Search Results (7,142)

The aim of this experiment was to investigate the differences in the uptake and accumulation of rare earth elements (REEs) between selected plant species and the substrates used (soil with increased REE content, ash, and smelter waste). Eight plant species were included in the study: common yarrow (Achillea millefolium), false mayweed (Triplerosperum maritimum), tall fescue (Festuca arundinacea), marigold (Tagetes sp.), maize (Zea mays), white mustard (Sinapis alba), red clover (Trifolium pratense L.), and autumn fern (Dryopteris erythrosora). The study focused on the following REE representatives: lanthanum (La), cerium (Ce), europium (Eu), and gadolinium (Gd). Plant samples, divided into roots and shoots, were analyzed by ICP-MS. The obtained REE concentrations in plant tissues ranged from 9 to 697 µg kg⁻¹ (La), 10 to 1518 µg kg⁻¹ (Ce), 9 to 69 µg kg⁻¹ (Eu), and 9 to 189 µg kg⁻¹ (Gd). To determine the ability of plants to phytoextract REE, two factors were calculated: the translocation factor (TF) and the bioconcentration factor (BCF). The highest TF value was obtained for D. erythrosora growing on a substrate consisting of soil with increased REE content (Gd, TF = 4.03). Additionally, TF > 1 was obtained for all REEs in T. pratense L. In the experiment, the BCF was lower than 1 for all the plants tested. The study provided insight into the varying ability of plants to accumulate REEs, depending on both the plant species and the chemical properties of the substrate. Full article

Crop residue returning to field inputs considerable nitrogen (N) into soils, which greatly influences the function and sustainability of the agricultural system. However, little is known about the transformation and physical stabilization of maize residue-derived N in soil matrix in response to changing N availability. To explore the distinct regulation of organo-mineral complexes on maize residue N translocation, a 38-week microcosm incubation was carried out amended with ¹⁵N-labeled maize residue in a Mollisols sampled from Gonghzuling, Northeast of China. Unlabeled inorganic N was added at different levels (0, 60.3 mg N kg⁻¹ soil (low level), 167 mg N kg⁻¹ soil (medium level), and 702 mg N kg⁻¹ soil (high level)). ¹⁵N enrichment in bulk soil and the separated particle size fractions were determined periodically in the bulk soils and the subsamples were analyzed. At the early stage of the incubation, the maize residue N concentration declined significantly in the sand fraction and increased in the silt and clay fractions. Temporally, the ¹⁵N enrichment in the silt fraction changed slightly after 4 weeks but that in the clay fraction increased continuously until the 18th week. These results indicated that the decomposing process controlled maize residue N translocation hierarchically from coarser into finer fractions. From the aspect of functional differentiation, the pass-in of the maize residue N into the silt fraction was apt to be balanced by the pass-out, while the absorption of clay particles was essential for the stabilization of the decomposed maize residue N. The inorganic N level critically controlled both the decomposition and translocation of maize residue in soil. High and medium inorganic N addition facilitated maize residue N decomposition compared to the low-level N addition. Furthermore, medium N availability is more favorable for maize residue N transportation and stabilization in the clay fraction. Comparatively, high-level inorganic N supply could possibly impede the interaction of maize residue N and clay minerals due to the competition of ammonium sorption/fixation on the active site of clay. This research highlighted the functional coupling of organic–inorganic N during soil N accumulation and stabilization, and such findings could present a theoretical perspective on optimal management of crop residue resources and chemical fertilizers in field practices. Full article

