Evaluation of agronomic performance of common beans varieties fertilized with elemental sulfur and biofortified with macro and micronutrients, evaluated with UAV-based highthroughput phenotyping and Artificial Intelligence methodology.

• Grant number: 22/15899-8
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: March 01, 2023
• End date: February 29, 2024
• Field of knowledge: Agronomical Sciences - Agronomy - Crop Science
• Principal Investigator: Rafael Simões Tomaz
• Grantee: Franco Monici Fabrino
• Host Institution: Faculdade de Ciências Agrárias e Tecnológicas. Universidade Estadual Paulista (UNESP). Campus de Dracena. Dracena , SP, Brazil

Abstract

The common bean (Phaseolus vulgaris L.) is one of the most used foods in Brazilian cuisine, much because of its high protein content contained in its grains, besides the presence of essential nutrients in its composition. The adoption of technologies, such as the use of improved varieties, biofortification, the adoption of sulfate fertilization, combined with analysis technology such as high-yield phenotyping using drones and the use of artificial intelligence in data analysis has allowed an increase in crop productivity in recent years. In order to evaluate the factors mentioned in the development of productivity of bean crops, an experiment will be conducted in a randomized block design, with three repetitions, in a triple factorial scheme 4x2x2, considering four varieties, two levels of biofotification and two levels and fertilization with elemental sulfur. The experiment will be implemented in the irrigated experimental area of FCAT UNESP - Campus de Dracena. Agronomic characteristics of crop development and productivity attributes will be evaluated. Additionally, high yield phenotyping will be performed with a Mavic 2 Pro drone. Periodic flights will be performed in the crop in order to collect images and make the association of these with the agronomic characteristics measured, using the Artificial Intelligence method (Artificial Neural Networks). We hope, with the execution of this experiment, to analyze the behavior of the varieties under the conditions evaluated in order to assess the efficiency of the biofortification protocol to be evaluated, providing knowledge to the scientific community as well as the popularization of the proposed methodologies, in order to allow the use of such technology in a conscious and sustainable way.