Cotton Genomics and Genetics 2025, Vol.16, No.2, 48-56 http://cropscipublisher.com/index.php/cgg 49 phenology, and yield at various scales. For instance, the use of Landsat 8 and other satellite technologies allows for the prediction and mapping of cotton lint yield by analyzing crop indices such as NDVI and other vegetation indices (Haghverdi et al., 2018; Sishodia et al., 2020). Remote sensing facilitates the application of variable rate technologies (VRT) by providing high-resolution images that inform precise input applications, such as fertilizers and water, thereby optimizing resource use and enhancing yield (Filintas et al., 2022). 2.2 GPS-guided machinery and variable rate technology (VRT) GPS-guided machinery and VRT are integral to precision agriculture, offering precise control over agricultural inputs. These technologies enable site-specific crop management by applying inputs like seeds, fertilizers, and water according to field variability. The integration of GPS with automatic controllers and sensors allows for the precise application of inputs, which is crucial for optimizing cotton yield and reducing environmental impact (Ali et al., 2024). Studies have shown that precision agriculture techniques, including VRT, can lead to significant increases in crop yield and reductions in water and fertilizer usage, highlighting their effectiveness in sustainable farming practices. 2.3 Internet of things (IoT) and sensor networks The internet of things (IoT) and sensor networks are transforming precision agriculture by providing real-time data on environmental conditions, crop health, and soil quality. IoT devices equipped with optical sensors can monitor critical indicators such as temperature, humidity, and chlorophyll content, which are essential for maintaining optimal growing conditions for cotton (Saha et al., 2023; Durai et al., 2024). These sensors transmit data wirelessly to central servers for analysis, enabling predictive analytics and informed decision-making regarding irrigation, pest management, and fertilizer application (Figure 1) (Alahmad et al., 2023). The use of IoT and wireless sensor networks enhances the efficiency of precision agriculture by reducing labor costs and increasing productivity (Shafi et al., 2019; Sanjeevi et al., 2020). Figure 1 Sensing technologies and their applications in agriculture (Adopted from Alahmad et al., 2023) 3 Data Analytics and Decision Support Systems (DSS) 3.1 Big data integration from multiple sources In precision agriculture, the integration of big data from various sources is crucial for optimizing crop yield and resource management. The use of unmanned aerial systems (UAS) and IoT sensors allows for the collection of real-time data on crop growth, soil conditions, and environmental factors. This data is then integrated into decision
RkJQdWJsaXNoZXIy MjQ4ODYzNA==