## 1 Introduction  
Smart agriculture dates back to the 1980s when the Global Positioning System became available to the general public. Precision agriculture helps farmers to improve productivity and quality by using minimal resources such as water, fertilizer, pesticides, and seeds [1]. Soil contains a mixture of different shapes, mineralogy, and particle sizes, which has a significant effect on soil behavior. Soils can be classified based on grain size and grain size distribution [2]. Conductivity measures the potential of a material to convey an electrical charge. [PERSON] [3] and [PERSON] et al. [4] described soil electrical conductivity (ECa) as the measurement corresponding to soil properties affecting crop productivity and soil texture, drainage conditions, and organic matter content. Soil conductivity relates strongly to soil grain size and texture [4]. Because clay soils hold more moisture and have a greater surface area, ensuring more particle-to-particle contact, it is a better conductor than sand or silts [5]. Soil conductivity can be measured in the field using the physical, direct contact of four electrodes with soil or via electromagnetic induction (EMI), which uses a transmitter coil to induce a field into the soil and a receiver coil to measure the response [3]. [PERSON] et al. [6] revealed that soil electrical conductivity is directly proportional to the nutrient concentration in soil and inversely proportional to soil depth. Moreso, soil electrical conductivity reflects soil salinity, i.e., the higher the ECa value, the higher the soil salinity, and vice versa. Magnetic susceptibility (MS) refers to the physical quantity describing material properties in the external magnetic field [7, 8]. The measurement of magnetic susceptibility is important in identifying the properties, factors, and processes of soil formation, and it applies to soil mapping [9]. Magnetic susceptibility can be measured with the use of a susceptometer. It is used when magnetic measurements may not be possible and has a broad dynamic resonant frequency range based on a proximity detector oscillator [10]. Some scanning methods and tools are used, in practice, to assess soil parameters based on the measurement of soil electrical conductivity and magnetic susceptibility. ARP03 (automated resistivity profiling) is a multi-pole scanning method that uses a computer-assisted acquisition tool to produce high-resolution maps of electrical resistivity. It generates data in real-time through a distinctive global positioning system [11]. This mobile system is an effective method of characterizing agricultural subsoil and allows for the execution of continuous resistivity profiling without a fixed device. Geophilus electricus (Geophilus) is another scanning system used to map complex electrical resistivity in soils [12]. Combined with GPS, it measures complex values of electrical resistivity in terms of amplitude (electrical conductivity) and phase (soil compaction) of up to 1.5 m in depth. This system is also used to image soil layers and their geometry with depth. Another system is the Veris 3100, which is an electrode-based system that makes direct contact with soil and records measurements by pulling sensors across the field. It records two ECa measurements simultaneously using six rolling electrodes at two different depths every second [13]. Scanning methods are widely used in the determination of agricultural management zones (MZ). Sentinel-2 satellite is a valid scanning method for delineating the management zone in the milieu of precision agriculture, as additional data is not required. [PERSON] et al. [14] stated that MZ delineation can be ameliorated by integrating soil, crop, and yield information and knowledge of agronomy and climate. Satellite-derived NDVI (normalized difference vegetation index) is useful for delineating management zones. [PERSON] et al. [15] stated that the stability of soil chemical properties (pH, P, K, and Mg) that can be used for stratified soil sampling is due to management zone delineation.