Proceedings :: International Society of Precision Agriculture

Proceedings

Find matching any: Reset

Silva, R.P

» Add more authors

Add filter to result:

Authors

Oliveira, M.F

Morata, G.T

Ortiz, B

Silva, R.P

Jimenez, A

Barbosa, M

Duron, D

Rontani, F

Bortolon, G

Moreira, B

Oliveira, L

Setiyono, T

Shiratsuchi, L

Silva, R.P

Holland, K.H

Silva, R.P

Riquiel, J.D

Andrade da Silva, A

Sales, E

Oliveira, T.M

de Souza Silva, R

Topics

Big Data, Data Mining and Deep Learning

Artificial Intelligence (AI) in Agriculture

Remote and Proximal Sensing of Soils and Crops

Type

Poster

Oral

Year

2022

2024

2026

Home » Authors » Results

Authors

Filter results3 paper(s) found.
1. Coupling Machine Learning Algorithms and GIS for Crop Yield Predictions Based on Remote Sensing Imagery and Topographic Indices In-season yield prediction can support crop management decisions helping farmers achieve their yield goals. The use of remote sensing to predict yield it is an alternative for non-destructive yield assessment but coupling auxiliary data such as topography features could help increase the accuracy of yield estimation. Predictive algorithms that can effectively identify, process and predict yield at field scale base on remote sensing and topography still needed. Machine learning could be an alternative... M.F. Oliveira, G.T. Morata, B. Ortiz, R.P. Silva, A. Jimenez
2. Multi-sensor Remote Sensing: an AI-driven Framework for Predicting Sugarcane Feedstock Predicting saccharine and bioenergy feedstocks in sugarcane enables stakeholders to determine the precise time and location for harvesting a better product in the field. Consequently, it can streamline workflows while enhancing the cost-effectiveness of full-scale production. On one hand, Brix, Purity, and total reducing sugars (TRS) can provide meaningful and reliable indicators of high-quality raw materials for industrial food and fuel processing. On the other hand, Cellulose, Hemicellulose,... M. Barbosa, D. Duron, F. Rontani, G. Bortolon, B. Moreira, L. Oliveira, T. Setiyono, L. Shiratsuchi, R.P. Silva, K.H. Holland Download paper
3. Quality of Interpolated Maps of Soil Mechanical Resistance to Penetration as Support for Variable Rate Compaction Management Reliable continuous maps of soil mechanical penetration resistance (SMPR) are essential for site‑specific compaction management, but their usefulness depends on how interpolation methods respond to different spatial dependence patterns along the soil profile. Rather than seeking a single “best” interpolator, this study explicitly addresses how the suitability of interpolation methods varies as a function of the spatial structure of SMPR, an aspect seldom explored in depth in previous... R.P. Silva, J.D. Riquiel, A. Andrade Da Silva, E. Sales, T.M. Oliveira, R. De Souza Silva

Filter results3 paper(s) found.

1. Coupling Machine Learning Algorithms and GIS for Crop Yield Predictions Based on Remote Sensing Imagery and Topographic Indices

In-season yield prediction can support crop management decisions helping farmers achieve their yield goals. The use of remote sensing to predict yield it is an alternative for non-destructive yield assessment but coupling auxiliary data such as topography features could help increase the accuracy of yield estimation. Predictive algorithms that can effectively identify, process and predict yield at field scale base on remote sensing and topography still needed. Machine learning could be an alternative... M.F. Oliveira, G.T. Morata, B. Ortiz, R.P. Silva, A. Jimenez

2. Multi-sensor Remote Sensing: an AI-driven Framework for Predicting Sugarcane Feedstock

Predicting saccharine and bioenergy feedstocks in sugarcane enables stakeholders to determine the precise time and location for harvesting a better product in the field. Consequently, it can streamline workflows while enhancing the cost-effectiveness of full-scale production. On one hand, Brix, Purity, and total reducing sugars (TRS) can provide meaningful and reliable indicators of high-quality raw materials for industrial food and fuel processing. On the other hand, Cellulose, Hemicellulose,... M. Barbosa, D. Duron, F. Rontani, G. Bortolon, B. Moreira, L. Oliveira, T. Setiyono, L. Shiratsuchi, R.P. Silva, K.H. Holland

Download paper

3. Quality of Interpolated Maps of Soil Mechanical Resistance to Penetration as Support for Variable Rate Compaction Management

Reliable continuous maps of soil mechanical penetration resistance (SMPR) are essential for site‑specific compaction management, but their usefulness depends on how interpolation methods respond to different spatial dependence patterns along the soil profile. Rather than seeking a single “best” interpolator, this study explicitly addresses how the suitability of interpolation methods varies as a function of the spatial structure of SMPR, an aspect seldom explored in depth in previous... R.P. Silva, J.D. Riquiel, A. Andrade Da Silva, E. Sales, T.M. Oliveira, R. De Souza Silva