**2. Precision agriculture**

PA is an innovative production system that is accomplished through the measurement of crop production variables coupled with the application of information technologies. Multiple terms have been coined by researchers to describe the application of PA practices to modern farming. The application of PA practices is sometimes termed "precision farming," "site-specific farming," "site-specific management," "spatially variable crop production," "grid farming," "technology-based agriculture," "smart farming," "satellite farming," and so on. The National Research Council [37] defined PA as "a management strategy that uses information technologies to bring data from multiple sources to bear on decisions associated with crop production." According to Olson [32], who proposed a complete definition of PA is "the application of a holistic management strategy that uses information technology (IT) to bring data from multiple sources to bear on decisions associated with agricultural production, marketing, finance, and personnel [32]." More simply defined, PA is a farming concept that utilizes GIS to map in-field variability to maximize the farm output via optimal use of inputs [34].

#### **Figure 2.** *Major components of PA.*

PA encompasses the integrated use of GIS and GNSS tools to provide detailed information on crop health and soil variability [38]. It combines sensors, IT tools, machinery, and informed management decisions to enhance and optimize agricultural productivity by accounting for in-field variability and uncertainties within agricultural systems [6]. The primary goal of PA is to enhance sustainable soil and crop management of the farm by utilizing resources to increase food production and long-term profitability while reducing variable costs and environmental contamination. The specific purposes of PA are, therefore, to i) increase farm profitability, ii) enhance production, iii) reduce investment, iv) reduce soil erosion, v) reduce the environmental impact of fertilizer and pesticides, and vi) manage large farms in an environmentally sensible manner [32, 39]. PA has mainly three major components, namely: i) information, ii) technology, and iii) management (**Figure 2**). Thus, PA can be accomplished by recording data at an appropriate scale and frequency, proper interpretation and analyses, and finally, generation of actionable management decisions to implement at an accurate scale and time [37].

Several "Rs" (R stands for right) are recognized in PA, especially for nutrient stewardship that optimizes maximum crop yield and reduces nutrient losses. PA encompasses the optimum management of production inputs by implementing three "Rs": the Right time, the Right amount, and the Right place [40]; four "Rs" [41] which includes an additional R, the Right source and five "Rs" [42] which described an additional R, the Right manner in addition to the earlier four "Rs". The "Rs" applied to nutrient stewardship in PA directs farmers to place optimum nutrients in the root zones and make them available for crops when needed. PA involves better management of crop production inputs such as fertilizers, seeds, pesticides, herbicides, and machinery fuel by implementing the right management practice at the right place and time [43].

### **3. Importance of precision agriculture**

PA is an approach for managing farms with the help of IT that improves the efficiency, productivity, and profitability of agriculture. PA can maximize land use, reduce the usage of inputs, and optimize crop management, resulting in healthier

#### *Precision Agriculture for Sustainable Soil and Crop Management DOI: http://dx.doi.org/10.5772/intechopen.101759*

crops and increased crop yield [35]. Technological advances are transforming agriculture as producers see many benefits from its innovation. Technologies such as GNSS guidance, autonomous tractors, agricultural drones, GIS, sensors, and software are assisting farmers to be more efficient than ever before [12, 38, 44, 45]. These technological advances help farmers specify the exact inputs and quantitates, and precisely where to apply, to produce better crops, more food, and save resources. Robert [46] alluded that "PA is not just the injection of new technologies, but it is rather an information revolution, made possible by new technologies that result in a higher level, a more precise farm management system."

Precision technologies precisely control various field operations required for crop production. PA advocates the need for precise agricultural input management in an environmentally sensible manner, which is consistent with the long-term sustainability of production agriculture [5, 24, 36]. Nevertheless, a farmer's understanding of the within-field variability is essential. In conventional farming systems, farmers generally apply inputs such as fertilizer and pesticides uniformly to the whole field. They rarely think about spatial variations due to soils types, electrical conductivity (EC), soil moisture content (MC), pH, and nutrient availability. Further, the spatial variability of soil across the fields can be caused by land topography, soil texture, and historical management practices such as cropping patterns, crop rotations, soil fertility programs, and soil compaction over the years [47]. The use of "blanket doses" of valuable inputs results in a portion of those inputs never being used by plants. This results in an increase in production costs of the farm while causing environmental pollution. In the U.K., considerable differences in the spatial patterns and magnitudes of crop yield variation were reported even in uniformly managed fields due to soil variability, rainfall, and field operations [15]. PA technologies assist in quantifying and managing spatial variability of soils by developing site-specific management zones (SSMZs), which subdivide the field by treatment regiments. Therefore, precise crop input management enhances nutrient use efficiency, especially environmentally sensitive macro- and micronutrients, particularly N [24, 48]; while maximizing farm output and profitability [32, 39].
