Search Results (642)

Chickpea is a highly weed-prone crop with limited herbicide options and high labor demands, raising the following question: Can fall-planted legume–cereal cover crops (CCs) improve soil properties while reducing herbicide use and manual weeding pressure? To explore this, we evaluated the effect of fall-planted winter rye (WR) alone in 2021 and mixed with hairy vetch (HV) in 2022 and 2023 at Randolph farm in Petersburg, Virginia. The objectives were two-fold: (a) to examine the effect of CCs on soil properties using monthly growth dynamics and biomass harvested from fifteen 0.25 m²-quadrants and (b) to evaluate the efficiency of five termination methods: (1) green manure (GM); (2) GM plus pre-emergence herbicide (GMH); (3) burn (BOH); (4) crimp mulch (CRM); and (5) mow-mulch (MW) in suppressing weeds in chickpea fields. Weed distribution, particularly nutsedge, was patchy and dominant on the eastern side. Growth dynamics followed an exponential growth rate in fall 2022 (R² ≥ 0.994, p < 0.0002) and a three-parameter sigmoidal curve in 2023 (R² ≥ 0.972, p < 0.0047). Biomass averaged 55.8 and 96.9 t/ha for 2022 and 2023, respectively. GMH consistently outperformed GM in weed suppression, though GM was not significantly different from no-till systems by the season’s end. Kabuli-type chickpeas under GMH had significantly higher yields than desi types. Pooled data fitted well to a three-parametric logistic curve, predicting half-time to 50% weed coverage at 35 (MM), 38 (CRM), 40 (BOH), 46 (GM), and 53 (GMH) days. Relapses of CCs were consistent in no-till systems, especially BOH and MW. Although soil properties improved, CCs alone did not significantly suppress weed. Full article

Melissa officinalis L. (Lamiaceae) is a perennial plant species widely used in the pharmaceutical and food industries, particularly valued for its sedative properties. This study investigates the impact of synthetic mulch film and planting density as two experimental factors on agronomic performance, raw material quality, and economic efficiency in lemon balm production. The experiment was conducted at three locations in Serbia (L1: Bačko Novo Selo, L2: Bavanište, L3: Vilandrica) from 2022 to 2024, using two planting densities on synthetic mulch film (F1: 8.3 plants m⁻²; F2: 11.4 plants m⁻²) and a control treatment without mulch (C). The synthetic mulch film used was a synthetic black polypropylene film (Agritela Black, 90 g/m²), uniformly applied in strips across the cultivation area, covering approximately 78% of the soil surface. The results showed consistent increases in morphological parameters and yield across the years. Plant height in F1 and F2 treatments ranged from 65 to 75 cm, while in the control it reached up to 50 cm (2022–2024). Fresh biomass yield varied from 13.4 g per plant (C) to 378.08 g per plant (F2), and dry biomass yield from 60.3 g (C) to 125.4 g (F2). The highest essential oil content was observed in F2 (1.2% in 2022), while the control remained at 0.8%. The F2 treatment achieved complete weed suppression throughout the experiment without the use of herbicides, demonstrating both agronomic and ecological advantages. Economic evaluation revealed that F2 generated the highest cumulative profit (€142,164.5) compared to the control (€65,555.3). Despite higher initial investment, F2 had the most favorable cost–benefit ratio in the long term. This study highlights the crucial influence of mulching and planting density on optimizing lemon balm production across diverse climatic and soil conditions, while also underscoring the importance of sustainable, non-chemical weed management strategies in lemon balm cultivation. Full article

The current study aimed to determine the optimum agronomic conditions—specifically sowing date and seeding density—for soybean cultivation in a temperate climate. A field experiment was conducted to evaluate three sowing dates based on soil temperature (S1—9 °C, S2—12 °C, S3—15 °C) and three seeding densities (D1—50, D2—70, D3—90 seeds·m⁻²). A field experiment was conducted in the years 2017–2019 in eastern Poland (Central Europe). Yields were strongly influenced by weather conditions. In 2019, the average yield was 2.61 Mg·ha⁻¹, making it the most favorable year, whereas 2018 was the least favorable, with an average yield of 1.41 Mg·ha⁻¹. Seeding density also affected soybean yields—the highest yield was obtained at the medium density (D2—2.36 Mg∙ha⁻¹). On the other hand, the highest thousand seed weight (159.30 g·m⁻²) was achieved at the lowest density (D1). Plant height and pod length depended on the sowing date. The tallest plants (69.96 cm) and the longest pods (4.55 cm) were obtained with early sowing (S1). The number of seeds per pod ranged from 1.8 to 2.7, with the highest values recorded in 2017, mainly with early sowing (S1) and low density (D1). It is recommended that sowing strategies be flexibly adjusted to the meteorological conditions of a given season. The findings indicate that appropriate selection of sowing parameters can significantly enhance the efficiency and stability of soybean yields under the variable climatic conditions of Poland. Full article

