Wheat (Triticum aestivum L.) is a major cereal crop essential for global food security, yet its productivity is severely constrained by diverse diseases caused by fungi, bacteria, viruses, and nematodes. These pathogens reduce yield, grain quality, and farmer income, particularly under favorable environmental conditions. Major fungal diseases such as rusts and Fusarium head blight, bacterial leaf streak, Karnal bunt, viral mosaic diseases, and cereal cyst nematodes significantly affect production worldwide. This manuscript reviews major wheat diseases, their symptoms, and impact, and presents a general methodological framework for disease assessment and management to ensure sustainable wheat production under changing climatic conditions.

The rapid growth of the digital era has resulted in the generation of huge and complex datasets from sectors such as healthcare, agriculture, environmental monitoring, finance, and social media. This has led to the emergence of Big Data, commonly characterized by the five V?s: volume, velocity, variety, veracity, and value. However, data alone cannot provide meaningful knowledge without proper analysis. Statistics plays a crucial role in Big Data by offering systematic tools for organizing, modeling, and interpreting large-scale datasets. Statistical techniques such as regression analysis, hypothesis testing, clustering, factor analysis, and predictive modeling help in identifying patterns, relationships, and trends, thereby supporting evidence-based decision-making. Modern tools including R, Python, SPSS, SAS, Apache Spark, Tableau, and Power BI enhance the processing and visualization of Big Data. Despite its benefits, challenges such as computational complexity, storage issues, privacy risks, and ethical concerns remain significant. Future developments must focus on scalable and transparent analytical methods for sustainable Big Data applications.

Streptococcal infections are among the most destructive bacterial diseases affecting aquaculture worldwide, particularly in warm-water fish such as Nile tilapia (Oreochromis niloticus). Despite long-term dependence on antibiotics, streptococcosis continues to cause recurrent outbreaks, high mortality, and severe economic losses. The persistence of this disease is largely attributed to pathogen diversity, virulence variation, host?pathogen interaction, and the emergence of antibiotic-resistant strains. Recent advances in genomic and proteomic studies have provided critical insights into the adaptive mechanisms and virulence determinants of fish-pathogenic Streptococcus spp. This article reviews the epidemiology, pathogenesis, genomic characterization, and current challenges in the management of streptococcal infections in aquaculture systems.