Abstract
The assessment of the nutritional status of plants is traditionally performed by wet-digestion methods using oven-dried and ground samples. This process requires sampling, takes time, and it is non-environmentally friendly. Agricultural and environmental science have been greatly benefited by in-field, ecofriendly methods, and real-time element measurements. This work employed the portable X-ray fluorescence spectrometry (pXRF) to analyze intact and fresh leaves of crops aiming to assess the effect of water content and leaf surface (adaxial and abaxial) on pXRF results. Also, pXRF data were used to predict the real concentration of macro- and micronutrients. Eight crops (bean, castor plant, coffee, eucalyptus, guava tree, maize, mango, and soybean) with contrasting water contents were used. Intact leaf fragments (∼2 × 2 cm), fresh or oven-dried (60 °C) were obtained to be analyzed via pXRF on both adaxial and abaxial surface. Conventional wet-digestion method was also performed on powdered material to obtain the concentration of macro- and micronutrients via ICP-OES. The data were subjected to descriptive statistics, principal component analysis (PCA) and random forest (RF) algorithm regression. RF was used to predict the real concentration of macro- and micronutrients based on pXRF measurements obtained directly on intact leaves. Water content had a significant effect on pXRF results. However, a positive correlation between the concentration of macro- and micronutrients obtained via pXRF directly on intact leaves and conventional analysis performed on powdered samples was obtained. PCA analysis allowed a clear differentiation of crops based on elemental composition. The concentrations of macro- and micronutrients were very accurately predicted via RF. Even elements not detected by pXRF (N and B) were satisfactory predicted. From this pilot study, it is possible to concluded that pXRF is feasible for in-field assessment of nutritional status of plants. Further studies are needed to obtain specific and robust calibrations for each crop.
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