Maize Organs Research Articles

Monitoring aboveground organs biomass of wheat and maize: A novel model combining ensemble learning and allometric theory

Accurate monitoring of crop organ biomass facilitates optimizing agronomic strategies to maximize yield or economic benefit. Unmanned aerial vehicle (UAV) is extensively employed for aboveground biomass (AGB) monitoring at the farm scale, but previous studies have mostly concentrated on total AGB rather than individual organ biomass. Furthermore, film-mulched crops, a widely used cropping pattern in northwest China, have received less attention for AGB monitoring. We aim to develop a novel model to precisely estimate the AGB of leaf (AGBLeaf), stem (AGBStem), and reproductive organs (AGBR) by UAV for film-mulched wheat and maize. The maize-wheat rotation field experiments with treatments of five nitrogen application amounts and three planting densities were conducted from 2021 to 2023, respectively. Firstly, we constructed allometric models at jointing, heading (tasseling), and grain filling stages by ground sampling data in 2021–2022. Next, the input feature set was obtained by feature selection methods (Lasso and Boruta) using UAV image data, and three traditional methods (partial least squares, ridge regression, and support vector machine) and three ensemble learning models (random forest, extreme gradient boosting, and local cascade ensemble (LCE)) were trained for AGBLeaf inversion based on the physically-based PROSAIL model simulation dataset. Finally, the optimal AGBLeaf inversion hybrid model was coupled with the allometric model to estimate the AGBStem and AGBR in 2022–2023. The results indicated that both wheat and maize organ biomass conformed to the allometric pattern. While feature selection helped reduce computation and complexity, but didn’t improve monitoring accuracy. The normalized root mean square error (NRMSE) of the optimal hybrid model (PROSAIL + Boruta + LCE) on the measured wheat and maize AGBLeaf datasets were 12.72 %–24.93 % and 19.65 %–25.16 %, respectively. After coupling the allometric model, the coefficient of determination (R2) of wheat and maize AGBStem were 0.64–0.85 and 0.63–0.68, and the NRMSE were 15.05 %–25.28 % and 24.10 %–27.06 %, respectively; and the corresponding R2 of AGBR was 0.67–0.76 and 0.72, and the NRMSE were 16.81 %–22.12 % and 21.66 %, for wheat and maize, respectively. Overall, the novel model performed well in film-mulched wheat and maize, providing a cost-effective approach for organ biomass monitoring. In the future, further validation of the model’s transferability is necessary to increase the potential for generalization in production practice.

A novel semi-dominant allele of the transmembrane NAC transcription factor ZmNTL2 reduces the size of multiple maize organs

Maize plant architecture influences planting density and, in turn, grain yield. Most of the plant architecture-related traits can be described as organ size. We describe a miniature maize mutant, Tiny plant 4 (Tip4), which exhibits reduced size of multiple organs and exhibits a semi-dominant monofactorial inheritance characteristic. Positional cloning confirmed that a 4-bp deletion in the NAC TF with transmembrane motif 1-Like (NTL) gene ZmNTL2, denoted as ZmNTL2Δ, confers the Tip4 mutation. qRT-PCR showed that ZmNTL2 was expressed in all tested tissues. ZmNTL2 functions as a transcriptional activator and is located in both the nucleus and biomembranes. The mutation does not affect the mRNA abundance of ZmNTL2 locus, but it does result in the loss of transmembrane domain and confines the ZmNTL2Δ protein to the nucleus. Knocking out ZmNTL2 has no effect on maize organ size development, indicating that the 4-bp deletion might be a gain-of-function mutation in organ size regulation. Combining transcriptome sequencing with cytokinin and auxin content determination suggests that the decreased organ size may be possibly mediated by changes in hormone homeostasis.

