Rossi et al., 2018 - Google Patents

Modelling the non-linear relationship between soil resistivity and alfalfa NDVI: a basis for management zone delineation

Rossi et al., 2018

Document ID
1594458384653753304
Author
Rossi R
Pollice A
Bitella G
Labella R
Bochicchio R
Amato M
Publication year
Publication venue
Journal of Applied Geophysics

External Links

Snippet

Alfalfa is one of the most important forage legumes in the world, and increasing its competitiveness is among European priorities. One issue that needs to be specifically addressed in designing agronomic strategies for perennial crops like alfalfa is their higher …
Continue reading at www.sciencedirect.com (other versions)

Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS
    • G01V3/00—Electric or magnetic prospecting or detecting; Measuring magnetic field characteristics of the earth, e.g. declination, deviation
    • G01V3/12—Electric or magnetic prospecting or detecting; Measuring magnetic field characteristics of the earth, e.g. declination, deviation operating with electromagnetic waves

Similar Documents

Publication Publication Date Title
Rossi et al. Modelling the non-linear relationship between soil resistivity and alfalfa NDVI: a basis for management zone delineation
Nawar et al. Delineation of soil management zones for variable-rate fertilization: A review
Basso et al. Variable rate nitrogen fertilizer response in wheat using remote sensing
Di Virgilio et al. Spatial variability of switchgrass (Panicum virgatum L.) yield as related to soil parameters in a small field
Rudolph et al. Linking satellite derived LAI patterns with subsoil heterogeneity using large-scale ground-based electromagnetic induction measurements
Schnur et al. Estimating root zone soil moisture at distant sites using MODIS NDVI and EVI in a semi-arid region of southwestern USA
Jégo et al. Using Leaf Area Index, retrieved from optical imagery, in the STICS crop model for predicting yield and biomass of field crops
Crow et al. Upscaling of field-scale soil moisture measurements using distributed land surface modeling
De Benedetto et al. Field partition by proximal and remote sensing data fusion
Tola et al. Characterization of spatial variability of soil physicochemical properties and its impact on Rhodes grass productivity
Merrill et al. Comparison of soil quality and productivity at two sites differing in profile structure and topsoil properties
Cordero et al. Spatial management strategies for nitrogen in maize production based on soil and crop data
Rabia et al. Principles and applications of topography in precision agriculture
James et al. Determination of soil type boundaries using electromagnetic induction scanning techniques
Munnaf et al. Multi-sensors data fusion approach for site-specific seeding of consumption and seed potato production
Singh et al. Soil carbon change across ten New South Wales farms under different farm management regimes in Australia
AKBAS Spatial variability of soil color parameters and soil properties in an alluvial soil
Pedrera-Parrilla et al. Mapping impaired olive tree development using electromagnetic induction surveys
Shaukat et al. Quasi-3D mapping of soil moisture in agricultural fields using electrical conductivity sensing
Brown et al. Time‐lapse mapping of crop and tillage interactions with soil water using electromagnetic induction
Nyengere et al. Analysis of spatial heterogeneity of soil physicochemical properties in Northern Malawi
Yao et al. Determining soil salinity and plant biomass response for a farmed coastal cropland using the electromagnetic induction method
Irmak et al. Relationship between plant avai lable soil water and yield for explaining soybean yield variability
Rejman et al. Soil redistribution and crop productivity in loess areas (Lublin Upland, Poland)
Gardin et al. Simulation of soil water content through the combination of meteorological and satellite data