Maize Diversity Research Articles

Genetic Diversity of Maize (Zea mays L.) Genotypes under Low Level of Nitrogen

Maize (Zea mays L.) is India's second most significant crop, behind rice. As a cross-pollinated crop, hybrid vigour is commonly used to achieve the best production potential. The selection of various genotypes is a primary goal in the maize hybrid breeding programme. Maize is a voracious feeder and requires a lot of fertiliser. The biggest limits on maize production in India are low soil nitrogen and high fertiliser costs. Jharkhand consumes only 82.5 kg of total fertiliser nutrients per acre. In order to discover genetically varied maize genotypes for nitrogen usage efficiency, the current study evaluated 121 maize genotypes in a randomised block design with two replications at low nitrogen levels. Plant height, days to 50% pollen shed, days to 50% silk, anthesis-silking interval (ASI), days to75% maturity, number of leaves per plant, root length, stover yield per plant, grain yield per plant, and harvest index were all recorded. Statistical analysis was performed using the morphological trait data. Analysis of variance revealed substantial (p≤0.05) variations in morphological features between maize genotypes. For statistical analysis, a clustering method was used to locate various genotypes with greater genetic distance in order to develop good heterotic combinations. One hundred twenty one genotypes were divided into six clusters using the dendogram-by-ward minimum variance approach. Cluster III and V had the greatest inter-cluster distance (79.26), followed by cluster III and VI (74.77) and cluster II and III (73.80). The many heterotic combinations developed from these clusters can be employed in subsequent breeding programmes to produce low nitrogen-requiring hybrids with a low yield penalty.

Development of a MaizeGerm50K array and application to maize genetic studies and breeding

Genotyping arrays based on single nucleotide polymorphisms (SNPs) provide a low-cost, high-throughput platform. The development of a SNP array that fully reflects the genetic diversity of maize (Zea mays L.) germplasm and is applicable to molecular breeding programs is desirable. In this study, we developed a MaizeGerm50K array comprising 50,852 SNPs selected from the resequencing data of 1604 maize inbred lines and other markers. A genome-wide association study using a landrace panel genotyped with the array permitted mapping of several known genes. We also verified a candidate gene, RNA-binding motif protein 24-like 1 (ZmRBM24L1), delaying flowering through overexpression lines. Genomic selection for yield and agronomic traits showed high prediction accuracy. The MaizeGerm50K array is thus a valuable genomic tool for maize genetic studies and breeding.

Caracterización morfoagronómica de poblaciones de maíz criollo (Zea mays L.), provincia de Manabí, Ecuador

Ecuador is a country with a wide genetic diversity of maize and there are populations of native maize conserved by farmers that have not yet been characterized. These genetic resources could be conserved and used in plant breeding programs. The objective of this research was to characterize the morpho-agronomic diversity of 38 populations of native maize from the province of Manabí, Ecuador, using 19 quantitative and 11 qualitative morpho-agronomic descriptors. During the dry season of 2022 (July - December) at the Portoviejo Experimental Station of the National Institute of Agricultural Research (INIAP), plots of 8 m2 were established for each population of native maize, with 0.3 m between plants and 0.8 m between furrows and each furrow was 5 m long. Cluster analysis showed the formation of four groups, where the populations of hard kernels with large ears and soft kernels with short ears were separated into different groups. The quantitative variables ear height, panicle length, percentage of lodging, number of kernels per row and biomass of the inflorescence rachis recorded "D" indices of 0.75, showing themselves as discriminant variables in the formation of the groups, while the most discriminating qualitative variables were kernel type (χ2 = 49.09***, P= 0.742, V= 0.64), kernel color (χ2= 51.955***, P= 0.75, V=0.64), row arrangement (χ2= 18.11*, P=0.56, V=0.39), and kernel surface shape (χ2 = 20.52*, P=0.58, V=0.41). The native maize races identified were Candela, Cubano, Tuxpeño, Tusilla, and Uchima, observing significant genetic diversity in the populations studied. It was concluded that the characterized native maize populations were a valuable genetic resource for the conservation and use of this cereal. Keywords: genotypes, landraces, genetic variability, conservation of genetic resources.

A genomic journey across the past, present, and future of South American maize.