Insight into the composition and differentiation of endophytic microbial communities in kernels via 368 maize transcriptomes

IntroductionKernels are important reproductive organs in maize, yet there is a lack of systematic investigation on the differences in the composition of endophytic microorganisms in plants from a population perspective. ObjectivesWe aimed to elucidate the composition of endophytic microorganisms in developing maize kernels, emphasizing differences among various inbred lines. MethodsThe transcriptomic data of 368 maize inbred lines were used to explore the composition and diversity of endophytic microorganisms. ResultsThe findings revealed a higher abundance of fungi than bacteria in developing maize kernels, followed by protozoa, while viruses were less abundant. There were significant differences in the composition and relative abundance of endophytic microorganisms among different maize lines. Diversity analysis revealed overall similarity in the community composition structure between tropical/subtropical (TST) and temperate (NSS) maize germplasm with apparent variations in community richness and abundance. The endophytic microorganisms network in the kernels from TST genotypes exhibited higher connectivity and stability compared to NSS kernels. Bacteria dominated the highly connected species in the networks, and different core species showed microbial phylum specificity. Some low-abundance species acted as core species, contributing to network stability. Beneficial bacteria were predominant in the core species of networks in TST kernels, while pathogenic bacteria were more abundant in the core species of networks in NSS kernels. ConclusionTropical maize germplasm may have advantages in resisting the invasion of pathogenic microorganisms, providing excellent genetic resources for disease-resistant breeding.

Study on The Transport and Transformation of Heavy Metal Lead from Agricultural Land in An Abandoned Mining Area in Southwestern Yunnan

In this paper, the heavy metals in the agricultural land around an abandoned mine in southwest Yunnan Province were taken as the object of study, 15 samples of topsoil, middle soil and deep soil were collected, and 5 maize plants were randomly selected in the soil sampling points to study the migration and transformation of heavy metal lead in the soil-maize system in the agricultural land around the abandoned mine. The results showed that the soils in the study area were enriched with heavy metal Pb, which was generally expressed as surface soil > middle soil > deep soil; the migration capacity of heavy metal Pb in different organs of maize: roots > leaves > stems and kernels. The results of the study can be used as a basis for judging the migration and transformation of heavy metals in soil-crop systems, providing new theoretical support for the migration of heavy metals in soils around abandoned mining areas, and promoting the ecological remediation of heavy metal pollution in agricultural land.

Genetic analysis of stay green related traits in maize with major gene plus polygenes mixed model.

Maize is one of the main food crops in the world, and cultivating high-yield and high-quality maize varieties is of great significance in addressing food security issues. Leaves are crucial photosynthetic organs in maize, and leaf senescence can result in the degradation of chlorophyll. This, in turn, impacts photosynthetic activity and the accumulation of photosynthetic products. Delaying leaf senescence and increasing carbon assimilation can enhance grain yield and biomass production. The stay green of maize is an important trait closely related to yield, feed quality and resistance. Therefore, this study employed multi-generation joint analysis of major genes and a polygene model to investigate the genetic inheritance of stay green-related traits. Four populations (P1, P2, F1 and F2) were obtained by crossing T01 (stay green) × Xin3 (non-stay green) and T01 (stay green) × Mo17 (non-stay green) under two environments. Six stay green-related traits, including visual stay green (VSG), number of green leaves (GLNM), SPAD value of ear leaf at anthesis (SPADS), SPAD value of ear leaf at maturity (SPADM), absolute green leaf area (GLAD), grain yield per plant (GYP), displayed continuous variations with kurtosis and skewness values of absolute value less than 1 and distribution close to normal. They were characterized by typical inheritance of quantitative traits, with these traits demonstrating the transgressive segregation. The correlation analysis among the traits revealed that five stay green traits have a positive impact on yield. VSG, GLNM and SPADM in the two populations were regulated by the two major genes of additive effects plus additive-dominance polygene model with a major gene heritability varying from 89.03 to 95.95% in the F2 generation. GLAD in TMF2 was controlled by two major genes of equal-additive dominance effects with high heritability (93.47%). However, in TXF2, GLAD was regulated by two major genes of additive-dominance interaction effects plus additive-dominance polygene model. These results provide important genetic information for breeding, which could guide the improvement of stay green-related traits. They also lay a foundation for quantitative trait loci mapping of the stay stay-green traits in maize.

