Ednaldo José Ferreira

Infrared spectroscopy: A potential tool in huanglongbing and citrus variegated chlorosis diagnosis

Huanglongbing (HLB) and citrus variegated chlorosis (CVC) are serious threats to citrus production and have caused considerable economic losses worldwide, especially in Brazil, which is one of the biggest citrus producers in the world. Neither disease has a cure nor an efficient means of control. They are also generally confused with each other in the field since they share similar initial symptoms, e.g., yellowing blotchy leaves. The most efficient tool for detecting these diseases is by polymerase chain reaction (PCR). However, PCR is expensive, is not high throughput, and is subject to cross reaction and contamination. In this report, a diagnostic method is proposed for detecting HLB and CVC diseases in leaves of sweet orange trees using attenuated total reflectance Fourier transform infrared spectroscopy and the induced classifier via partial least-squares regression. Four different leaf types were considered: healthy, CVC-symptomatic, HLB-symptomatic, and HLB-asymptomatic. The results show a success rate of 93.8% in correctly identifying these different leaf types. In order to understand which compounds are responsible for the spectral differences between the leaf types, samples of carbohydrates starch, sucrose, and glucose, flavonoids hesperidin and naringin, and coumarin umbelliferone were also analyzed. The concentration of these compounds in leaves may vary due to biotic stresses.

Evaluation of laser induced breakdown spectroscopy for multielemental determination in soils under sewage sludge application.

Laser induced breakdown spectroscopy (LIBS) is an atomic emission spectroscopy technique for simple, direct and clean analysis, with great application potential in environmental sustainability studies. In a single LIBS spectrum it is possible to obtain qualitative information on the sample composition. However, quantitative analysis requires a reliable model for analytical calibration. Multilayer perceptron (MLP), an artificial neural network, is a multivariate technique that is capable of learning to recognize features from examples. Therefore MLP can be used as a calibration model for analytical determinations. Accordingly, the present study proposes to evaluate the traditional linear fit and MLP models for LIBS calibration, in order to attain a quantitative multielemental method for contaminant determination in soil under sewage sludge application. Two sets of samples, both composed of two kinds of soils were used for calibration and validation, respectively. The analyte concentrations in these samples, used as reference, were determined by a reference analytical method using inductively coupled plasma optical emission spectrometry (ICP OES). The LIBS-MLP was compared to a LIBS-linear fit method. The values determined by LIBS-MLP showed lower prediction errors, correlation above 98% with values determined by ICP OES, higher accuracy and precision, lower limits of detection and great application potential in the analysis of different kinds of soils.

Multiple response optimization of laser-induced breakdown spectroscopy parameters for multi-element analysis of soil samples.

Laser-induced breakdown spectroscopy (LIBS) is an emerging analytical technique to perform elemental analysis in natural samples independent of their physical state (solid, liquid, or gaseous). Due to its instrumental features, LIBS shows promising potential to perform analysis in situ and in environments at risk. Since the analytical performance of LIBS strongly depends on the choice of experimental conditions, each particular application needs a specific instrumental adjustment. The present study evaluated three LIBS instrumental parameters regarding their influences on signal-to-noise ratio (SNR) of seven elements in soil samples: laser pulse energy, delay time, and integration time gate. A multivariate technique was used due to the significant interaction among the evaluated parameters. Subsequently, to optimize LIBS parameters for each individual element response, a method for multiple response optimization was used. With only one simple screening design, it was possible to obtain a good combination among the studied parameters in order to simultaneously increase the SNR for all analytes. Moreover, the analysis of individual response for elements is helpful to understand their physical behavior in the plasma and also how they are embedded in the sample matrix.

Evaluation of the Nutritional Changes Caused by Huanglongbing (HLB) to Citrus Plants Using Laser-Induced Breakdown Spectroscopy

Huanglongbing (HLB) is the most recent and destructive bacterial disease of citrus and has no cure yet. A promising alternative to conventional methods is to use laser-induced breakdown spectroscopy (LIBS), a multi-elemental analytical technique, to identify the nutritional changes provoked by the disease to the citrus leaves and associate the mineral composition profile with its health status. The leaves were collected from adult citrus trees and identified by visual inspection as healthy, HLB-symptomatic, and HLB-asymptomatic. Laser-induced breakdown spectroscopy measurements were done in fresh leaves without sample preparation. Nutritional variations were evaluated using statistical tools, such as Students t-test and analysis of variance applied to LIBS spectra, and the largest were found for Ca, Mg, and K. Considering the nutritional profile changes, a classifier induced by classification via regression combined with partial least squares regression was built resulting in an accuracy of 73% for distinguishing the three categories of leaves.