Open AccessSoil bulk electrical resistivity and forage ground cover: nonlinear models in an alfalfa (Medicago sativa L.) case study
Author(s) -
Roberta Rossi,
Alessio Pollice,
Giovanni Bitella,
Rocco Bochicchio,
Amedeo D'Antonio,
Alaa Aldin Alromeed,
Anna Maria Stellacci,
Rosanna Labella,
Mariana Amato
Publication year - 2015
Publication title -
italian journal of agronomy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.509
H-Index - 24
eISSN - 2039-6805
pISSN - 1125-4718
DOI - 10.4081/ija.2015.647
Subject(s) - loam , medicago sativa , normalized difference vegetation index , environmental science , forage , soil science , soil texture , productivity , soil fertility , vegetation (pathology) , soil water , agronomy , leaf area index , biology , medicine , macroeconomics , pathology , economics
Alfalfa is a highly productive and fertility-building forage crop; its performance, can be highly variable as influenced by within-field soil spatial variability. Characterising the relations between soil and forage- variation is important for optimal management. The aim of this work was to model the relationship between soil electrical resistivity (ER) and plant productivity in an alfalfa (Medicago sativa L.) field in Southern Italy. ER mapping was accomplished by a multi-depth automatic resistivity profiler. Plant productivity was assessed through normalised difference vegetation index (NDVI) at 2 dates. A non-linear relationship between NDVI and deep soil ER was modelled within the framework of generalised additive models. The best model explained 70% of the total variability. Soil profiles at six locations selected along a gradient of ER showed differences related to texture (ranging from clay to sandy-clay loam), gravel content (0 to 55%) and to the presence of a petrocalcic horizon. Our results prove that multi-depth ER can be used to localise permanent soil features that drive plant productivity