, vitamins, and minerals. Biofortified maize cultivars enriched with essential minerals and vitamins could be particularly impactful in rural areas with limited access to diversified diet, dietary supplements, and fortified foods. Significant progress has been made in developing, testing, and deploying maize cultivars biofortified with quality protein maize (QPM), provitamin A, and kernel zinc. In this review, we outline the status and prospects of developing nutritionally enriched maize by successfully harnessing conventional and molecular marker-assisted breeding, highlighting the need for intensification of efforts to create greater impacts on malnutrition in maize-consuming populations, especially in the low- and middle-income countries. Molecular marker-assisted selection methods are particularly useful for improving nutritional traits since conventional breeding methods are relatively constrained by the cost and throughput of nutritional trait phenotyping. [ABSTRACT FROM AUTHOR]

Maize (Zea mays L.) hybrids with enhanced provitamin A (proVA) content have been deployed in sub‐Saharan Africa, where low soil nitrogen and drought stress are common. The objectives of this study were to assess: (i) the effects of drought and low‐N stress on grain proVA content of hybrids with enhanced proVA content, and (ii) the inheritance of proVA carotenoids under these stress conditions. An 11‐line diallel cross (55 F1 crosses) was evaluated for carotenoid content and grain yield under optimum conditions, drought, and low‐N stress. Compared with the optimum treatment, mean proVA was lower under both stress treatments. The consistency of genetic effects across stress treatments suggested that hybrids with improved proVA content can be developed for a broad range of environments, provided they are sufficiently adapted. General combining ability (GCA) was significant (P < 0.01), and accounted for >85% of the variation among hybrids, whereas specific combining ability (SCA) effects were generally weak (P < 0.05), accounting for 5 to 15% of hybrid sums of squares across the three treatments. These results indicated that the inheritance of proVA was not affected by stress treatments. A negative correlation between grain yield and proVA carotenoids was detected, but the data suggested that it was caused by the genetic background of the germplasm used rather than pleiotropy. Our results provide insights that may help breeders design effective breeding strategies to develop proVA‐enriched cultivars for resource‐limited farming systems. [ABSTRACT FROM AUTHOR]

High throughput phenotyping technologies are lagging behind modern marker technology impairing the use of secondary traits to increase genetic gains in plant breeding. We aimed to assess whether the combined use of hyperspectral data with modern marker technology could be used to improve across location pre-harvest yield predictions using different statistical models. A maize bi-parental doubled haploid (DH) population derived from F1, which consisted of 97 lines was evaluated in testcross combination under heat stress as well as combined heat and drought stress during the 2014 and 2016 summer season in Ciudad Obregon, Sonora, Mexico (27°20" N, 109°54" W, 38 m asl). Full hyperspectral data, indicative of crop physiological processes at the canopy level, was repeatedly measured throughout the grain filling period and related to grain yield. Partial least squares regression (PLSR), random forest (RF), ridge regression (RR) and Bayesian ridge regression (BayesB) were used to assess prediction accuracies on grain yield within (two-fold cross-validation) and across environments (leave-one-environment-out-cross-validation) using molecular markers (M), hyperspectral data (H) and the combination of both (HM). Highest prediction accuracy for grain yield averaged across within and across location predictions (rGP) were obtained for BayesB followed by RR, RF and PLSR. The combined use of hyperspectral and molecular marker data as input factor on average had higher predictions for grain yield than hyperspectral data or molecular marker data alone. The highest prediction accuracy for grain yield across environments was measured for BayesB when molecular marker data and hyperspectral data were used as input factors, while the highest within environment prediction was obtained when BayesB was used in combination with hyperspectral data. It is discussed how the combined use of hyperspectral data with molecular marker technology could be used to introduce physiological genomic estimated breeding values (PGEBV) as a pre-harvest decision support tool to select genetically superior lines. [ABSTRACT FROM AUTHOR]