The agricultural sector faces significant sustainability, productivity, and environmental impact challenges. In this context, geographic information systems (GISs) have become a key tool to optimize resource management and make informed decisions based on spatial data. These data support planning the best cotton planting and harvest dates based on agroclimatic conditions, such as temperature, precipitation, and soil type, as well as identifying areas with a lower risk of water or thermal stress. As a result, cotton productivity is optimized, and costs associated with supplementary irrigation or losses due to adverse conditions are reduced. However, data from automatic weather stations in Mexico are scarce and incomplete. Instead, grid meteorological databases (DMM, in Spanish) were used with daily temperature and precipitation data from 1983 to 2020 to determine the heat units (HUs) for each cotton crop development stage; daily and accumulated HU; minimum, mean, and maximum temperatures; and mean annual precipitation. This information was used to determine areas that comply with environmental, geographic, and regulatory conditions (NOM-059-SEMARNAT-2010, NOM-026-SAG/FITO-2014) to delimit areas with agricultural potential for planting genetically modified (GM) cotton. The methodology made it possible to produce thirty-four maps at a 1:250,000 scale and a digital GIS with 95% accuracy. These maps indicate whether a given agricultural parcel is optimal for cultivating GM cotton. Full article

In order to mitigate the reduction in soybean yield caused by soil salinization, a soybean gene, GmSNF4, which promotes plant tolerance to salt–alkali stress, was identified in this study. The STRING database was used to predict the interaction between GmSNF4 and GmPKS4. The GmPKS4 gene was experimentally shown to be involved in salt–alkali stress tolerance. Firstly, the yeast two-hybrid technique and bimolecular fluorescence complementation (BiFC) technique were used to confirm the interaction between GmSNF4 and GmPKS4: the AMPK-CBM-CBS1 conserved domain was thereby determined to be the region of the GmSNF4 protein involved in the interaction. Secondly, the GmSNF4 gene was induced by salt–alkali stress according to qRT-PCR analysis, and the GmSNF4 protein was localized in the nucleus and cytoplasm. Finally, analysis of GmSNF4’s role in resistance to salt–alkali stress in transgenic soybean plants showed that transgenic lines had better phenotypic, physiological, and stress-related gene expression than non-transgenic soybeans. Thus, GmSNF4 may play a significant role in plant salt–alkali stress tolerance. Full article

Soybean is a dual-purpose crop for food and oil, playing a crucial role in China’s grain production. Seed size and weight are key agronomic traits directly influencing the yield. Cytokinin oxidases/dehydrogenases (CKXs) specifically degrade certain isoforms of endogenous cytokinins (CKs), thereby modulating plant growth and seed development. However, their role in soybeans remains largely uncharacterized. In a previous genome-wide association study of 250 soybean core germplasms, we identified GmCKX3 as a yield-related gene. To elucidate its function, we developed GmCKX3-deficient mutants using CRISPR/Cas9 gene editing in soybean Williams82 and conducted a three-year phenotypic analysis. Loss of GmCKX3 function significantly enhanced the seed size and weight, which was attributed to an increased cell size and fat accumulation in the endosperm. This enhancement was driven by elevated endogenous CK levels resulting from suppressed GmCKX3 expression. Subcellular localization revealed that GmCKX3 resides in the endoplasmic reticulum and predominantly degrades the isopentenyladenine (iP)-type CK. Integrated transcriptomic and metabolomic analyses uncovered key genes and pathways involved in CK regulation, supporting GmCKX3’s central role in seed-trait modulation. These findings advance our understanding of cytokinin-mediated seed development and offer promising targets for molecular breeding aimed at improving the soybean yield. Full article

