Proceedings :: International Society of Precision Agriculture

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Amin, S

Ochoa, O

Ward, M.D

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Authors

Jha, S

Saraswat, D

Ward, M.D

Balboa, G

Degioanni, A

Bongiovanni, R

Melchiori, R

Cerliani, C

Scaramuzza, F

Bongiovanni, M

Gonzalez, J

Balzarini, M

Videla, H

Amin, S

Esposito, G

Erazo, E

Mosquera, C

Ochoa, O

Topics

Big Data, Data Mining and Deep Learning

Education and Outreach in Precision Agriculture

Artificial Intelligence (AI) in Agriculture

Type

Oral

Year

2018

2022

2024

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Filter results3 paper(s) found.
1. Analyzing Trends for Agricultural Decision Support System Using Twitter Data The trends and reactions of the general public towards global events can be analyzed using data from social platforms, including Twitter. The number of tweets has been reported to help detect variations in communication traffic within subsets like countries, age groups and industries. Similarly, publicly accessible data and (in particular) data from social media about agricultural issues provide a great opportunity for obtaining instantaneous snapshots of farmers’ opinions and a method to... S. Jha, D. Saraswat, M.D. Ward Download paper
2. 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 Download paper
3. RMAPs: an Integrated Tool to Delimitate Homogeneous Management Zones Management zones are one of the most studied methods in precision agriculture to optimize crop yield from the soil, plant, management, and climate input parameters. We present Rmaps, an R package that integrates soil and crop yield spatial variability using geostatistical methods and one-hidden-layer perceptron (OHLP) to identify how input parameters influence crop yield and delimitate homogenous zones. From georeferenced data of soil, plant, management, climate, and crop yield parameters, Rmaps... E. Erazo, C. Mosquera, O. Ochoa Download paper

Filter results3 paper(s) found.

1. Analyzing Trends for Agricultural Decision Support System Using Twitter Data

The trends and reactions of the general public towards global events can be analyzed using data from social platforms, including Twitter. The number of tweets has been reported to help detect variations in communication traffic within subsets like countries, age groups and industries. Similarly, publicly accessible data and (in particular) data from social media about agricultural issues provide a great opportunity for obtaining instantaneous snapshots of farmers’ opinions and a method to... S. Jha, D. Saraswat, M.D. Ward

Download paper

2. 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

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3. RMAPs: an Integrated Tool to Delimitate Homogeneous Management Zones

Management zones are one of the most studied methods in precision agriculture to optimize crop yield from the soil, plant, management, and climate input parameters. We present Rmaps, an R package that integrates soil and crop yield spatial variability using geostatistical methods and one-hidden-layer perceptron (OHLP) to identify how input parameters influence crop yield and delimitate homogenous zones. From georeferenced data of soil, plant, management, climate, and crop yield parameters, Rmaps... E. Erazo, C. Mosquera, O. Ochoa

Download paper