Physical and Biological Soil Attributes and the Use of Organomineral Fertilizers in Sugarcane Cultivation

• Grant number: 25/13580-2
• Support Opportunities: Scholarships in Brazil - Master
• Start date: September 01, 2025
• End date: August 31, 2027
• Field of knowledge: Agronomical Sciences - Agronomy - Soil Science
• Principal Investigator: Carlos Alexandre Costa Crusciol
• Grantee: Douglas Gonçalves Saraiva
• 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 recent decades, recognizing that the dynamic response of soil properties to land management and use is highly dependent on site-specific factors, which must be considered when interpreting results (NUNES et al., 2021). In land management and use, soil fertility management directly affects SQ, including the use of bioinputs. Under the challenges posed by climate change, the application of bioinputs can be considered a suitable mitigation strategy, as they improve the physical, chemical, and biological properties of 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). However, understanding SQ remains challenging due to the complex interactions occurring in the soil, such as the connection between plant responses to bioinputs and the formulation of precise and robust agronomic recommendations. The systematic collection of data and analysis through artificial intelligence tools, such as Large Language Models (LLMs), may help address these issues and generate predictive models that optimize the use of bioinputs under different agricultural conditions across the country. This approach contributes to achieving the overall objective of the proposal by generating new agronomic knowledge on soil quality (in citrus crops), transforming the current version of Bulletin 100 (analog, focused on physical-chemical aspects) into a digital version (Smart B100; integrating physical, chemical, and biological aspects) using AI tools. The objective of this work plan is to survey and analyze scientific publications related to citrus and to seek repeatability and robustness of the information. Articles on soil quality will be collected from scientific literature databases (PUBMED, SCOPUS, CAPES). The main expected outcomes of this plan within the CCD-SB100 framework are: (i) that the data survey on soil quality in citrus will provide reliable information with repeatability and robustness; (ii) that this robustness and repeatability can feed LLM-based models, resulting in a high-quality product that can be used by technicians and farmers. (AU)