Bioscience Evidence 2024, Vol.14, No.6, 260-269 http://bioscipublisher.com/index.php/be 261 enhance soybean yield. The research focuses on investigating the effectiveness of sensor-based nutrient and irrigation management, integrating physiological principles with environmental data to optimize farm management, and identifying practical solutions to improve soybean productivity. Ultimately, this study aims to contribute to global food security and promote sustainable farming practices. 2 Precision Agriculture Technologies for Soybean 2.1 Overview of precision agriculture Precision agriculture involves the use of advanced technologies to monitor and manage field variability in crops, aiming to optimize returns on inputs while preserving resources. This approach includes the use of GPS, GIS, remote sensing, and various sensors to collect data on soil and crop conditions, which can then be used to make informed decisions about planting, fertilizing, and irrigating crops (Hedley, 2015; Smidt et al., 2016). The goal is to enhance crop productivity and resource-use efficiency, ensuring sustainable agricultural practices (Figure 1). Figure 1 Precision tillage of soybean crops (Photo credit: Yuting Zhong) 2.2 GPS and GIS technologies in soybean farming GPS and GIS technologies are fundamental to precision agriculture, providing accurate location data and spatial analysis capabilities. These technologies enable farmers to create detailed maps of their fields, showing variations in soil properties, crop health, and yield. This spatial information allows for site-specific management practices, such as variable rate seeding and fertilization, which can optimize input use and improve crop yields (Hedley, 2015; Smidt et al., 2016). The integration of GPS with variable rate technology (VRT) has enabled precise application of inputs, reducing waste and increasing efficiency. 2.3 Remote sensing and drones for yield monitoring Remote sensing technologies, including the use of drones, have revolutionized yield monitoring in soybean farming. Drones equipped with multispectral and hyperspectral sensors can capture high-resolution images of fields, providing valuable data on crop health and growth stages. This data can be used to estimate yields accurately and identify areas needing attention (Eugenio et al., 2020; Skakun et al., 2021; Ren et al., 2023). Machine learning algorithms further enhance the predictive power of remote sensing data, allowing for more precise yield estimations and better decision-making (Maimaitijiang et al., 2020). 2.4 Soil sensors and variable rate technology (VRT) Soil sensors play a crucial role in precision agriculture by providing real-time data on soil moisture, nutrient levels, and other critical parameters. This information is essential for implementing variable rate technology (VRT),
RkJQdWJsaXNoZXIy MjQ4ODYzMg==