Artificial intelligence applications in precision agriculture to predict the effect of Root-Knot nematodes and grafting on vegetable crop health from proximal remote sensing machines

Yassine Hamdane; Khaoula Abrougui; Francisco Javier Sorribas; José Luis Araus; Shawn C. Kefauver

Article Details

Artificial intelligence applications in precision agriculture to predict the effect of Root-Knot nematodes and grafting on vegetable crop health from proximal remote sensing machines

Authors:

Yassine Hamdane | Khaoula Abrougui | Francisco Javier Sorribas | José Luis Araus | Shawn C. Kefauver

Publisher:

Journal of Oasis Agriculture and Sustainable Development (JOASD)

Journal:

JOURNAL OF OASIS AGRICULTURE AND SUSTAINABLE DEVELOPMENT Vol.4 Issue 4, pp.1-10

Document Type:

Article

Publication Date:

1/2022

Document Language:

English

Document ID (Org No.):

2001529700

pISSN:

2724-7007

Keywords:

Abstract:

 In precision agriculture, the Normalized Difference Vegetative Index (NDVI) considers the spectral characteristics of healthy green vegetation. This index is an effective way of detecting the green state of plants. This is why we choose to use NDVI as a reference index to predict the effect of Root-Knot nematodes and grafting on vegetable crop health from proximal remote sensing machines. These machines were used to estimate different physiological, biochemical, and agronomic parameters as indicators of stress (GA, GGA, SPAD, and canopy temperature). Leaf level pigments were measured using a handheld sensor (SPAD). Canopy vigor and biomass were assessed using vegetation indices derived from RGB images and the NDVI was measured with a portable spectroradiometer (Greenseeker). The plant level water stress was assessed indirectly by plant temperature using an infrared thermometer. We conclude that the grafted plants were less stressed and more protected against nematode attack. The comparison of NDVI index predicted by AI models showed that artificial neural network MLP demonstrated the best prediction performance than the linear regression method. However, their R-squared decreased from 0.820 to 0.772, and NRMSE increased from 12.3% to 12.4%, respectively.

Article Details

Artificial intelligence applications in precision agriculture to predict the effect of Root-Knot nematodes and grafting on vegetable crop health from proximal remote sensing machines

Authors:

Yassine Hamdane | Khaoula Abrougui | Francisco Javier Sorribas | José Luis Araus | Shawn C. Kefauver

Publisher:

Journal of Oasis Agriculture and Sustainable Development (JOASD)

Journal:

JOURNAL OF OASIS AGRICULTURE AND SUSTAINABLE DEVELOPMENT Vol.4 Issue 4, pp.1-10

Document Type:

Article

Publication Date:

1/2022

Document Language:

English

Document ID (Org No.):

2001529700

pISSN:

2724-7007

Artificial intelligence

precision agriculture

crop health indicator

grafting

remote sensing machines

Issues

Article Details

Artificial intelligence applications in precision agriculture to predict the effect of Root-Knot nematodes and grafting on vegetable crop health from proximal remote sensing machines

Authors: Yassine Hamdane | Khaoula Abrougui | Francisco Javier Sorribas | José Luis Araus | Shawn C. Kefauver

Publisher: Journal of Oasis Agriculture and Sustainable Development (JOASD)

Journal: JOURNAL OF OASIS AGRICULTURE AND SUSTAINABLE DEVELOPMENT Vol.4 Issue 4, pp.1-10

Document Type: Article

Publication Date: 1/2022

Document Language: English

Document ID (Org No.): 2001529700

pISSN: 2724-7007

Artificial intelligence

precision agriculture

crop health indicator

grafting

remote sensing machines

Issues

Authors:

Yassine Hamdane | Khaoula Abrougui | Francisco Javier Sorribas | José Luis Araus | Shawn C. Kefauver

Publisher:

Journal of Oasis Agriculture and Sustainable Development (JOASD)

Journal:

JOURNAL OF OASIS AGRICULTURE AND SUSTAINABLE DEVELOPMENT Vol.4 Issue 4, pp.1-10

Document Type:

Article

Publication Date:

1/2022

Document Language:

English

Document ID (Org No.):

2001529700

pISSN:

2724-7007