Search Results (1,072)

Soil degradation and limited root-exploitable depth restrict maize productivity in Plinthosols of tropical regions. However, the combined effects of subsoiling and amendments derived from termite mound materials on soil functionality and yield remain insufficiently quantified. This study examines how variations in a functionally exploitable rooting depth, within a management system combining subsoiling and termite mound amendments, are associated with soil physicochemical properties and spatial variability of maize (Zea mays L.) grain yield in the Lubumbashi region of the Democratic Republic of the Congo. Spatial soil sampling and correlation analyses were used to identify the dominant pedological factors controlling yield variability. The results indicate a reduced vertical stratification of most nutrients within the explored depth, reflecting a more homogeneous distribution of soil properties within the managed profile, although direct causal attribution to specific practices cannot be established in the absence of untreated control plots. Improved rooting conditions were reflected by high and spatially variable productivity (2.3 to 11.1 t ha⁻¹ across blocks), accompanied by a moderate average gain between seasons (<1 t ha⁻¹), while extractable manganese emerged as a consistent negative predictor of yield. These patterns are consistent with a larger functionally exploitable rooting depth and an improved soil environment, although causal contributions of subsoiling and termite mound amendments cannot be isolated in the absence of control plots. Overall, the results highlight the importance of jointly considering structural and chemical soil properties when interpreting productivity gradients in Plinthosols and designing sustainable management strategies for degraded tropical soils. Full article

Maize is one of the top three crops globally, ranking only behind rice and wheat, making it an important crop of interest. Aboveground biomass is a key indicator for assessing maize growth and its yield potential. This study developed an efficient and stable biomass prediction model to estimate the aboveground biomass (AGB) of spring maize (Zea mays L.) under subsurface drip irrigation in arid regions, based on UAV multispectral remote sensing and machine learning techniques. Focusing on typical subsurface drip-irrigated spring maize in arid Xinjiang, multispectral images and field-measured AGB data were collected from 96 sample points (selected via stratified random sampling across 24 plots) over four key phenological stages in 2024 and 2025. Sixteen vegetation indices were calculated and 40 texture features were extracted using the gray-level co-occurrence matrix method, while an integrated feature-selection strategy combining Elastic Net and Random Forest was employed to effectively screen key predictor variables. Based on the selected features, six machine learning models were constructed, including Elastic Net Regression (ENR), Gradient Boosting Decision Trees (GBDT), Gaussian Process Regression (GPR), Partial Least Squares Regression (PLSR), Random Forest (RF), and Extreme Gradient Boosting (XGB). Results showed that the fused feature set comprised four vegetation indices (GRDVI, RERVI, GRVI, NDVI) and five texture features (R_Corr, NIR_Mean, NIR_Vari, B_Mean, B_Corr), thereby retaining red-edge and visible-light texture information highly sensitive to AGB. The GPR model based on the fused features exhibited the best performance (test set R² = 0.852, RMSE = 2890.74 kg ha⁻¹, MAE = 1676.70 kg ha⁻¹), demonstrating high fitting accuracy and stable predictive ability across both the training and test sets. Spatial inversions over the two growing seasons of 2024 and 2025, derived from the fused-feature GPR optimal model at four key phenological stages, revealed pronounced spatiotemporal heterogeneity and stage-dependent dynamics of spring maize AGB: the biomass accumulates rapidly from jointing to grain filling, slows thereafter, and peaks at maturity. At a constant planting density, AGB increased markedly with nitrogen inputs from N0 to N3 (420 kg N ha⁻¹), with the high-nitrogen N3 treatment producing the greatest biomass; this successfully captured the regulatory effect of the nitrogen gradient on maize growth, provided reliable data for variable-rate fertilization, and is highly relevant for optimizing water–fertilizer coordination in subsurface drip irrigation systems. Future research may extend this integrated feature selection and modeling framework to monitor the growth and estimate the yield of other crops, such as rice and cotton, thereby validating its generalizability and robustness in diverse agricultural scenarios. Full article

