Proceedings :: International Society of Precision Agriculture

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Alves de Morais, R.M

Archer, J.K

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Authors

Archer, J.K

Delgadillo, C.A

Shen, F

Alves de Morais, R.M

, G

Faria, R.D

Silva, L.S

Oliveira, M.D

Zavala, E.H

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

Standards & Data Stewardship

Agricultural Robotics, Automation, and Mechanization

Remote and Proximal Sensing of Soils and Crops

Type

Oral

Poster

Year

2016

2026

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Filter results3 paper(s) found.
1. Key Data Ownership, Privacy and Protection Issues and Strategies for the International Precision Agriculture Industry Precision agriculture companies seek to leverage technology to process greater volumes of data, greater varieties of data, and at a velocity unfathomable to most. The promises of boundless benefits are coupled with risks associated with data ownership, stewardship and privacy. This paper presents some risks related to the management of farm data, in general, as well as those unique to operating in the international arena. Examples of U.S. and international laws related to data protection... J.K. Archer, C.A. Delgadillo, F. Shen Download paper
2. 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
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. Key Data Ownership, Privacy and Protection Issues and Strategies for the International Precision Agriculture Industry

Precision agriculture companies seek to leverage technology to process greater volumes of data, greater varieties of data, and at a velocity unfathomable to most. The promises of boundless benefits are coupled with risks associated with data ownership, stewardship and privacy. This paper presents some risks related to the management of farm data, in general, as well as those unique to operating in the international arena. Examples of U.S. and international laws related to data protection... J.K. Archer, C.A. Delgadillo, F. Shen

Download paper

2. 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

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.