Assessing the performance of proximal sensors for soil and plant analysis

Abstract

The characterization of soil and plants has been greatly benefited by the use of portable and in-field sensors. This doctoral thesis employed two sensors: portable X-ray fluorescence spectrometry (pXRF) and Nix Pro Color Sensor for soil and plant characterization. The pXRF can be considered one of the most important advances for soil and plant analysis worldwide. Nix Pro is a pocket-sized sensor with smartphone connection via Bluetooth recently launched in the market that allows to obtain color parameters in different systems (RGB, CMYK, CIELab) of any solid surface. To assess the performance of the above-mentioned sensors, this work was split into two distinct parts: Soil and Plant. In the Soil section, pXRF was employed to obtain the total elemental composition of wetland soils from Brazilian Savannah (“Veredas”). The pXRF results were compared to those obtained after wet digestion method. In the Plant section, pXRF was used to analyse more than 600 samples from different Brazilian crops. Also, the pXRF results were correlated to the conventional and standard method for foliar analysis. Finally, the sensibility of the Nix Pro Color Sensor to measure the greenness of intact plant leaves was verified. For that, a color-dependent parameter (SPAD index) was used as dependent variable. The pXRF revealed great potential for characterization of Cerrado wetland soils. Several elements were successfully determined via pXRF under lab conditions. Further in-field investigations may be greatly benefited by pXRF contributing to still scarce inventory of Cerrado wetland soils. For plant analysis, pXRF revealed to be an alternative environmental-friendly method to determine macro- and micronutrients in dried and ground plant materials. The Nix Pro Color Sensor revealed to be sensible and an effective way to determine the color of intact plant leaves. From this pilot study, several other applications and calibrations can be performed for different plant species and environmental conditions worldwide, for example, to estimate the real chlorophyll content, N and Mg contents, and many factors influencing the nutritional status of plants, based exclusively on color parameters from NixTM Pro color sensor.