Effects of different water‐soluble phosphorus on the distribution and utilization of phosphorus in maize in Xinjiang, China

AbstractPhosphorus (P) is the main limiting nutrient in agriculture. Most of the P fertilizers applied to the soil remain ineffective because of the weak movement and transfer of P in the soil. Current agricultural production requires large amounts of P fertilizers, leading to the accumulation of residual P in the soil and serious ecological problems. Fixation of P is a vital reason for limited fertilizer effectiveness. Therefore, improving soil P effectiveness is the key to reducing soil P accumulation. This study explored the effects of different water‐soluble P fertilizers on maize yield and economic benefits by comparing the relationships between soil P distribution and P absorption and utilization of maize in calcareous soil of Xinjiang province in China. The main results indicated that (1) the drip application of ammonium polyphosphate (APP) and urea phosphate (UP) was more beneficial for increasing the total P content in the deep soil layer; the drip application of APP was beneficial in increasing the available P content of the deep soil layer. (2) Dripping acid fertilizer was more conducive to reducing soil acidity and alkalinity (pH). (3) The application of different P fertilizers favoured the accumulation of P in all organs of maize, among which APP and UP were the most effective since they increased accumulation by 75.8% and 60.4% (at the flowering stage) and 98.2% and 62.3% (at the maturity stage), respectively, compared with CK (without P fertilizer). (4) pH was the main factor affecting P uptake and transformation, and the drip application of P fertilizer had the most significant effect on pH. (5) The application of different water‐soluble P fertilizers increased maize yield and economic benefits. Among the five water‐soluble P fertilizers selected in this study, APP had the greatest economic benefits, followed by UP and monoammonium phosphate (MAP); they increased yields by 31.6%, 24.5%, and 22.0%, respectively, compared with CK.

Win-Former: Window-Based Transformer for Maize Plant Point Cloud Semantic Segmentation

Semantic segmentation of plant point clouds is essential for high-throughput phenotyping systems, while existing methods still struggle to balance efficiency and performance. Recently, the Transformer architecture has revolutionized the area of computer vision, and has potential for processing 3D point clouds. Applying the Transformer for semantic segmentation of 3D plant point clouds remains a challenge. To this end, we propose a novel window-based Transformer (Win-Former) network for maize 3D organic segmentation. First, we pre-processed the Pheno4D maize point cloud dataset for training. The maize points were then projected onto a sphere surface, and a window partition mechanism was proposed to construct windows into which points were distributed evenly. After that, we employed local self-attention within windows for computing the relationship of points. To strengthen the windows’ connection, we introduced a Cross-Window self-attention (C-SA) module to gather the cross-window features by moving entire windows along the sphere. The results demonstrate that Win-Former outperforms the famous networks and obtains 83.45% mIoU with the lowest latency of 31 s on maize organ segmentation. We perform extensive experiments on ShapeNet to evaluate stability and robustness, and our proposed model achieves competitive results on part segmentation tasks. Thus, our Win-Former model effectively and efficiently segments the maize point cloud and provides technical support for automated plant phenotyping analysis.

Temporal and Spatial Dynamics of Organ Water Content in Maize with Different Senescence Types.

Understanding the water status of specific organs can be helpful in evaluating the life activities and growth conditions of maize. To accurately judge organ growth conditions and thus design appropriate interventions, it is necessary to clarify the true water dynamics of each maize organ. Using multiple maize cultivars with different growth periods, spatio-temporal water dynamics were analyzed here in the leaves, stalks, and ear components. Leaf water content was found to gradually decrease from both the bottom and top of the plant to the middle, whereas stalk water content decreased sequentially from the top to the bottom. Each successively higher node from the bottom of the plant was associated with decreases of 0.99% and 1.27% water content in the leaves and stalks, respectively. The water dynamics in leaves and internodes showed three clear stages: the slow loss, rapid loss, and balance stage. A water content of 60% appeared to be an irreversible turning point for initiation of senescence. Using normalized growth period as a measure, each of the tested cultivars could be assigned into one of two types based on their water dynamics: stay-water or general type. General-type cultivars had a shorter duration with a high water content and a water loss rate approximately twice as high as that of the stay-water type. This may have been related to the leaf senescence characteristics. However, the stay-water trait did not interfere with water dynamics of the ear components. Therefore, it may not be robust to evaluate the kernel dehydration of maize according to leaf senescence conditions due to the weak correlation between kernel water content and leaf senescence characteristics.

