Proceedings :: International Society of Precision Agriculture

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Magalhães, P.G

McCornack, B

Mahjoub, O.A

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Authors

Mahjoub, O.A

Modaihsh, A.S

Fontenelli, J.V

Amaral, L.R

Demattê, J.M

Magalhães, P.G

Sanches, G

Spiesman, B

Grijalva, I

Holthaus, D

McCornack, B

Grijalva Teran, I.A

Spiesman, B

Clark, N

McCornack, B

Topics

Precision Conservation and Carbon Management

Proximal Sensing in Precision Agriculture

Big Data, Data Mining and Deep Learning

Artificial Intelligence (AI) in Agriculture

Type

Poster

Oral

Year

2012

2016

2024

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Filter results4 paper(s) found.
1. Soil Salinity, Sand Encroachment and Erosion as Indicators of Land Degradation in Harad Center, Saudi Arabia This study presents the main results of a thorough evaluation of land degradation in Saudi Arabia (Harad Centre). The study was carried out in 2006-2007 as part of a project aimed to study features and causes of land degradation in Saudi Arabia. The study area occupies... O.A. Mahjoub, A.S. Modaihsh Download paper
2. Soil Attributes Estimation Based on Diffuse Reflectance Spectroscopy and Topographic Variability The local management of crop areas, which is the basic concept of precision agriculture, is essential for increasing crop yield. In this context, diffuse reflectance spectroscopy (DRS) and digital elevation modelling (DEM) appears as an important technique for determining soil properties, on an adequate scale to agricultural management, enabling faster and less costly evaluations in soil studies. The objective of this work was to evaluate the use of DRS together with topographic parameters for... J.V. Fontenelli, L.R. Amaral, J.M. Demattê, P.G. Magalhães, G. Sanches Download paper
3. Sampling Bumble Bees and Floral Resources Using Deep Learning and UAV Imagery Pollinators, essential components of natural and agricultural systems, forage over relatively large spatial scales. This is especially true of large generalist species, like bumble bees. Thus, it can be difficult to estimate the amount and diversity of floral resources available to them. Floral cover and diversity are often estimated over large areas by extrapolation from small scale samples (e.g., a 1-m quadrat) but the accuracy of such estimates can vary depending on the spatial patchiness of... B. Spiesman, I. Grijalva, D. Holthaus, B. Mccornack
4. Detection of Sorghum Aphids with Advanced Machine Vision Sorghum aphid, Melanaphis sorghi (Theobald), became a significant pest concern due to the significant yield losses caused in the sorghum production region. Different management practices, including monitoring and applying insecticides, have been used to manage this invasive pest in sorghum. The most common management strategy consists of visual assessments of aphids on sorghum leaves to determine an economic threshold level to spray. However, because of their rapid reproduction,... I.A. Grijalva Teran, B. Spiesman, N. Clark, B. Mccornack Download paper

Filter results4 paper(s) found.

1. Soil Salinity, Sand Encroachment and Erosion as Indicators of Land Degradation in Harad Center, Saudi Arabia

This study presents the main results of a thorough evaluation of land degradation in Saudi Arabia (Harad Centre). The study was carried out in 2006-2007 as part of a project aimed to study features and causes of land degradation in Saudi Arabia. The study area occupies... O.A. Mahjoub, A.S. Modaihsh

Download paper

2. Soil Attributes Estimation Based on Diffuse Reflectance Spectroscopy and Topographic Variability

The local management of crop areas, which is the basic concept of precision agriculture, is essential for increasing crop yield. In this context, diffuse reflectance spectroscopy (DRS) and digital elevation modelling (DEM) appears as an important technique for determining soil properties, on an adequate scale to agricultural management, enabling faster and less costly evaluations in soil studies. The objective of this work was to evaluate the use of DRS together with topographic parameters for... J.V. Fontenelli, L.R. Amaral, J.M. Demattê, P.G. Magalhães, G. Sanches

Download paper

3. Sampling Bumble Bees and Floral Resources Using Deep Learning and UAV Imagery

Pollinators, essential components of natural and agricultural systems, forage over relatively large spatial scales. This is especially true of large generalist species, like bumble bees. Thus, it can be difficult to estimate the amount and diversity of floral resources available to them. Floral cover and diversity are often estimated over large areas by extrapolation from small scale samples (e.g., a 1-m quadrat) but the accuracy of such estimates can vary depending on the spatial patchiness of... B. Spiesman, I. Grijalva, D. Holthaus, B. Mccornack

4. Detection of Sorghum Aphids with Advanced Machine Vision

Sorghum aphid, Melanaphis sorghi (Theobald), became a significant pest concern due to the significant yield losses caused in the sorghum production region. Different management practices, including monitoring and applying insecticides, have been used to manage this invasive pest in sorghum. The most common management strategy consists of visual assessments of aphids on sorghum leaves to determine an economic threshold level to spray. However, because of their rapid reproduction,... I.A. Grijalva Teran, B. Spiesman, N. Clark, B. Mccornack

Download paper