Maize (Zea mays ssp. mays) diverged from one of its wild relatives, the teosinte Zea mays ssp. parviglumis, in the lowlands of southwest Mexico approximately 9000 years ago. Following this divergence, maize rapidly expanded throughout the Americas, becoming a staple food. This dispersal was accompanied by significant demographic and selective changes, leading to the development of numerous local varieties with a complex evolutionary history that remains incompletely understood. In recent years, genomic advances have challenged traditional models of maize domestication and spread to South America. At least three distinct genetic lineages associated with different migratory waves have been described: ancestral Andean, ancestral Lowland, and Pan-American. Additionally, the significant role of the teosinte Zea mays ssp. mexicana, in the evolution of modern maize has been recently uncovered. Genomic studies have shed light into highland adaptation processes, revealing largely independent adaptation events in Meso- and South America. As new evidence emerges, the regional complexity underlying maize diversity and the need for comprehensive, multi-scale approaches become evident. In the face of climate change and evolving agricultural landscapes, the conservation of native maize in South America is of growing interest, with genomics serving as an invaluable tool for identifying and preserving the genetic variability of locally adapted germplasm.

Leveraging the complex interplay between arbuscular mycorrhizal fungi, seasonal dynamics, and genotypic diversity to optimize maize productivity in semi-arid agroecosystems

Maize production under low-input agricultural systems in semi-arid areas of Sub-Saharan Africa faces significant challenges, primarily stemming from the synergistic impacts of climate variability and suboptimal agronomic practices. Harnessing soil microbiota, particularly arbuscular mycorrhizal fungi (AMF), represents a pivotal strategy for bolstering low-input systems. However, their functional utility is contingent upon their compatibility with the prevailing environmental conditions and biotic interactions. This study examines the influence of two distinct AMF inoculants on the growth and yield attributes of diverse maize genotypes across varying seasons within semi-arid regions of Kenya. We hypothesized that AMF inoculants exhibit differential adaptability to varying environmental sites and seasons, and their interaction will enhance the provision of key ecosystem services important for maize production. Field experiments were conducted in three semi-arid Counties (Tharaka-Nithi, Embu, and Kitui) during the 2019/2020 cropping seasons. A randomized complete block design with three replications and three treatments was adopted. Treatments consisted of Rhizatech (a commercial AMF inoculant), a consortium of AMF isolates (Rhizophagus irregularis and Funneliformis mosseae), and a non-inoculated control. In season one, notable interaction effects were observed for both site × maize genotype (p = 0.0007) and site × AMF inoculation (p < 0.0001), whereby Duma 43 genotype had the highest yield in Embu (11.93 t ha−1) and Kitui (11.76 t ha−1) counties, and Rhizatech and consortium inoculation consistently led to elevated grain yields across all three genotypes in Kitui, surpassing non-inoculated controls. AMF inoculation notably augmented phosphorus (P) uptake, with Rhizatech demonstrating a 79.7 % increase and consortium showing a 38.7 % increase in shoot P content compared to control plants in season 1. These findings highlight the complex interplay between AMF effectiveness, seasonal variations, and maize diversity. Further research is needed to elucidate the underlying mechanisms driving these seasonal shifts, allowing for optimized AMF inoculation strategies for improved maize performance under diverse conditions.

Extraction and Quantification of Phenolic Compounds in Maize.

Plants accumulate hundreds of thousands of specialized metabolites that participate in their interactions with the environment. Among these compounds, phenolics represent a large class, and they play important physiological roles, such as providing a first barrier against pathogens, cues to pollinators, and radiation protection. Maize is one of the most important crops worldwide for food, animal feed, and biofuels, and it has the potential to accumulate different phenolics in vegetative tissues as well as in seeds. Recent studies have identified a large number of phenolic compounds-with a diversity of chemical decorations-in different maize tissues, but these likely represent just a fraction of the metabolic diversity of maize. In this protocol, we describe a specific method for the extraction and quantification of maize phenolic compounds by ultra-high-pressure liquid chromatography-tandem multiple reaction monitoring mass spectrometry (UHPLC-MRM-MS/MS) analysis. We provide detailed instructions for the extraction of phenolics using acidic methanol, and for the quantification of 33 different compounds in maize stems, including flavonoids, phenolic acids, and lignin precursors.