Immature leaves are the dominant volatile-sensing organs of maize

Plants perceive herbivory-induced volatiles and respond to them by upregulating their defenses. To date, the organs responsible for volatile perception remain poorly described. Here, we show that responsiveness to the herbivory-induced green leaf volatile (Z)-3-hexenyl acetate (HAC) in terms of volatile emission, transcriptional regulation, and jasmonate defense hormone activation is largely constrained to younger maize leaves. Older leaves are much less sensitive to HAC. In a given leaf, responsiveness to HAC is high at immature developmental stages and drops off rapidly during maturation. Responsiveness to the non-volatile elicitor ZmPep3 shows an opposite pattern, demonstrating that this form of hyposmia (i.e., decreased sense of smell) is not due to a general defect in jasmonate defense signaling in mature leaves. Neither stomatal conductance nor leaf cuticle composition explains the unresponsiveness of older leaves to HAC, suggesting perception mechanisms upstream of jasmonate signaling as driving factors. Finally, we show that hyposmia in older leaves is not restricted to HAC and extends to the full blend of herbivory-induced volatiles. In conclusion, our work identifies immature maize leaves as dominant stress volatile-sensing organs. The tight spatiotemporal control of volatile perception may facilitate within plant defense signaling to protect young leaves and may allow plants with complex architectures to explore the dynamic odor landscapes at the outer periphery of their shoots.

基于生物量的玉米可视化模型构建

Maize is one of the characteristic species in Shanxi Province. It has strong drought and cold tolerance. The study of maize growth and development law through the construction of the model is helpful to accurately understand the growth characteristics of maize, improve the yield, and further provide an important theoretical basis for the realization of precision agriculture. In this paper, "Xianyu 335" maize was taken as the research object. The data of leaf length, leaf width, stem length, stem number and tassel length, as well as leaf, stem, tassel, ear, cob and root organ morphology and biomass of maize during the whole growth period were obtained by field experiment. The maize geometric form structure module was constructed. The dynamic simulation of maize growing process was realized by object-oriented programming in Visual Studio software platform. With the help of 3D OpenGL graphic library Nurbs (Non-Uniform Rational B-Splines) curve and surface simulation technology, the growth visualization of maize organs was realized based on the idea of curve and surface control point selection parameter modeling.

Earthworm activity effectively mitigated the negative impact of microplastics on maize growth

Microplastic pollution can have detrimental effects on soil environments and inhibit crop growth. Earthworms, known as soil engineers, promote crop growth, but their role and impact on the amelioration of microplastic-polluted soil is not yet clear. In this study, we investigated the impact and pathways of earthworm activity on microplastic-contaminated soil by introducing varying densities (without earthworm:0, low-density: 1, medium-density: 2, high-density: 5 ind column−1) of earthworms (epi-endogeic) into soil contaminated with two types of microplastics: polyethylene and polyvinyl chloride. Our results showed that earthworms all survived in soil polluted with two types of microplastics. Meanwhile, earthworm activity increased nutrient content and enzyme activity by 0.2–36.1% and 2.9–34.3%, respectively, and significantly increased soil microbial biomass and community diversity index. Earthworm activity also decreased antioxidant enzyme activity and promoted maize plant growth, including agronomic traits such as plant height, biomass, root length, and root surface area. Furthermore, the nutrient content of maize organs increased by 1.1–29.7%. Partial least squares models confirmed that earthworm activity alleviated the stress effect of microplastic pollution on plant growth by improving soil structure, fertility, and microbial abundance and diversity. The greatest effect on maize growth was observed with the improvement of soil physical-chemical properties. Our results suggest that medium densities of earthworms have the greatest soil improvement effect and provide an important basis for bioremediation of farmland contaminated by microplastics and promoting green and efficient development in agriculture.

