Proceedings :: International Society of Precision Agriculture

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Kalmar, J

Balabantaray, A

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Authors

Nyeki, A

Milics, G

Kovacs, A.J

Neményi, M

Kalmar, J

Balabantaray, A

Pitla, S

Topics

Precision Agriculture and Climate Change

Artificial Intelligence (AI) in Agriculture

Type

Oral

Year

2016

2024

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Filter results2 paper(s) found.
1. Climate Sensitivity Analysis on Maize Yield on the Basis of Precision Crop Production In this paper by prediction we have defined maize yield in precision plant production technologies according to five different climate change scenarios (Ensembles Project) until 2100 and in one scenario until 2075 using DSSAT v. 4.5.0. CERES-Maize decision support model. Sensitivity analyses were carried out. The novelty of the method presented here is that precision, variable rate technologies from relatively small areas (in our case 2500 m2) enable a large amount of data to be collected... A. Nyeki, G. Milics, A.J. Kovacs, M. Neményi, J. Kalmar Download paper
2. AI Enabled Targeted Robotic Weed Management In contemporary agriculture, effective weed management presents a considerable challenge necessitating innovative solutions. Traditional weed control methods often rely on the indiscriminate application of broad-spectrum herbicides, giving rise to environmental concerns and unintended crop damage. Our research addresses this challenge by introducing an innovative AI-enabled robotic system designed to identify and selectively target weeds in real-time. Utilizing the advanced Machine Learning technique... A. Balabantaray, S. Pitla

Filter results2 paper(s) found.

1. Climate Sensitivity Analysis on Maize Yield on the Basis of Precision Crop Production

In this paper by prediction we have defined maize yield in precision plant production technologies according to five different climate change scenarios (Ensembles Project) until 2100 and in one scenario until 2075 using DSSAT v. 4.5.0. CERES-Maize decision support model. Sensitivity analyses were carried out. The novelty of the method presented here is that precision, variable rate technologies from relatively small areas (in our case 2500 m2) enable a large amount of data to be collected... A. Nyeki, G. Milics, A.J. Kovacs, M. Neményi, J. Kalmar

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2. AI Enabled Targeted Robotic Weed Management

In contemporary agriculture, effective weed management presents a considerable challenge necessitating innovative solutions. Traditional weed control methods often rely on the indiscriminate application of broad-spectrum herbicides, giving rise to environmental concerns and unintended crop damage. Our research addresses this challenge by introducing an innovative AI-enabled robotic system designed to identify and selectively target weeds in real-time. Utilizing the advanced Machine Learning technique... A. Balabantaray, S. Pitla