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Amaral, M.M
Balzarini, M
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Authors
Balboa, G
Degioanni, A
Bongiovanni, R
Melchiori, R
Cerliani, C
Scaramuzza, F
Bongiovanni, M
Gonzalez, J
Balzarini, M
Videla, H
Amin, S
Esposito, G
Baker, A.P
, G
Oliveira, M.D
Zavala, E.H
Alves de Morais, R.M
Amaral, M.M
de Castro, A.Ă
Silva, L.S
Paccioretti, P
CĂłrdoba, M
Balzarini, M
Balboa, G
Topics
Education and Outreach in Precision Agriculture
Remote and Proximal Sensing of Soils and Crops
Decision Support Systems, Cloud Platforms, and Open Data Solutions
Type
Oral
Poster
Year
2022
2026
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1. Overcoming Educational Barriers for Precision Agriculture Adoption: a University Diploma in Precision Agriculture in Argentina

The lack of educational programs in Precision Agriculture (PA) has been reported as one of the barriers for adoption. Our goal was to improve professional competence in PA through education in crop variability, management, and effective practices of PA in real cases. In the last 20 years different efforts has been made in Argentina to increase adoption of PA. The Universidad Nacional de Rio Cuarto (UNRC) launched in 2021 the first University Diploma in PA, a 9-month program to train agronomist... G. Balboa, A. Degioanni, R. Bongiovanni, R. Melchiori, C. Cerliani, F. Scaramuzza, M. Bongiovanni, J. Gonzalez, M. Balzarini, H. Videla, S. Amin, G. Esposito

2. 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.

3. An Online Decision Support Tool for Homogeneous Zone Delineation in Precision Agriculture

Management zone delineation is a key component of site-specific management in precision agriculture, enabling the spatial optimization of inputs and an improved understanding of within-field variability. Traditionally, homogeneous zones have been derived from historical yield maps or soil-related variables obtained through proximal sensing. More recently, the increasing availability of multispectral satellite imagery and derived vegetation indices has expanded the range of data sources available...