Fresh sweet and waxy maize (Zea mays) are valuable specialty crops in southern China. Hyperspectral remote sensing offers a powerful tool for detecting maize foliar nutrients non-destructively. This study aims to investigate the capability of leaf spectroscopy (SVC HR-1024i spectrometer, wavelength range: 400–2500 nm) to retrieve maize foliar nutrients. Specifically, we (1) explored the effects of nitrogen application rates (0, 150, 225, 300, and 450 kg·N·ha⁻¹), maize cultivars (GLT-27 and TGN-932), and growth stages (third leaf (vegetation V3), stem elongation stage (vegetation V6), silking stage (reproductive R2), and milk stage (reproductive R3)) on foliar nutrients (nitrogen, phosphorus, and carbon) and leaf spectra; (2) evaluated the transferability of the regression and physical models in retrieving foliar nutrients across maize cultivars. We found that the PLSR (partial least squares regression), SVR (support vector machine regression), and RFR (random forest regression) regression model accuracies were fair within a specific cultivar, with the highest R² of 0.60 and the lowest NRMSE (normalized RMSE = RMSE/(Max − Min)) of 17% for nitrogen, R² of 0.19 and NRMSE of 21% for phosphorous, and R² of 0.45 and NRMSE of 19% for carbon. However, when these cultivar-specific models were used to predict foliar nitrogen across cultivars, lower R² and higher NRMSE values were observed. For the physical model, which does not rely on the dataset, the R² and NRMSE for foliar chlorophyll-a and -b (C_ab), carotenoid (C_xc), and equivalent water thickness (EWT) were 0.76 and 15%, 0.67 and 34%, and 0.47 and 21%, respectively. However, the prediction accuracy for foliar nitrogen, expressed as foliar protein in PROSPECT-PRO, was lower, with an R² of 0.22 and NRMSE of 27%, which was comparable to that of the regression models. The primary reasons for this limited transferability were attributed to (1) the insufficient number of samples and (2) the lack of strong absorption features for foliar nutrients within the 400–2500 nm wavelength range and the confounding effects of other foliar biochemicals with strong absorption features. Future efforts are needed to investigate the physical mechanisms underlying hyperspectral remote sensing of foliar nutrients and incorporate transfer learning techniques into foliar nutrient models. Full article

Paramyrothecium eichhorniae TBRC10637 has been reported as a potential biocontrol agent of water hyacinth (Eichhornia crassipes) in Thailand. Despite its great potential, it remained unclear whether the strain may cause disease in other plant species, especially those sharing the same niche as water hyacinth. Here, we examined the strain for its specificity and pathogenicity on 55 plant species from 26 families ranging from crop plants to aquatic weeds. We showed that, except for water hyacinth, P. eichhorniae TBRC10637 did not cause leaf spot or leaf blight or on any of the tested plants. Scanning electron microscopy of spores inoculated on eight plant species, including economically important plants such as maize (Zea mays) and chilli (Capsicum annuum) at 0, 24, 48, and 72 h after inoculation, showed no spore germination, except on water hyacinth. Inoculation with spore-free culture washing led to blight symptoms on leaves of water hyacinth 72 h after inoculation, suggesting that enzymes and secondary metabolites may be involved in causing the blight symptoms. Our results confirmed high specificity of P. eichhorniae TBRC10637 towards water hyacinth, paving the way to control the spread of water hyacinth effectively. Full article

Seed germination is a critical phase during which plants are particularly sensitive to environmental stresses, especially heat stress, due to the high metabolic and physiological activities required for initial growth. Melatonin (MT), a key antioxidant, is crucial for assisting plants in managing abiotic stresses. While the impact of melatonin on heat stress has been explored in other developmental stages or species, this is the first study to specifically focus on its role during maize seed germination under heat stress. The treatment with 50 μM melatonin significantly enhanced seed germination under heat stress by improving antioxidant capacity, osmotic regulation, and hydrolytic enzyme activity, likely through the modulation of key signaling pathways, thus reducing oxidative damage and starch content. Furthermore, melatonin application promoted the accumulation of endogenous gibberellins (GAs) and significantly inhibited abscisic acid (ABA) content, thereby maintaining a dynamic equilibrium between these phytohormones. Principal component analysis and correlation analysis provided deeper insights into the overall effects of these physiological and biochemical parameters. Integrated transcriptomic and metabolomic analysis revealed that melatonin exerted its regulatory effects by modulating key genes and pathways associated with antioxidant defense, stress responses, and plant hormone signal transduction. Furthermore, melatonin significantly modulated the GA and ABA signaling pathways, starch and sucrose metabolism, and phenylpropanoid biosynthesis, thereby reducing oxidative damage induced by heat stress and strengthening the defense mechanisms of maize seeds. The alignment between the qRT-PCR findings and transcriptomic data further validated the robustness of these underlying mechanisms. In conclusion, this study provides novel insights into the role of melatonin in enhancing maize seed germination under heat stress and offers a promising strategy for improving crop heat tolerance through melatonin application in agricultural practices. Full article