Maize (Zea mays L.), a vital crop for global food and economic security, faces intensifying biotic and abiotic stresses driven by climate change, including drought, heat, and erratic rainfall. This review synthesizes emerging biotechnology-driven strategies designed to enhance maize resilience under these shifting environmental conditions. We present an integrated framework that encompasses CRISPR/Cas9 and next-generation genome editing, Genomic Selection (GS), Environmental Genomic Selection (EGS), and multi-omics platforms—spanning transcriptomics, proteomics, metabolomics, and epigenomics. These approaches have significantly deepened our understanding of complex stress-adaptive traits and genotype-by-environment interactions, revealing precise targets for breeding climate-resilient cultivars. Furthermore, we highlight enabling technologies such as high-throughput phenotyping, artificial intelligence (AI), and nanoparticle-based gene delivery—including novel in planta and transformation-free protocols—that are accelerating translational breeding. Despite these technical breakthroughs, barriers such as genotype-dependent transformation efficiency, regulatory landscapes, and implementation costs in resource-limited settings remain. Bridging the gap between laboratory innovation and field deployment will require coordinated policy support and global collaboration. By integrating molecular breakthroughs with practical deployment strategies, this review offers a comprehensive roadmap for developing sustainable, climate-resilient maize varieties to meet future agricultural demands. Full article

Maize (Zea mays L.) is a major economic crop highly susceptible to Colletotrichum graminicola, the causal agent of anthracnose leaf blight, which causes substantial annual yield losses. This fungal pathogen employs numerous effectors to manipulate plant immunity, yet the functions of many secreted proteins during biphasic infection remain poorly characterized. In this study, we identified CgMas2, a candidate secreted protein in C. graminicola and a homolog of Magnaporthe oryzae MoMas2. Deletion of CgMAS2 in the wild-type strain CgM2 did not affect fungal vegetative growth or conidial morphology but significantly impaired virulence on maize leaves. Leaf sheath infection assays revealed that CgMas2 is required for biotrophic invasive hyphal growth, as the mutant showed defective spreading of invasive hyphae to adjacent cells. Subcellular localization analysis indicated that CgMas2 localizes to the cytoplasm of conidia and to the primary infection hyphae. Furthermore, DAB staining demonstrated that disrupt of CgMAS2 leads to host reactive oxygen species (ROS) accumulation. Comparative transcriptome analysis of maize infected with ΔCgmas2 versus CgM2 revealed enrichment of GO terms related to peroxisome and defense response, along with up-regulation of benzoxazinoid biosynthesis genes (benzoxazinone biosynthesis 3, 4 and 5) at 60 h post-inoculation (hpi). Conversely, six ethylene-responsive transcription factors (ERF2, ERF3, ERF56, ERF112, ERF115 and ERF118) involved in ethylene signaling pathways were down-regulated at 96 hpi. These expression patterns were validated by RT-qPCR. Collectively, our results demonstrate that CgMas2 not only promotes invasive hyphal growth during the biotrophic stage but may also modulate phytohormone signaling and defense compound biosynthesis during the necrotrophic phase of infection. Full article

Agroforestry is defined as a multifunctional approach to land management that enhances biodiversity and soil health while mitigating environmental impacts compared to intensive agriculture. The efficacy of maize cultivation in agroforestry systems is significantly influenced by nutrient competition. The factors that influence this phenomenon include the dimensions and configuration of the tree rows, as well as the availability of nutrients. This study examined the effect of nitrogen fertilization, tree line spacing, and seasonal changes on the productivity and the leaf spectral characteristics of the intercropped maize (Zea mays L.) within a willow-based agroforestry system in eastern Hungary. The experiment involved the cultivation of maize with two spacings (narrow and wide field strips) and four nitrogen levels (0, 50, 100, and 150 kg N ha⁻¹) across two growing seasons (2023–2024). The results demonstrated that yield-related parameters, including biomass, cob size and weight, and grain weight, exhibited a strong response to nitrogen level and tree line spacing. The reduction in spacing resulted in a decline in maize productivity. However, a high nitrogen input (150 kg N ha⁻¹) partially mitigated this effect in the first growing season. Vegetation indices demonstrated a high degree of sensitivity to annual variations, particularly with regard to tree competition and weather conditions. Multispectral vegetation indices exhibited a heightened responsiveness to environmental and management factors when compared to indices based on visible light (RGB). The findings of this study demonstrate that a combination of optimized tree spacing and optimized nitrogen management fosters productivity while maintaining agroecological sustainability in temperate agroforestry systems. Full article

