Maize Flowering Research Articles

The evening complex promotes maize flowering and adaptation to temperate regions.

Maize (Zea mays) originated in southern Mexico and has spread over a wide latitudinal range. Maize expansion from tropical to temperate regions has necessitated a reduction of its photoperiod sensitivity. In this study, we cloned a quantitative trait locus (QTL) regulating flowering time in maize and show that the maize ortholog of Arabidopsis thaliana EARLY FLOWERING3, ZmELF3.1, is the causal locus. We demonstrate that ZmELF3.1 and ZmELF3.2 proteins can physically interact with ZmELF4.1/4.2 and ZmLUX1/2, to form evening complex(es; ECs) in the maize circadian clock. Loss-of-function mutants for ZmELF3.1/3.2 and ZmLUX1/2 exhibited delayed flowering under long-day and short-day conditions. We show that EC directly represses the expression of several flowering suppressor genes, such as the CONSTANS, CONSTANS-LIKE, TOC1 (CCT) genes ZmCCT9 and ZmCCT10, ZmCONSTANS-LIKE 3, and the PSEUDORESPONSE REGULATOR (PRR) genes ZmPRR37a and ZmPRR73, thus alleviating their inhibition, allowing florigen gene expression and promoting flowering. Further, we identify two closely linked retrotransposons located in the ZmELF3.1 promoter that regulate the expression levels of ZmELF3.1 and may have been positively selected during postdomestication spread of maize from tropical to temperate regions during the pre-Columbian era. These findings provide insights into circadian clock-mediated regulation of photoperiodic flowering in maize and new targets of genetic improvement for breeding.

Phytonematode population dynamics in common bean cultivation under crop rotation and no-tillage conditions

Strategies for conserving natural resources and reducing agricultural inputs are the great challenge for agriculture, such as sustainable alternatives to control agricultural pests of high economic impact, e.g. plant-parasitic nematodes. This work aimed to evaluate phytonematode’s population dynamics in common bean cultivation grown under crop rotations and no-tillage system. The maize was seeded under pearl millet straw and intercropped with three different crops systems: i) exclusive maize system, ii) maize intercropped with brachiaria and, iii) maize intercropped with crotalaria. The experimental design was a randomized complete block with three treatments (crops systems) and 4 blocks (5 subsamples each block). The common bean was seeded on the straw of exclusive or intercropped maize. The phytonematode population was evaluated in the soil and in the roots in seven moments: (i) fallow; (ii) pearl millet flowering; (iii) pearl millet maturity; (iv) maize flowering; (v) maize maturity; (vi) common bean flowering; and (vii) common bean maturity. The greatest control of the phytonematodes species described in the area was in the maize intercropped with crotalaria treatment, as the phytonematodes population decreased 2.49-fold in this treatment when compared to exclusive maize, resulting in an increase of 11.27% in common bean yield. Therefore, maize intercropped with crotalaria is a viable alternative to reduce phytonematodes infestation in common bean crop.

Effects of drought and heat stresses during reproductive stage on pollen germination, yield, and leaf reflectance properties in maize (Zea mays L.).

Drought and heat stresses are the major abiotic stress factors detrimental to maize ( Zea mays L.) production. Much attention has been directed toward plant responses to heat or drought stress. However, maize reproductive stage responses to combined heat and drought remain less explored. Therefore, this study aimed to quantify the impact of optimum daytime (30°C, control) and warmer daytime temperatures (35°C, heat stress) on pollen germination, morpho‐physiology, and yield potential using two maize genotypes (“Mo17” and “B73”) under contrasting soil moisture content, that is, 100% and 40% irrigation during flowering. Pollen germination of both genotypes decreased under combined stresses (42%), followed by heat stress (30%) and drought stress (19%). Stomatal conductance and transpiration were comparable between control and heat stress but significantly decreased under combined stresses (83% and 72%) and drought stress (52% and 47%) compared with the control. Genotype “Mo17” reduced its green leaf area to minimize the water loss, which appears to be one of the adaptive strategies of “Mo17” under stress conditions. The leaf reflectance of both genotypes varied across treatments. Vegetation indices associated with pigments (chlorophyll index of green, chlorophyll index of red edge, and carotenoid index) and plant health (normalized difference red‐edge index) were found to be highly sensitive to drought and combined stressors than heat stress. Combined drought and heat stresses caused a significant reduction in yield and yield components in both Mo17 (49%) and B73 (86%) genotypes. The harvest index of genotype “B73” was extremely low, indicating poor partitioning efficiency. At least when it comes to “B73,” the cause of yield reduction appears to be the result of reduced sink number rather than the pollen and source size. To the best of our awareness, this is the first study that showed how the leaf‐level spectra, yield, and quality parameters respond to the short duration of independent and combined stresses during flowering in inbred maize. Further studies are required to validate the responses of potential traits involving diverse maize genotypes under field conditions. This study suggests the need to develop maize with improved tolerance to combined stresses to sustain production under increasing temperatures and low rainfall conditions.