Planting speed has an important impact on plant spacing variability and also grain yield. In a two-year study, the effects of planting speeds of 6, 9, and 12 km/h on maize plant spacing and, consequently, ear parameters were investigated. We wanted to determine whether increasing the planting speed increases the plant spacing parameters and what effects this has on ear parameters and grain yield. In both experimental years, no differences between the three planting speeds were found in terms of mean plant spacing, plant density, the multiple index, and the miss index. However, the standard deviation of reference spacings and precision increased with the increase in planting speed from 6 to 12 km/h. In 2022, the differences between plant spacings measured using UAV photogrammetry and manual measurements were smaller (<1 cm) than in 2023. The plant spacing data obtained from 3D point clouds show a strong correlation (r = 0.97) with the manual measurements for all three planting speeds. The proposed method is suitable for measuring plant spacing in maize. In 2022, no differences appeared in grain yield and ear parameters between the planting speeds; however, in 2023, the grain yield and kernel mass per ear were greater at planting speeds of 6 and 9 km/h than at a planting speed of 12 km/h in 2023. Individual ear analysis in 2023 showed an increase of 0.73 g in kernel mass per plant with a 1 cm increase in plant spacing, resulting in a 58 kg/ha yield increase. Full article

Fusarium verticillioides can systematically infect maize through seeds, triggering stalk rot and ear rot at a later stage, thus resulting in yield loss and quality decline. Seeds carrying F. verticillioides are unsuitable for storage and pose a serious threat to human and animal health due to the toxins released by the fungus. Previously, the candidate gene ZmC2GnT was identified, using linkage and association analysis, as potentially implicated in maize seed resistance to F. verticillioides; however, its disease resistance mechanism remained unknown. Our current study revealed that ZmC2GnT codes an N-acetylglucosaminyltransferase, using sequence structure and evolutionary analysis. The candidate gene association analysis revealed multiple SNPs located in the UTRs and introns of ZmC2GnT. Cloning and comparing ZmC2GnT showed variations in the promoter and CDS of resistant and susceptible materials. The promoter of ZmC2GnT in the resistant parent contains one extra cis-element ABRE associated with the ABA signal, compared to the susceptible parent. Moreover, the amino acid sequence of ZmC2GnT in the resistant parent matches that of B73, but the susceptible parent contains ten amino acid alterations. The resistant material BT-1 and the susceptible material N6 were used as parents to observe the expression level of the ZmC2GnT. The results revealed that the expression of ZmC2GnT in disease-resistant maize seeds was significantly up-regulated after infection with F. verticillioides. After treatment with F. verticillioides or ABA, the expression activity of the ZmC2GnT promoter increased significantly in the resistant material, but no discernible difference was detected in the susceptible material. When ZmC2GnT from resistant and susceptible materials was overexpressed in Arabidopsis thaliana, the seeds’ resistance to F. verticillioides increased, although there was no significant difference between the two types of overexpressed plants. Our study revealed that ZmC2GnT could participate in the immune process of plants against pathogenic fungus. ZmC2GnT plays a significant role in regulating the disease-resistance process of maize seeds, laying the foundation for future research into the regulatory mechanism and the development of new disease-resistant maize varieties. Full article

