Proceedings :: International Society of Precision Agriculture

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Fenech, A

Kayad, A.G

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Authors

Al-Gaadi, K

Hassaballa, A.A

Tola, E

Madugundu, R

Kayad, A.G

Javed, B

Cambouris, A

Duchemin, M

Longchamps, L

Basran, P.S

Arnold, S

Fenech, A

Karam, A

Topics

Precision Agriculture and Global Food Security

Type

Oral

Year

2018

2024

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Filter results2 paper(s) found.
1. Applying a Bivariate Frequency Ratio Technique for Potato High Yield Susceptibility Mapping Spatial variation of soil characteristics and vegetation conditions are viewed as the most important indicators of crop yield status. Therefore, this study was designed to develop a crop yield prediction model through spatial autocorrelation between the actual yield of potato (Solanum tuberosum L.) crop and selected yield status indicators (soil N, EC, pH, texture and vegetation condition), where the vegetation condition was represented by the cumulative normalized difference vegetation index... K. Al-gaadi, A.A. Hassaballa, E. Tola, R. Madugundu, A.G. Kayad Download paper
2. In-season Nitrogen Prediction Evaluation Using Airborne Imagery with AI Techniques in Commercial Potato Production In modern agriculture, timely and precise nitrogen (N) monitoring is essential to optimize resource management and improve trade benefits. Potato (Solanum tuberosum L.) is a staple food in many regions of the world, and improving its production is inevitable to ensure food security and promote related industries. Traditional methods of assessing nitrogen are labour-intensive, time-consuming, and require subjective observations. To address these limitations, a combination of multispectral... B. Javed, A. Cambouris, M. Duchemin, L. Longchamps, P.S. Basran, S. Arnold, A. Fenech, A. Karam Download paper

Filter results2 paper(s) found.

1. Applying a Bivariate Frequency Ratio Technique for Potato High Yield Susceptibility Mapping

Spatial variation of soil characteristics and vegetation conditions are viewed as the most important indicators of crop yield status. Therefore, this study was designed to develop a crop yield prediction model through spatial autocorrelation between the actual yield of potato (Solanum tuberosum L.) crop and selected yield status indicators (soil N, EC, pH, texture and vegetation condition), where the vegetation condition was represented by the cumulative normalized difference vegetation index... K. Al-gaadi, A.A. Hassaballa, E. Tola, R. Madugundu, A.G. Kayad

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2. In-season Nitrogen Prediction Evaluation Using Airborne Imagery with AI Techniques in Commercial Potato Production

In modern agriculture, timely and precise nitrogen (N) monitoring is essential to optimize resource management and improve trade benefits. Potato (Solanum tuberosum L.) is a staple food in many regions of the world, and improving its production is inevitable to ensure food security and promote related industries. Traditional methods of assessing nitrogen are labour-intensive, time-consuming, and require subjective observations. To address these limitations, a combination of multispectral... B. Javed, A. Cambouris, M. Duchemin, L. Longchamps, P.S. Basran, S. Arnold, A. Fenech, A. Karam

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