Biofortified orange corn increases xanthophyll density and yolk pigmentation in egg yolks from laying hens.

Plant breeding has developed corn genotypes with grain higher in levels of carotenoids. Dietary consumption of specific carotenoids by humans has been associated with improved eye health, notably with some protection against age-related macular degeneration. Increasing dietary sources of macular carotenoids in the standard American diet might be accomplished by using high carotenoid Orange Corn in poultry diets to increase macular carotenoid concentrations in egg yolks. Three hundred sixty laying hens (Novogen White) were fed three different diets over 31 days. Each diet had six replicates of 20 hens housed in enrichable colony cages. The only difference was the type of corn included - white, yellow, and orange, in order to assess the impact of each type of corn on egg production, yolk pigmentation, and carotenoid deposition. This study assessed yolk color and carotenoid densities using a portable colorimeter and the DSM YolkFan, and by high performance liquid chromatography (HPLC) on eggs from the feeding study and on 43 cartons of 12 eggs commercially available and produced in various production settings: conventional cage, cage-free, cage-free organic, free-range/pasture, and free-range/pasture organic. Yolks from hens fed with the Orange Corn diet produced eggs with higher (P < 0.01) DSM yolk color (6 to 10) and total xanthophylls (23.5 to 35.3 µg/g of egg yolk) compared to the yellow diet (5 to 6 DSM and 12.3 to 17.7 µg/g xanthophylls) and white diet (1 to 2 DSM and 2.5 to 3.0 µg/g xanthophylls). Egg yolks reached a maximum xanthophyll accumulation with the Orange Corn diet (35.3 µg/g of egg yolk) after twelve days of treatment and maintained steady levels at subsequent time points. In general, xanthophyll levels in yolks from the Orange Corn diet were superior (30-61% higher) to any of the commercial egg brands, suggesting that feeding high carotenoid Orange Corn increases xanthophyll density in eggs.

Eleven biosynthetic genes explain the majority of natural variation in carotenoid levels in maize grain.

Vitamin A deficiency remains prevalent in parts of Asia, Latin America, and sub-Saharan Africa where maize (Zea mays) is a food staple. Extensive natural variation exists for carotenoids in maize grain. Here, to understand its genetic basis, we conducted a joint linkage and genome-wide association study of the US maize nested association mapping panel. Eleven of the 44 detected quantitative trait loci (QTL) were resolved to individual genes. Six of these were correlated expression and effect QTL (ceeQTL), showing strong correlations between RNA-seq expression abundances and QTL allelic effect estimates across six stages of grain development. These six ceeQTL also had the largest percentage of phenotypic variance explained, and in major part comprised the three to five loci capturing the bulk of genetic variation for each trait. Most of these ceeQTL had strongly correlated QTL allelic effect estimates across multiple traits. These findings provide an in-depth genome-level understanding of the genetic and molecular control of carotenoids in plants. In addition, these findings provide a roadmap to accelerate breeding for provitamin A and other priority carotenoid traits in maize grain that should be readily extendable to other cereals.

High-resolution genome-wide association study pinpoints metal transporter and chelator genes involved in the genetic control of element levels in maize grain.

Despite its importance to plant function and human health, the genetics underpinning element levels in maize grain remain largely unknown. Through a genome-wide association study in the maize Ames panel of nearly 2,000 inbred lines that was imputed with ∼7.7 million SNP markers, we investigated the genetic basis of natural variation for the concentration of 11 elements in grain. Novel associations were detected for the metal transporter genes rte2 (rotten ear2) and irt1 (iron-regulated transporter1) with boron and nickel, respectively. We also further resolved loci that were previously found to be associated with one or more of five elements (copper, iron, manganese, molybdenum, and/or zinc), with two metal chelator and five metal transporter candidate causal genes identified. The nas5 (nicotianamine synthase5) gene involved in the synthesis of nicotianamine, a metal chelator, was found associated with both zinc and iron and suggests a common genetic basis controlling the accumulation of these two metals in the grain. Furthermore, moderate predictive abilities were obtained for the 11 elemental grain phenotypes with two whole-genome prediction models: Bayesian Ridge Regression (0.33-0.51) and BayesB (0.33-0.53). Of the two models, BayesB, with its greater emphasis on large-effect loci, showed ∼4-10% higher predictive abilities for nickel, molybdenum, and copper. Altogether, our findings contribute to an improved genotype-phenotype map for grain element accumulation in maize.

