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The aim of this study was to compare three different soil-sampling methods used in Precision Agriculture and their environmental impact on agricultural production. The sampling methods used were: zone management by elevation, grid sampling (GS) and sampling oriented by apparent soil electrical conductivity (OS). Three different fields were tested. When the recommendations were compared, a significant difference among the suggested doses was observed. This indicated the need to improve the soilsampling techniques, since there were doubts about input deficits or overdoses, regardless of the technology studied. The GS method was the most environmentally viable alternative for phosphorus (P) compared to other methods and the OS presented as the better option for potassium (K) and nitrogen (N). However, the use of soil sensors appeared to be a viable technology that needs further improvement in order to improve productivity and, hence, economic and environmental benefits. Introduction Although the modest technological availability, precision agriculture (PA) is a modern concept of agricultural management (Pierpaoli et al., 2013). It is considered one of the ten greatest revolutions in agriculture (Crookston, 2006), as it provides for more reliable decision-making (Pierce and Nowak, 1999), affords more accurate fertiliser application, and, therefore, production cost savings (Catania et al., 2020). Also, it creates opportunities for intensive data collection, provides accurate tracking and production adjustments, and allows management zones to be defined for customized input administration (Mulla, 2013). According to Gomes and Barizon (2014) both people and the environment can be damaged severely by the misuse of compounds, such as (N), (P), (K); these fertilizers usually reach the water bodies due to soil accumulation and end up in streams and rivers (Simplício, 2015). As described by Artuzo (2015), only 17.28% of farmers understand the need for environmental improvement by reducing the use of fertilizers, which is becoming a relevant issue. Therefore, agricultural production and the risk of environmental contamination can be optimized by implementing PA (Ragagnin et al., 2010; Sanchez et al., 2012), thus avoiding the use of excessive doses of nutrients, which would leach or end in water bodies (Klein and Agne, 2012; Vargas, 2012; Biesdorf et al., 2016). Silva (2009) found that the rational use of fertilizers in PA makes it possible to reduce pollution by up to 73% and costs by up to 71%. An integrated management of nutrients promotes sustainable production and, consequently, the protection of the environment (Zhang et al., 2010). Celinski (2008) evaluated the need to search for new technologies aimed at reducing production costs and negative environmental impacts. In this context, PA shows a direct relationship between economic gain and environmental benefit with the efficient use of agricultural inputs (Costa and Guilhoto, 2013). However, few studies evaluated the positive impacts of PA on the environment. This situation can be considered alarming, since Brazil is the largest fertilizer consumer worldwide (Beras, 2014), and the overuse of fertilizers is directly related to the environmental impacts of agriculture (Mulla, 2013; Artuzo, 2015). In order to refine management practices and evaluate agricultural effects, it is crucial to understand the spatial variability of soil properties, which is a relevant factor in a production system aimed at sustainability through site-specific management (Ferraz et al., 2019). Moreover, spatial characteristics allow us to quantify several natural phenomena (Wang et al., 2018). Studies conducted Correspondence: Daniele Sarri, Department of Agricultural, Food, Environment and Forestry (DAGRI), Biosystem Engineering Division, University of Florence, Piazzale delle Cascine 15, 50144 Florence,

Comparative analysis of soil-sampling methods used in precision agriculture