Linkage Mapping Reveals QTL for Flowering Time-Related Traits under Multiple Abiotic Stress Conditions in Maize.

Variation in flowering plays a major role in maize photoperiod adaptation during long-term domestication. It is of high value to investigate the genetic basis of maize flowering under a wide range of environmental conditions in order to overcome photoperiod sensitivity or enhance stress tolerance. A recombinant inbred line (RIL) population derived from a cross between Huangzaosi and Mo17, composed of 121 lines and genotyped by 8329 specifically developed markers, was field evaluated in two consecutive years under two planting densities (67,500 and 120,000 plants ha−1) and two water treatments (normal irrigation and drought stress at the flowering stage). The days to silking (DTS), days to anthesis (DTA), and anthesis to silking interval (ASI) were all evaluated. Within the RIL population, DTS and DTA expanded as planting density and water deficit increased. For DTA, DTS, ASI, and ASI-delay, a total of 22, 17, 21, and 11 QTLs were identified, respectively. More than two significant QTLs were identified in each of the nine chromosomal intervals. Under diverse conditions and locations, six QTLs (quantitative trait locus) for DTS and DTA were discovered in Chr. 8: 118.13–125.31 Mb. Three chromosome regions, Chr. 3: 196.14–199.89 Mb, Chr. 8: 169.02–172.46 Mb, and Chr. 9: 128.12–137.26 Mb, all had QTLs for ASI-delay under normal and stress conditions, suggesting their possible roles in stress tolerance enhancement. These QTL hotspots will promote early-maturing or multiple abiotic stress-tolerant maize breeding, as well as shed light on the development of maize varieties with a broad range of adaptations.

An adaptive teosinte mexicana introgression modulates phosphatidylcholine levels and is associated with maize flowering time

Native Americans domesticated maize (Zea mays ssp. mays) from lowland teosinte parviglumis (Zea mays ssp. parviglumis) in the warm Mexican southwest and brought it to the highlands of Mexico and South America where it was exposed to lower temperatures that imposed strong selection on flowering time. Phospholipids are important metabolites in plant responses to low-temperature and phosphorus availability and have been suggested to influence flowering time. Here, we combined linkage mapping with genome scans to identify High PhosphatidylCholine 1 (HPC1), a gene that encodes a phospholipase A1 enzyme, as a major driver of phospholipid variation in highland maize. Common garden experiments demonstrated strong genotype-by-environment interactions associated with variation at HPC1, with the highland HPC1 allele leading to higher fitness in highlands, possibly by hastening flowering. The highland maize HPC1 variant resulted in impaired function of the encoded protein due to a polymorphism in a highly conserved sequence. A meta-analysis across HPC1 orthologs indicated a strong association between the identity of the amino acid at this position and optimal growth in prokaryotes. Mutagenesis of HPC1 via genome editing validated its role in regulating phospholipid metabolism. Finally, we showed that the highland HPC1 allele entered cultivated maize by introgression from the wild highland teosinte Zea mays ssp. mexicana and has been maintained in maize breeding lines from the Northern United States, Canada, and Europe. Thus, HPC1 introgressed from teosinte mexicana underlies a large metabolic QTL that modulates phosphatidylcholine levels and has an adaptive effect at least in part via induction of early flowering time.