The importance of dominance and genotype-by-environment interactions on grain yield variation in a large-scale public cooperative maize experiment.

High-dimensional and high-throughput genomic, field performance, and environmental data are becoming increasingly available to crop breeding programs, and their integration can facilitate genomic prediction within and across environments and provide insights into the genetic architecture of complex traits and the nature of genotype-by-environment interactions. To partition trait variation into additive and dominance (main effect) genetic and corresponding genetic-by-environment variances, and to identify specific environmental factors that influence genotype-by-environment interactions, we curated and analyzed genotypic and phenotypic data on 1918 maize (Zea mays L.) hybrids and environmental data from 65 testing environments. For grain yield, dominance variance was similar in magnitude to additive variance, and genetic-by-environment variances were more important than genetic main effect variances. Models involving both additive and dominance relationships best fit the data and modeling unique genetic covariances among all environments provided the best characterization of the genotype-by-environment interaction patterns. Similarity of relative hybrid performance among environments was modeled as a function of underlying weather variables, permitting identification of weather covariates driving correlations of genetic effects across environments. The resulting models can be used for genomic prediction of mean hybrid performance across populations of environments tested or for environment-specific predictions. These results can also guide efforts to incorporate high-throughput environmental data into genomic prediction models and predict values in new environments characterized with the same environmental characteristics.

Dominance Effects and Functional Enrichments Improve Prediction of Agronomic Traits in Hybrid Maize.

Single-cross hybrids have been critical to the improvement of maize (Zea mays L.), but the characterization of their genetic architectures remains challenging. Previous studies of hybrid maize have shown the contribution of within-locus complementation effects (dominance) and their differential importance across functional classes of loci. However, they have generally considered panels of limited genetic diversity, and have shown little benefit from genomic prediction based on dominance or functional enrichments. This study investigates the relevance of dominance and functional classes of variants in genomic models for agronomic traits in diverse populations of hybrid maize. We based our analyses on a diverse panel of inbred lines crossed with two testers representative of the major heterotic groups in the U.S. (1106 hybrids), as well as a collection of 24 biparental populations crossed with a single tester (1640 hybrids). We investigated three agronomic traits: days to silking (DTS), plant height (PH), and grain yield (GY). Our results point to the presence of dominance for all traits, but also among-locus complementation (epistasis) for DTS and genotype-by-environment interactions for GY. Consistently, dominance improved genomic prediction for PH only. In addition, we assessed enrichment of genetic effects in classes defined by genic regions (gene annotation), structural features (recombination rate and chromatin openness), and evolutionary features (minor allele frequency and evolutionary constraint). We found support for enrichment in genic regions and subsequent improvement of genomic prediction for all traits. Our results suggest that dominance and gene annotations improve genomic prediction across diverse populations in hybrid maize.

Maize genomes to fields (G2F): 2014-2017 field seasons: genotype, phenotype, climatic, soil, and inbred ear image datasets.

OBJECTIVES: Advanced tools and resources are needed to efficiently and sustainably produce food for an increasing world population in the context of variable environmental conditions. The maize genomes to fields (G2F) initiative is a multi-institutional initiative effort that seeks to approach this challenge by developing a flexible and distributed infrastructure addressing emerging problems. G2F has generated large-scale phenotypic, genotypic, and environmental datasets using publicly available inbred lines and hybrids evaluated through a network of collaborators that are part of the G2F's genotype-by-environment (G × E) project. This report covers the public release of datasets for 2014-2017. DATA DESCRIPTION: Datasets include inbred genotypic information; phenotypic, climatic, and soil measurements and metadata information for each testing location across years. For a subset of inbreds in 2014 and 2015, yield component phenotypes were quantified by image analysis. Data released are accompanied by README descriptions. For genotypic and phenotypic data, both raw data and a version without outliers are reported. For climatic data, a version calibrated to the nearest airport weather station and a version without outliers are reported. The 2014 and 2015 datasets are updated versions from the previously released files [1] while 2016 and 2017 datasets are newly available to the public.

