101313 Understanding Spatiotemporal Variability of Soil-Plant Relationships in a Heterogeneous Coastal Farmland in Northern Italy.

Poster Number 319-716

See more from this Division: ASA Section: Agronomic Production Systems
See more from this Session: On-Farm Research: Advancing Precision Ag Tools, Data Analysis and Extension implications (includes student competition)

Tuesday, November 8, 2016
Phoenix Convention Center North, Exhibit Hall CDE

Elia Scudiero1, Francesco Morari2, Todd H. Skaggs1, Federica Braga3 and Pietro Teatini4, (1)USDA-ARS, Riverside, CA
(2)Department of Agronomy, Food, Natural resources, Animals, and Environment (DAFNAE), University of Padua, Legnaro, ITALY
(3)Institute of Marine Sciences (ISMAR), National Research Council, Venice, Italy
(4)Department of Civil, Environmental, and Architectural Engineering (ICEA), University of Padua, Padua, Italy
Poster Presentation
  • 101313_Scudiero_poster_landscape.pdf (1.9 MB)
  • Abstract:
    Coastal farmland in northeastern Italy is often characterized by high spatial variability of yield within a single field due to contrasting soil types (from silty clay to sand), salt water contamination, and other edaphic factors (e.g., acidic peats). Spatial analyses of the relationships between soil properties and canopy reflectance can help address the spatiotemporal variability in crop growth due to soil-related issues (e.g., water availability) in this region. A rainfed 21-ha maize (Zea mays L.) field was monitored in 2010 (rainfall = 535mm) and 2011 (rainfall = 200mm). At the field, 1) soil texture and salinity were analyzed at 120 sampling locations (0-1.2 m) and then mapped using sensor measurements of soil reflectance, apparent electrical conductivity, and micro-elevation; 2) crop growth was monitored using canopy reflectance retrieved from Landsat 5 (resolution =900 m2, every 16 days) and WorldView II (resolution =4 m2, once a season, during the pre-tasseling stage), and, three times a season, by analyzing hyper spectral reflectance and leaf quality (e.g., mass and ion composition) at selected locations; and 3) yield maps were acquired at harvest. Preliminary analyses indicated that salinity limited crop growth in both years, whereas texture limited growth especially in 2011 (dry year). The spatiotemporal variability of the soil-plant relationships was described using geographically weighted regression (GWR) between the satellite canopy reflectance and the soil maps. The GWR analysis found localized relationships between plant growth and specific soil properties throughout the year. For example, in 2011 the GWR indicated that saline areas had poor crop performance during early vegetation stages; growth in sandy areas was strongly limited during the pre-tasseling and reproductive stages; and areas with finer texture never suffered from water scarcity. Such information can be used to support site-specific management and address soil-plant issues in a timely manner.

    See more from this Division: ASA Section: Agronomic Production Systems
    See more from this Session: On-Farm Research: Advancing Precision Ag Tools, Data Analysis and Extension implications (includes student competition)