Analysis on Heat Characteristics for Summer Maize Cropping in a Semi-Arid Region

Heat stress during flowering is a critical limitation for summer maize production. However, the incidence of heat varies with years and locations, and it poses a great risk to successful maize reproduction and kernel setting. Therefore, it is essential to provide a sound quantification of heat occurrence in relation to maize growth and development. Here, we analyzed the characteristics of heat occurrence based on climate data for over 60 years on Huaibei Plain, China. The effective accumulated temperature showed a slight interannual variation. The average maximum temperature (T¯max) during flowering was 32 °C–33 °C, which was approximately 2 °C higher than that over the whole growing season. The probability (P) for the daily Tmax > 33 °C during flowering was closer to 50% and this maximum temperature ranged between 33 °C and 37 °C. The five levels from normal to extreme heat for Tmax were defined. Across the six studied sites, the mild level heat stress accounted for most of incidents (P, 25–50%), followed by moderate (P, 13–25%) and severe (P, 0.5–13%), and the minimum for extreme heat stress (P, 0.5%). Four phases bracketing flowering during maize development were given, i.e., 1 week prior to anthesis, 1 week during anthesis, 1 week for anthesis-silking, and 1week post silking. There was a greater probability for heat stress incidents from anthesis to silking compared to the other developmental stages. Additionally, maize grain yield slightly increased with the increase in Tmax to 33 °C, but it declined as Tmax surpassed 33 °C. In conclusion, the pattern and characteristics of heat stress were quantified bracketing maize flowering. These findings assist to advise summer maize cropping strategies on the semi-arid and semi-humid Huaibei Plain, China or similar climate and cropping regions.

Increased heat stress risk for maize in arid-based climates as affected by climate change: threats and solutions

Heat stress in combination with drought has become the biggest concern and threat for maize yield production, especially in arid and hot regions. Accordingly, different optimal solutions should be considered in order to maintain maize production and reduce the risk of heat stress under the changing climate. In the current study, the risk of heat stress across Iranian maize agro-ecosystems was analyzed in terms of both intensity and frequency. The study areas comprised 16 provinces and 24 locations classified into five climate categories: arid and hot, arid and temperate, semi-arid and hot, semi-arid and temperate, and semi-arid and cold. The impact of heat stress on maize under a future climate was based on a 5-multi-model ensemble under two optimistic and pessimistic emission scenarios (RCP4.5 and RCP8.5, respectively) for 2040-2070 using the APSIM crop model. Simulation results illustrated that in the period of 2040-2070, intensity and the frequency of heat stress events increased by 2.37°C and 79.7%, respectively, during maize flowering time compared to the baseline. The risk of heat stress would be almost 100% in hot regions in the future climate under current management practices, mostly because of the increasing high-risk window for heat stress which will result in a yield reduction of 0.83 t ha-1. However, under optimal management practices,farmers will economically obtain acceptable yields (6.6 t ha-1). The results also indicated that the high-risk windows in the future will be lengthening from 12 to 33days in different climate types. Rising temperatures in cold regions as a result of global warming would provide better climate situations for maize growth, so that under optimistic emission scenarios and optimal management practices, farmers will be able to boost grain yield up to 9.2 t ha-1. Overall, it is concluded that farmers in hot and temperate regions need to be persuaded to choose optimal sowing dates and new maize cultivars which are well adapted to each climate to reduce heat stress risk and to shift maize production to cold regions.

Automated variety trial plot growth and flowering detection for maize and soybean using machine vision