Utility of Climatic Information via Combining Ability Models to Improve Genomic Prediction for Yield Within the Genomes to Fields Maize Project.

Genomic prediction provides an efficient alternative to conventional phenotypic selection for developing improved cultivars with desirable characteristics. New and improved methods to genomic prediction are continually being developed that attempt to deal with the integration of data types beyond genomic information. Modern automated weather systems offer the opportunity to capture continuous data on a range of environmental parameters at specific field locations. In principle, this information could characterize training and target environments and enhance predictive ability by incorporating weather characteristics as part of the genotype-by-environment (G×E) interaction component in prediction models. We assessed the usefulness of including weather data variables in genomic prediction models using a naïve environmental kinship model across 30 environments comprising the Genomes to Fields (G2F) initiative in 2014 and 2015. Specifically four different prediction scenarios were evaluated (i) tested genotypes in observed environments; (ii) untested genotypes in observed environments; (iii) tested genotypes in unobserved environments; and (iv) untested genotypes in unobserved environments. A set of 1,481 unique hybrids were evaluated for grain yield. Evaluations were conducted using five different models including main effect of environments; general combining ability (GCA) effects of the maternal and paternal parents modeled using the genomic relationship matrix; specific combining ability (SCA) effects between maternal and paternal parents; interactions between genetic (GCA and SCA) effects and environmental effects; and finally interactions between the genetics effects and environmental covariates. Incorporation of the genotype-by-environment interaction term improved predictive ability across all scenarios. However, predictive ability was not improved through inclusion of naive environmental covariates in G×E models. More research should be conducted to link the observed weather conditions with important physiological aspects in plant development to improve predictive ability through the inclusion of weather data.

Genome-Wide Association Study and Pathway-Level Analysis of Kernel Color in Maize.

Rapid development and adoption of biofortified, provitamin A-dense orange maize (Zea mays L.) varieties could be facilitated by a greater understanding of the natural variation underlying kernel color, including as it relates to carotenoid biosynthesis and retention in maize grain. Greater abundance of carotenoids in maize kernels is generally accompanied by deeper orange color, useful for distinguishing provitamin A-dense varieties to consumers. While kernel color can be scored and selected with high-throughput, low-cost phenotypic methods within breeding selection programs, it remains to be well established as to what would be the logical genetic loci to target for selection for kernel color. We conducted a genome-wide association study of maize kernel color, as determined by colorimetry, in 1,651 yellow and orange inbreds from the Ames maize inbred panel. Associations were found with y1, encoding the first committed step in carotenoid biosynthesis, and with dxs2, which encodes the enzyme responsible for the first committed step in the biosynthesis of the isoprenoid precursors of carotenoids. These genes logically could contribute to overall carotenoid abundance and thus kernel color. The lcyE and zep1 genes, which can affect carotenoid composition, were also found to be associated with colorimeter values. A pathway-level analysis, focused on genes with a priori evidence of involvement in carotenoid biosynthesis and retention, revealed associations for dxs3 and dmes1, involved in isoprenoid biosynthesis; ps1 and vp5, within the core carotenoid pathway; and vp14, involved in cleavage of carotenoids. Collectively, these identified genes appear relevant to the accumulation of kernel color.

Maize Genomes to Fields: 2014 and 2015 field season genotype, phenotype, environment, and inbred ear image datasets.

OBJECTIVES: Crop improvement relies on analysis of phenotypic, genotypic, and environmental data. Given large, well-integrated, multi-year datasets, diverse queries can be made: Which lines perform best in hot, dry environments? Which alleles of specific genes are required for optimal performance in each environment? Such datasets also can be leveraged to predict cultivar performance, even in uncharacterized environments. The maize Genomes to Fields (G2F) Initiative is a multi-institutional organization of scientists working to generate and analyze such datasets from existing, publicly available inbred lines and hybrids. G2F's genotype by environment project has released 2014 and 2015 datasets to the public, with 2016 and 2017 collected and soon to be made available. DATA DESCRIPTION: Datasets include DNA sequences; traditional phenotype descriptions, as well as detailed ear, cob, and kernel phenotypes quantified by image analysis; weather station measurements; and soil characterizations by site. Data are released as comma separated value spreadsheets accompanied by extensive README text descriptions. For genotypic and phenotypic data, both raw data and a version with outliers removed are reported. For weather data, two versions are reported: a full dataset calibrated against nearby National Weather Service sites and a second calibrated set with outliers and apparent artifacts removed.