Water and salt stresses reduce net CO₂ assimilation (A_N) primarily by restricting stomatal conductance (g_s) and mesophyll conductance (g_m), while altering leaf structure, anatomy, and cell wall composition. Although some reports observed relationships between these modifications and g_m, in others they remain less clear. Here, we compiled data on studies in which major cell wall components (cellulose; C, hemicellulose; H; pectins; P) were determined with photosynthetic, structural and anatomical features, obtaining a dataset presenting distinct species subjected to both stresses. Among parameters previously reported to affect g_m (leaf mass per area: LMA; chloroplast surface area exposed to intercellular air spaces per unit of leaf surface area: S_c/S; fraction of intercellular air spaces: f_ias; cell wall thickness: T_cw), pectins and the P/(C + H) ratio were the unique consistently varying in salt- and water-stressed plants. Despite no single trait correlated with g_m, it was positively linked with [P/(C + H) × S_c/S × f_ias]/[T_cw × Lignin × LMA] in studies in which all parameters were tested, suggesting that distinct traits may exert antagonistic influences on g_m. Although further experiments are needed to reinforce our findings, we hypothesize that increases in pectins under stress could limit larger g_m declines, improving g_m/g_s ratio and water use efficiency (WUE). Full article

Belowground buds play a vital role in the clonal propagation and structural regulation of perennial herbaceous plants, especially in alpine environments, where vegetative renewal depends heavily on bud bank dynamics. However, the interactive effects of nitrogen addition and phenological stages on bud development and aboveground branching remain poorly understood. In this study, we examined the responses of rhizome buds, tiller buds, and aboveground tiller types of Kentucky bluegrass to six nitrogen levels (0, 6, 9, 12, 15, and 18 g/m²) across five growth stages on the Qinghai–Tibet Plateau. The results showed that moderate nitrogen input (N2, 9 g/m²) significantly enhanced total bud density, particularly at the heading and maturity stages, indicating a threshold response. Aboveground reproductive tiller density peaked at N2 (9 g/m²), while vegetative and total tiller densities plateaued beyond N3 (12 g/hm²), suggesting a diminishing marginal effect of nitrogen on aboveground tiller density. Furthermore, bud density showed stage-specific correlations with tiller types: vegetative tillers were primarily influenced at the heading stage, and reproductive tillers were mainly influenced at the mature stage, with weakened associations in senescence. These findings highlight the phenological specificity and non-linear response of clonal grass regeneration to nitrogen input and provide a theoretical basis for optimizing nutrient management in cold alpine grasslands. Full article

Deubiquitination plays a pivotal role in regulating plant responses to abiotic stress, growth, and development. Among the deubiquitinase (DUB) families, ubiquitin-specific proteases (UBPs) constitute the largest group. Despite this, limited research has been conducted on the functional characteristics of the UBP gene family in soybean (Glycine max). In this study, we identified 52 UBP gene family members in soybean, all of which harbored UCH (ubiquitin C-terminal hydrolase) domains with short yet evolutionarily conserved Cys-box and His-box. These genes were phylogenetically classified into 14 distinct groups; GmUBP genes within the same group shared analogous patterns of conserved domains and motifs. Moreover, a synteny analysis reveals that the GmUBP family has undergone extensive gene duplication events and shares a close evolutionary relationship with Arabidopsis thaliana. We conducted a focused analysis on GmUBP7, which is a gene exhibiting high expression levels in soybean seeds. Intriguingly, this gene exhibited several haplotypes in natural soybean varieties, with significant differences being observed in relation to seed traits, such as 100-seed weight, total fatty acid content, and protein content among different haplotypes. Collectively, the findings from this study provide a foundation for the functional characterization of GmUBP genes, offering new insights into the regulatory network underlying seed development in soybean. Full article

