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Precision Crop Protection, Pest, and Plant Health
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Authors
, L
Alves, R.Q
Alvez, R.Q
Apolo-Apolo, E
Arnosti, M.C
Arnosti, M.C
Barboza, T.O
Carreira, V.D
Carreño, N
Ciancio, N
Cohen, Y
Corrêa Dalvi, N.B
Costa Barboza, T
Costa Barboza, T
Costa Souza, J.B
Costa, O.P
Costa, O.P
De Oliveira Vieira, I
Dias Borges, R
Ductra Bortolotti, G
Edan, Y
Felipe dos Santos, A
Felipe dos Santos, A
Felipe dos Santos, A
Felipe dos Santos, A
Felipe, J.C
Ferreira, E.J
Ferreira, E.J
Ferreira, J
Filho, R.Z
Franco Neto, A.R
Françani, A.O
Gafni, R
Gallo, B.B
Garcia Ramirez, D.Y
Gentili, M
Gomes Mesquita, G
Goncalves, L.M
Gonçalves, D.C
Hatum de Almeida, S.L
Hatum, S.L
Jimenez Lopez, F.R
Jimenez, A
Jorge, L.A
Jorge, L.A
Jørgensen, J.R
Jørgensen, R.N
Júnior, D.G
La Rosa, A
Lacerda, L
Lennartsson, E
Levanon, D
Lima, M
Lo Celso, I
Lopes, B.V
Lüdtke, L
Ma, Y
Machado, W.J
Madsen, M.S
Maldaner, I
Martínez-Guanter, J
Müllich, A
Nichols, V.A
Nizzoli, A
Nunes, A.R
Oliveira, A.M
Oliveira, J
Pan, D
Pereira da Silva, R.P
Pilcon, C
Polastreli, R.L
Pérez-Ruiz, M
Rezende, P.S
Ribeiro, M
Rolim Farias da Silva, E
Rossi, C
Santos, A
Santos, A
Scaramuzza, F.M
Sgarbossa, J
Shmuel, L
Silveira Pavão, L
Silveira, G.L
Silveira, G.L
Silveira, G.L
Silveira, P
Sousa Vieira, M
Sánchez-Fernández, L
Tangerino, G.P
Teixeira, S.A
Tsukahara, R
Valdes Fernandez, G
Valdez, G.F
Valdivino, R
Weih, M
Wu, Q
Xiaoyu, S
Xu, X
Yan, J
Zhang, J
Zhao, L
Zhao, L
da Silva, W.B
da Silva, W.B
de Queiroz, R.F
Topics
Precision Crop Protection, Pest, and Plant Health
Type
Poster
Oral
Year
2026
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Filter results19 paper(s) found.

1. Characterization of Spray Application with a 110015 Ad Nozzle Using a Remotely Piloted Aircraft: Evaluation of Flight Altitude and Collector Type

Remotely piloted aircraft (RPA) spray systems represent an innovative technology in modern agriculture, offering pesticide application with high precision and operational efficiency. A comparative study of different collector substrates is essential for precision agriculture, as each substrate exhibits specific droplet absorption and retention properties that significantly affect the evaluation of spray performance and pesticide deposition efficacy. Investigating the interaction of sprayed dr... R.F. de queiroz, P.S. Rezende, A.M. Oliveira, G.P. Tangerino, A.R. Franco neto

2. The Influence of Field Geometry on the Operational Stability of Uav-based Spraying

The use of spraying drones has expanded rapidly in precision agriculture; however, operational factors such as field geometry may compromise application stability. This study aimed to evaluate the influence of field shape on operational variability and operational capacity during spraying performed with a DJI Agras T100 drone. The experiment was conducted in two fields with distinct geometries: a regular (rectangular) field and an irregularly shaped field, located at the Technology Developmen... A. Felipe dos santos, R.Q. alvez, T.O. Barboza, M.C. Arnosti, G.F. Valdez , G.L. Silveira

3. Inversion of Potato Chlorophyll Content Based on Radiation Transfer Model and Machine Learning Algorithm

Leaf chlorophyll content (LCC) significantly correlates with crop growth conditions, nitrogen content, yield, etc. It is a crucial indicator for elucidating the senescence process of plants and can reflect their growth and nutrition status. However, the performance of traditional LCC inversion models is limited by the quality and scale of training data. It is difficult to satisfy the needs of precision agriculture. 【Objective】Therefore, this study proposes a hybrid modeling framework base... Y. Ma, J. Zhang, D. Pan, Q. Wu, S. Xiaoyu, X. Xu