Carotenoid Stability during Dry Milling, Storage, and Extrusion Processing of Biofortified Maize Genotypes.

Translation of the breeding efforts designed to biofortify maize ( Z. mays) genotypes with higher levels of provitamin A carotenoid (pVAC) content for sub-Saharan Africa is dependent in part on the stability of carotenoids during postharvest through industrial and in-home food processing operations. The purpose of this study was to simulate production of commercial milled products by determining the impact of dry milling and extrusion processing on carotenoid stability in three higher pVAC maize genotypes (C17xDE3, Orange ISO, Hi27xCML328). Pericarp and germ removal of biofortified maize kernels resulted in ∼10% loss of total carotenoids. Separating out the maize flour fraction (<212 µm) resulted in an additional ∼15% loss of total carotenoids. Carotenoid degradation was similar across milled maize fractions. Dry-milled products of Orange ISO and Hi27xCML328 genotypes showed ∼28% pVAC loss after 90-days storage. Genotype C17xDE3, with highest levels of all- trans-ß-carotene, showed a 68% pVAC loss after 90-day storage. Extrusion processing conditions were optimal at 35% extrusion moisture, producing fully cooked instant maize flours with high pVAC retention (70-93%). These results support the notion that postharvest losses in maize milled fractions may be dependent, in part, on genotype and that extrusion processing may provide an option for preserving biofortified maize products.

Genetic relatedness of previously Plant-Variety-Protected commercial maize inbreds.

The emergence of high-throughput, high-density genotyping methods combined with increasingly powerful computing systems has created opportunities to further discover and exploit the genes controlling agronomic performance in elite maize breeding populations. Understanding the genetic basis of population structure in an elite set of materials is an essential step in this genetic discovery process. This paper presents a genotype-based population analysis of all maize inbreds whose Plant Variety Protection certificates had expired as of the end of 2013 (283 inbreds) as well as 66 public founder inbreds. The results provide accurate population structure information and allow for important inferences in context of the historical development of North American elite commercial maize germplasm. Genotypic data was obtained via genotyping-by-sequencing on 349 inbreds. After filtering for missing data, 77,314 high-quality markers remained. The remaining missing data (average per individual was 6.22 percent) was fully imputed at an accuracy of 83 percent. Calculation of linkage disequilibrium revealed that the average r2 of 0.20 occurs at approximately 1.1 Kb. Results of population genetics analyses agree with previously published studies that divide North American maize germplasm into three heterotic groups: Stiff Stalk, Non-Stiff Stalk, and Iodent. Principal component analysis shows that population differentiation is indeed very complex and present at many levels, yet confirms that division into three main sub-groups is optimal for population description. Clustering based on Nei's genetic distance provides an additional empirical representation of the three main heterotic groups. Overall fixation index (FST), indicating the degree of genetic divergence between the three main heterotic groups, was 0.1361. Understanding the genetic relationships and population differentiation of elite germplasm may help breeders to maintain and potentially increase the rate of genetic gain, resulting in higher overall agronomic performance.

The effect of artificial selection on phenotypic plasticity in maize.

Remarkable productivity has been achieved in crop species through artificial selection and adaptation to modern agronomic practices. Whether intensive selection has changed the ability of improved cultivars to maintain high productivity across variable environments is unknown. Understanding the genetic control of phenotypic plasticity and genotype by environment (G × E) interaction will enhance crop performance predictions across diverse environments. Here we use data generated from the Genomes to Fields (G2F) Maize G × E project to assess the effect of selection on G × E variation and characterize polymorphisms associated with plasticity. Genomic regions putatively selected during modern temperate maize breeding explain less variability for yield G × E than unselected regions, indicating that improvement by breeding may have reduced G × E of modern temperate cultivars. Trends in genomic position of variants associated with stability reveal fewer genic associations and enrichment of variants 0-5000 base pairs upstream of genes, hypothetically due to control of plasticity by short-range regulatory elements.

