No abstract

In this research, proximal soil sensor data fusion was defined as a multifaceted process which integrates geospatially correlated data, or information, from multiple proximal soil sensors to accurately characterize the spatial complexity of soils. This has capability of providing improved understanding of soil heterogeneity for potential applications associated with crop production and natural resource management. To assess the potential of data fusion for the purpose of improving thematic soil mapping over the single sensor approach, data from multiple proximal soil sensors were combined to develop and validate predictive relationships with laboratory-measured soil physical and chemical properties. The work was conducted in an agricultural field with both mineral and organic soils. The integrated data included: topography records obtained using a real-time kinetic (RTK) global navigation satellite system (GNSS) receiver, apparent soil electrical conductivity (ECa) obtained using an electromagnetic induction sensor, and content of several naturally occurring radioisotopes detected using a mobile gamma-ray spectrometer. In addition, the soil profile data were collected using a commercial ruggedized multi-sensor platform carrying a visible and near-infrared (vis-NIR) optical sensor and a galvanic contact soil ECa sensor. The measurements were carried out at predefined field locations covering the entire study area identified from sensor measured a priori information on field elevation, ECa and gamma-ray count. The information was used to predict: soil organic matter (SOM), pH, lime buffer capacity (LBC), as well as concentration of phosphorus (P), potassium (K), calcium (Ca), magnesium (Mg), and aluminum (Al). Partial least squares regressions (PLSRs) were used to predict soil properties from individual sensors and different sensor combinations (sensor data fusion).

The aim of this study was to investigate the effects of short-term repeated passes tillage operations on bulk density, soil penetration resistance, soil porosity and the moisture of a clay loam soil of Malaysia. A field experiment for three seasons was conducted at Sungai Burong Tanjung Karang Kuala Selangor, Malaysia to study treatments consisting of (I) no-tillage NT (II) first tillage FT (III) second tillage (ST), (IV) third tillage (TT) operations. The soil bulk density, soil penetrometer resistance, pore distribution, and moisture content characteristics were determined before and after for each of the three tillage. The penetration resistance was determined at the depths of 0-80 cm while the soil moisture was determined on the surface (0-20 cm). These properties were determined directly before and after tillage operations. All the tillage operations were significantly different in their effects on soil bulk density and soil penetration resistance. The soil bulk density decreased with the degree of soil manipulation after first and third tillage and increased after second tillage, with NT having the highest mean bulk density 1.04, 0.95 and 1.03 g/cm3 while TT having the least 0.84, 0.83 and 0.72 g/cm3 for 1st, 2nd and 3rd season respectively. The soil penetration resistance decreased due to tillage operation, with NT also having the highest resistance of 1.69 MPa and 1.44 Mpa in hardpan during 1st and 2nd season and the lowest PR was 0.09, 0.17 and 0.21 Mpa at TT in 1st, 2nd and 3rd season. Highest mean porosity was 0.68 in 2nd season at TT and the lowest mean porosity was 0.36 in 3rd season at NT. The lowest volumetric moisture content was at ST 0.26 and 0.27 in 1st and 2nd season at ST, and the highest was at TT 0.56, 0.57 and 0.68 at TT in 1st, 2nd and 3rd season respectively. The soil particle density was increased after three tillage operation. The highest increase (23.73%) was noted in FT 2nd season and the minimum was in TT in 1 st season (6.04%) while it decreased in ST during the three seasons.

Irrigation practices change the soil moisture in agricultural fields and influence emissions of greenhouse gases (GHG). A 2 yr field study was conducted to assess carbon dioxide (CO2) and nitrous oxide (N2O) emissions from surface and subsurface drip irrigated tomato (Solanum lycopersicum L.) fields on a loamy sand in southern Ontario. Surface and subsurface drip irrigation are common irrigation practices used by tomato growers in southern Ontario. The N2O fluxes were generally ≤50 μg N2O-N m−2 h−1, with mean cumulative emissions ranging between 352 ± 83 and 486 ± 138 mg N2O-N m−2. No significant difference in N2O emissions between the two drip irrigation practices was found in either study year. Mean CO2 fluxes ranged from 22 to 160 mg CO2-C m2 h−1 with cumulative fluxes between 188 ± 42 and 306 ± 31 g CO2-C m−2. Seasonal CO2 emissions from surface drip irrigation were significantly greater than subsurface drip irrigation in both years, likely attributed to sampling time temperature differences. We conclude that these irrigation methods did not have a direct effect on the GHG emissions from tomato fields in this study. Therefore, both irrigation methods are expected to have similar environmental impacts and are recommended to growers.