Effects of climate,soil and water source on determining exchangeable copper concentration in lowland paddy fields in Sri Lanka

Copper(Cu)is an essential micronutrient for rice.However,the current status of Cu in Sri Lankan paddy soils is not known.Therefore,the current study was conducted to determine the distribution of exchangeable Cu concentration and examine the interactive effects of the agro-climatic zone(ACZ),soil order,and water source in determining the exchangeable Cu concentration in lowland paddy fields in Sri Lanka.A total of 7,544 soil samples representing six ACZs,six soil orders,and three water sources were collected using a stratified random sampling approach.Soil exchangeable Cu fraction was extracted in 0.01 M CaCl_(2)and measured using Inductively Coupled Plasma Mass Spectrophotometry.Exchangeable Cu concentration was in the range of 0.04−728μg·kg^(−1)with a mean value of 62.4μg·kg^(−1).Only 5%of the soil samples tested had Cu concentration greater than 200μg·kg^(−1)indicating a widespread Cu deficiency in Sri Lankan paddy fields(i.e.critical level causing Cu deficiency;200-300μg·kg^(−1)).Among the climatic zones Wet zone had higher and the Dry zone had lower Cu concentrations.Among the soil orders,histosols had higher and alfisols had lower Cu concentrations.Water sources used for rice cultivation did not determine Cu concentration.Moreover,Cu concentration was positively correlated with soil pH.As most of the soil samples were deficient in soil exchangeable Cu,spatial maps generated in the current work could be used to develop ACZ and soil order-specific agronomic and management strategies to improve soil Cu fertility status.

Use of Smartphones for Rapid Location Tracking in Mega Scale Soil Sampling

Conventional, grid-based sampling location tracking approach with GPS or topographic maps is time-consuming and inconvenient. Therefore, this study combined the freely available virtual/digital globe with recent advancements of smartphone geo-browsers to develop a new sampling location tracking approach. The sampling frame was developed with pre-uploaded point map formulated in GIS environment by combining land-use map and one-kilometer grid with center coordinates. The sampling location grid was uploaded to smartphone and each point was tracked with Google Map path finder using point ID (coded grid coordinate) when searching each sampling location. The suitability of the new approach was tested for soil sample collection from paddy lands distributed in 0.9 million hectares in Sri Lanka. The sampling locations could be reached conveniently with the help of Google path-finder voice direction guide and optional routes. The efficiency of new approach was found to be remarkably high, i.e., over 99% of the 9000 sampling points, which were spread across Sri Lanka having an area of 65,610 km2. All sampling points in the country could be covered with twelve member field investigation crew who were guided through smartphones uploaded with sampling point grid on six motorbikes within 60 days. The new sampling location tracking approach is effective in terms of cost, time, human resource requirements, thus can be adopted in large-scale soil/plant sampling frames with high accuracy.