Novel Loci Underlie Natural Variation in Vitamin E Levels in Maize Grain.

Tocopherols, tocotrienols, and plastochromanols (collectively termed tocochromanols) are lipid-soluble antioxidants synthesized by all plants. Their dietary intake, primarily from seed oils, provides vitamin E and other health benefits. Tocochromanol biosynthesis has been dissected in the dicot Arabidopsis thaliana, which has green, photosynthetic seeds, but our understanding of tocochromanol accumulation in major crops, whose seeds are nonphotosynthetic, remains limited. To understand the genetic control of tocochromanols in grain, we conducted a joint linkage and genome-wide association study in the 5000-line U.S. maize (Zea mays) nested association mapping panel. Fifty-two quantitative trait loci for individual and total tocochromanols were identified, and of the 14 resolved to individual genes, six encode novel activities affecting tocochromanols in plants. These include two chlorophyll biosynthetic enzymes that explain the majority of tocopherol variation, which was not predicted given that, like most major cereal crops, maize grain is nonphotosynthetic. This comprehensive assessment of natural variation in vitamin E levels in maize establishes the foundation for improving tocochromanol and vitamin E content in seeds of maize and other major cereal crops.

Retention of Carotenoids in Biofortified Maize Flour and ß-Cryptoxanthin-Enhanced Eggs after Household Cooking.

Biofortification of crops to enhance provitamin A carotenoids is a strategy to increase the intake where vitamin A deficiency presents a widespread problem. Heat, light, and oxygen cause isomerization and oxidation of carotenoids, reducing provitamin A activity. Understanding provitamin A retention is important for assessing efficacy of biofortified foods. Retention of carotenoids in high-xanthophyll and high-ß-carotene maize was assessed after a long-term storage at three temperatures. Carotenoid retention in high-ß-cryptoxanthin maize was determined in muffins, non-nixtamalized tortillas, porridge, and fried puffs made from whole-grain and sifted flour. Retention in eggs from hens fed high-ß-cryptoxanthin maize was assessed after frying, scrambling, boiling, and microwaving. Loss during storage in maize was accelerated with increasing temperature and affected by genotype. Boiling whole-grain maize into porridge resulted in the highest retention of all cooking and sifting methods (112%). Deep-fried maize and scrambled eggs had the lowest carotenoid retention rates of 67-78 and 84-86%, respectively.

Influence of Temperature and Humidity on the Stability of Carotenoids in Biofortified Maize (Zea mays L.) Genotypes during Controlled Postharvest Storage.

Maize is a staple crop that has been the subject of biofortification efforts to increase the natural content of provitamin A carotenoids. Although significant progress toward increasing provitamin A carotenoid content in maize varieties has been made, postharvest handling factors that influence carotenoid stability during storage have not been fully established. The objectives of this study were to determine carotenoid profiles of six selected provitamin A biofortified maize genotypes at various developmental stages and assess the stability of carotenoids in maize kernels during controlled storage conditions (12 month period), including elevated temperature and relative humidity. There were no significant changes in the content of individual carotenoids within genotypes during kernel development from 45 days after pollination through the time of harvest. Carotenoid losses through traditional grain drying were also minimal (<9%). However, the stability of carotenoids in maize kernels over storage time after harvest was found to be dependent on both temperature and humidity, with variation observed among genotypes. Different forms of provitamin A carotenoids follow similar degradation rates. The genotype C17xDE3 had a degradation rate 2 times faster than those of the other genotypes evaluated (P < 0.001). These differences in carotenoid stability under controlled storage were attributed, in part, to observed differences in the physical properties of the kernels (surface area and porosity). These results support the notion that effective control of moisture content and temperature of the kernels during storage conditions is essential to reduce the speed of degradative reactions.

A foundation for provitamin A biofortification of maize: genome-wide association and genomic prediction models of carotenoid levels.

