Proceedings :: International Society of Precision Agriculture

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Arruda, P.M

Alves de Morais, R.M

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Authors

Alves de Morais, R.M

, G

Faria, R.D

Silva, L.S

Oliveira, M.D

Zavala, E.H

Leite, D.H

Valente, D.S

Arruda, P.M

Tancredi, F.D

Queiroz, D

Dumbá Monteiro de Castro, G

Baker, A.P

, G

Oliveira, M.D

Zavala, E.H

Alves de Morais, R.M

Amaral, M.M

de Castro, A.�

Silva, L.S

Topics

Agricultural Robotics, Automation, and Mechanization

Decision Support Systems, Cloud Platforms, and Open Data Solutions

Remote and Proximal Sensing of Soils and Crops

Type

Poster

Oral

Year

2026

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Filter results3 paper(s) found.
1. Effect of Terrain Slope Obtained by LiDAR on Operational Performance in Semi-mechanized Coffee Transplanting with Autopilot. The application of precision agriculture techniques has become an important tool in surveying coffee plantations, allowing for the rapid assessment of slope profiles in these areas and indicating the possibility of mechanizing the plots. Therefore, there is a need to work with quality in semi-mechanized transplanting operations using autopilot to optimize future processes related to coffee cultivation. The objective of this study was to determine the efficiency of use and mechanical availability... R. , G. , R.D. Faria, L.S. Silva, M.D. Oliveira, E.H. Zavala
2. Web Application Based on CNN for Classification of Biotic and Abiotic Stresses in Coffee Leaves The use of digital systems can assist coffee growers and professionals in diagnosing stresses that affect coffee plantations, ensuring that crop management is carried out correctly and efficiently. Therefore, the aim of this study was to develop a web application based on a pre-trained Convolutional Neural Network to classify coffee leaf images exhibiting symptoms of biotic and abiotic stresses. Initially, a dataset consisting of coffee leaf images affected by biotic and abiotic stresses was constructed.... D.H. Leite, D.S. Valente, P.M. Arruda, F.D. Tancredi, D. Queiroz, G. Dumbá monteiro de castro Download paper
3. Spectral Behavior of Coffee Fruit Ripeness Using a Hyperspectral Camera Selective harvesting is essential to ensure high beverage quality in coffee production; however, the coexistence of fruits at multiple ripeness stages on the same plant makes manual selection subjective, labor‑intensive, and time‑consuming. This preliminary study aimed to develop a non‑destructive method based on spectral information for the classification of Coffea arabica L. cv. Arara fruits at green (unripe) and yellow (ripe) stages, using images acquired on a laboratory bench with hyperspectral... A. Palma diniz baker, G. , M.D. Oliveira, E.H. Zavala, R. , M.M. Amaral, A.

Filter results3 paper(s) found.

1. Effect of Terrain Slope Obtained by LiDAR on Operational Performance in Semi-mechanized Coffee Transplanting with Autopilot.

The application of precision agriculture techniques has become an important tool in surveying coffee plantations, allowing for the rapid assessment of slope profiles in these areas and indicating the possibility of mechanizing the plots. Therefore, there is a need to work with quality in semi-mechanized transplanting operations using autopilot to optimize future processes related to coffee cultivation. The objective of this study was to determine the efficiency of use and mechanical availability... R. , G. , R.D. Faria, L.S. Silva, M.D. Oliveira, E.H. Zavala

2. Web Application Based on CNN for Classification of Biotic and Abiotic Stresses in Coffee Leaves

The use of digital systems can assist coffee growers and professionals in diagnosing stresses that affect coffee plantations, ensuring that crop management is carried out correctly and efficiently. Therefore, the aim of this study was to develop a web application based on a pre-trained Convolutional Neural Network to classify coffee leaf images exhibiting symptoms of biotic and abiotic stresses. Initially, a dataset consisting of coffee leaf images affected by biotic and abiotic stresses was constructed.... D.H. Leite, D.S. Valente, P.M. Arruda, F.D. Tancredi, D. Queiroz, G. Dumbá monteiro de castro

Download paper

3. Spectral Behavior of Coffee Fruit Ripeness Using a Hyperspectral Camera

Selective harvesting is essential to ensure high beverage quality in coffee production; however, the coexistence of fruits at multiple ripeness stages on the same plant makes manual selection subjective, labor‑intensive, and time‑consuming. This preliminary study aimed to develop a non‑destructive method based on spectral information for the classification of Coffea arabica L. cv. Arara fruits at green (unripe) and yellow (ripe) stages, using images acquired on a laboratory bench with hyperspectral... A. Palma diniz baker, G. , M.D. Oliveira, E.H. Zavala, R. , M.M. Amaral, A.