Drought can alter plant nutrient constraints, yet it remains uncertain whether macronutrient limitation hierarchies primarily reflect intrinsic responses or can be reshaped by targeted treatments. In a pot experiment with maize (Zea mays L.), we tested elemental sulfur (ES) and salicylic acid (SA) applied either as foliar sprays or soil amendments under two soil water regimes (30% vs. 60% field water capacity, FWC). Six treatments were evaluated (control, ES-foliar, SA-foliar, SA-soil, ES-soil, and ES + SA-soil; n = 72). Regression tree analysis of data indicated sulfur-potassium co-dominance under drought (24.6% importance each; R² = 0.914), while untreated controls showed nitrogen dominance (27.1%), confirming the S-K pattern is treatment-mediated. Under optimal irrigation (FWC 60%), nutrient importance was balanced across treatments (N, P, K, S; ~22–23%; R² = 0.991). ES + SA applied to soil produced the greatest drought tolerance, increasing dry biomass by 56% at FWC 30%, whereas ES-soil maintained favorable N/S ratios (9.64–9.86). Redundancy analysis confirmed that water availability explained 63.4% of nutrient variance and revealed significant Treatment × FWC interactions. These findings reveal that nutrient hierarchies can be strategically manipulated through targeted fertilization, representing a nutrient management approach for enhancing drought tolerance. Full article

This study investigates the accumulation potential of Brassica napus L. and Zea mays L. cultivated on soils contaminated with Zn, Cd, Cu and Pb, using HEDTA—Hydroxyethyl Ethylenediamine Triacetic Acid—to enhance metal mobility. The research addresses a gap in the literature regarding the dual-purpose use of energy crops for assisted phytoextraction and bioenergy recovery. Two pot experiments were conducted on soils of different textures, with HEDTA applied at 2.5 and 5 mmol·kg⁻¹. Metal concentrations in soil and plant tissues were measured, and indices such as the geoaccumulation index (Igeo), bioconcentration factors (BCF), translocation factor (TF), metal tolerance index (MTI), crop growth rate (CGR) and higher heating value (HHV) were calculated. Results showed that HEDTA significantly increased Cd and Zn mobility, leading to higher accumulation in rapeseed shoots. Maize demonstrated phytostabilization by retaining metals in roots. Rapeseed biomass exhibited a higher HHV (up to 20.6 MJ·kg⁻¹) and greater carbon and hydrogen content, indicating suitability for thermochemical conversion. Maize, with lower ash content, showed potential for bioethanol production. The findings support the integration of chelate-assisted phytoextraction with energy recovery from biomass. Full article

The resident microbiota in agricultural soils strongly influences crop health and productivity. In this study, we evaluated the prokaryotic diversity of two clay soils with similar physicochemical characteristics but contrasting levels of maize (Zea mays L.) and wheat (Triticum aestivum L.) production using 16S rRNA gene sequencing. Yield records showed significant differences in grain production over five consecutive years. When comparing prokaryotic alpha diversity between the “non-productive” and “productive” soils, no major differences were found, and the abundance of ammonia-oxidizing archaea (AOA) and bacterial genera such as Arthrobacter, Neobacillus, and Microvirga remained consistent across soils. Analysis of the top 20 genera showing the greatest abundance shifts by compartment (bulk soil vs. rhizosphere) revealed that genera such as Priestia, Neobacillus, Sporosarcina, and Pontibacter decreased in the rhizosphere of the non-productive soil, while in the productive soil, these genera remained unchanged. In the non-productive soil, genera such as Flavisobacter decreased in abundance in the rhizosphere, whereas Arthrobacter increased. Principal coordinates analysis (PCoA) showed no clear clustering by compartment (bulk vs. rhizosphere), but two distinct clusters emerged when grouping by soil type (productive vs. non-productive). Interaction networks varied by soil type: non-productive soils showed positive Candidatus–Bacillus and negative Massilia links, while productive soils were dominated by Flavisolibacter and negative Pontibacter. Across soils, Rhizobium–Bradyrhizobium associations were positive, whereas Neobacillus and Priestia were negative. These findings highlight that a few potential beneficial microbiota and their interactions may be key drivers of soil productivity, representing targets for microbiome-based agricultural management. Full article