Efforts are underway for development of crops with improved levels of provitamin A carotenoids to help combat dietary vitamin A deficiency. As a global staple crop with considerable variation in kernel carotenoid composition, maize (Zea mays L.) could have a widespread impact. We performed a genome-wide association study (GWAS) of quantified seed carotenoids across a panel of maize inbreds ranging from light yellow to dark orange in grain color to identify some of the key genes controlling maize grain carotenoid composition. Significant associations at the genome-wide level were detected within the coding regions of zep1 and lut1, carotenoid biosynthetic genes not previously shown to impact grain carotenoid composition in association studies, as well as within previously associated lcyE and crtRB1 genes. We leveraged existing biochemical and genomic information to identify 58 a priori candidate genes relevant to the biosynthesis and retention of carotenoids in maize to test in a pathway-level analysis. This revealed dxs2 and lut5, genes not previously associated with kernel carotenoids. In genomic prediction models, use of markers that targeted a small set of quantitative trait loci associated with carotenoid levels in prior linkage studies were as effective as genome-wide markers for predicting carotenoid traits. Based on GWAS, pathway-level analysis, and genomic prediction studies, we outline a flexible strategy involving use of a small number of genes that can be selected for rapid conversion of elite white grain germplasm, with minimal amounts of carotenoids, to orange grain versions containing high levels of provitamin A.

Genetic architecture controlling variation in grain carotenoid composition and concentrations in two maize populations.

KEY MESSAGE: Genetic control of maize grain carotenoid profiles is coordinated through several loci distributed throughout three secondary metabolic pathways, most of which exhibit additive, and more importantly, pleiotropic effects. The genetic basis for the variation in maize grain carotenoid concentrations was investigated in two F2:3 populations, DEexp × CI7 and A619 × SC55, derived from high total carotenoid and high ß-carotene inbred lines. A comparison of grain carotenoid concentrations from population DEexp × CI7 grown in different environments revealed significantly higher concentrations and greater trait variation in samples harvested from a subtropical environment relative to those from a temperate environment. Genotype by environment interactions was significant for most carotenoid traits. Using phenotypic data in additive, environment-specific genetic models, quantitative trait loci (QTL) were identified for absolute and derived carotenoid traits in each population, including those specific to the isomerization of ß-carotene. A multivariate approach for these correlated traits was taken, using carotenoid trait principal components (PCs) that jointly accounted for 97 % or more of trait variation. Component loadings for carotenoid PCs were interpreted in the context of known substrate-product relationships within the carotenoid pathway. Importantly, QTL for univariate and multivariate traits were found to cluster in close proximity to map locations of loci involved in methyl-erythritol, isoprenoid and carotenoid metabolism. Several of these genes, including lycopene epsilon cyclase, carotenoid cleavage dioxygenase1 and beta-carotene hydroxylase, were mapped in the segregating populations. These loci exhibited pleiotropic effects on α-branch carotenoids, total carotenoid profile and ß-branch carotenoids, respectively. Our results confirm that several QTL are involved in the modification of carotenoid profiles, and suggest genetic targets that could be used for the improvement of total carotenoid and ß-carotene in future breeding populations.

Genome-wide association study and pathway-level analysis of tocochromanol levels in maize grain.

Tocopherols and tocotrienols, collectively known as tocochromanols, are the major lipid-soluble antioxidants in maize (Zea mays L.) grain. Given that individual tocochromanols differ in their degree of vitamin E activity, variation for tocochromanol composition and content in grain from among diverse maize inbred lines has important nutritional and health implications for enhancing the vitamin E and antioxidant contents of maize-derived foods through plant breeding. Toward this end, we conducted a genome-wide association study of six tocochromanol compounds and 14 of their sums, ratios, and proportions with a 281 maize inbred association panel that was genotyped for 591,822 SNP markers. In addition to providing further insight into the association between ZmVTE4 (γ-tocopherol methyltransferase) haplotypes and α-tocopherol content, we also detected a novel association between ZmVTE1 (tocopherol cyclase) and tocotrienol composition. In a pathway-level analysis, we assessed the genetic contribution of 60 a priori candidate genes encoding the core tocochromanol pathway (VTE genes) and reactions for pathways supplying the isoprenoid tail and aromatic head group of tocochromanols. This analysis identified two additional genes, ZmHGGT1 (homogentisate geranylgeranyltransferase) and one prephenate dehydratase parolog (of four in the genome) that also modestly contribute to tocotrienol variation in the panel. Collectively, our results provide the most favorable ZmVTE4 haplotype and suggest three new gene targets for increasing vitamin E and antioxidant levels through marker-assisted selection.

