Proceedings :: International Society of Precision Agriculture

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Ribeiro Silva, G

Teixeira, S.A

Xu, X

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Authors

Teixeira, S.A

Valdivino, R

Tsukahara, R

Ribeiro, M

Dos Reis Rodrigues, A.E

da Silva, M.A

Rodrigues Oliveira, J.D

Ribeiro Silva, G

Lopes de Brito Filho, A

da Silva Brochado, M.G

Krohn, N.G

Morlin Carneiro, F

Xu, X

Meng, Y

Yang, G

Song, Y

Xue, H

Topics

Precision Crop Protection, Pest, and Plant Health

Remote and Proximal Sensing of Soils and Crops

Type

Oral

Poster

Year

2026

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Filter results3 paper(s) found.
1. 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 throughput... S.A. Teixeira, R. Valdivino, R. Tsukahara, M. Ribeiro Download paper
2. Utilization of Proximal Remote Sensing As a Non-destructive Method for Assessing the Quality of Corn Seeds The physiological quality of corn seeds plays a key role in crop establishment. It directly influences final productivity. Although germination and vigor tests are well established, they have practical limitations. These tests are time-consuming. They require laboratory infrastructure and can involve destructive procedures. These factors limit their use in situations demanding faster, scalable assessments. In this scenario, proximal remote sensing has gained attention as a practical, non-destructive... A.E. Dos Reis Rodrigues, M.A. Da Silva, J.D. Rodrigues Oliveira, G. Ribeiro Silva, A. Lopes De Brito Filho, M.G. Da Silva Brochado, N.G. Krohn, F. Morlin Carneiro Download paper
3. Evaluation of Vertical C/N Distribution in Maize Canopy Using Ensemble Learning with Hyperspectral Data Metabolic status of carbon (C) and nitrogen (N) as two essential elements in crop plants has essential influence on the ultimate formation of yield and quality in crop production. Ratio of carbon to nitrogen (C/N), defined as the ratio of LCC (leaf carbon concentration) to LNC (leaf nitrogen concentration), is useful for understanding and quantifying carbon and nitrogen metabolism in crops, and is one metrics for effectively evaluating the balance of carbon and nitrogen, nutrient status and growth... X. Xu, X. Xu, Y. Meng, G. Yang, Y. Song, H. Xue Download paper

Filter results3 paper(s) found.

1. 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 throughput... S.A. Teixeira, R. Valdivino, R. Tsukahara, M. Ribeiro

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2. Utilization of Proximal Remote Sensing As a Non-destructive Method for Assessing the Quality of Corn Seeds

The physiological quality of corn seeds plays a key role in crop establishment. It directly influences final productivity. Although germination and vigor tests are well established, they have practical limitations. These tests are time-consuming. They require laboratory infrastructure and can involve destructive procedures. These factors limit their use in situations demanding faster, scalable assessments. In this scenario, proximal remote sensing has gained attention as a practical, non-destructive... A.E. Dos Reis Rodrigues, M.A. Da Silva, J.D. Rodrigues Oliveira, G. Ribeiro Silva, A. Lopes De Brito Filho, M.G. Da Silva Brochado, N.G. Krohn, F. Morlin Carneiro

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3. Evaluation of Vertical C/N Distribution in Maize Canopy Using Ensemble Learning with Hyperspectral Data

Metabolic status of carbon (C) and nitrogen (N) as two essential elements in crop plants has essential influence on the ultimate formation of yield and quality in crop production. Ratio of carbon to nitrogen (C/N), defined as the ratio of LCC (leaf carbon concentration) to LNC (leaf nitrogen concentration), is useful for understanding and quantifying carbon and nitrogen metabolism in crops, and is one metrics for effectively evaluating the balance of carbon and nitrogen, nutrient status and growth... X. Xu, X. Xu, Y. Meng, G. Yang, Y. Song, H. Xue

Download paper