Abstract
ABSTRACT In agricultural areas with a historical of systematic soil sampling, alternative methodologies such as directed sampling design based on management zones (MZ) have been proposed to reduce sampling costs. The aim of this study was to evaluate the technical and economic impacts of replacing a dense systematic soil sampling design (cell size of 0.5 ha) by a systematic sampling with a smaller number of samples (cell size ranging from 1 to 4.5 ha), directed or conventional sampling design on the mapping of soil plant-available phosphorus (P), exchangeable potassium (K), and pHwater. The study was carried out in an agricultural area of 120 ha with soil classified as an Oxisol. The directed sampling designs were based on MZ delimited from data of elevation and overlapping of crop yield maps. Our finding revealed that systematic samplings with grids larger than 2 ha were not efficient to detect the spatial variability of soil P, K and pHwater. Larger systematic grid sizes, directed and conventional sampling design resulted in more generalist thematic maps, losing information about spatial variability of the soil attributes. Thus, from a technical point of view, soil sampling designs with a low density were little efficients, particularly for mapping P and K, due to their higher spatial variability. However, because soil P and K contents were close to or above critical levels and soil acidity was low (average pH close to 5.5), the different sampling designs presented little influence on fertilizer and liming recommendations. Therefore, we concluded that systematic soil sampling design may be replaced by soil sampling directed based on MZ or even by conventional sampling in soils with high fertility to reduce sampling costs. Nevertheless, crop responses must be monitored to validate fertilization management based on these simplifications on soil sampling procedure.
Highlights
Soil fertility management has been performed based on conventional soil sampling design, which does not consider the spatial variability of soil attributes (CQFS-RS/SC, 2016)
The mean values of P and K at all sampling schemes were close to 13 and 190 mg dm−3, respectively (Table 1), being classified as high and very high by CQFS/RS-SC (2016). These results showed that the different sampling designs would not result in significant differences in the fertilizers recommendations, if fixed rates were applied
Our results were in accordance with those reported by Cherubin et al (2015), who concluded that grids with smaller cell sizes and larger number of samples allowed detecting subareas with soil P and K contents very low, which may potentially reduce crop yields
Summary
Soil fertility management has been performed based on conventional soil sampling design, which does not consider the spatial variability of soil attributes (CQFS-RS/SC, 2016). Geo-referenced soil sampling for recognizing the spatial variability of soil attributes and application of variable rates of fertilizers and correctives has been widely adopted in Brazil (Corá & Beraldo, 2006, Soares Filho & Cunha, 2015, Baio et al, 2017). Soil fertility mapping can optimize the use of agricultural inputs, increase crop yield, promote higher profitability for farmers and mitigate environmental impacts derived from agriculture (Mallarino & Wittry, 2004, Baio et al, 2017). Systematic soil sampling by grid sampling is the most widespread methodology for mapping soil fertility attributes (Cherubin et al, 2016).
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