Akademik Veri Yönetim Sistemi
Empowering Wheat Cultivation with GIS, Digital Approaches and Artificial Intelligence, Springer International Publishing Ag, ss.105-124, 2025
The advancement of wheat breeding is crucial to meeting the increasing global food demand, and integrating high-throughput phenotyping (HTP) with genomic approaches represents a transformative strategy for achieving precise wheat improvement. This chapter explores the multifaceted role of HTP technologies, including unmanned aerial vehicles (UAVs), imaging sensors, and satellite imagery, in enhancing phenotypic data acquisition. By utilizing various imaging techniques, such as RGB, multispectral, thermal, and hyperspectral sensors, breeders can capture detailed physiological traits, enabling more informed selection decisions. Coupled with genomic approaches, such as next-generation sequencing, quantitative trait loci mapping, and genome-wide association studies, the synergy between these methodologies significantly enhances prediction accuracy and optimizes complex traits, including drought resistance and yield potential. By harnessing big data and machine learning, breeders can analyze vast datasets to refine breeding strategies and improve varietal development efficiency. The comprehensive examination of these cutting-edge technologies highlights the critical need for collaborative efforts in wheat research aimed at developing resilient varieties capable of thriving under changing climate conditions. Overall, this chapter underscores the promise of combining HTP and genomics to revolutionize precision wheat breeding and contribute to sustainable food security.