Title:	LIBS como ferramenta diagnóstica em plantas: um estudo nutricional de folhas de soja na busca pelos efeitos da infestação por Aphelenchoides besseyi.
Authors:	RANULFI, A. C.
Date Issued:	2019
Citation:	2019. Tese (Doutorado) - Instituto de Física de São Carlos, Universidade de São Paulo. São Carlos, 2019. Orientadora: Débora Marcondes Bastos Pereira.
Pages:	147
Description:	RANULFI, A.C. LIBS as a diagnostic tool in plants: a nutritional study of soybean leaves in the search for the infestation effects by Aphelenchoides besseyi. 2019. 147 p. Tese (Doutorado em Ciências) - Instituto de Física de São Carlos, Universidade de São Paulo, São Carlos, 2019. Soybeans and their by-products are one of the most valuable and traded commodities in the world. Brazil is the second largest soybean producer in the world, whose soy complex is the main generator of foreign exchange for the country. However, one of the main factors that can limit crop yields and product quality is the occurrence of disease. To avoid further damage, it is important to quickly identify which disease affects the plant and determine the most effective method of management. Currently, a disease newly discovered and of concern to producers is the infestation by the nematode Aphelenchoides besseyi, which causes the disease known as GSFR (Green Steam and Foliar Retention). There are still no methods to provide a precise diagnosis for the disease, which is, nowadays, performed by visual inspection of the plantation. Knowing that healthy and diseased plants have different nutrient profiles, this work proposes the use of the LIBS technique, associated with the calibration free method (CF), as an alternative tool for the disease detection. The LIBS technique allows simultaneous multi-element analysis, quickly and inexpensively. The CF method has the main advantage of avoiding the use of any compatible standard matrix, or reference material, for LIBS quantifications, based on the physical characteristics of the plasma formed. Thus, the association of both becomes absolutely suitable for the analytical determination of unknown samples. Qualitative characterization studies using a low-resolution LIBS system, and semiquantitative and quantitative analysis using LIBS measurements in a high-resolution detection system (DP LIBS), were performed. The first study showed that it was possible to achieve, on average, 90% accuracy in the differentiation between diseased and healthy samples, and to infer that the disease provokes relative decrease in Ca and Mg concentration, and a small increase in K levels. Quantifications achieved by the CF method were considered satisfactory since it is a pioneer study in the analysis of pure soybean leaves. Classifiers were constructed from the nutritional profiles quantified by CF, applying classification via regression associated with partial least square regression, with accuracy of 94%, 92% and 90%, respectively, for the concentration data obtained by the reference technique, and DP LIBS + CF colinear and orthogonal. In attempt to eliminate the use of any chemical reagent and still obtain an efficient diagnostic tool, a semiquantitative study was conducted, also fromthe DP LIBS + CF association and based on the elementary relations between the analytes that make up the sample, with accuracy diagnosis greater than 90% for DP LIBS in orthogonal geometry. Therefore, this study allowed the development of a diagnostic methodology that respects 100% of green chemistry principles, and adds a lot to the current system, if the desire is a rapid diagnostic evaluation for immediate decision making in the field
Thesagro:	Soja
Keywords:	LIBS Perfil nutricional Espectroscopia de emissão óptica com plasma induzido por laser Calibration free
Type of Material:	Teses
Access:	openAccess
Appears in Collections:	Tese/dissertação (CNPDIA)