Research and system development for Asian soybean rust (Phakopsora pachyrhizi) early detection by reflectance spectrometry

• Grant number: 18/15318-0
• Support Opportunities: Research Grants - Innovative Research in Small Business - PIPE
• Duration: April 01, 2019 - December 31, 2019
• Field of knowledge: Agronomical Sciences - Agronomy - Plant Health
• Principal Investigator: Ticyana Carone Banzato
• Grantee: Ticyana Carone Banzato
• Host Company: Ticyana Carone Banzato - ME
• CNAE: Cultivo de soja ; Atividades de apoio à agricultura
• City: Piracicaba
• Associated researchers: André Fróes de Borja Reis ; José Otávio Machado Menten ; Luis Eduardo Aranha Camargo ; Sônia Maria De Stefano Piedade
• Associated scholarship(s): 19/06303-1 - Research and system development for Asian soybean rust (Phakopsora pachyrhizi) early detection by reflectance spectrometry, BP.TT; 19/10498-2 - Research and system development for Asian soybean rust (Phakopsora pachyrhizi) early detection by reflectance spectrometry, BP.TT; 19/10502-0 - Research and system development for Asian soybean rust (Phakopsora pachyrhizi) early detection by reflectance spectrometry, BP.TT; 19/03869-4 - Research and system development for Asian soybean rust (Phakopsora pachyrhizi) early detection by reflectance spectrometry, BP.PIPE; 19/04260-3 - Research and system development for Asian soybean rust (Phakopsora pachyrhizi) early detection by reflectance spectrometry, BP.TT

Abstract

Trinanguli is an associate company of ESALQ - USP (ESALQTEC) Technology Based Business Incubator. Its technology is innovative and makes use of spectrometers to anticipate the diagnosis of important diseases of cultivated plants. Spectrometers are measurement tools, used in various areas of knowledge. The range of needs that a spectrometer reads needs is very broad, providing data for immediate analysis, optimizing methods and factors for a fast result. In agriculture, there are several studies involving early detection of diseases, pesticides detection, vegetation analysis and nutrients quantification in food. In plant pathology, the technique has been used as a fast and non-destructive way to detect anomalies caused by the manifestations of plant diseases. Many spectroscopic and imaging techniques have already been studied for symptomatic and asymptomatic plant diseases detection. Thus, develop a model for Asian soybean rust (Phakopsora pachyrhizi) early detection, based on the analysis of the data obtained by spectrometry, using a spectrometer, is a promising technology because it would serve a very large market. It is estimated a 13.8% reduction in maximum soybean yield, due to the disease severity in the crops. In a hypothetical study, with the data from Brazilian market, this severity rate would be equivalent a loss of R $ 7.7 billion, or 5.6 million tons of soybeans less, due to the occurrence of disease. This model of spectroscopic technique shows an advantage when it points out the possibility of a system for early detection of soybean rust integrated into an autonomous agricultural vehicle. (AU)