The Fabaceae family, the third-largest among flowering plants, is nutritionally vital, providing rich sources of protein, dietary fiber, vitamins, and minerals. Leguminous plants, such as soybeans, peas, and chickpeas, typically contain two to three times more protein than cereals like wheat and rice, with low fat content (primarily unsaturated fats) and no cholesterol, making them essential for cardiovascular health and blood sugar management. Since the release of the soybean genome in 2010, genomic research in Fabaceae has advanced dramatically. High-quality reference genomes have been assembled for key species, including soybeans (Glycine max), common beans (Phaseolus vulgaris), chickpeas (Cicer arietinum), and model legumes like Medicago truncatula and Lotus japonicus, leveraging long-read sequencing, single-cell technologies, and improved assembly algorithms. These advancements have enabled telomere-to-telomere (T2T) assemblies, pan-genome constructions, and the identification of structural variants (SVs) and presence/absence variations (PAVs), enriching our understanding of genetic diversity and domestication history. Functional genomic tools, such as CRISPR-Cas9 gene editing, mutagenesis, and high-throughput omics (transcriptomics, metabolomics), have elucidated regulatory networks controlling critical traits like photoperiod sensitivity (e.g., E1 and Tof16 genes in soybeans), seed development (GmSWEET39 for oil/protein transport), nitrogen fixation efficiency, and stress resilience (e.g., Rpp3 for rust resistance). Genome-wide association studies (GWAS) and comparative genomics have further linked genetic variants to agronomic traits, such as pod size in peanuts (PSW1) and flowering time in common beans (COL2). This review synthesizes recent breakthroughs in legume genomics, highlighting the integration of multi-omic approaches to accelerate gene cloning and functional confirmation of the genes cloned. Full article

The plant-specific PLATZ transcription factors play crucial roles in plant growth, development, and responses to abiotic stresses. However, despite their functional significance, PLATZ genes remain poorly characterized in soybeans. In this study, we conducted a genome-wide analysis of the GmPLATZ gene family and investigated their expression profiles under salt stress. We identified a total of 29 GmPLATZ genes in the soybean genome and systematically analyzed their physicochemical properties, conserved domains, evolutionary relationships, cis-acting elements, and expression regulation patterns. Subcellular localization predictions indicated nuclear localization for most GmPLATZs, except for GmPLATZ5 and GmPLATZ14, which showed dual chloroplast–nuclear localization. A gene family expansion analysis indicated that 21 segmental duplication events were the primary driver of GmPLATZ diversification. A phylogenetic analysis classified the GmPLATZ genes into four subgroups, while gene structure and motif analyses revealed conserved zinc-binding domains and identified multiple cis-acting elements associated with light responsiveness, hormone signaling, and stress responses. Expression profiling showed tissue-specific expression patterns, with 13 GmPLATZ genes differentially expressed under salt stress, including root-preferential members (e.g., GmPLATZ1, GmPLATZ10) and leaf-preferential members (e.g., GmPLATZ8, GmPLATZ9). This study provides a theoretical basis for further investigation of GmPLATZ gene functions in soybean development and stress tolerance. Full article

Soybean cyst nematodes (SCNs) are a significant disease that causes yield loss and reducing seed quality in soybeans (Glycine max). Developing SCN-resistant soybean varieties can minimize the need for insecticide use and reduce yield loss. Cinnamate-4-hydroxylase (C4H) and laccase (Lac) are key enzymes in the lignin synthesis pathway. In this study, SCN stress significantly promoted lignin accumulation in soybean roots and upregulated the expression of lignin signaling pathway genes GmC4H (Glyma.02G236500), GmLac55 (Glyma.13G076900), and GmLac85 (Glyma.20G051900). Using Agrobacterium rhizogenes-mediated transformation, the pNI900 expression vector was introduced into the soybean cultivar Williams 82 to generate GmLac55-overexpressing plants. The overexpression of GmLac55 enhanced soybean roots resistance to SCN and inhibited the further development of J2 larvae. Our study presents a strategy for increasing SCN resistance in soybean through Agrobacterium-mediated targeted mutagenesis of the GmLac55 gene. Full article

