Foliar Application of a Mixture of Amino Acid-Based Growth Promoters Enhances Tomato Seedling Production

Horticulturae, Год журнала: 2025, Номер 11(6), С. 582 - 582

Опубликована: Май 24, 2025

A mixture of amino acids, including aspartic acid, arginine, glycine, and tryptophan, can effectively promote tomato seedling growth. This research aimed to evaluate how the foliar spraying an acid mixture, applied at various doses intervals, influences growth seedlings in a traditional seedbed. An experiment was conducted field, with treatments distributed factorial arrangement (3 × 2) completely randomized block design five replications. The parameters were improved by combining three (0.25, 0.50, 0.75 L ha−1 as VIUSID® agro) two application intervals (weekly biweekly). Results indicated that 0.25 weekly enhances stem thickness, length, root leaf area index, root, shoot, total dry biomass accumulation. Therefore, investing production robust high-quality lead establishment, faster development, reduced losses, earlier higher yields. discovery indicates using low acids could be effective environmentally friendly option for improving seedbed conditions.

Язык: Английский

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AI-Based Deep Learning of the Water Cycle System and Its Effects on Climate Change

Fractal and Fractional, Год журнала: 2025, Номер 9(6), С. 361 - 361

Опубликована: Май 30, 2025

This study combines artificial intelligence (AI) with mathematical modeling to improve the forecasting of water cycle mechanism. The proposed model simulates development global temperature, precipitation, and availability, integrating key climate parameters that control these dynamics. Using a system fractional-order differential equations in fractal–fractional sense derivatives, captures interactions between solar radiation, greenhouse effect, evaporation, runoff. deep learning framework is trained on extensive datasets, allowing it refine predictions identify complex patterns within cycle. By applying AI techniques alongside modeling, this procedure provides valuable insights into change resource administration. model’s can contribute assessing future states, optimizing environmental policies, designing sustainable management strategies. Furthermore, hybrid methodology improves decision-making by offering data-driven solutions for adaptation. findings illustrate effectiveness AI-driven models addressing challenges improved precision.

Язык: Английский

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Effects of drought on morpho-physiological attributes and secondary metabolites of wheat genotypes: Growth traits, seed yield and stress tolerance indices

South African Journal of Botany, Год журнала: 2024, Номер 171, С. 425 - 446

Опубликована: Июнь 25, 2024

Язык: Английский

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Transcriptomic and Metabolomic Analyses Reveal the Response to Short-Term Drought Stress in Bread Wheat (Triticum aestivum L.)

Agronomy, Год журнала: 2024, Номер 14(4), С. 704 - 704

Опубликована: Март 28, 2024

Drought stress, a major abiotic significantly affects wheat (Triticum aestivum L.) production globally. To identify genes and metabolic pathways crucial for responding to short-term drought we conducted transcriptomic metabolomic analyses of winter cultivar Jimai 418 at four developmental stages: jointing (GS31), booting (GS45), anthesis (GS65), 8 days after (DAA8). Transcriptomic analysis identified 14,232 differentially expressed (DEGs) under stress compared the control. Specifically, 1387, 4573, 7380, 892 DEGs were stages, respectively. Enriched associated with these included plant hormone signal transduction, mitogen-activated protein kinase (MAPK) signaling, galactose metabolism, starch sucrose metabolism. Totals 222, 633, 358, 38 accumulated metabolites (DAMs) Correlation both datasets revealed DAMs arginine proline ABC transporters, amino acid biosynthesis. These findings offer significant insights into 418’s molecular response stress. The DEGs, DAMs, enriched contribute our understanding tolerance. This research will facilitate further investigations tolerance mechanisms guide breeding varieties enhanced resistance.

Язык: Английский

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Genotypic Selection Using QTL for Better Productivity under High Temperature Stress in Tomato (<em>Solanum lycopersicum</em> L.)

Опубликована: Июнь 21, 2024

High temperature stress affects tomato production both in tropical and sub-tropical environments worldwide. To explore genetic variation for heat tolerance tomato, 329 transcontinental varieties were evaluated at The Ministry of Municipality Environment (MME) greenhouses near Doha, Qatar. Preliminary phenotypic analysis identified a diverse set 71 hybrid pure line more detailed studies. selected subset was examined the greenhouse randomized complete block design under stress. materials phenotyped fruit size, weight, hardness, locules, (%), total soluble solids (TSS), yield. Significant differences among genotypes observed all traits assessed. basis genotyped using 104 SNP markers previous genome wide association studies (GWAS). Nineteen QTL associated could reliably select tolerant terms better yield, set, TSS. These are located on Chromosome 1, 5, 6, 8, 9, 12. Interestingly, two clusters chromosome 6 linked to significant effects TSS high temperature. Some within these regions also reported as with other Eighteen out nineteen mapped gene body. Based genotypic analysis, an elite five approval findings have significance not only Qatar, but they valuable wider application locations 19 presented here be adopted by breeders marker-assisted selection (MAS) tolerance.

Язык: Английский

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