Agricultural drought is a condition that threatens natural ecosystems, water security, and food security. The timely identification of an agricultural drought event is essential to mitigating its effects. However, achieving a reliable and accurate assessment is challenging due to the interannual variability of precipitation in a region. Therefore, the objective of this study was to identify the months with drought during the agricultural cycle of the maize crop (Zea mays L.) in the Atlacomulco Rural Development District (ARDD) as a study area using the SPI and SPEI indices and their impact on each phenological stage. The results show that when analyzing the historical period (1985–2017), the ARDD is a region prone to agricultural droughts with a duration of one month. The stages of grain filling and ripening were the most vulnerable, since SPI and SPEI-1 quantify that 25% and 31% of the total months with drought occur during those stages, respectively. Towards the 2041–2080 horizon, the MCG ACCESS-ESM1-5 with the SSP2-4.5 scenario identified an occurrence of dry periods with 17% and 20% by SPI and SPEI, respectively, while for SSP5-8.5, 17% and 22% of the total number of periods corresponded to dry months with SPI and SPEI, respectively. Greater recurrence will be observed in the future, specifically after the year 2061, meaning an increase in the frequency of agricultural drought events in the region, causing difficult and erratic productive conditions for each agricultural cycle and threatening sustainable development. Therefore, it is necessary to take action to mitigate the effects of climate change in this sector. Full article

Nitrogen (N) fertilizer incorporation of efficiency enhancer is a well-established practice aiming at reducing N loss while enhancing crop yield. However, the effect of different kinds of fertilizer efficiency enhancer on N use efficiency (NUE) and gas loss are rarely compared and poorly comprehended. Here, we conducted a field experiment involving the combination of urease and nitrification inhibitor (NI), the biological inhibitor eugenol (DE) and the bioploymer poly-glutamic acid (PG) and their combinations (NI + PG, NI + DE, PG + DE) to evaluate their effects on crop yield, NUE, NH3 volatilization and greenhouse gas emissions (GHGs). Results indicated that NI, DE, PG and their combinations significantly enhanced the crop yield, N uptake and NUE. NI, DE and PG are all effective in reducing NH₃ volatilization and N₂O emission, averagely decreased by 11.13%, 6.83%, 8.29%, respectively, and by 11.15%, 4.32%, 8.35%, respectively, while have no significant effects on CO₂-C and CH₄-C fluxes, except PG significantly increases CO₂-C emission and thus global warming potential. The combination of these three efficiency enhancers has no multiply effect on maize yield, NUE and gas loss. These findings help to screen the fertilizer efficiency enhancer that can be more effectively utilized in agricultural practices and contribute to their application strategies within agricultural systems. Full article

Polymer-coated controlled-release fertilizers’ (CRFs) unique nutrient release mechanism has the potential to mitigate the leaching of mobile soil nutrients, such as nitrate-nitrogen (NO₃-N). The study aimed to evaluate the capacity of a polymer-coated CRFs to maintain maize (Zea mays L.) crop growth/health indicators and production goals, while reducing NO₃-N leaching risks compared to conventional (CONV) fertilizers in North Florida. Four CRF rates (168, 224, 280, 336 kg N ha⁻¹) were assessed against a no nitrogen (N) application and the current University of Florida Institute for Food and Agricultural Sciences (UF/IFAS) recommended CONV (269 kg N ha⁻¹) fertilizer rate. All CRF treatments, even the lowest CRF rate (168 kg N ha⁻¹), produced yields, leaf tissue N concentrations, plant heights, aboveground biomasses (AGB), and leaf area index (LAI) significantly (p < 0.05) greater than or similar to the CONV fertilizer treatment. Additionally, in 2022, the CONV fertilizer treatment resulted in increases in late-season movement of soil NO₃-N into highly leachable areas of the soil profile (60–120 cm), while none of the CRF treatments did. However, back-to-back leaching rainfall (>76.2 mm over three days) events in the 2023 growing season masked any trends as NO₃-N was likely completely flushed from the system. The results of this two-year study suggest that polymer-coated CRFs can achieve desirable crop growth, crop health, and production goals, while also having the potential to reduce the late-season leaching potential of NO₃-N; however, more research is needed to fully capture and quantify the movement of NO₃-N through the soil profile. Correlation and Principal Component Analysis (PCA) revealed that CRF performance was significantly influenced by environmental factors such as rainfall and temperature. In 2022, temperature-driven nitrogen release aligned with crop uptake, supporting higher yields and minimizing NO₃-N movement. In 2023, however, rainfall-driven variability led to an increase in NO₃-N leaching and masked the benefits of CRF treatments. These analyses provided critical insights into the relationships between environmental factors and CRF performance, emphasizing the importance of adaptive fertilizer management under varying climatic conditions. Full article

