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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. Abstract 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.

Key message A major QTL of qRtsc8-1 conferring TSC resistance was identified and fine mapped to a 721 kb region on chromosome 8 at 81 Mb, and production markers were validated in breeding lines. Abstract Tar spot complex (TSC) is a major foliar disease of maize in many Central and Latin American countries and leads to severe yield loss. To dissect the genetic architecture of TSC resistance, a genome-wide association study (GWAS) panel and a bi-parental doubled haploid population were used for GWAS and selective genotyping analysis, respectively. A total of 115 SNPs in bin 8.03 were detected by GWAS and three QTL in bins 6.05, 6.07, and 8.03 were detected by selective genotyping. The major QTL qRtsc8-1 located in bin 8.03 was detected by both analyses, and it explained 14.97% of the phenotypic variance. To fine map qRtsc8-1, the recombinant-derived progeny test was implemented. Recombinations in each generation were backcrossed, and the backcross progenies were genotyped with Kompetitive Allele Specific PCR (KASP) markers and phenotyped for TSC resistance individually. The significant tests for comparing the TSC resistance between the two classes of progenies with and without resistant alleles were used for fine mapping. In BC5 generation, qRtsc8-1 was fine mapped in an interval of ~ 721 kb flanked by markers of KASP81160138 and KASP81881276. In this interval, the candidate genes GRMZM2G063511 and GRMZM2G073884 were identified, which encode an integral membrane protein-like and a leucine-rich repeat receptor-like protein kinase, respectively. Both genes are involved in maize disease resistance responses. Two production markers KASP81160138 and KASP81160155 were verified in 471 breeding lines. This study provides valuable information for cloning the resistance gene, and it will also facilitate the routine implementation of marker-assisted selection in the breeding pipeline for improving TSC resistance.

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.

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

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.

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.

In light of anticipated climate change, we assessed the possibility to use an airborne platform to measure canopy temperature (CT) and the normalized differential vegetation index (NDVI) as well as the suitability of both traits for their use in breeding for tolerance to heat stress. We evaluated 71 subtropical maize (Zea maysL.) hybrids under heat stress and combined heat and drought stress in an environment with average temperatures of 29.8°C during the growing season and 31.2°C during the flowering period. Grain yield (GY) ranged from 0.33 to 4.19 Mg ha−1 under heat stress and from 0 to 1.37 Mg ha−1 under combined heat and drought stress, going along with increases in CT from 42.5°C to 49.5°C and decreases in NDVI from 0.54 to 0.48. The NDVI explained differences between and within treatments, while CT explained differences in GY among treatments and genotypes within the heat and drought stress treatment, as indicated by genetic correlations with GY. A principal component analysis was used to identify combinations of physiological characteristics associated with genotypic variation in GY. Results showed that selection gains for GY could be improved by 0.486 Mg ha−1 and 0.015 Mg ha−1 under heat and combined heat and drought stress, respectively, if selection is simultaneously carried out for GY, NDVI, and lower CT and shorter anthesis silking interval. We postulate that the use of selection indices, including CT and NDVI in conjunction with GY, will improve selection gains and increase cost efficiency of breeding programs. Fil: Neiff, Nicolás. Centro Internacional de Mejoramiento de Maíz y Trigo; México. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Dhliwayo, Thanda. Centro Internacional de Mejoramiento de Maíz y Trigo; México Fil: Suarez, Edgar A.. Centro Internacional de Mejoramiento de Maíz y Trigo; México Fil: Burgueno, Juan. Centro Internacional de Mejoramiento de Maíz y Trigo; México Fil: Trachsel, Samuel. Centro Internacional de Mejoramiento de Maíz y Trigo; México

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.