Enhanced Soil Fertility and Carbon Dynamics in Organic Farming Systems: The Role of Arbuscular Mycorrhizal Fungal Abundance.

Arbuscular mycorrhizal fungi (AMF) are critical for soil ecosystem services as they enhance plant growth and soil quality via nutrient cycling and carbon storage. Considering the growing emphasis on sustainable agricultural practices, this study investigated the effects of conventional and organic farming practices on AMF diversity, abundance, and ecological functions in maize, pepper, and potato-cultivated soils. Using next-generation sequencing and quantitative PCR, we assessed AMF diversity and abundance in addition to soil health indicators such as phosphorus content, total nitrogen, and soil organic carbon. Our findings revealed that, while no significant differences in soil physicochemical parameters or AMF diversity were observed across farming systems when all crop data were combined, organic farming significantly enhances AMF abundance and fosters beneficial microbial ecosystems. These ecosystems play vital roles in nutrient cycling and carbon storage, underscoring the importance of organic practices in promoting robust AMF communities that support ecosystem services. This study not only deepens our understanding of AMF's ecological roles but also highlights the potential of organic farming to leverage these benefits for improving sustainability in agricultural practices.

Inter-subspecies diversity of maize to drought stress with physio-biochemical, enzymatic and molecular responses.

Drought is the most significant factor limiting maize production, given that maize is a crop with a high water demand. Therefore, studies investigating the mechanisms underlying the drought tolerance of maize are of great importance. There are no studies comparing drought tolerance among economically important subspecies of maize. This study aimed to reveal the differences between the physio-biochemical, enzymatic, and molecular mechanisms of drought tolerance in dent (Zea mays indentata), popcorn (Zea mays everta), and sugar (Zea mays saccharata) maize under control (no-stress), moderate, and severe drought stress. Three distinct irrigation regimes were employed to assess the impact of varying levels of drought stress on maize plants at the V14 growth stage. These included normal irrigation (80% field capacity), moderate drought (50% field capacity), and severe drought (30% field capacity). All plants were grown under controlled conditions. The following parameters were analyzed: leaf relative water content (RWC), loss of turgidity (LOT), proline (PRO) and soluble protein (SPR) contents, membrane durability index (MDI), malondialdehyde (MDA), and hydrogen peroxide (H2O2) content, the antioxidant enzyme activities of superoxide dismutase (SOD), ascorbate peroxidase (APX), and catalase (CAT). Additionally, the expression of heat shock proteins (HSPs) was examined at the transcriptional and translational levels. The effects of severe drought were more pronounced in sugar maize, which had a relatively high loss of RWC and turgor, membrane damage, enzyme activities, and HSP90 gene expression. Dent maize, which is capable of maintaining its RWC and turgor in both moderate and severe droughts, and employs its defense mechanism effectively by maintaining antioxidant enzyme activities at a certain level despite less MDA and H2O2 accumulation, exhibited relatively high drought tolerance. Despite the high levels of MDA and H2O2 in popcorn maize, the up-regulation of antioxidant enzyme activities and HSP70 gene and protein expression indicated that the drought coping mechanism is activated. In particular, the positive correlation of HSP70 with PRO and HSP90 with enzyme activities is a significant result for studies examining the relationships between HSPs and other stress response systems. The discrepancies between the transcriptional and translational findings provide an opportunity for more comprehensive investigations into the role of HSPs in stress conditions.

Tools and Resources at the Maize Genetics and Genomics Database (MaizeGDB).

The Maize Genetics and Genomics Database (MaizeGDB) is the community resource for maize researchers, offering a suite of tools, informatics resources, and curated data sets to support maize genetics, genomics, and breeding research. Here, we provide an overview of the key resources available at MaizeGDB, including maize genomes, comparative genomics, and pan-genomics tools. This review aims to familiarize users with the range of options available for maize research and highlights the importance of MaizeGDB as a central hub for the maize research community. By providing a detailed snapshot of the database's capabilities, we hope to enable researchers to make use of MaizeGDB's resources, ultimately assisting them to better study the evolution and diversity of maize.