Mostly, phosphorus (P) fertilizers are fixed in the interlayer of soil and become unavailable to crop plants. Combined inorganic fertilizers with organic manures could be a suitable solution to release these nutrients from the soil. P deficiency in soil adversely affected crop growth and development to a larger extent. To check out this problem, present research was conducted over a two-year period to evaluate the efficiency of a combined mixture of inorganic P and organic manure as a better farming strategy, in relation to their sole treatments, for enhancing P availability, plant growth, yield and quality, and soil properties. The inorganic source of P was SSP in the form of P₂O₅, while the organic source was cattle manure mixed with crop residues called farmyard manure (FYM). The experiment consisted of the same six treatments over each year: (i) control (0F+0P), (ii) 45 kg P₂O₅ ha⁻¹ (45P), (iii) 90 kg P₂O₅ ha⁻¹ (90P), (iv) 45 kg P₂O₅ ha⁻¹ + 1000 kg FYM ha⁻¹ (45P+1000F), (v) 1000 kg FYM ha⁻¹ (1000F), and (vi) 2000 kg FYM ha⁻¹ (2000F), using randomized complete block design (RCBD), to five replications. Results demonstrated that the combination of SSP with FYM increased the plant height (27.9%), grain yield (23.4%), and plant P uptake efficiency (43.7%) of maize as compared to sole SSP at 90 kg P₂O₅ ha⁻¹, which occurred due to improved P availability in soil. By comparing sole amendments of P fertilizer sources, FYM-treated plots have performed better in increasing maize growth and yield components such as plant height, dry matter, crop growth rate (CGR), net photosynthetic rate, grain yield, and crude protein (e.g., nitrogen contents); this happened due to enhanced soil chemical properties that might be related to improvement in P level and decreased bulk density of soil. Further, significant positive correlations were exhibited among studied crop and soil data. The plant available P and grain protein contents (N concentration) also showed a significant positive correlation and exhibited higher nitrogen contents under organic amendments of P fertilizer, as compared to inorganic treatments. The study concluded that combined SSP at 45 kg P₂O₅ ha⁻¹ with organic cattle manure at 1000 kg ha⁻¹ has a great potential for enhancing maize productivity under water deficit conditions. Results of this research may further be improved by including rigorous soil samples and field heterogeneity data between the plots and the years, which will provide more clear findings from a combined mixture of organic and inorganic fertilization. Full article

Cadmium is a toxic, carcinogenic element that threatens food safety due to its tendency to be absorbed by plants along with essential nutrients. This study conducted a genome-wide association study (GWAS) using SNP genotyping data from 170 natural maize populations to analyze cadmium content in maize grains across three environments. The MLM_Q+Kinship and MLM_PCA+Kinship models identified 6424 (HN), 991 (JMO), and 1358 (JMT) SNPs linked to cadmium accumulation in the MLM_Q+Kinship model, with 121 SNPs common across all environments. Additionally, the MLM_PCA+Kinship model detected 824 (HN), 950 (JMO), and 910 (JMT) SNPs, with 14 shared loci. In total, 126 reliable SNP loci, representing 14 QTLs, were identified, highlighting 12 superior haplotypes and 2 favorable alleles. A negative correlation between these loci and cadmium content was observed. Within 100 kbp of the QTLs, 45 candidate genes were identified, associated with 11 GO terms and 5 KEGG pathways. Analysis revealed 12 maize lines with at least one stable locus, all of which showed reduced Cd levels. Key hybrids, such as CAU95×CAU65 and CAU95×CAU266, demonstrated the potential for low Cd accumulation. This study provides valuable insights for breeding maize with reduced Cd uptake using stable gene loci discovered through GWAS. Full article

