Abstract
This research studies the effect of stratifying soil samples to try and find a suitable depth to establish a geospatial relationship for a practical soil sampling grid in New Zealand hill country. Cores were collected from 200 predetermined sites in grids at two trial sites at “Patitapu” hill country farm in the Wairarapa, New Zealand. Trial 1 was a 200 m × 100 m grid located in a gently undulating paddock. Trial 2 was a 220 m × 80 m grid located on a moderately sloped paddock. Each grid had cores taken at intervals of 5 m, 10 m, or 20 m. Core sites were mapped out prior to going into the field; these points were found using a Leica Geo Systems GS15 (real time kinematic GPS) and marked with pigtail pegs and spray-paint on the ground. Cores were taken using a 50 mm-diameter soil core sampler. Cores were cut into three sections according to depth: A—0–30 mm, B—30–75 mm, and C—75–150 mm. Olsen P lab results were obtained for half of the total 1400 samples due to financial constraints. The results indicate that there was a significant decrease in variability from Section A to Section B for both trials. Section B and C for Trial 1 had similar variability, whereas there was another significant drop in variability from Section B to C in Trial 2. Measuring samples below the top 3 cm appeared to effectively reduce noise when sampled from 3 to 15 cm. However, measuring from 7.5 cm to 15 cm on the slope in Trial 2 reduced variability so much that all results were almost identical, which may mean that there is no measurable representation of plant available P. The reduction in noise by removing the top 3 cm of soil samples is significant for improving current soil nutrient testing methods by allowing better geospatial predictions for whole paddock soil nutrient variability mapping.
Highlights
Capital and or maintenance fertilizer applications are essential in sustaining New Zealand hill-country farms’ production and increasing their profit margin
The reduction in noise by removing the top 3 cm of soil samples is significant for improving current soil nutrient testing methods by allowing better geospatial predictions for whole paddock soil nutrient variability mapping
This suggests that either the topography or the difference in fertilizer application regimes of these different parts of Patitapu farm had an influence on the Olsen P values, and the two sites are independent in terms of measured Olsen P values
Summary
Capital and or maintenance fertilizer applications are essential in sustaining New Zealand hill-country farms’ production and increasing their profit margin. If fertilizer application is to be improved, a better understanding of the variability of soil fertilizer management in order such to variably apply fertilizer as required, which precisely determine thedecisions level nutrients as phosphate across a farm or paddock to is inform nutrient levelsusing bothcomputer-controlled spatially andofthrough the profile is required. 0–75 mm could reduce the impact of be soilimproved, noise in the data (i.e., decrease variability) from animal excreta, If fertilizer application is to possible using computer-controlled technology [6]. A better understanding of the variability of soil whichnutrient would improve the accuracy ofimproved, current methods, as data with noise are levels both spatially through the sampling profile required. This research aims to determine the excreta, which would the accuracy of current sampling methods, as data points with this nutrient phosphorus map improve for variable rate fertilizer applications. Appropriate sampling depth to assess the spatial variability of soil Olsen P in order to produce a
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