Determination of nitrogen status in Mavuno pastures through image analysis using artificial neural networks (ANN)

• Grant number: 20/00345-1
• Support Opportunities: Regular Research Grants
• Start date: June 01, 2020
• End date: May 31, 2022
• Field of knowledge: Agronomical Sciences - Animal Husbandry - Pastures and Forage Crops
• Principal Investigator: Adriano Rogério Bruno Tech
• Grantee: Adriano Rogério Bruno Tech
• Host Institution: Faculdade de Zootecnia e Engenharia de Alimentos (FZEA). Universidade de São Paulo (USP). Pirassununga , SP, Brazil
• Associated researchers: Lilian Elgalise Techio Pereira ; Lucas da Rocha Carvalho ; Wilson Manuel Castro Silupu
• Associated scholarship(s): 21/01766-3 - Determination of the critical level of N (% Nc) of Mavuno grass pastures, BP.TT; 21/00073-4 - Performance of artificial neural networks (RNAs) to predict the N status of Mavuno pastures, BP.TT

Abstract

Pasture-based livestock systems in Brazil have been under major transformations, particularly in recent decades. Major innovations have been responsible for improvements, though still slight, in pasture-based livestock productivity rates. Among the main innovations experienced in these systems, that stand out is the broadening understanding, that each forage species has particularities in growth patterns and morphological attributes, and the recognition that stable and productive pasture systems depend on the balance between their components, soil. -plant-animal-management, and the adoption of appropriate fertilization strategies is essential in maintaining this balance. Recognizing the importance of pasture fertilization, innovations regarding timing and quantities required by forage crops are still needed. It is recognized that misapplication of fertilizers, particularly nitrogen, can substantially contribute to greenhouse gas emissions, especially nitrous oxide (N2O), which has a global warming potential about 300 times higher than CO2. Parallel to this new conception of pasture systems, the introduction of new forage species and cultivars, notably more productive, more adapted and/or tolerant to certain edaphoclimatic particularities, has contributed substantially to the national livestock scenario. Mavuno grass, a hybrid of Brachiaria brizantha x B. ruziziensis species, has been recently launched and has growth attributes that make it an important option in the composition of pasture systems, including high sprouting speed, broad and robust root system and nutritional value. higher than the known species of the genus Brachiaria. However, scientific studies that prove its production potential are practically non-existent in the literature until the present. In order to contribute to the definition of nitrogen fertilization strategies compatible with the demand of the plant and, in order to design productive, sustainable pasture systems with minimal environmental impact, this work aims to measure the forage production and the concentration of N in leaf tissues (NFoliar) in Mavuno grass pastures submitted to nitrogen fertilization. From the relationship between accumulated biomass and NFoliar concentration it will be constructed the dilution curve, following the method proposed by Lemaire et al. (2008) and the nitrogen nutrition index (IUU) was determined in order to evaluate the possibility of applying fertilization at variable rates. (AU)

Scientific publications

(5)

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

LILIAN ELGALISE TECHIO PEREIRA; LUAN JARDIM DE SOUSA; LIANDRA MARIA ABAKER BERTIPAGLIA; VALDO RODRIGUES HERLING; ADRIANO ROGÉRIO BRUNO TECH. Concentração crítica e manejo da adubação nitrogenada no estabelecimento de Brachiaria híbrida Mavuno. Rev. Ciênc. Agron., v. 52, n. 4, 2021-09-27. (20/00345-1)

WELLINGTON RENATO MANCIN; LILIAN ELGALISE TECHIO PEREIRA; RACHEL SANTOS BUENO CARVALHO; YEYIN SHI; WILSON MANUEL CASTRO SILUPU; ADRIANO ROGÉRIO BRUNO TECH. Uso de visão computacional na classificação de capim Xaraés segundo o status nutricional em nitrogênio. Rev. Ciênc. Agron., v. 53, 2021-11-24. (20/00345-1)

MANCIN, WELLINGTON RENATO; TECHIO PEREIRA, LILIAN ELGALISE; BUENO CARVALHO, RACHEL SANTOS; SHI, YEYIN; CASTRO SILUPU, WILSON MANUEL; BRUNO TECH, ADRIANO ROGERIO. The use of computer vision to classify Xaraes grass according to nutritional status in nitrogen. REVISTA CIENCIA AGRONOMICA, v. 53, 2022. (20/00345-1)

TECHIO PEREIRA, LILIAN ELGALISE; HERLING, VALDO RODRIGUES; BRUNO TECH, ADRIANO ROGERIO. Current Scenario and Perspectives for Nitrogen Fertilization Strategies on Tropical Perennial Grass Pastures: A Review. AGRONOMY-BASEL, v. 12, n. 9, p. 19-pg., 2022-09-01. (20/00345-1)

TECHIO PEREIRA, LILIAN ELGALISE; DE SOUSA, LUAN JARDIM; ABAKER BERTIPAGLIA, LIANDRA MARIA; HERLING, VALDO RODRIGUES; BRUNO TECH, ADRIANO ROGERIO. Critical concentration and management of nitrogen fertilization in the establishment of Brachiaria hybrid Mavuno. REVISTA CIENCIA AGRONOMICA, v. 52, n. 4, 2021. (20/00345-1)