Artificial intelligence and portable Infrared for papaya quality and maturation point analysis

• Grant number: 23/10566-3
• Support Opportunities: Research Grants - Innovative Research in Small Business - PIPE
• Start date: March 01, 2024
• End date: November 30, 2024
• Field of knowledge: Agronomical Sciences - Agronomy - Crop Science
• Agreement: SEBRAE-SP
• Principal Investigator: Karla Rodrigues Borba
• Grantee: Karla Rodrigues Borba
• Company: Karla Rodrigues Borba Consultoria em Tecnologia da Informação Ltda
• CNAE: Atividades de apoio à agricultura ; Atividades de pós-colheita
• Associated researchers: Poliana Cristina Spricigo ; Poliana Cristina Spricigo
• Associated scholarship(s): 24/03088-0 - Artificial intelligence and portable infrared in the analysis of quality and ripeness of papaya, BP.PIPE

Abstract

Brazil is the second-largest producer of papayas in the world, with approximately one million, two hundred thousand tons produced in 2021. Its crop extends over 28,495 ha, with emphasis on the northern regions of Espírito Santo and southern Bahia, with Europe, the United States, and other countries in South America being its biggest importers. Quality control during fruit export is strict and batches can be returned if they do not meet the minimum requirements. The harvest time is an important factor to be considered, as it exerts a great influence on the final quality of the fruits. Harvesting immature fruits causes a high rate of water loss, increased susceptibility to physiological disorders, and impairs ripening, affecting the final quality of the fruit in terms of attributes such as flavor, appearance, and texture. On the other hand, very ripe fruits harvested quickly lose quality due to accelerated deterioration and less resistance to handling, with a reduced marketing time. Therefore, it is of great importance to develop alternatives and new methods with greater precision, speed, and practicality for producers. Over the last two decades, the miniaturization of near-infrared spectrometers, together with the great advances in the area of artificial intelligence, made the NIR technique much more attractive for direct consumers in the agro (producers, processors, and intermediaries of the process). Portable NIRs, that present performance equivalent to the large benchtop spectrometers, can now be taken to each stage of the agricultural process, including the field. This enables fast and effective decision-making and more accurate evaluation. Despite the various advances, scientific studies, and equipment developed, this technology is still not accessible to all producers. (AU)