Landfill leachate reverse osmosis (RO) treatment generates a highly concentrated stream rich in recalcitrant organic matter, particularly humic substances (HS), which present potential for recovery and reuse as a biofertilizer. This study evaluated HS recovery from the RO concentrate of the Seropédica Landfill (Rio de Janeiro, Brazil) using a nanofiltration (NF) process with a polyethersulfone membrane (MWCO = 1000 Da) operated at 9 bar. The NF system achieved a volume reduction factor of 2.5, rejecting 70–75% of the organic matter. At the same time, salts were predominantly transmitted to the permeate. The phytotoxicity of recovered HS solution was evaluated through maize (Zea mays L.) germination assays at concentrations ranging from 20 to 100 mg HS/L. All treatments showed germination indices above 100%, indicating the absence of phytotoxicity, and seedling growth significantly improved relative to the control, especially at 20 mg HS/L. Trace metal concentrations in the recovered HS complied with Brazilian standards for irrigation water. Overall, the results show that nanofiltration is highly effective in concentrating humic substances from leachate RO concentrate, minimizing the presence of salts, and contributing to strategies for landfill leachate management. Full article

Potassium (K) is crucial for global maize (Zea mays L.) production, yet the issue of “high K fertilizer input but low utilization efficiency” in K-rich soils of Xinjiang remains underexplored. A three-year field experiment (2020, 2021, 2024) in Xinjiang evaluated the effects of reduced K application on maize growth, grain yield (GY), and K-use efficiency. Five treatments were tested: K100 (136.0 kg K₂O·ha⁻¹), K60 (83.5 kg K₂O·ha⁻¹), K40 (55.6 kg K₂O·ha⁻¹), K0 (no K), and CK (no fertilizer). The research shows that K60 significantly outperforms K100 in terms of physiological parameters (plant height + 2.7–34.7%, leaf area index (LAI) + 6.3–26.8%, dry matter + 22.0–28.8%); GY and thousand kernel weight (TKW) improved by 6.9–15.1% and 9.3–30.3%, respectively. The potassium fertilizer productivity (PFP_K) and potassium fertilizer agronomic efficiency (AE_K) increased by 78–112.3% and 176.4–2085% compared to the K100. During the three-year period, the maximum net income of K60 reached 28,206 CNY·ha⁻¹, which was 18.9–20.7% higher than that of K100. Regression analysis identified an optimal K rate of 82.2–85 kg·ha⁻¹ for maximum yield. Least squares structural equation mode (PLS-SEM) and correlation analyses revealed that moderate K reduction enhanced vegetative growth and optimized yield structure, indirectly boosting yield, thereby directly driving net income. Thus, reducing K input can achieve “lower input with higher efficiency”, offering a practical basis for optimizing K management in arid-region maize systems. Full article