GA Associated Dwarf 5 encodes an ent-kaurenoic acid oxidase required for maize gibberellin biosynthesis and morphogenesis

Gibberellin (GA) functions in plant growth and development. However, genes involved in the biosynthesis and regulation of GA in crop plants are poorly understood. We isolated the mutant gad5-1 (GA-Associated Dwarf 5), characterized by dwarfing, short internodes, and dark green and short leaves. Map-based gene cloning and allelic verification confirmed that ZmGAD5 encodes ent-kaurenoic acid oxidase (KAO), which catalyzes KA (ent-kaurenoic acid) to GA12 conversion during GA biosynthesis in maize. ZmGAD5 is localized to the endoplasmic reticulum and is present in multiple maize organs. In gad5-1, the expression of ZmGAD5 is severely reduced, and the levels of the direct substrate of KAO, KA, is increased, leading to a reduction in GA content. The abnormal phenotype of gad5-1 was restored by exogenous application of GA3. The biomass, plant height, and levels of GA12 and GA3 in transgenic Arabidopsis overexpressing ZmGAD5 were increased in comparison with the corresponding controls Col-0. These findings deepen our understanding of genes involved in GA biosynthesis, and could lead to the development of maize lines with improved architecture and higher planting-density tolerance.

Novel insights into maize (Zea mays) development and organogenesis for agricultural optimization

In maize, intrinsic hormone activities and sap fluxes facilitate organogenesis patterning and plant holistic development; these hormone movements should be a primary focus of developmental biology and agricultural optimization strategies. Maize (Zea mays) is an important crop plant with distinctive life history characteristics and structural features. Genetic studies have extended our knowledge of maize developmental processes, genetics, and molecular ecophysiology. In this review, the classical life cycle and life history strategies of maize are analyzed to identify spatiotemporal organogenesis properties and develop a definitive understanding of maize development. The actions of genes and hormones involved in maize organogenesis and sex determination, along with potential molecular mechanisms, are investigated, with findings suggesting central roles of auxin and cytokinins in regulating maize holistic development. Furthermore, investigation of morphological and structural characteristics of maize, particularly node ubiquity and the alternate attachment pattern of lateral organs, yields a novel regulatory model suggesting that maize organ initiation and subsequent development are derived from the stimulation and interaction of auxin and cytokinin fluxes. Propositions that hormone activities and sap flow pathways control organogenesis are thoroughly explored, and initiation and development processes of distinctive maize organs are discussed. Analysis of physiological factors driving hormone and sap movement implicates cues of whole-plant activity for hormone and sap fluxes to stimulate maize inflorescence initiation and organ identity determination. The physiological origins and biogenetic mechanisms underlying maize floral sex determination occurring at the tassel and ear spikelet are thoroughly investigated. The comprehensive outline of maize development and morphogenetic physiology developed in this review will enable farmers to optimize field management and will provide a reference for de novo crop domestication and germplasm improvement using genome editing biotechnologies, promoting agricultural optimization.

Nitrogen partitioning in maize organs and underlined mechanisms from different plant density levels and N application rate in China

Nitrogen partitioning in maize organs and underlined mechanisms from different plant density levels and N application rate in China

Effects of Biodegradable Film and Polyethylene Film Residues on Soil Moisture and Maize Productivity in Dryland

With the dramatic increased use of agricultural film, the potential environmental risks associated with it have been receiving widespread attention. Biodegradable film (BF) is considered an alternative to conventional polyethylene film (PF), but its feasibility to replace PF needs to be verified. Thus, we conducted a two-year field experiment in the Loess Plateau region of China, exploring the effects of residual biodegradable film and polyethylene film (RBF and RPF) on soil moisture, maize root, and productivity at different residual levels (75 kg ha−1, 150 kg ha−1 and 300 kg ha−1). Regardless of the residual film type, soil water content (SWC), root length density (RLD), and root surface area density (RSD) all decreased with increasing residual level; this phenomenon observed significant differences when the residual level exceeded 150 kg ha−1. Different organs (root and shoot) of maize differed in their sensitivity and sensitivity period to residual film. The two-year degradation rate of RBF was 59.24%, which was higher than that of RPF. Compared to the RPF treatments, the SWC, RLD, RSD, biomass, and root–shoot ratio of the RBF treatments were closer to the no residual film treatment in the second maize growing season. After the two-year experiment, compared to the grain yield, water use efficiency, and precipitation use efficiency of the RPF treatments, that of the RBF treatments increased 0.41–6.24%, 0.12–4.44%, and 0.41–06.24%. The application of BF to replace PF is beneficial to sustainable maize production in dryland, but finding efficient methods to recycle the residual film remains a priority.