Smallholder farmers’ diverse values in maize landrace conservation: A case study from Chiapas, Mexico

Conservation of maize landraces in the Mexico center of origin is critical for sustainable agriculture. However, farmers in many regions of Mexico are reducing landraces for more modern maize varieties, particularly hybrid maize. The reasons why farmers choose to maintain maize landraces have been recently recognized to be strongly linked to their specific values (i.e., intrinsic, instrumental, and relational values). However, there is a lack of studies that empirically investigate the nuances of farmers' specific values and how these values are adequately considered in broad agricultural policies. Using a mixed-methods case study based in indigenous and mestizo communities in Chiapas, Mexico, we analyzed farmers' maize production strategies, how those strategies connect to farmers’ value orientations, and the limitations that they confront in enacting such values. We found that households within both indigenous and mestizo communities fell into one of three categories regarding their maize production: 1) hybrid maize production for market sales, 2) landrace production for household consumption, and 3) a combination of these two strategies. All farmers hold a diversity of values in which mostly instrumental and relational values were mentioned among the three groups of farmers, who emphasized the livelihood and subsistence value of maize. Value differences for farmers who prioritize the cultivation of maize landraces were related to the strength of relational values, such as the biocultural diversity and heritage value of maize. In contrast, the farmers relying on hybrid varieties were the ones confronting the most limitations to their maize production, particularly economic limitations. Based on our empirical findings, we conclude that policies aimed at promoting the conservation of landraces must extend beyond a purely economic and market-oriented approach. The current policy emphasis on instrumental values is likely to fall short in achieving the desired outcomes since it does not sufficiently foster plural values that underpin the continued production of maize landraces.

Structural variants contribute to phenotypic variation in maize.

Comprehensively identifying the loci shaping trait variation has been challenging, in part because standard approaches often miss many types of genetic variants. Structural variants, especially transposable elements are likely to affect phenotypic variation but we need better methods in maize for detecting polymorphic structural variants and TEs using short-read sequencing data. Here, we used a whole genome alignment between two maize genotypes to identify polymorphic structural variants and then genotyped a large maize diversity panel for these variants using short-read sequencing data. We characterized variation of SVs within the panel and identified SV polymorphisms that are associated with life history traits and genotype-by-environment interactions. While most of the SVs associated with traits contained TEs, only one of the SV's boundaries clearly matched TE breakpoints indicative of a TE insertion, whereas the other polymorphisms were likely caused by deletions. All of the SVs associated with traits were in linkage disequilibrium with nearby single nucleotide polymorphisms (SNPs), suggesting that this method did not identify variants that would have been missed in a SNP association study.

Data blanks by design: Intellectual property and restrictions on genetic diversity assessments of the maize standing crop in the USA Upper Midwest

Societal Impact StatementAll US commercial maize (Zea mays) is a single race, “Corn Belt Dent,” and its genetic base has been in decline for at least 40 years. Independent genotyping can only be conducted after patent and licensing restrictions have expired, a period of 20 years. These restrictions also impede a molecular based assessment of the standing crop by the United States Department of Agriculture (USDA) as recommended by experts. Data blanks about landscape vulnerability put farmers at risk of crop failure and the public at risk of food insecurity. Understanding maize diversity experts' perspectives and analysis helps describe the contours of these data blanks and inform policy recommendations.Summary Recommendations by the Maize Crop Germplasm Committee to the United States Department of Agriculture (USDA) for a molecular based vulnerability assessment on the US standing maize (Zea mays) crop have not been acted on because of intellectual property and licensing restrictions. This research explores maize diversity experts' access to data and perceptions and analysis of the standing crop. The data come from semi‐structured interviews conducted with 44 maize diversity experts in the public and private sectors. Experts explain that genetic data blanks restrict non‐industry research, describe public sector concerns that standing diversity is narrow(ing), and find historic sources of pedigree data in Plant Variety Protection and patent records are no longer reliable. Some interviewees perceive that industry monitoring of standing diversity is in their best financial interest. Industry participants describe concentration in US maize allows them to control diversity over time, while public researchers discuss efficiency of scale narrowing genetic diversity and global concentration spreading this trend. Knowledge gaps about genetic diversity in US commercial maize are designed through patents, contracts, non‐disclosure agreements, and confidentiality agreements by patent holders who do not want their inbred lines genotyped by competitors. This restricts research and knowledge flow about genetic information into public networks. The Maize Crop Germplasm Committee is a node for knowledge flow; however, the lack of mechanisms for action suggests it is performative. We recommend all protections used on seed include exemptions for research, breeding, and seed saving; an independent assessment of how industry monitors standing diversity; and a molecular analysis of the standing crop conducted by the USDA.

