Digital platform for customized nutrition and fertilization in tomato crop

• Grant number: 22/15327-4
• Support Opportunities: Research Grants - Innovative Research in Small Business - PIPE
• Start date: January 01, 2024
• End date: December 31, 2025
• Field of knowledge: Agronomical Sciences - Agronomy - Crop Science
• Principal Investigator: Carolina Cinto de Moraes
• Grantee: Carolina Cinto de Moraes
• Company: Carolina Cinto de Moraes
• CNAE: Atividades de apoio à agricultura
• City: Cerquilho
• Pesquisadores principais:( Atuais ): Jonatan Andres Gomez Parada
• Pesquisadores principais:( Anteriores ): Rodolfo Ribeiro Lindemute de Araújo
• Associated scholarship(s): 25/01931-5 - Digital platform for customized nutrition and fertilization in tomato crop, BP.PIPE; 24/19504-3 - Nutritional Diagnosis of Tomato Plants Through Rapid Analysis of Soil Solution and Plant Sap, BP.TT; 24/01095-0 - Digital platform for customized nutrition and fertilization in tomato crop, BP.PIPE; 24/01098-9 - Digital platform for customized nutrition and fertilization in tomato crop, BP.PIPE

Abstract

The inadequate application of fertilizers in tomato cultivation results in lower production, nutritional imbalances, low quality products and, consequently, lower profitability. In addition, the cost of fertilizers has increased considerably in the last two years, therefore, in order to make cultivation more sustainable with product and soil quality, optimal management of nutrition and rational application of fertilizers is essential. For that, the genetic characteristics of each hybrid and the environmental factors that interfere in the quantity and proportionality of the absorbed nutrients must be taken into account. In this way, a software that generates a customized fertilization suggestion, considering the needs of the plants and the influences of the cultivation conditions on the absorption of nutrients, is a solution for farmers, seed companies and other agricultural professionals. The development of this technology started during the PIPE phase I, with the Marcha FertiSense, which is a statistical model for estimating the nutrient accumulation of tomato cultivars, with a lower cost, logistics and labor. So, for the Marcha FertiSense to be well applied in practice, the next step is to develop the FertiSense App, an application that, through data science, generates a customized fertilization recommendation, taking into account the absorption of nutrients by the genetic material and the of growing conditions. The objectives of this project are the construction of a statistical model that will estimate the customized fertilization suggestions, the execution of field tests to validate the fertilization suggestions provided by the FertiSense App algorithm, as well as the development and improvement of the App's minimum viable product . Marchas FertiSense will be held in tomato plants in the first and second semesters. From this, the variables accumulation of nutrients, production, air temperature and characteristics of plant development will be obtained. These data, together with a database of different genetic materials, will enable the execution of multivariate statistical analyses, through which it will be measured and separated what is a genetic influence and what is an influence of the cultivation conditions in relation to the accumulation of each nutrient in the tomato. Thus, a final statistical model will be determined that will estimate the customized fertilization suggestions. These amounts of fertilizers will be applied in the next tomato crop to test the technology, where parameters of nutritional status and plant development, soil solution and economic analysis will be evaluated. Thus, the software algorithm will be developed and improved based on test results and user feedback. As a result, it is expected the improvement and commercialization of the Marcha FertiSense service, the development of the minimum viable product of the FertiSense App and the acquisition of early adopter customers. (AU)