SMART B100: Research 1 - Chemical Attributes and the Use of Organominerals in Sugarcane Cultivation

• Grant number: 25/06802-9
• Support Opportunities: Scholarships in Brazil - Master
• Start date: June 01, 2025
• End date: May 31, 2027
• Field of knowledge: Agronomical Sciences - Agronomy - Soil Science
• Principal Investigator: Carlos Alexandre Costa Crusciol
• Grantee: Lilybeth Namie Tomita
• Host Institution: Faculdade de Ciências Agronômicas (FCA). Universidade Estadual Paulista (UNESP). Campus de Botucatu. Botucatu , SP, Brazil
• Associated research grant: 24/00985-1 - Smart B100 Advanced Research Center (CCD-SB100), AP.CCD

Abstract

The concept of soil quality (SQ) has evolved over the past decades, recognizing that the dynamic response of soil properties to land management and use is highly dependent on site-specific factors that must be considered when interpreting results (NUNES et al., 2021). In land management and use, soil fertility management directly affects SQ, as in the case of using bioinputs. Given the consequences of climate change, the use of bioinputs can be considered an appropriate mitigation option, since they improve the physical, chemical, and biological properties of the soil, increasing nutrient availability, water retention, and microbial activity (MAITRA et al., 2022). Therefore, the study of SQ involves the integration of various physical, chemical, and biological soil properties (BÜNEMANN et al., 2018), and the main difficulty in understanding SQ lies in the multiple interactions that occur in the soil-such as the connection with plant responses to the use of bioinputs and the need for precise and robust agronomic recommendations. The systematic collection of data and analysis through AI tools, such as Large Language Models (LLMs), could help address these issues and generate predictive models to optimize the use of bioinputs under the different conditions found in agricultural areas across the country. This approach contributes to achieving the general goal of the proposal by gathering new agronomic knowledge about soil quality (in sugarcane crops), transforming the current version of Bulletin 100 (analog, physico-chemical) into a digital version (Smart B100; physico-chemical-biological) through the use of AI tools. The objective of this work plan is related to the review and analysis of publications concerning sugarcane cultivation and the pursuit of repeatability and robustness of the information. Articles on soil quality will be sourced from scientific literature databases (PUBMED, SCOPUS, CAPES). The main expected outcomes of this plan within the CCD-SB100 are: (i) that the data collection on soil quality in sugarcane cultivation will provide reliable information with repeatability and robustness; (ii) that this robustness and repeatability can feed LLM models, generating a high-quality product that can be used by technicians and farmers.