Purple corn (Zea mays L.) is a nutraceutical crop of increasing economic importance in Peru, yet its productivity is highly influenced by genotype × environment (G × E) interactions across heterogeneous agro-ecological zones. Therefore, selecting suitable genotypes for specific environments is essential to optimize variety deployment and maximize site-specific yield. Five purple-maize genotypes (INIA-601, INIA-615, Canteño, PMV-581, and Sintético-MM) were evaluated in four contrasting Peruvian sites using a randomized complete-block design. Grain yield, field weight, anthesis–silking interval (ASI), plant height, and ear-rot incidence were analyzed with combined analysis of variance (ANOVA), the additive main effects and multiplicative interaction (AMMI), genotype and genotype-by-environment (GGE) biplots, Weighted Average of Absolute Scores (WAAS), weighted average of absolute scores and best yield index (WAASBY), and Y × WAAS indices. Environment accounted for 90.1% of field-weight variation (p < 0.0001) and 50.2% of grain-yield variation (p < 0.001), while significant G × E interactions (3.93% and 18.14%, respectively) justified bilinear modeling. AMMI1 and GGE “which-won-where” biplots identified INIA-615 and PMV-581 as broadly adapted, with INIA-615 achieving the highest WAASBY and positioning in quadrant IV of Y × WAAS (high yield, high stability). INIA-601 and Sintético-MM exhibited exceptional stability (low ASV) but moderate productivity; Canteño showed limited adaptability. Chumbibamba emerged as a key discriminating, high-productivity location. From an agronomic perspective, INIA-615 is recommended for high-productivity valleys such as Sulluscocha and Santa Rita, where its yield potential and stability are maximized. These findings underscore the potential of integrating multivariate stability metrics with physiological and disease-resistance traits to guide the selection of superior purple corn cultivars. Overall, INIA-615 represents a robust candidate for enhancing yield stability, supporting sustainable intensification, and expanding the nutraceutical value chain of purple corn in the Andean highlands. Full article

The increasing environmental challenges facing modern agriculture necessitate development of sustainable, eco-friendly alternatives to chemical inputs. This study aimed to isolate and characterize rhizophilic bacterial strains from the rhizosphere of the maize hybrid Turan 480 SV (Zea mays L.), with a focus on their plant growth-promoting and biocontrol traits. A total of 23 bacterial isolates were obtained, including 15 Gram-negative and 8 Gram-positive strains. Among these, three strains—CR14, CR18 and CR22—were selected for detailed analysis. All three demonstrated significant indole-3-acetic acid (IAA) production, phosphate and zinc solubilization, nitrogen fixation and antifungal activity. CR14 synthesized 56.01 mg L⁻¹ of IAA and demonstrated the highest zinc solubilization, while CR18 exhibited superior phosphate solubilization and protease activity. CR22 produced the highest IAA (61.46 mg L⁻¹) and demonstrated strong cellulase and amylase activity. In antagonism tests, CR14 suppressed Alternaria alternata with an 80 mm inhibition zone, while CR18 and CR22 effectively inhibited both A. alternata and Fusarium graminearum. Phylogenetic analysis based on 16S rRNA sequencing identified CR18 as Serratia quinivorans, CR14 as Pantoea agglomerans and CR22 as Pantoea sp. The functional diversity of rhizobacteria holds promise as bioinoculants for enhancing maize growth and protecting against soil-borne pathogens in sustainable agriculture. Full article

The Lagunera Region, located in northern Mexico, is home to the country’s most important dairy basin, situated in a semi-arid environment. In this region, forage corn (Zea mays L.) is the main input in dairy cattle feed. In this context, optimizing water use and nitrogen nutrition is a priority to ensure the sustainability of this activity. The main objective of this study was to evaluate the productivity and water use efficiency of forage corn under different humidity, nitrogen, and substrate type levels. A randomized block design with sub-subdivided plots was used. The larger plot contained two usable moisture levels (80 and 50%); the subplots were assigned according to three nitrogen levels: 13.6 (N1), 6.8 (N2), and control 0.35 (N3) NO₃ mmol·L⁻¹; the sub-subplots were assigned based on two substrates: sand and a mixture (MI) of sand, perlite, and peat moss. The results showed significant triple interactions (p < 0.05) in the root volume traits, where nitrogen played a determining role, as well as double interactions (Nutrition*Substrate) for all vegetative and radicle production variables and water use efficiency. Principal components analysis explained 91.4% of the total observed variation, where basal diameter had the vector with the highest load value. Cluster analysis identified that the main discriminant factor was nutrition. It is concluded that usable moisture levels up to 50% with 6.8 mmol·L⁻¹ of NO₃ show acceptable levels of vegetative production and root volume in forage corn. These results suggest the possibility of reducing water and nitrogen fertilizer consumption without compromising yield, with significant economic and environmental benefits for agriculture in arid and semi-arid regions. Full article

