Proceedings :: International Society of Precision Agriculture

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Claro, E

McCallister, D.M

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Authors

Luiz Panini, R

Tamara, A.R

Franco, G.M

de Oliveira, V.C

Lemos, H.R

Nishikawa, M

Forti, P.R

Biagi, M

Dudek, L.F

Hauschild, M.C

Ruscito, G.N

da Silva, M.P

Claro, E

de Souza, Z.M

Dhaliwal, A

Bastos, L

SV, K

Bhattarai, A

Jakhar, A

Poudel, K

McCallister, D.M

Jaconis , S.Y

Topics

Agricultural Robotics, Automation, and Mechanization

Predictive Modeling, Phenotyping, and Digital Tools for Decision Support

Type

Oral

Poster

Year

2026

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Filter results2 paper(s) found.
1. Field-Based Evaluation of Targeted Herbicide Spraying Efficacy: A Comparison of Qualitative and Quantitative Approaches Weed control remains one of the main challenges for maintaining agricultural productivity. In this context, selective spraying based on optical sensors and embedded vision systems emerges as a promising alternative for localized weed management, aligned with the principles of precision agriculture and sustainability. However, the adoption of these technologies on a commercial scale demands robust methods to evaluate agronomic efficacy and operational performance under real field conditions. This... R. Luiz Panini, A.R. Tamara, G.M. Franco, V.C. De Oliveira, H.R. Lemos, M. Nishikawa, P.R. Forti, M. Biagi, L.F. Dudek, M.C. Hauschild, G.N. Ruscito, M.P. Da Silva, E. Claro, Z.M. De Souza Download paper
2. Main Environmental and Variety Drivers of Cotton Seed Quality: Historical Insights from the United States Cotton Belt  Cotton seed quality traits including oil content, nitrogen (protein), and gossypol significantly influence seed value and end-use applications, yet their predictability based on environmental conditions across varied U.S. growing regions remains poorly understood. This study aimed to: (i) identify critical environmental predictors of seed composition; (ii) build machine learning models to predict seed quality as a function of seasonal weather patterns; and (iii) assess differences... A. Dhaliwal, L. Bastos, K. Sv, A. Bhattarai, A. Jakhar, K. Poudel, D.M. Mccallister, S.Y. Jaconis

Filter results2 paper(s) found.

1. Field-Based Evaluation of Targeted Herbicide Spraying Efficacy: A Comparison of Qualitative and Quantitative Approaches

Weed control remains one of the main challenges for maintaining agricultural productivity. In this context, selective spraying based on optical sensors and embedded vision systems emerges as a promising alternative for localized weed management, aligned with the principles of precision agriculture and sustainability. However, the adoption of these technologies on a commercial scale demands robust methods to evaluate agronomic efficacy and operational performance under real field conditions. This... R. Luiz Panini, A.R. Tamara, G.M. Franco, V.C. De Oliveira, H.R. Lemos, M. Nishikawa, P.R. Forti, M. Biagi, L.F. Dudek, M.C. Hauschild, G.N. Ruscito, M.P. Da Silva, E. Claro, Z.M. De Souza

Download paper

2. Main Environmental and Variety Drivers of Cotton Seed Quality: Historical Insights from the United States Cotton Belt 

Cotton seed quality traits including oil content, nitrogen (protein), and gossypol significantly influence seed value and end-use applications, yet their predictability based on environmental conditions across varied U.S. growing regions remains poorly understood. This study aimed to: (i) identify critical environmental predictors of seed composition; (ii) build machine learning models to predict seed quality as a function of seasonal weather patterns; and (iii) assess differences... A. Dhaliwal, L. Bastos, K. Sv, A. Bhattarai, A. Jakhar, K. Poudel, D.M. Mccallister, S.Y. Jaconis