High-provitamin A carotenoid (Orange) maize increases hepatic vitamin A reserves of offspring in a vitamin A-depleted sow-piglet model during lactation.

The relationship of dietary vitamin A transfer from mother to fetus is not well understood. The difference in swine offspring liver reserves was investigated between single-dose vitamin A provided to the mother post-conception compared with continuous provitamin A carotenoid dietary intake from biofortified (enhanced provitamin A) orange maize (OM) fed during gestation and lactation. Vitamin A-depleted sows were fed OM (n = 5) or white maize (WM) + 1.05 mmol retinyl palmitate administered at the beginning of gestation (n = 6). Piglets (n = 102) were killed at 0, 10, 20, and 28 d after birth. Piglets from sows fed OM had higher liver retinol reserves (P < 0.0001) and a combined mean concentration from d 10 to 28 of 0.11 ± 0.030 µmol/g. Piglets from sows fed WM had higher serum retinol concentrations (0.56 ± 0.25 µmol/L; P = 0.0098) despite lower liver retinol concentrations of 0.068 ± 0.026 µmol/g from d 10 to 28. Milk was collected at 0, 5, 10, 20, and 28 d. Sows fed OM had a higher milk retinol concentration (1.36 ± 1.30 µmol/L; P = 0.038), than those fed WM (0.93 ±1.03 µmol/L). Sow livers were collected at the end of the study (n = 3/group) and had identical retinol concentrations (0.22 ± 0.05 µmol/g). Consumption of daily provitamin A carotenoids by sows during gestation and lactation increased liver retinol status in weanling piglets, illustrating the potential for provitamin A carotenoid consumption from biofortified staple foods to improve vitamin A reserves. Biofortified OM could have a measurable impact on vitamin A status in deficient populations if widely adopted.

Comparative intake of white- versus orange-colored maize by Zambian children in the context of promotion of biofortified maize.

BACKGROUND: Vitamin A deficiency is associated with poor health outcomes related to reproduction, growth, vision, and immunity. Biofortification of staple crops is a novel strategy for combating vitamin A deficiency in high-risk populations where staple food intakes are high. African populations are proposed beneficiaries of maize (Zea mays) biofortified with provitamin A carotenoids, often called "orange maize" because of its distinctive deep yellow-orange kernels. The color facilitates ready recognition but presents a cultural challenge to maize-consuming populations, including those in much of Africa, who traditionally eat white varieties. OBJECTIVE: This study explores the intake patterns of, as well as adaptation to, traditional foods made with provitamin A-biofortified maize compared with white maize in rural Zambian children 3 to 5 years of age (n = 189) during a 3-month feeding trial. METHODS: The subjects were fed a breakfast of maize porridge (sweet mush), a lunch of maize nshima (stiff mush) with various side dishes, and an afternoon snack based on a 6-day rotating menu. The trial was conducted in 2010. The orange maize used in the trial came from three different sources. O1 maize was from the 2009 harvest and was stored in a freezer until use in 2010. O2 maize was also from the 2009 harvest and was stored in a cold room until 2010. O3 ("fresh") maize was from the 2010 harvest and was fed immediately after harvest in week 9 of the study and then stored in a freezer until milling for the final four weeks. RESULTS: Consumption of menu items, except snacks, was influenced by week (p < .0084). The intakes of porridge and nshima made with orange maize equaled those of porridge and nshima made with white maize from week 2 onward. The intakes of porridge and nshima prepared from O1 and O2 did not differ, but intakes became significantly higher when meals made from O3 were introduced (p < .014 for porridge and p < or = .013 for nshima). CONCLUSIONS: These results demonstrate quick adaptation to orange maize, a preference for recently harvested maize, and an optimistic outlook for similar adaptation patterns in other biofortified-maize target countries.