Hundreds of crop variety trial sites are operated across Australia with up to 100 small plots (20 m2) that require manual, labour-intensive monitoring for emergence, height, canopy cover and flowering status. Machine vision systems can reduce labour in monitoring, and infield fixed cameras are most suitable to provide low-cost continuous sensing without requiring labour of travelling to sites. Height is commonly detected using stereo cameras; however, a low-cost single camera system is preferable for broad scale use at variety trial sites. Existing low-cost fixed camera systems assess multiple plots in the image’s field of view from a fixed mask that needs to be manually updated as the crop grows. Perspective transformation could be applied automatically to identify plot locations in the image. Existing systems also analyse multiple images independently and filter results to remove impacts from lighting variations. An alternative approach is to only analyse images in the same lighting conditions each day to reduce the need for filtering. In addition, a series of daily images can be used to track multiple leaf positions to monitor plant growth. A machine vision system has been developed that combines these technologies to track plant height from a series of daily images selected in the same lighting conditions, in combination with perspective transformation, in multiple plots in the camera’s field of view. Emergence, canopy cover and flowering status were also identified at the canopy surface in each plot using colour segmentation and/or shape analysis. The algorithms were evaluated on 5 and 10 m towers monitoring randomised trials of 16 maize and soybean plots and detected maize flowering date within one day, soybean height (RMSE = 18.38 cm; R2 = 0.880), maize height (RMSE = 47.73 cm; R2 = 0.838), soybean canopy cover (RMSE = 22.14%; R2 = 0.818) and maize canopy cover (RMSE = 14.01%; R2 = 0.750). The larger error in maize height detection was due to the flowers being tracked by the algorithm instead of vegetation. Further work is required to transfer the algorithms to other crops and varieties.

A Heterochromatic Knob Reducing the Flowering Time in Maize.

Maize flowering time is an important agronomic trait, which has been associated with variations in the genome size and heterochromatic knobs content. We integrated three steps to show this association. Firstly, we selected inbred lines varying for heterochromatic knob composition at specific sites in the homozygous state. Then, we produced homozygous and heterozygous hybrids for knobs. Second, we measured the genome size and flowering time for all materials. Knob composition did not affect the genome size and flowering time. Finally, we developed an association study and identified a knob marker on chromosome 9 showing the strongest association with flowering time. Indeed, modelling allele substitution and dominance effects could offer only one heterochromatic knob locus that could affect flowering time, making it earlier rather than the knob composition.

Recruitment of an ancient branching program to suppress carpel development in maize flowers

Carpels in maize undergo programmed cell death in half of the flowers initiated in ears and in all flowers in tassels. The HD-ZIP I transcription factor gene GRASSY TILLERS1 (GT1) is one of only a few genes known to regulate this process. To identify additional regulators of carpel suppression, we performed a gt1 enhancer screen and found a genetic interaction between gt1 and ramosa3 (ra3). RA3 is a classic inflorescence meristem determinacy gene that encodes a trehalose-6-phosphate (T6P) phosphatase (TPP). Dissection of floral development revealed that ra3 single mutants have partially derepressed carpels, whereas gt1;ra3 double mutants have completely derepressed carpels. Surprisingly, gt1 suppresses ra3 inflorescence branching, revealing a role for gt1 in meristem determinacy. Supporting these genetic interactions, GT1 and RA3 proteins colocalize to carpel nuclei in developing flowers. Global expression profiling revealed common genes misregulated in single and double mutant flowers, as well as in derepressed gt1 axillary meristems. Indeed, we found that ra3 enhances gt1 vegetative branching, similar to the roles for the trehalose pathway and GT1 homologs in the eudicots. This functional conservation over ∼160 million years of evolution reveals ancient roles for GT1-like genes and the trehalose pathway in regulating axillary meristem suppression, later recruited to mediate carpel suppression. Our findings expose hidden pleiotropy of classic maize genes and show how an ancient developmental program was redeployed to sculpt floral form.

Meta-Analysis of Flowering-Related Traits and Mining of Candidate Genes in Maize

Maize flowering is an important agronomic character, which is controlled by quantitative trait loci (QTL). Over the years, a large number of flowering-related QTL have been found in maize and exist in public databases. However, combining these data, re-analyzing and mining candidate loci and fine mapping of flowering-related traits to reduce confidence intervals has become a hot issue in maize. In this study, the QTL of 6 important agronomic traits of maize flowering were collected from 15 published articles, including flowering period (DA), Days to tasseling (DTT), Days to silking (DS), Days to pollen shedding (DTP), anthesis-silking interval (ASI) and the photosensitive (PS). Through meta-analysis, 622 QTL were integrated into 26 meta-QTLs (MQTL). Finally, the candidate genes related to maize flowering (Gene IDs: ZM00001D005791, ZM00001D019045, ZM00001D050697, ZM00001D011139) were identified by Gene Ontology (GO) enrichment and hierarchical cluster analysis of expression profile. Based on the results of this study, the genetic characteristics of maize flowering traits will be further analyzed, which is of great significance to guide the improvement of important agronomic characters and improve the efficiency of breeding.

