Combined use of remote sensing and soil sensors to detect variability in orchards with previous changes in land use and landforms: consequences for management

Abstract

The present work investigated the application of detailed airborne images and a resistivity soil sensor (Veris 3100) to detect soil and crop spatial variability to assist in orchard management. The research was carried out in a peach orchard (Prunus persica). Soil apparent electrical conductivity (ECa), NDVI from a multispectral image (0.25 m/pixel) and soil properties at 40 sampling points (0–30 cm) were acquired. The ECa was standardized at 25°C. It showed a strong relationship with former landforms, altered by land levelling. A positive correlation of EC25 with EC1:5, water holding capacity at −1500 kPa and soil depth was found. NDVI was correlated only in the textural fractions coarser than clay. Two types of management zones were proposed: a) to improve the water holding capacity of soils and b) to regulate tree vigour and yield.