https://www.alice.cnptia.embrapa.br/alice/handle/item/206 Artigo em anais de congresso (CNPDIA) 2026-06-11T23:26:14Z https://www.alice.cnptia.embrapa.br/alice/handle/doc/1186876 Título: Optimizing maize planting density for enhanced economic returns. Autoria: NAIME, J. de M.; SPERANZA, E. A.; LOPES, I. de O. N.; VAZ, C. M. P.; INAMASU, R. Y.; NOGARA NETO, F.; FRANCHINI, J. C. Conteúdo: Abstract: Variable rate seeding (VRS) can enhance profitability, but its adoption by small and medium-sized producers is limited. This work presents a practical on-farm methodology to determine economically optimal corn seeding rates, designed for direct use by farm managers. The methodology was applied in two commercial fields in Paraná State, Brazil. In Field A, four seeding rates were tested on two corn hybrids using a planter with a mechanical drive. In Field B, four management zones (MZs) were delineated using multiple data layers, and variable seeding rates were applied to assess spatially-differentiated responses. Results showed distinct responses between hybrids and MZs. In Field A, increasing the seeding rate by approximately 10% boosted yield by 7.9% for one hybrid but was detrimental to the other. In Field B, an economic analysis revealed that the profit-maximizing seeding rate varied by MZ: a 20% rate increase was optimal in MZ2 (+2.44% profit), while a 10% increase was optimal in MZ4 (+2.57% profit). The study demonstrates that this accessible, on-farm experimental approach allows growers to effectively customize seeding rates, optimizing resource use and profitability without requiring significant investment in specialized technology or expertise. 2025-01-01T00:00:00Z https://www.alice.cnptia.embrapa.br/alice/handle/doc/1181494 Título: A milk-probe to identify the stability condition of the raw milk. Autoria: MELO, W. L. de B.; ZANELA, M. B.; FOSCHINI, M. M.; PERES, R. P. Conteúdo: Abstract: This work concerns an application of the milk probe equipment with the purpose of identifying the stability conditions, whether stable (normal) or unstable (acidic) milk. The milk probe is an instrument composed basically of a light source, LEDs, with 12 different wavelengths. The equivalent absorbance spectrum is obtained through the application of the Kubelka-Munk function. Approximately 537 samples of herd milk were used. The statistical methods were Random Forest, Support Vector Machine (Polynomial SVM) and Logistic Regression in 4095 models of arrangement of wavelengths. The results indicated excellent agreement between the predicted values and those of the classifications. However, these are agreement values, and their precision or accuracy cannot be affirmed. Resumo: Este trabalho trata de uma aplicação do equipamento sondaleite com a finalidade de identificar as condições de estabilidade do leite, se normal ou ácido. O Sondaleite é um instrumento composto basicamente por um fonte de luz, LEDs, com 12 comprimentos de onda distintos. O espectro de absorbância equivalente se obtém através da função de Kubelka-Munk. Cerca de 537 amostras de leites de rebanho foram usadas. O método estatístico foram Random Forest, Support Vector Machine (Polynomial SVM) and Logistic Regression em 4095 modelos de arranjos dos comprimentos de onda. Os resultados indicaram ótimas concordâncias entre os valores previstos e aqueles das classificações. Contudo, trata-se de valor de concordância, não podendo afirmar sua precisão ou acurácia. 2025-01-01T00:00:00Z https://www.alice.cnptia.embrapa.br/alice/handle/doc/1179143 Título: Sensor-Based Platform for Evaluation of Atmospheric Carbon Sequestration's Potential by Maize Crops. Autoria: CRUVINEL, P. E.; COLNAGO, L. A. Conteúdo: The development of sensor-based techniques has been allowing advanced studies for agriculture’s decision support systems. This paper discusses an innovative sensorbased method for the evaluation of CO₂ sequestration potential from the atmosphere by agricultural crop environments. This study has led to new insights into the management of crop fields for food and biomass production for energy. It also brings together information related to the carbon sequestration potential, which can allow opportunities not only for the use of sensors and related techniques in soil science but also for value aggregation for the agricultural process and environmental care. For validation, an experimental maize crop area has been used. Besides, studies about atmospheric carbon sequestration potential were evaluated. Such analyses have become possible by using vegetation indexes related to the normalized difference vegetation and the modified chlorophyll absorption in reflective, both calculated with data acquired using a multispectral sensor. In addition, three other sensors have been used for solar light intensity, soil water content, and air temperature measurements. Results have shown the spatial variability of the carbon sequestration potential, as well as its temporal variability when considering different phenomenological phases of the maize culture. Furthermore, a positive correlation with plant management and the carbon sequestration potential has been found, i.e., leading to an adequate new sensor-based descriptor for atmospheric carbon sequestration by plants evaluation. 2025-01-01T00:00:00Z https://www.alice.cnptia.embrapa.br/alice/handle/doc/1179142 Título: Reducing the Dead Zone Time Effect of Actuators in Sensor-Based Agricultural Sprayers under S-shaped Functions Gain Scheduling Management of a Generalized Predictive Control (GPC) Strategy. Autoria: SCHUTZ, D. R.; OLIVEIRA, V. A.; CRUVINEL, P. E. Conteúdo: —This paper presents a study on the relationship between sensors, control systems and actuators for agricultural spraying. Sensors associated with appropriate control systems can be used to support decision-making processes for nozzles in relation to the correct application of pesticides. In such a context, results related to a comparison were evaluated considering not only an adaptive generalized predictive control based on both fuzzy and sigmoid-based strategies for scheduling management but also the enhancement of the dead zone management improving actuators performance in relation to the nozzles stitching’s processes. These systems involving sensors, controllers and switching are essential for the automation of agricultural sprayers, especially for those that work with variable rate application, in management based on precision agriculture. A Sigmoid-based Generalized Predictive Control (SGPC) is proposed for flow rate regulation in agricultural pesticide sprayers. Evaluated against conventional Fuzzy Logic-based GPC (FGPC), the SGPC shows reduced Integral Absolute Error (IAE) and faster rise time despite higher overshoot in certain scenarios. Results indicate enhanced tracking accuracy and dynamic response compared to traditional fuzzy logic approaches. This framework demonstrates potential for improving precision in agricultural spraying systems. Such results can be valuable for the current machinery agricultural industry, which needs to improve productivity and quality gains and reduce negative externalities in favor of food security and sustainability 2025-01-01T00:00:00Z