## 3 Technologies of Monitoring in Montado  
### Laboratory Analysis for Soil and Pasture Characterization  
The characterization of soils in agricultural fields is traditionally carried out by collecting several soil samples per hectare (always a limited number), followed by physicochemical laboratory analyses [6,78]. However, this method is limited and very expensive since it is impossible to sample the field, in addition to the great need for labor [6,79]. The spatial variability of soil nutrients can be affected by the type of soil, topography, vegetation, climate, and anthropogenic activities [79], making the traditional sampling method fallible due to the heterogeneity that may exist on the same plot of land. Traditional soil sampling and the consequent laboratory analyses are also time-consuming, expensive, and impractical from a practical perspective, leading to a growing interest in automatic monitoring methods [78]. The same authors refer to the NIR (near infrared) sensor as an excellent option for quantifying the spatial variability of the leading chemical parameters and soil fertility. [PERSON] et al. [80] conducted a study using a benchtop NIR sensor to estimate soil moisture and P in pastures in Montado. These authors obtained high correlations for the calibration (r\({}^{2}\) = 0.85 and r\({}^{2}\) = 0.777 for OM and P, respectively) of the sensor and for its validation (r\({}^{2}\) = 0.847 and r\({}^{2}\) = 0.761 for soil moisture and P, respectively). Although with benchtop NIR, no physical-chemical analysis of the soil is necessary, collecting samples in the field is still necessary, with all the inherent disadvantages already listed.  
Regarding the methods for assessing pasture biomass, they are grouped into direct and indirect [81]. Direct methods require cutting and laboratory determinations (Figure 4), while indirect methods use sensors to assess the pasture. Laboratory methods for quantifying pasture nutritive value are expensive and time-consuming, and due to the high cost of determinations, sampling is limited to specific locations, which limits the possibility of managing or exploring variability within and between pastures [7].  
According to [PERSON] et al. [56], to assess pasture quality, conventional laboratory methods have been used, such as wet chemistry, according to the \"Association of Official Analytical Chemists\" [82]. However, that methodology falls short of what is necessary and  
Figure 4: Explanatory diagram of the traditional pasture sampling and laboratory processing process.  
required from the point of view of monitoring pasture quality, considering the spatial and temporal variability of these systems. Using the NIR technique to assess pasture quality is considered reliable, especially in terms of CP and NDF [83]. However, using benchtop NIR equipment has the drawbacks already mentioned, which are inherent in the cutting and processing of pasture samples [66], although wet chemistry analyses are avoided. Therefore, the survey of the spatial and temporal variability of productivity, based on the cutting and collection of samples of pasture for bromatological analysis, is a demanding method in terms of labor [84], destructive [85], time-consuming and expensive [56; 57; 86], and unfeasible from a practical perspective, which has led to growing interest in expedited methods [7]. According to [PERSON] et al. [8], recent developments in the technological field of portable electronic sensors are an adequate response, allowing for fast, reliable, and large-scale measurements. Indirect pasture sampling methods minimized the physical removal of vegetation and were developed mainly to obtain quick results and be able to be used in large areas [87]. Therefore, it becomes imperative to use new non-destructive technologies, which allow us to better understand the variability of production in large areas and implement new production strategies, such as precision agriculture (PA), or zones of differentiated management [81].