Decision Agriculture

In this chapter, the latest developments in the field of decision agriculture are discussed. The practice of management zones in digital agriculture is described for efficient and smart faming. Accordingly, the methodology for delineating management zones is presented. Modeling of decision support systems is explained along with discussion of the issues and challenges in this area. Moreover, the precision agriculture technology is also considered. Moreover, the chapter surveys the state of the decision agriculture technologies in the countries such as Bulgaria, Denmark, France, Israel, Malaysia, Pakistan, United Kingdom, Ukraine, and Sweden. Finally, different field factors such as GPS accuracy and crop growth are also analyzed

On the Description of Soil Variability Through EMI Sensors and Traditional Soil Surveys in Precision Agriculture

In Precision Agriculture electromagnetic induction (EMI) sensors are generally used to obtain soil electrical conductivity (EC) maps for the delineation of homogeneous management zones (MZ). EC measurements are related to many physical-chemical soil properties and, moreover, are average values referred to the soil depth explored by the sensor. Consequently, the following questions arise: how reliable are EC measurements to describe soil variability, compared to the data provided by a pedological survey? To which extent MZs correspond to pedological units in a soil map? Texture analysis was conducted on 38 soils samples collected at three depths with a manual auger in a rice farm (province of Pavia, Italy) characterized by sandy-loamy soils. Four pedological units were recognized, mainly based on differences in clay content distribution with depth. Four MZs were recognized from the EC maps. MZ and pedological soil maps showed similar spatial distributions of soil types, particularly at field scale. However, at the farm scale, different MZs may correspond to the same pedological unit, because of the different soil properties to which the two classification approaches are sensitive: clay contents for pedological soil mapping, and sand contents for MZ mapping. Finally, ANOVA was carried out to evaluate the statistical significance of this result