Bioscience Method 2024, Vol.15, No.2, 58-65 http://bioscipublisher.com/index.php/bm 62 4.2 Technological accessibility and affordability While the development of novel sensors and remote sensing techniques offers instantaneous and effective disease detection, the accessibility and affordability of such technologies are critical for widespread adoption by farmers. The use of support vector machines (SVM) for detecting sugarcane borer diseases demonstrates the potential for technology to reduce labor and misjudgment in disease detection. However, the cost and complexity of these technologies must be considered to ensure they are accessible and affordable for farmers, particularly in less developed agricultural settings. 4.3 Data management and decision support systems The implementation of machine learning algorithms and deep learning frameworks for sugarcane disease detection generates a significant amount of data that must be managed efficiently (Srivastava et al., 2020). The use of IoT for disease detection in sugarcane leaf further emphasizes the need for robust data management systems that can handle the information collected from sensor nodes. Decision support systems that can process this data and provide actionable insights are essential for farmers to make informed decisions regarding disease management. Transfer learning approaches to sugarcane foliar disease classification and the development of mobile applications for disease detection are examples of how technology can aid in data management and decision-making processes (Daphal and Koli, 2021). Figure 1 Optical sensing technologies for plant viral disease detection can be classified by their platform and associated spatial resolution and extent (Adopted from Wang et al., 2022) Image caption: Sensors also vary by band position, the spectral range within the whole electromagnetic spectrum (Adopted from Wang et al., 2022) In conclusion, the integration of technology in sugarcane disease detection and management involves a multifaceted approach that includes educating farmers, ensuring the accessibility and affordability of technologies, and implementing effective data management and decision support systems. These components
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