Assessing genetic gains from historical data provides insights to improve breeding programs. This study evaluated the Mozambique National Maize Program’s (MNMP’s) genetic gains using data from advanced germplasm trials conducted at 21 locations between 2014 and 2020. Genetic gains were calculated by regressing the genotypic best linear unbiased estimates of grain yield and complementary agronomic traits against the initial year of genotype evaluation (n = 592). The annual genetic gain was expressed as a percentage of the trait mean. While grain yield, the primary breeding focus, showed no significant improvement, significant gains were observed for the plant height (0.67%), ear height (1.74%), ears per plant (1.31%), ear position coefficient (1.22%), and husk cover (4.7%). Negative genetic gains were detected for the days to anthesis (−0.5%), the anthesis–silking interval or ASI (−9.31%), and stalk lodging (−5.01%). These results indicate that while MNMP did not achieve the desired positive genetic gain for grain yield, progress was made for traits related to plant resilience, particularly the ASI and stalk lodging. MNMP should seek to incorporate new breeding technologies and human resources to enhance genetic gains for grain yield and other key traits in the maize breeding program, while developing and deploying high-yielding, climate-resilient maize varieties to address emerging food security challenges in Mozambique. Full article

The prediction of grain protein function is essential for the advancement of food science. Traditional experimental methods are associated with high costs and significant time requirements. Computational methods are recognized for their efficiency and reduced time demands. A new multimodal deep learning method, MMSNet, is proposed in this study, and protein data of four types of grains (japonica, indica, maize, and wheat) are analyzed. This method fuses the protein structure information predicted by AlphaFold2 and combines a multiscale one-dimensional convolutional neural network (1DCNN) with a two-dimensional convolutional neural network (2DCNN) to enable the model to capture sequence and structural information effectively. We used a residual attention mechanism to replace the traditional pooling layer, thereby improving the feature extraction capability of the network layers in 2DCNN. The experimental results indicate that secondary structure and spatial structure information contribute to improving model performance. Compared with two classical methods, MMSNet demonstrates optimal performance, which validates the effectiveness of our approach in integrating complex grain protein data and highlights its potential to open new avenues for grain protein function prediction. Full article

As global populations grow and environmental constraints intensify, improving agricultural water management is essential for sustainable food production. Traditional irrigation methods often lack adaptability, leading to inefficient water use. Reinforcement learning (RL) offers a promising solution for developing dynamic irrigation strategies that balance productivity and resource conservation. However, agricultural RL tasks are characterized by sparse actions—irrigation only when necessary—and delayed rewards realized at the end of the growing season. This study integrates RL with AquaCrop-OSPy simulations in the Gymnasium framework to develop adaptive irrigation policies for maize. We introduce a reward mechanism that penalizes incremental water usage while rewarding end-of-season yields, encouraging resource-efficient decisions. Using the Proximal Policy Optimization (PPO) algorithm, our RL-driven approach outperforms fixed-threshold irrigation strategies, reducing water use by 29% and increasing profitability by 9%. It achieves a water use efficiency of 76.76 kg/ha/mm, a 40% improvement over optimized soil moisture threshold methods. These findings highlight RL’s potential to address the challenges of sparse actions and delayed rewards in agricultural management, delivering significant environmental and economic benefits. Full article