Spatial variability of soil pH sampled by two methodologies used in precision agriculture in farms under crop rotation

Abstract

This study aimed to characterize the spatial variability of pH in soils of two farms in the state of Paraná, Brazil, based on two different sampling methods used in precision agriculture, by means of geostatistical analyzes. The first method of sampling the pH grid consisted in the collection of soil samples by the traditional method (1 point / ha). The second method of pH determination was by on-the-go soil sensor (200 points / ha). The spherical model was better suited to most semivariograms, regardless of the sampling method. After adjusting the semivariograms for soil pH determination methods, thematic maps were made using normal kriging. The best spatial distribution of pH was obtained where the attribute was sampled by the on-the-go sensor. The number of pH samples collected and the sampling method influenced the visual representation of pH variability.

Land suitability for irrigation of small reservoirs using spatial techniques in the upper regions of Ghana

“…Studies have revealed that the higher nugget values (0 to 1) are, the smoother and more accurate the layers, but some nugget values in this study were outside the limit; hence, the RMSE was used (Clark, 2010). Additionally, research has reported that RMSE values close to 1 suggest higher accuracy (Benoit et al, 2019; Ferraz et al, 2019; Setianto & Triandini, 2015). From Table 6, it can be seen that RMSE values range from 0.513 to 1.303, indicating acceptable levels of accuracy on the individuals, suggesting that these layers are recommendable for further analysis.…”

“…However, some crops may need to be tolerant to specific soil properties such as pH, which are not always favourable for diverse cropping. For instance, ideal soil conditions for growing rice include relatively low pH levels that ensure optimal soil submergence while being sufficient to keep salt, harmful ion and reduction product levels low (Ferraz et al, 2019).…”

Comparative analysis of soil-sampling methods used in precision agriculture

“…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).…”

“…Zhang et al (2010) stated that the knowledge of spatial distribution associated with the definition of management zones through regionalized maps could result in a more efficient application of agricultural fertilizers, a reduction of input costs, an optimized use of fertilizers as well as economic and environmental gains. Management zones could also be defined by soil electrical conductivity sensors (Mallarino and Wittry, 2004), which are already available to farmers (Ferraz et al, 2019). According to Mulla (2013), the use of high technology, such as soil sensors to optimize the use of fertilizer, appears a viable alternative to promote the mitigation of increasing environmental pollution .…”