Data driven discovery and quantification of hyperspectral leaf reflectance phenotypes across a maize diversity panel

Data driven discovery and quantification of hyperspectral leaf reflectance phenotypes across a maize diversity panel

Visualizing Anthocyanins: Colorimertic Analysis of Blue Maize

Anthocyanin, vibrant pigments found in a wide range of plants, including maize, contribute to the red, blue, and purple hues observed in fruits, vegetables, and grains. The inherent color variations in maize, including natural shades of purple, red, blue, and even rainbow colors, pose a significant challenge in accurately assessing maize maturity. This study recognizes the importance of visualizing the distinct blue purplish anthocyanin coloration to determine the optimal harvest time for blue maize, particularly among small-scale producers. To address this crucial need, this research project presents the development of the MaizeMeter, an advanced colorimeter specifically designed to analyze maize color based on anthocyanin pigmentation. Leveraging the power of Internet of Things (IoT) implementation, the MaizeMeter provides real-time monitoring and interpretation of anthocyanin color values. The proposed methodology encompasses the calibration of the color sensor and the prototyping of the MaizeMeter, culminating in the establishment of a comprehensive database of anthocyanin color profiles in blue maize. The generated anthocyanin color database by the MaizeMeter will serve as a vital tool for small-scale farmers and researchers, enabling more efficient and accurate assessment of maize maturity in the future.

Molecular assessment of genetic diversity of Tanzanian and aflatoxin-resistant maize (Zea mays. L) accessions

Molecular assessment of genetic diversity of Tanzanian and aflatoxin-resistant maize (Zea mays. L) accessions

Natural variation in root traits identifies significant SNPs and candidate genes for phosphate deficiency tolerance in Zea mays L.

Phosphorus (P) is a crucial macronutrient required for normal plant growth. Its effective uptake from the soil is a trait of agronomic importance. Natural variation in maize (339 accessions) root traits, namely root length and number of primary, seminal, and crown roots, root and shoot phosphate (Pi) contents, and root-to-shoot Pi translocation (root: shoot Pi) under normal (control, 40 ppm) and low phosphate (LP, 1 ppm) conditions, were used for genome-wide association studies (GWAS). The Bayesian-information and Linkage-disequilibrium Iteratively Nested Keyway (BLINK) model of GWAS provided 23 single nucleotide polymorphisms (SNPs) and 12 relevant candidate genes putatively linked with root Pi, root: shoot Pi, and crown root number (CRN) under LP. The DNA-protein interaction analysis of Zm00001d002842, Zm00001d002837, Zm00001d002843 for root Pi, and Zm00001d044312, Zm00001d045550, Zm00001d025915, Zm00001d044313, Zm00001d051842 for root: shoot Pi, and Zm00001d031561, Zm00001d001803, and Zm00001d001804 for CRN showed the presence of potential binding sites of key transcription factors like MYB62, bZIP11, ARF4, ARF7, ARF10 and ARF16 known for induction/suppression of phosphate starvation response (PHR). The in-silico RNA-seq analysis revealed up or down-regulation of candidate genes along with key transcription factors of PHR, while Uniprot analysis provided genetic relatedness. Candidate genes that may play a role in P uptake and root-to-shoot Pi translocation under LP are proposed using common PHR signaling components like MYB62, ARF4, ARF7, ARF10, ARF16, and bZIP11 to induce changes in root growth in maize. Candidate genes may be used to improve low P tolerance in maize using the CRISPR strategy.