Nitrogen is pivotal for high-yield maize (Zea mays L.), but excessive nitrogen application and improper timing remain common in production. Clarifying nitrogen strategies and population nitrogen accumulation under high density is urgent. This study set two density levels (7.5 × 10⁴ plants ha⁻¹; 12.0 × 10⁴ plants ha⁻¹) and eight nitrogen management methods: the no nitrogen (N0), all-basal nitrogen (Fbase, total nitrogen: 360 kg ha⁻¹), and post-silking topdressing methods (total nitrogen: 360 kg ha⁻¹) with nitrogen proportions of 0% (F0%, post-silking topdressing: 0 kg ha⁻¹), 20% (F20%, post-silking topdressing: 72 kg ha⁻¹), 40% (F40%, post-silking topdressing: 144 kg ha⁻¹), 60% (F60%, post-silking topdressing: 216 kg ha⁻¹), 80% (F80%, post-silking topdressing: 288 kg ha⁻¹), and 100% (F100%, post-silking topdressing: 360 kg ha⁻¹). Fertilization was applied via drip irrigation. Results demonstrated that the highest yield was obtained under F60% at 7.5 × 10⁴ plants ha⁻¹ and under F40% at 12.0 × 10⁴ plants ha⁻¹. Appropriate post-silking nitrogen increments synergistically improved kernel number per ear and 1000-kernel weight. The post-silking nitrogen topdressing proportion significantly affected maize stand nitrogen accumulation. At maturity, the highest nitrogen accumulation was observed under F60% at 7.5 × 10⁴ plant ha⁻¹ density and under F40% at 12.0 × 10⁴ plants ha⁻¹ density. For the 7.5 × 10⁴ condition, the duration of the rapid nitrogen accumulation period was extended by 11.9–39.2 days and maximum nitrogen accumulation increased by 15.52–57.20%; at 12.0 × 10⁴, maximum nitrogen accumulation rose by 15.89–64.46%. In summary, appropriately increasing the proportion of post-silking nitrogen application can enhance maize yield, nitrogen accumulation, and nitrogen uptake efficiency. Specifically, a 60% post-silking nitrogen application ratio is recommended for a 7.5 × 10⁴ plants ha⁻¹ density and a 40% ratio for a 12.0 × 10⁴ plants ha⁻¹ density. These two strategies can significantly increase kernel number per ear and 1000-kernel weight, thereby improving maize yield and nitrogen use efficiency. Full article

Nitrogen (N) is essential for maize (Zea mays L.) productivity, yet its acquisition is limited by the low N uptake efficiency of current varieties. Root cortical aerenchyma (RCA) formation provides a carbon-saving strategy that enhances soil exploration and N acquisition by reducing the metabolic cost of root tissue. However, the genetic basis of RCA formation remains poorly characterized. This study employed an association panel of 295 maize inbred lines to dissect the genetic architecture of RCA formation under low nitrogen (LN) stress. Phenotypic analysis demonstrated that LN stress significantly induced RCA area (RCAA) and proportion (RCAP), with responses ranging from −0.31 to 1.16 mm² for RCAA and −11.34% to 40.18% for RCAP. The non-stiff stalk (NSS) subpopulation exhibited 29.19% higher RCAA under LN than the stiff stalk subgroup. Genome-wide association analysis detected a total of 560 significant SNPs and 810 candidate genes associated with RCA-related traits. Transcriptomic profiling further identified 537 differentially expressed genes between inbred lines with contrasting RCA phenotypes. Integrated GWAS and transcriptomic analysis pinpointed 12 co-localized candidates, subsequently refined to four core genes (GRMZM2G033570, GRMZM2G052422, GRMZM2G080603, and GRMZM2G472266), which were implicated in ethylene signaling and stress-responsive root development. Favorable haplotypes of three genes were predominantly distributed in the NSS (25.64–56.00%) and tropical/subtropical (20.51–46.67%) subpopulations. These findings elucidate the genetic basis of LN-responsive RCA formation and provide fundamental resources for marker-assisted breeding of N-efficient maize. Full article