ZmCCT regulates photoperiod-dependent flowering and response to stresses in maize

BackgroundAppropriate flowering time is very important to the success of modern agriculture. Maize (Zea mays L.) is a major cereal crop, originated in tropical areas, with photoperiod sensitivity. Which is an important obstacle to the utilization of tropical/subtropical germplasm resources in temperate regions. However, the study on the regulation mechanism of photoperiod sensitivity of maize is still in the early stage. Although it has been previously reported that ZmCCT is involved in the photoperiod response and delays maize flowering time under long-day conditions, the underlying mechanism remains unclear.ResultsHere, we showed that ZmCCT overexpression delays flowering time and confers maize drought tolerance under LD conditions. Implementing the Gal4-LexA/UAS system identified that ZmCCT has a transcriptional inhibitory activity, while the yeast system showed that ZmCCT has a transcriptional activation activity. DAP-Seq analysis and EMSA indicated that ZmCCT mainly binds to promoters containing the novel motifs CAAAAATC and AAATGGTC. DAP-Seq and RNA-Seq analysis showed that ZmCCT could directly repress the expression of ZmPRR5 and ZmCOL9, and promote the expression of ZmRVE6 to delay flowering under long-day conditions. Moreover, we also demonstrated that ZmCCT directly binds to the promoters of ZmHY5, ZmMPK3, ZmVOZ1 and ZmARR16 and promotes the expression of ZmHY5 and ZmMPK3, but represses ZmVOZ1 and ZmARR16 to enhance stress resistance. Additionally, ZmCCT regulates a set of genes associated with plant development.ConclusionsZmCCT has dual functions in regulating maize flowering time and stress response under LD conditions. ZmCCT negatively regulates flowering time and enhances maize drought tolerance under LD conditions. ZmCCT represses most flowering time genes to delay flowering while promotes most stress response genes to enhance stress tolerance. Our data contribute to a comprehensive understanding of the regulatory mechanism of ZmCCT in controlling maize flowering time and stress response.

Interplay between extreme drift and selection intensities favors the fixation of beneficial mutations in selfing maize populations

Population and quantitative genetic models provide useful approximations to predict long-term selection responses sustaining phenotypic shifts, and underlying multilocus adaptive dynamics. Valid across a broad range of parameters, their use for understanding the adaptive dynamics of small selfing populations undergoing strong selection intensity (thereafter High Drift-High selection regime, HDHS) remains to be explored. Saclay Divergent Selection Experiments (DSEs) on maize flowering time provide an interesting example of populations evolving under HDHS, with significant selection responses over 20 generations in two directions. We combined experimental data from Saclay DSEs, forward individual-based simulations, and theoretical predictions to dissect the evolutionary mechanisms at play in the observed selection responses. We asked two main questions: How do mutations arise, spread, and reach fixation in populations evolving under HDHS? How does the interplay between drift and selection influence observed phenotypic shifts? We showed that the long-lasting response to selection in small populations is due to the rapid fixation of mutations occurring during the generations of selection. Among fixed mutations, we also found a clear signal of enrichment for beneficial mutations revealing a limited cost of selection. Both environmental stochasticity and variation in selection coefficients likely contributed to exacerbate mutational effects, thereby facilitating selection grasp and fixation of small-effect mutations. Together our results highlight that despite a small number of polymorphic loci expected under HDHS, adaptive variation is continuously fueled by a vast mutational target. We discuss our results in the context of breeding and long-term survival of small selfing populations.

Identification of ZmNF-YC2 and its regulatory network for maize flowering time.