Analysis of the sequences of 74 randomly selected BACs demonstrated that the maize nuclear genome contains ≈37,000 candidate genes with homologues in other plant species. An additional ≈5,500 predicted genes are severely truncated and probably pseudogenes. The distribution of genes is uneven, with ≈30% of BACs containing no genes. BAC gene density varies from 0 to 7.9 per 100 kb, whereas most gene islands contain only one gene. The average number of genes per gene island is 1.7. Only 72% of these genes show collinearity with the rice genome. Particular LTR retrotransposon families (e.g., Gyma) are enriched on gene-free BACs, most of which do not come from pericentromeres or other large heterochromatic regions. Gene-containing BACs are relatively enriched in different families of LTR retrotransposons (e.g., Ji). Two major bursts of LTR retrotransposon activity in the last 2 million years are responsible for the large size of the maize genome, but only the more recent of these is well represented in gene-containing BACs, suggesting that LTR retrotransposons are more efficiently removed in these domains. The results demonstrate that sample sequencing and careful annotation of a few randomly selected BACs can provide a robust description of a complex plant genome. [ABSTRACT FROM AUTHOR]

Maize (Zea mays L.) improvement involves formation, evaluation, selection, and recombination of genetically variable families or inbred lines, and because cultivars must combine many desirable traits, the process can be complicated and lengthy. This study compared 12 experimental open-pollinated varieties (OPVs) developed from maize population Pool 9A by two approaches, full-sib (FS) selection alone and FS selection combined with inbreeding with selection for Maize streakvirus (MSV) resistance. The experimental OPVs were evaluated in 13 environments in Africa, including three sites with artificial MSV inoculation. Full-sib selection combined with inbreeding and selection for MSV resistance [with mild selection for gray leaf spot resistance (GLS, caused by Cercospora zeae maydis Tehon & Daniels)], reduced ear height and reduced days to flowering] resulted in OPVs with similar grain yield but superior MSV resistance (P < 0.01), fewer days to anthesis (P < 0.01), and lower ear height (P < 0.05) than OPVs developed by FS selection alone. Each generation (from S0 to S3) of inbreeding with selection resulted in OPVs that were 16, 8, 2, and 1% improved for MSV and GLS resistance, ear height, and days to anthesis, respectively. Our results demonstrate improvement of a maize population for MSV resistance and other traits by selection during inbreeding (from S0 to S3), without negative impact on gains for grain yield achieved by evaluation and selection among the progenitor FS families. [ABSTRACT FROM AUTHOR]

Maize weevil (Sitophilus zeamais Motschulsky) is an important pest of maize (Zea mays L.) in the tropics, causing serious losses for many resource-poor farmers who store grain on-farm for use as food and seed. This study evaluated whether weevil resistance of six maize populations could be divergently changed by S[sub 1] and S[sub 2] selection, and assessed the importance of replicating grain samples when screening for resistance. Weevil resistance was evaluated for unreplicated S[sub 1] and for replicated and unreplicated S[sub 2] lines by infesting 50-g grain samples with 32 young adult weevils, and then incubating the samples in a controlled temperature and relative humidity (CTH) laboratory. Divergent synthetics were formed by recombining the most resistant 10% and the most susceptible 10% of at least 100 lines screened for weevil resistance for each maize population. Replicated S[sub 2] selection was successful for both populations where it was applied, resulting in an average of 16% (P < 0.01), 49% (P < 0.05), and 20% (P < 0.01) difference between divergent synthetics for weevil progeny emerged, grain weight loss, and the Dobie index of susceptibility, respectively. S[sub 1] unreplicated selection was successful for two of the six populations, while S[sub 2] unreplicated selection was not successful. Reciprocal effects were significant (P < 0.01) for weevil resistance of F[sub 1] varietal crosses among the divergently selected synthetics, indicating the influence of maternal effects. Nevertheless, the most resistant crosses were those among the most resistant synthetics, confirming that additive gene action for weevil resistance was important. Our results provide practical insights regarding methodologies and demonstrate that it is possible to improve weevil resistance of maize populations. [ABSTRACT FROM AUTHOR]

Genotype, environmental temperature, and agronomic management of parents influence seed yield in three-way cross hybrid maize seed production. The objective of this research was to generate information on the seed production of six three-way cross hybrids and their progenitors, adapted to tropical lowlands. Data on days to—and duration of—flowering, distance to spike and stigmas, and seed yield of five female single crosses and five male inbred lines were recorded for different combinations of four planting densities and four sowing dates in Mexico. The effect of planting density was not significant. The male inbred line T10 was the earliest and highest seed yield and T31 the latest, occupying second place in yield. The single crosses T32/T10 and T13/T14 were the earliest and had the highest effective seed yield. At the earliest sowing date, the females were later in their flowering, accumulated fewer growing degree days (GDD), and obtained higher yields since the grain-filling period coincided with hot days and cool nights. To achieve greater floral synchronization and therefore greater production of hybrid seed, differential planting dates for parents are recommended based on information from the accumulated GDD of each parent. The three-way cross hybrids were classified according to the expected seed yield of the females and the complexity in the synchronization of flowering of their parents. [ABSTRACT FROM AUTHOR]

