Drought stress threatens agriculture and food security, significantly impacting soybean yield and physiology. Despite the documented role of nanosilica (n-SiO₂) in enhancing crop resilience, its full growth-cycle effects on soybeans under drought stress remain elusive. This study aimed to evaluate the efficacy of n-SiO₂ at a concentration of 100 mg kg⁻¹ in a soil medium for enhancing drought tolerance in soybeans through a full life-cycle assessment in a greenhouse setup. To elucidate the mechanisms of n-SiO₂ action, key physiological, biochemical, and yield parameters were systematically measured. The results demonstrated that n-SiO₂ significantly increased silicon content in shoots and roots, restored osmotic balance by reducing the Na⁺/K⁺ ratio by 40%, and alleviated proline accumulation by 35% compared to the control, thereby mitigating osmotic stress. Enzyme activities related to nitrogen metabolism, including nitrate reductase (NR) and glutamine synthetase (GS), improved by 25–30% under n-SiO₂ treatment compared to the control. Additionally, antioxidant activity, including superoxide dismutase (SOD) levels, increased by 15%, while oxidative stress markers such as hydrogen peroxide (H₂O₂) and malondialdehyde (MDA) decreased by 20–25% compared to the control. Furthermore, yield components were significantly enhanced, with pod number and grain weight increasing by 15% and 20%, respectively, under n-SiO₂ treatment compared to untreated plants in drought conditions. These findings suggest that n-SiO₂ effectively enhances drought resilience in soybeans by reinforcing physiological and metabolic processes critical for growth and yield. This study underscores the potential of n-SiO₂ as a sustainable amendment to support soybean productivity in drought-prone environments, contributing to more resilient agricultural systems amidst increasing climate variability. Future research should focus on conducting large-scale field trials to evaluate the effectiveness and cost-efficiency of n-SiO₂ applications under diverse environmental conditions to assess its practical viability in sustainable agriculture.

Soybean is a vital crop globally and a key source of food, feed, and biofuel. With advancements in high-throughput technologies, soybeans have become a key target for genetic improvement. This comprehensive review explores advances in multi-omics, artificial intelligence, and economic sustainability to enhance soybean resilience and productivity. Genomics revolution, including marker-assisted selection (MAS), genomic selection (GS), genome-wide association studies (GWAS), QTL mapping, GBS, and CRISPR-Cas9, metagenomics, and metabolomics have boosted the growth and development by creating stress-resilient soybean varieties. The artificial intelligence (AI) and machine learning approaches are improving genetic trait discovery associated with nutritional quality, stresses, and adaptation of soybeans. Additionally, AI-driven technologies like IoT-based disease detection and deep learning are revolutionizing soybean monitoring, early disease identification, yield prediction, disease prevention, and precision farming. Additionally, the economic viability and environmental sustainability of soybean-derived biofuels are critically evaluated, focusing on trade-offs and policy implications. Finally, the potential impact of climate change on soybean growth and productivity is explored through predictive modeling and adaptive strategies. Thus, this study highlights the transformative potential of multidisciplinary approaches in advancing soybean resilience and global utility.

Cullins are crucial components of the ubiquitin–proteasome system, playing pivotal roles in the regulation of protein metabolism. This review provides insight into the wide-ranging functions of cullins, particularly focusing on their impact on plant growth, development, and environmental stress responses. By modulating cullin-mediated protein mechanisms, researchers can fine-tune hormone-signaling networks to improve various agronomic traits, including plant architecture, flowering time, fruit development, and nutrient uptake. Furthermore, the targeted manipulation of cullins that are involved in hormone-signaling pathways, e.g., cytokinin, auxin, gibberellin, abscisic acids, and ethylene, can boost crop growth and development while increasing yield and enhancing stress tolerance. Furthermore, cullins also play important roles in plant defense mechanisms through regulating the defense-associated protein metabolism, thus boosting resistance to pathogens and pests. Additionally, this review highlights the potential of integrating cullin-based strategies with advanced biological tools, such as CRISPR/Cas9-mediated genome editing, genetic engineering, marker-associated selections, gene overexpression, and gene knockout, to achieve precise modifications for crop improvement and sustainable agriculture, with the promise of creating resilient, high-yielding, and environmentally friendly crop varieties.

Adonis amurensis Regel et Radde is a remarkable and important spring ephemeral plant and gained considerable attention because of its remarkable medicinal properties. Extensive research has been conducted on its therapeutic applications, physical characteristics, flowering patterns, reproductive, cultural and molecular biology. However, there is a lack of comprehensive understanding regarding the metabolic changes associated with flower developmental stages. This study was designed to investigate the changes in metabolites and their interrelationships at five distinct developmental stages of A. amurensis flower: Flower Primordium (FP), Sepal Stage (SE), Perianth Primordium (PE), Stamens Stage (SE), and Pistil Stage (PI). High-performance liquid chromatography coupled with mass spectrometry (HPLC-MS) was utilized to investigate and characterize the metabolites associated with specific flower developmental stages. The various stages of flower development exerted a substantial influence on both the quantity and composition of metabolites present, signifying significant changes in the types and quantities of metabolites throughout the developmental progression of the flower. Metabolite Set Enrichment Analysis (MSEA) and annotation via the KEGG database highlighted enriched pathways such as flavonoid biosynthesis and plant hormone signal transduction, which are crucial for flower maturation. The highest number of differentially expressed metabolites was identified between the SE and PI stages, emphasizing a marked appreciation in metabolite expression linked to the development of reproductive organs. Key pathways such as flavonoid biosynthesis and plant hormone signal transduction were markedly enriched, underscoring their roles in flower maturation and potential pharmacological applications. Our research not only helps us in understanding the metabolomic dynamics during the flower development of A. amurensis but also emphasizes the potential pharmacological implication of stage-specific metabolites. Identifying these metabolites can help targeted bioprospecting and optimization of extraction methods to tackle the plant’s full therapeutic potential, particularly in the development of treatments for cardiac insufficiency, edema, and possibly cancer.