4. Use of Multispectral UAV Imagery to Monitor Late-Season Defoliation in Peanut Production Systems

Reduced leaf area late in the growing season is commonly associated with lower physiological activity in peanut plants, particularly when foliar diseases intensify near harvest. As canopy biomass declines, peg strength may be compromised, increasing the risk of pod loss during digging operations if harvest is delayed. Although canopy biomass decreases become more noticeable near harvest, visual field assessments do not always reflect belowground conditions, making it difficult to determine th... R. Dias borges, C. Pilcon, A. Felipe dos santos, L. Lacerda, C. Rossi

5. Autonomous Robotic Spraying System for Weed Management in Woody Perennial Crops

Weed management in woody crops remains a major agronomic, economic, and environmental challenge. In orchard environments, tree trunks, low canopies, and narrow intra-row spacing severely restrict conventional machinery access to the under-canopy zone. As a result, weed control near tree trunks remains predominantly manual. This limitation coincides with an increasing scarcity of agricultural labor, leading to higher production costs and delays in weed... M. Pérez-ruiz, L. Sánchez-fernández, A. Nizzoli, E. Apolo-apolo, J. Martínez-guanter

6. Machine Learning Pipeline to Estimate Soybean Rust Severity Using UAV-derived Multispectral Indices

Asian Soybean Rust is one of the most destructive diseases affecting soybean crops worldwide and can result in yield losses of up to 90% when control measures are not implemented in a timely manner. Conventional disease monitoring based on field scouting is time-consuming, labor-intensive, and inherently subjective, often failing to adequately represent the spatial variability of disease across production fields. These limitations highlight the need for automated, objective, and high throughp... S.A. Teixeira, R. Valdivino, R. Tsukahara, M. Ribeiro

7. Deep Learning-based Anomaly Detection System for Rice Crop Health Monitoring

Global food security relies heavily on the stable production of rice (Oryza sativa L.), yet cultivation remains vulnerable to various phytosanitary anomalies, including foliar diseases like Pyricularia and Rhynchosporium, scald, and abiotic stressors such as herbicide damage. Traditional agronomic management relies on visual scouting, which is inherently subjective, labor-intensive, and often leads to delayed interventions. This study proposes an automated, high-throughput solution for real-t... F.R. Jimenez lopez, A. Jimenez, D.Y. Garcia ramirez

8. Tracking Multi-Nutrient Dynamics in Spring Crops Using Field Hyperspectral Imaging and Chemometrics

Within crop nutrient ecology we still lack a clear and growth-stage-specific understanding of which nutrient elements are most limiting in field conditions and during different periods of the growing season, and how the (co-)limitation pattern is influenced by different management conditions. This is particularly relevant in Nordic systems with short growing seasons, where nutrient constraints can appear rapidly. At the same time, precision nutrient management still requires robust non-destru... E. Lennartsson, J. Oliveira, M. Weih

9. High-Sensitivity Flexible LIG/GO Humidity Sensors for Continuous Environmental Monitoring in Agricultural Applications

The efficiency of agricultural production depends substantially on the continuous monitoring of environmental variables, particularly humidity, which directly influences plant physiological processes, the physicochemical properties of soil, and the preservation of plant materials in the post-harvest stage. This study presents the development of a capacitive humidity sensor based on laser-induced graphene (LIG) and graphene oxide (GO), characterized by its flexibility and adaptability to diffe... A. La rosa, P. Silveira, B.B. Gallo, B.V. Lopes, L.M. Goncalves, N. Carreño

10. Evaluation of Horizontal Distribution in Spraying with RPA in Static and Dynamic Modes

The application of plant protection products (PPPs) using remotely piloted aircraft (RPA) represents a significant innovation in the context of modern agriculture, especially regarding the pursuit of greater operational efficiency and the reduction of environmental impacts. The use of this technology has stood out for the possibility of carrying out more precise applications, with better control of droplet deposition and potential reduction in in input consumption. However, despite its promis... G. Gomes mesquita , J.B. Costa souza, I. De oliveira vieira, S.L. Hatum de almeida, V.D. Carreira, R.P. Silva, A. Felipe dos santos

11. Characterizing Cross-Crop Stink Bug Spectral Signatures from Hyperspectral Data

Effective crop protection in agricultural production systems requires the ability to detect pest-induced stress in a timely and reliable manner. In large-scale farming systems, stink bugs attack multiple crop species, making cross-crop pest detection a critical capability for scalable monitoring solutions. Rather than developing crop-specific models that require retraining for each species, identifying crop-independent spectral signatures of stink bug infestation enables transferable detectio... A.O. Françani, L. Zhao, J. Ferreira , J. Yan, E.J. Ferreira, L.A. Jorge