Medium and small seed companies require information on maize parental seed production to make rational choices on what germplasm to introduce into their seed and breeding pipelines. The objective of this study was to generate public data on the appropriate hybrid seed production information of five female lines (T21, T26, T28, T33 and T38) and one line (T10) as a male hybrid parent. The effect of female and male sowing date and sowing density on hybrid seed production characteristics including flowering time, flowering duration, distance between tassel and stigmas and effective seed yield was determined. Recommendations to stagger male and female sowing to achieve flowering synchrony for the hybrid parents were complemented with data of seedling growth stages. The results were similar for T21, T26, T28, and T38; sowing the female and T10 on a row proportion of 4 females:1 male, and on a second date, when the coleoptiles of the female plants are halfway to emerge, sowing the missing male row to complete the 4:2 ratio. T33 is a late flowering line, therefore it is desirable to sow T33 first and T10 five days later, or when the T33 coleoptile begins to emerge. Plant densities did not cause differences in most plant characteristics. Line T21 showed good female parental traits. While this study provides a knowledge framework for seed production technology for these single cross hybrids, data specific to seed production regions need to be generated by seed companies to define the best regimes for hybrid production. [ABSTRACT FROM AUTHOR]

Genetic improvement of maize with elevated levels of zinc (Zn) can reduce Zn deficiency among populations who rely on maize as a staple. Inbred lines of quality protein maize (QPM) and non-QPM with elevated Zn levels in the kernel have been identified. However, information about the optimal strategy to utilize the germplasm in breeding for high-Zn concentration is lacking. As a preliminary step, this study was conducted to ascertain the potential of QPM, non-QPM, or a combination of QPM and non-QPM hybrids for attaining desirable Zn concentration. Twenty elite inbreds, 10 QPM and 10 non-QPM, were crossed according to a modified mating design to generate hybrids, which were evaluated in four environments in Mexico during 2015 and 2016 in order to evaluate their merits as parents of hybrids. The highest mean values of Zn were observed when high-Zn QPM lines were crossed with high-Zn non-QPM lines. Hybrids with high Zn and grain yield were identified. General combining ability (GCA) effects for Zn concentration were more preponderant than specific combining ability (SCA) effects, suggesting the importance of additive gene action for the inheritance of Zn. [ABSTRACT FROM AUTHOR]

Zinc (Zn) deficiency is a major risk factor for human health, affecting about 30% of the world's population. To study the potential of genomic selection (GS) for maize with increased Zn concentration, an association panel and two doubled haploid (DH) populations were evaluated in three environments. Three genomic prediction models, M (M1: Environment + Line, M2: Environment + Line + Genomic, and M3: Environment + Line + Genomic + Genomic x Environment) incorporating main effects (lines and genomic) and the interaction between genomic and environment (G x E) were assessed to estimate the prediction ability (rMP) for each model. Two distinct cross-validation (CV) schemes simulating two genomic prediction breeding scenarios were used. CV1 predicts the performance of newly developed lines, whereas CV2 predicts the performance of lines tested in sparse multi-location trials. Predictions for Zn in CV1 ranged from -0.01 to 0.56 for DH1, 0.04 to 0.50 for DH2 and -0.001 to 0.47 for the association panel. For CV2, rMP values ranged from 0.67 to 0.71 for DH1, 0.40 to 0.56 for DH2 and 0.64 to 0.72 for the association panel. The genomic prediction model which included G x E had the highest average rMP for both CV1 (0.39 and 0.44) and CV2 (0.71 and 0.51) for the association panel and DH2 population, respectively. These results suggest that GS has potential to accelerate breeding for enhanced kernel Zn concentration by facilitating selection of superior genotypes. [ABSTRACT FROM AUTHOR]