Enhancing solar photovoltaic (PV) power generation is fundamental to achieving energy sustainability goals. However, elevated module temperatures can diminish photoelectric conversion efficiency and output power, impacting the safe and efficient operation of PV modules. Therefore, understanding module temperature distribution is crucial for predicting power generation performance and optimizing cleaning schedules in PV power plants. To investigate the combined effects of multiple factors on the temperature distribution and output power of dusty PV modules, a heat transfer model was developed. Validation against experimental data and comparisons with the NOCT model demonstrated the validity and advantages of the proposed model in accurately predicting PV module behavior. This validated model was then employed to simulate and analyze the influence of various parameters on the temperature of dusty modules and to evaluate the module output power, providing insights into sustainable PV energy generation. Results indicate that the attenuation of PV glass transmittance due to dust accumulation constitutes the primary determinant of the lower temperature observed in dusty modules compared to clean modules. This highlights a significant factor impacting long-term performance and resource utilization efficiency. Dusty module temperature exhibits a positive correlation with irradiance and ambient temperature, while displaying a negative correlation with wind speed and dust accumulation. Notably, alignment of wind direction and module orientation enhances module heat dissipation, representing a passive cooling strategy that promotes efficient and sustainable operation. At an ambient temperature of 25 °C and a wind speed of 3 m/s, the dusty module exhibits a temperature reduction of approximately 11.0% compared to the clean module. Furthermore, increasing the irradiance from 200 W/m² to 800 W/m² results in an increase in output power attenuation from 51.4 W to 192.6 W (approximately 30.4% attenuation rate) for a PV module with a dust accumulation of 25 g/m². This underscores the imperative for effective dust mitigation strategies to ensure long-term viability, economic sustainability, and optimized energy yields from solar energy investments. Full article

Industrial Internet of Things (IIoT) deployments in thermal power plants face significant energy efficiency challenges due to harsh operating conditions and device resource constraints. This paper presents gradient memory double-deep Q-network (GM-DDQN), a lightweight reinforcement learning approach for energy optimization on resource-constrained IIoT devices. At its core, GM-DDQN introduces the gradient memory mechanism, a novel memory-efficient alternative to experience replay. This core innovation, combined with a simplified neural network architecture and efficient parameter quantization, collectively reduces memory requirements by 99% and computation time by 85–90% compared to standard methods. Experimental evaluations across three realistic simulated thermal power plant scenarios demonstrate that GM-DDQN improves energy efficiency by 42% compared to fixed policies and 27% compared to threshold-based approaches, extending battery lifetime from 8–9 months to 14–15 months while maintaining 96–97% PSR. The method enables sophisticated reinforcement learning directly on IIoT edge devices without requiring cloud connectivity, reducing maintenance costs and improving monitoring reliability in industrial environments. Full article

Zinc (Zn) fertilization is widely used in maize (Zea mays L.) production to alleviate Zn deficiency and improve biomass and grain yield. However, limited research exists on Zn management in maize cultivated in high-pH paddy soils following rice-based systems, where altered soil chemistry may affect Zn availability and plant uptake. This study aimed to evaluate the effects of Zn application rates on growth, yield, and Zn uptake in two hybrid maize varieties under such conditions. Field experiments were conducted during the 2019 and 2020 dry seasons in Phetchabun Province, Thailand, using a randomized complete block design with a 4 × 2 factorial arrangement and four replications. Treatments included four Zn rates (0, 5, 10, and 20.6 kg of Zn/ha), applied as Zn sulfate monohydrate (ZnSO₄·H₂O, 36% Zn) by soil banding at the V6 stage, and two hybrid varieties, Suwan 5731 (SW5731) and Suwan 5819 (SW5819). In 2019, significant Zn × variety interactions were observed for biomass, crop growth rate (CGR), and grain yield. SW5819 at 10 kg of Zn/ha produced the highest biomass (31.6 t/ha) and CGR (25.6 g/m²/day), increasing by 15.3% and 39.1%, respectively, compared to its own no Zn treatment. In contrast, 20.6 kg of Zn/ha reduced SW5819 biomass by 6.6% and 13.1% relative to SW5731 and its own no-Zn treatment, respectively. Grain yield in SW5819 peaked at 14.7 t/ha under 5 and 10 kg of Zn/ha, significantly higher than SW5731 under 0 and 5 kg of Zn/ha by 16.7%, while SW5731 showed no significant response. In SW5819, shoot and grain Zn uptake significantly increased under 5 and 10 kg of Zn/ha by up to 36.8% and 33.3%, respectively, compared to no Zn treatment. The lowest shoot Zn uptake was found in SW5819 under 20.6 kg of Zn/ha (264.1 ± 43.9 g/ha), which was lower than all its Zn treatments and all SW5731 treatments, showing a reduction of 19.4–43.6%. Zn application improved soil Zn availability, and Zn partitioning among plant organs varied with Zn rate and season. A moderate Zn rate (10 kg of Zn/ha) optimized maize performance under high-pH, rice-based conditions, emphasizing the need for variety-specific Zn management. Full article