Allometric Relationships between Dry Matter Weights of Maize Organs and Their Responses to Drought

To understand the drought response mechanisms of dry matter partitioning of maize, pot experiments under drought conditions were conducted during the vegetative and reproductive growth periods of maize. The aim was to calculate allometric relationships between the dry matter weight of different organs and their responses to drought. Results showed that allometric relationships between the roots, above-ground plant, and total biomass gradually increased with maize growth approaching maturity under a normal water supply. Drought during the vegetative period reinforced allometric relationships during the growth process and after rewatering and increased the size-dependence of the root shoot ratio. However, drought during the reproductive period weakened them. The ear–shoot allometric relationship was more significant during growth than at later growth under normal conditions but strengthened during later growth in those plants suffering droughts during the vegetative and reproductive stages. The ear–shoot allometric relationship and the size-dependence of harvest index at later growth were significantly enhanced by drought during the reproductive period compared to the vegetative period.

PhenoTrack3D: an automatic high-throughput phenotyping pipeline to track maize organs over time.

High-throughput phenotyping platforms allow the study of the form and function of a large number of genotypes subjected to different growing conditions (GxE). A number of image acquisition and processing pipelines have been developed to automate this process, for micro-plots in the field and for individual plants in controlled conditions. Capturing shoot development requires extracting from images both the evolution of the 3D plant architecture as a whole, and a temporal tracking of the growth of its organs. We propose PhenoTrack3D, a new pipeline to extract a 3D + t reconstruction of maize. It allows the study of plant architecture and individual organ development over time during the entire growth cycle. The method tracks the development of each organ from a time-series of plants whose organs have already been segmented in 3D using existing methods, such as Phenomenal [Artzet et al. in BioRxiv 1:805739, 2019] which was chosen in this study. First, a novel stem detection method based on deep-learning is used to locate precisely the point of separation between ligulated and growing leaves. Second, a new and original multiple sequence alignment algorithm has been developed to perform the temporal tracking of ligulated leaves, which have a consistent geometry over time and an unambiguous topological position. Finally, growing leaves are back-tracked with a distance-based approach. This pipeline is validated on a challenging dataset of 60 maize hybrids imaged daily from emergence to maturity in the PhenoArch platform (ca. 250,000 images). Stem tip was precisely detected over time (RMSE < 2.1cm). 97.7% and 85.3% of ligulated and growing leaves respectively were assigned to the correct rank after tracking, on 30 plants × 43 dates. The pipeline allowed to extract various development and architecture traits at organ level, with good correlation to manual observations overall, on random subsets of 10-355 plants. We developed a novel phenotyping method based on sequence alignment and deep-learning. It allows to characterise the development of maize architecture at organ level, automatically and at a high-throughput. It has been validated on hundreds of plants during the entire development cycle, showing its applicability on GxE analyses of large maize datasets.

Segmentation and Stratification Methods of Field Maize Terrestrial LiDAR Point Cloud