Flowering time is an important agronomic trait that determines the distribution and adaptation of plants. The accurate prediction of flowering time in elite germplasm is critical for maize breeding. However, the molecular mechanisms underlying the photoperiod response remain elusive in maize. Here we cloned the flowering time-controlling gene, ZmNF-YC2, by map-based cloning and confirmed that ZmNF-YC2 is the nuclear transcription factor Y subunit C-2 protein and a positive regulator of flowering time in maize under long-day conditions. Our results show that ZmNF-YC2 promotes the expression of ZmNF-YA3. ZmNF-YA3 negatively regulates the transcription of ZmAP2. ZmAP2 suppresses the expression of ZMM4 to delay flowering time. We then developed a gene regulatory model of flowering time in maize using ZmNF-YC2, ZmNF-YA3, ZmAP2, ZMM4, and other key genes. The cascading regulation by ZmNF-YC2 of maize flowering time has not been reported in other species.

Dissecting the Genetic Basis of Flowering Time and Height Related-Traits Using Two Doubled Haploid Populations in Maize.

In the field, maize flowering time and height traits are closely linked with yield, planting density, lodging resistance, and grain fill. To explore the genetic basis of flowering time and height traits in maize, we investigated six related traits, namely, days to anthesis (AD), days to silking (SD), the anthesis–silking interval (ASI), plant height (PH), ear height (EH), and the EH/PH ratio (ER) in two locations for two years based on two doubled haploid (DH) populations. Based on the two high-density genetic linkage maps, 12 and 22 quantitative trait loci (QTL) were identified, respectively, for flowering time and height-related traits. Of these, ten QTLs had overlapping confidence intervals between the two populations and were integrated into three consensus QTLs (qFT_YZ1a, qHT_YZ5a, and qHT_YZ7a). Of these, qFT_YZ1a, conferring flowering time, is located at 221.1–277.0 Mb on chromosome 1 and explained 10.0–12.5% of the AD and SD variation, and qHT_YZ5a, conferring height traits, is located at 147.4–217.3 Mb on chromosome 5 and explained 11.6–15.3% of the PH and EH variation. These consensus QTLs, in addition to the other repeatedly detected QTLs, provide useful information for further genetic studies and variety improvements in flowering time and height-related traits.

Advancing Tassel Detection and Counting: Annotation and Algorithms

Tassel counts provide valuable information related to flowering and yield prediction in maize, but are expensive and time-consuming to acquire via traditional manual approaches. High-resolution RGB imagery acquired by unmanned aerial vehicles (UAVs), coupled with advanced machine learning approaches, including deep learning (DL), provides a new capability for monitoring flowering. In this article, three state-of-the-art DL techniques, CenterNet based on point annotation, task-aware spatial disentanglement (TSD), and detecting objects with recursive feature pyramids and switchable atrous convolution (DetectoRS) based on bounding box annotation, are modified to improve their performance for this application and evaluated for tassel detection relative to Tasselnetv2+. The dataset for the experiments is comprised of RGB images of maize tassels from plant breeding experiments, which vary in size, complexity, and overlap. Results show that the point annotations are more accurate and simpler to acquire than the bounding boxes, and bounding box-based approaches are more sensitive to the size of the bounding boxes and background than point-based approaches. Overall, CenterNet has high accuracy in comparison to the other techniques, but DetectoRS can better detect early-stage tassels. The results for these experiments were more robust than Tasselnetv2+, which is sensitive to the number of tassels in the image.

Maize Tassel Detection From UAV Imagery Using Deep Learning.

The timing of flowering plays a critical role in determining the productivity of agricultural crops. If the crops flower too early, the crop would mature before the end of the growing season, losing the opportunity to capture and use large amounts of light energy. If the crops flower too late, the crop may be killed by the change of seasons before it is ready to harvest. Maize flowering is one of the most important periods where even small amounts of stress can significantly alter yield. In this work, we developed and compared two methods for automatic tassel detection based on the imagery collected from an unmanned aerial vehicle, using deep learning models. The first approach was a customized framework for tassel detection based on convolutional neural network (TD-CNN). The other method was a state-of-the-art object detection technique of the faster region-based CNN (Faster R-CNN), serving as baseline detection accuracy. The evaluation criteria for tassel detection were customized to correctly reflect the needs of tassel detection in an agricultural setting. Although detecting thin tassels in the aerial imagery is challenging, our results showed promising accuracy: the TD-CNN had an F1 score of 95.9% and the Faster R-CNN had 97.9% F1 score. More CNN-based model structures can be investigated in the future for improved accuracy, speed, and generalizability on aerial-based tassel detection.