Genetic characterization and evaluation of pigmented maize (Zea mays L.) landraces of the North East Hill Region of India-an established centre of maize diversity

Abstract The North East Hill Region (NEHR) of India is home to diverse maize landraces including pigmented accessions rich in antioxidants and nutritional properties. The present study attempted to characterize a representative collection of this mostly unexplored diversity. Altogether eighty-three local maize landraces from the seven hill states of the NEHR were studied with special emphasis on pigmentation diversity. For the morphological traits, a significant ANOVA indicated the presence of substantial genetic variability for which selection would be fruitful. A number of these accessions were found to have traits that help cope with moisture stress, improve stalk strength and optimize photosynthesis. Principal component analysis studies for the yield attributing traits indicated that ear weight was most variable. The bleaching/histological studies confirmed that anthocyanin pigment when present was always restricted to the aleurone layer of the kernels, typical of blue maize. Quantitative analysis for kernel anthocyanin/phlobaphene content also revealed genetic differences among the accessions. Genetic analysis using the model-based STRUCTURE indicated significant population structuring among the accessions. Specifically, for the pigmentation diversity studies both principal coordinate analysis and neighbour joining methods revealed near concurrent population structuring due in part to the high differentiation of seven of the twenty-one pigmentation specific loci studied. The results obtained provide comprehensive evidence of a significant amount of genetic differentiation among the landraces under study. Landraces are valuable reservoirs of favourable alleles for which selection can be made and, as in this study, identify accessions for breeding maize with enhanced levels of beneficial secondary metabolites.

Transgenes in Mexican Maize: Evidence of Increased Productivity, Lower Environmental Impacts, and No Impact on Maize Diversity

Transgenes in Mexican Maize: Evidence of Increased Productivity, Lower Environmental Impacts, and No Impact on Maize Diversity

Physical Traits and Phenolic Compound Diversity in Maize Accessions with Blue-Purple Grain (Zea mays L.) of Mexican Races

Consumer interest in foods enriched with phytochemical compounds for health benefits has prompted plant breeders to focus on developing new cultivars with an enhanced content of specific compounds. Studies regarding the exploration of germplasms of species of great economic importance, such as maize, could be useful in this task. This study aimed to assess the physical grain traits and phenolic compound variations (including anthocyanins, flavonoids, and proanthocyanidins) in blue-purple maize accessions from various Mexican races. We examined 207 accessions from 21 Mexican maize races, evaluating physical grain traits such as weight of one hundred grains (W100G), endosperm type (ET), pigment location, and grain color. Phenolic composition analysis encompassed total soluble phenolics (TSP), total anthocyanin content (TAC), flavonoids (FLAV), and proanthocyanidins (PAs). The predominant endosperm type was floury, with W100G values indicating a large grain size and the pigment primarily located in the aleurone layer. Among phenolic composition variables, only TSP exhibited a normal distribution, while others skewed towards the left side. A hierarchical analysis of phenolic composition data revealed three distinct groups comprising different numbers of Mexican varieties, with TAC proving the most effective for grouping. Our comprehensive exploration of maize diversity featuring blue-purple grain coloration has led to the identification of novel maize varieties with outstanding phenolic contents.

Image Filtering to Improve Maize Tassel Detection Accuracy Using Machine Learning Algorithms.

Unmanned aerial vehicle (UAV)-based imagery has become widely used to collect time-series agronomic data, which are then incorporated into plant breeding programs to enhance crop improvements. To make efficient analysis possible, in this study, by leveraging an aerial photography dataset for a field trial of 233 different inbred lines from the maize diversity panel, we developed machine learning methods for obtaining automated tassel counts at the plot level. We employed both an object-based counting-by-detection (CBD) approach and a density-based counting-by-regression (CBR) approach. Using an image segmentation method that removes most of the pixels not associated with the plant tassels, the results showed a dramatic improvement in the accuracy of object-based (CBD) detection, with the cross-validation prediction accuracy (r2) peaking at 0.7033 on a detector trained with images with a filter threshold of 90. The CBR approach showed the greatest accuracy when using unfiltered images, with a mean absolute error (MAE) of 7.99. However, when using bootstrapping, images filtered at a threshold of 90 showed a slightly better MAE (8.65) than the unfiltered images (8.90). These methods will allow for accurate estimates of flowering-related traits and help to make breeding decisions for crop improvement.