Three-dimensional (3D) laser point cloud technology is an important research method in the field of agricultural remote sensing research. The collection and processing technology of terrestrial light detection and ranging (LiDAR) point cloud of crops has greatly promoted the integration of agricultural informatization and intelligence. In a smart farmland based on 3D modern agriculture, the manager can efficiently and conveniently achieve the growth status of crops through the point cloud collection system and processing model integrated in the smart agricultural system. To this end, we took field maize as the research object in this study and processed four sets of field maize point clouds, named Maize-01, Maize-02, Maize-03, and Maize-04, respectively. In this research, we established a field individual maize segmentation model with the density-based clustering algorithm (DBSCAN) as the core, and four groups of field maize were used as research objects. Among them, the value of the overall accuracy (OA) index, which was used to evaluate the comprehensive performance of the model, were 0.98, 0.97, 0.95, and 0.94. Secondly, the multi-condition identification method was used to separate different maize organ point clouds from the individual maize point cloud. In addition, the organ stratification model of field maize was established. In this organ stratification study, we take Maize-04 as the research object and obtained the recognition accuracy rates of four maize organs: tassel, stalk, ear, and leaf at 96.55%, 100%, 100%, and 99.12%, respectively. We also finely segmented the leaf organ obtained from the above-mentioned maize organ stratification model into each leaf individual again. We verified the accuracy of the leaf segmentation method with the leaf length as the representative. In the linear analysis of predicted values of leaf length, R2 was 0.73, RMSE was 0.12 m, and MAE was 0.07 m. In this study, we examined the segmentation of individual crop fields and established 3D information interpretations for crops in the field as well as for crop organs. Results visualized the real scene of the field, which is conducive to analyzing the response mechanism of crop growth and development to various complex environmental factors.

Maize associated bacterial microbiome linked mitigation of heavy metal stress: A multidimensional detoxification approach

The indiscriminate discharge and consequent accumulation of heavy metals (HMs) from various anthropogenic sources into the environment is a major global concern for food security and human health. Since HMs are non-degradable, they persist in soils, and above threshold levels alter the soil-plant systems. Following accumulation in soils and uptake by maize plants, HMs either alone or in synergism modify the composition and physiological activity of root-associated bacterial microbiome, soil nutrient pool, metabolism of maize plants, and pose risks to living organisms via the food chain. To solve HMs issues, the root-associated microbiome (rhizobiome) with high metal tolerating ability has been identified and applied for enhancing maize yield in contaminated soils; though reports on the use of metal tolerant rhizobiome in maize cultivation are limited. Recognizing the importance of maize as a food/feed crop and the lack of information on metal-induced phytotoxicity and its abatement strategies, this review attempts to provide the latest information on the importance of the metal tolerant microbiome in stress alleviation and crop nutrition and yield optimization/stability of maize in changing metal-enriched agro-ecosystems. In addition to the ameliorative roles of microbiome and plants in counteracting the stress, the distinct advances made in the metal tolerant rhizobiome-maize interactions are discussed, including the strategies and mechanisms adopted by biosensor microbiomes to accelerate maize-metal tolerance and growth. This review further explains the translocation, internalization, and distribution of metals in different maize organs. The impact of several metal tolerant biological enhancers as one of the incredibly attractive and highly promising technology to clean up metals and their importance in maize nutrition and crop production are highlighted. The simultaneous metal detoxification and bio-enhancing activity of the metal tolerant microbiome provides a better option for optimizing maize production in contaminated open field conditions.

Characterization and Functional Analysis of ZmSWEET15a in Maize.

The sugars will eventually be exported transporters (SWEETs) gene family is a new type of sugar transporters, which plays an important role in plant growth and development, physiological metabolism, and abiotic stress. In this study, we used quantitative real-time PCR to analyze the expression of ZmSWEET15a gene in different organs of maize and under different abiotic stresses. The results showed that ZmSWEET15a was expressed in roots, stems, leaves, and grains, with the highest expression level in leaves, which was highly correlated with leaf development. Under the treatment of polyethylene glycol (PEG), NaCl, H2O2, and abscisic acid stress, the expression of ZmSWEET15a was upregulated, while under the treatment of cold stress, the expression of ZmSWEET15a was inhibited. In sugar-specific experiments, we found that sucrose was the most effective carbon source for maize seed germination. The expression analysis of ZmSWEET15a in different carbon sources suggested that the expression of ZmSWEET15a was more likely to be induced by sucrose. Overexpression of ZmSWEET15a in maize plants could reduce the sucrose content in leaves and increase the sucrose content in grains. The heterologous expression of ZmSWEET15a in the yeast mutant strain SUSY7/ura indicated that ZmSWEET15a is a sucrose transporter and pH independent. This study provides new insight into sugar transport and carbohydrate partitioning in maize and other crops, and provide more genetic information for improving crop quality at the molecular level.