RNA-Seq Analysis of Gene Expression Changes Related to Delay of Flowering Time under Drought Stress in Tropical Maize

Few studies have reported on the flowering time mechanism of tropical maize under short-day conditions. Drought, another important factor that affects flowering time, has been reported to delay the silking date in tropical maize. However, due to the lack of genetic information related to flowering in maize, the mechanism by which drought delays flowering is unclear. To further understand this process, we analyzed drought-responsive genes using RNA sequencing and identified genes related to flowering time, including contigs from de novo assembly. The results revealed changes in the expression of flowering-time genes, including INDETERMINATE1 (ID1), Heading date 3a (Hd3a), CONSTANS-like genes, and ZEA MAYS CENTRORADIALES8 (ZCN8), which are known to be crucial factors in flowering. In particular, Hd3a, CONZ1, and ZCN8, which have been reported to accelerate flowering under short-day conditions, were downregulated by drought stress. Changes in gene expression appear to play an important role in changes in flowering time under drought. These expression profiles will help to further understand the flowering-time genes of tropical maize and the delayed flowering time resulting from drought.

Joint analysis of days to flowering reveals independent temperate adaptations in maize.

Domesticates are an excellent model for understanding biological consequences of rapid climate change. Maize (Zea mays ssp. mays) was domesticated from a tropical grass yet is widespread across temperate regions today. We investigate the biological basis of temperate adaptation in diverse structured nested association mapping (NAM) populations from China, Europe (Dent and Flint) and the United States as well as in the Ames inbred diversity panel, using days to flowering as a proxy. Using cross-population prediction, where high prediction accuracy derives from overall genomic relatedness, shared genetic architecture, and sufficient diversity in the training population, we identify patterns in predictive ability across the five populations. To identify the source of temperate adapted alleles in these populations, we predict top associated genome-wide association study (GWAS) identified loci in a Random Forest Classifier using independent temperate-tropical North American populations based on lines selected from Hapmap3 as predictors. We find that North American populations are well predicted (AUC equals 0.89 and 0.85 for Ames and USNAM, respectively), European populations somewhat well predicted (AUC equals 0.59 and 0.67 for the Dent and Flint panels, respectively) and that the Chinese population is not predicted well at all (AUC is 0.47), suggesting an independent adaptation process for early flowering in China. Multiple adaptations for the complex trait days to flowering in maize provide hope for similar natural systems under climate change.

Dual Functional Coatings for Urea to Reduce Ammonia Volatilization and Improve Nutrients Use Efficiency in a Brazilian Corn Crop System

The investigation aimed to evaluate the use of micronutrients Zn, B, and the urease inhibitor (N-(n-butyl) thiophosphoric triamide) (NBPT), associated with an organic polymer to reduce ammonia losses (N-NH3) and increase maize yield. Two experiments were conducted under field conditions in Luminarias and Ingai, Minas Gerais, Brazil. The treatments consisted of the application of prilled urea, urea coated by an organic polymer, polymer + zinc (Zn), and boron (B) or NBPT, which are urease inhibitors in the soil, and a control treatment without N application. The reduction of N-NH3 losses applying the studied sources ranged between 0.2 and 42% on average. Leaf N concentration at flowering varied between 21 and 27 g kg−1, Zn concentration varied between 34 and 38 mg kg−1, and grain yield ranged from 3403 to 4810 kg ha−1. Grain yield increased by 15% on average compared to the control treatment. The addition of the organic polymer alone to urea reduces N losses by volatilization compared to prilled urea. However, when associated with Zn and B additions, this approach becomes more effective. The NBPT (N-(n-butyl) thiophosphoric triamide) concentrations used in this study exhibited low efficiencies in reducing N losses by volatilization. The application of Zn and B with the organic polymer affected nutrient uptake at the maize flowering stage but was not enough to increase maize yield. The removal of Zn and B by the grains was enhanced by the addition of these micronutrients to the organic polymer coating, regardless of the Zn source.