12. Spatio-Temporal Sampling-Point Allocation for High-Density Robotic Pest Monitoring and Precision Treatment

Efficient monitoring of pests in crops, such as the two-spotted spider mite (Tetranychus urticae), is essential for optimizing pesticide application and minimizing yield losses. However, conventional manual scouting is labor-intensive and costly, limiting spatial coverage and sampling frequency. Consequently, infestation hotspots are often detected too late, reducing the effectiveness of timely and targeted interventions. This ... D. Levanon, Y. Cohen, R. Gafni, L. Shmuel, Y. Edan

13. Guiding Spot Sprayer Decisions: Toward Species-Selective Weed Control

Site-specific weed management is a key approach in precision crop protection, enabling spatially targeted herbicide application based on within-field variability in weed distribution. However, most operational spot-spraying systems rely on uniform nozzle activation rules, implicitly treating all detected weeds equally despite differences in competitive ability and ecological function. This limits the potential of precision systems to exploit species-level differentiation in practice. ... M. Gentili, M.S. Madsen, V.A. Nichols, R.N. Jørgensen, J.R. Jørgensen,

14. Early Detection of Soybean Pest Infestations Using Leaf-Level Reflectance Spectroradiometry and Machine Learning

The agricultural sector plays a central role in sustaining global food production, energy supply, and economic development. However, population growth, climate change, resource scarcity, and increasing sustainability demands have intensified production challenges. Pest and disease outbreaks are major contributors to crop losses worldwide, underscoring the urgent need for reliable methods capable of enabling early detection and timely intervention. In this context, leaf-level spectroradiometry... M. Lima, J.C. Felipe, E.J. Ferreira, L.A. Jorge, L. Zhao

15. Multi-Band UAV-Borne SAR Sensitivity (C, L, and P Bands) for Detecting Leaf-Cutting Ant Nests in Eucalyptus Plantations

Planted forests in Brazil cover approximately 10.5 million hectares and are recognized worldwide for sustainable management and the supply of bioproducts derived from renewable raw materials. In addition, the country stands out in pulp production and exports, ranking second only to the United States. However, the planted forest sector has faced phytosanitary challenges, particularly related to leaf-cutting ants, which cause biomass losses and reduce leaf area, compromising photosynthetic capa... W. Batista da silva , A. Santos, T. Costa barboza, O.P. Costa, G. Valdes fernandez , M. Ciscato, G. . Silveira, R. . Filho

16. From Area-wide Management to Site-specific and Individual Plant Management: the Evolution of Weed Control in Argentina

Selective herbicide spraying represents one of the most significant innovations in the evolution of Precision Agriculture, enabling a shift from uniform broadcast applications toward spatially explicit and plant-by-plant management models. In a context characterized by the increasing prevalence of herbicide-resistant weed biotypes, rising input costs, and growing environmental and regulatory pressure, these technologies are becoming strategic tools to enhance input-use efficiency and improve ... I. Lo celso, N. Ciancio, F.M. Scaramuzza

17. Detection of Sticky Disease (PMeV) and Papaya Ringspot (PRSV-P) in Papaya Plants (Carica papaya) Using Optical Sensors

The papaya plant (Carica papaya L.) is one of the main tropical fruit crops cultivated in Brazil, with significant economic and social importance, especially in the state of Espírito Santo. Despite its high productive potential, the crop has been severely affected by viral diseases, notably papaya ringspot, caused by Papaya ringspot virus type P (PRSV-P), and sticky disease, associated with the viral complex PMeV and PMeV2. Given this scenario, the present study aimed to evaluate the p... D.C. Gonçalves, S. . hatum, M. Sousa vieira , D. . júnior, W. . Machado, A. . nunes, N. . corrêa dalvi, R.L. polastreli

18. Comparison Between Conventional and Aerial Spraying Using Remotely Piloted Aircraft in the Control of the Coffee Leaf Miner

A traça-do-café (Leucoptera coffeella) é uma das principais influências que influenciam o cultivo do café, impactando diretamente a produtividade da cultura. Seu controle pode ser desafiador em algumas áreas devido às condições do terreno e à escassez de mão de obra. Este estudo teve como objetivo comparar a eficiência agronômica e a dinâmica de controle do traçado-do-café utilizando do... W. Batista da silva , A. Santos, A. Felipe dos santos, T. Costa barboza, O.P. Costa, G.L. silveira, R.Q. Alves

19. Digital Agriculture in Decision-Making for Sustainable Disease Management in Soybean Crops

Soybean (Glycine max L.) stands out as one of the main crops of agronomic interest, widely used in human and animal nutrition due to its high protein content and diversity of derivatives. Soybean crop productivity is strongly influenced by meteorological conditions, adopted management practices, and the incidence of pathogens, which can significantly reduce the plant’s photosynthetically active area, directly impacting final yield. In this context, the present study aimed to ev... E. Rolim farias da silva, L. Lüdtke, G. Ductra bortolotti, I. Maldaner, L. , J. sgarbossa, L. Silveira pavão, A. Müllich