A Cost-Effective Sampling Strategy for Monitoring Soil pH Value in Small-Scale Smart Farming

Abstract

Field variability assessment is an important part of smart farming. The precise application of agricultural resources depends on the precise estimation of field variability. Traditionally, field variability is measured by grid-based soil sampling strategy. This method is not cost-effective for small-scale fragmented land structure. The cost can be reduced for small-scale farming by minimizing the sample size and using standardized sensors for field variability assessment. An effective sampling strategy can reduce the sample size. This study compares non-aligned systematic and simple random techniques with standard grid sampling method to measure the pH variability of a small-scale field of size 20 m × 10 m in West Bengal, India. The comparison result shows that non-aligned systematic sampling can assess the whole field pH variability with only 10 samples (p-value 0.650). Thus, the proposed method reduces the cost of soil testing by minimizing the sample size.