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Azam, S
Ahmad, A
Archila-Diaz, J.F
Anselmi, A.A
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Authors
Liaghat, S
Mansor, S
Shafri, H
Meon, S
Ehsani, R
Azam, S
Noh, N
Anselmi, A.A
Molin, J.P
Khosla, R
Anselmi, A.A
Federizzi , L.C
Bredemeier, C
Molin, J.P
Anselmi, A.A
Molin, J.P
eitelwein, M.T
Trevisan, R
Colaço, A
Archila-Diaz, J.F
Becker, M
Ahmad, A
Aggarwal, V
Saraswat, D
El Gamal, A
Johal, G
Topics
Precision Horticulture
Spatial Variability in Crop, Soil and Natural Resources
Profitability, Sustainability and Adoption
Spatial Variability in Crop, Soil and Natural Resources
Engineering Technologies and Advances
Applications of Unmanned Aerial Systems
Type
Poster
Oral
Year
2012
2014
2016
2022
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Filter results6 paper(s) found.

1. Early Detection of Oil Palm Fungal Disease Infestation Using A Mid-Infrared Spectroscopy Technique

Basal stem rot (BSR) caused by Ganoderma boninense is known as the most destructive disease of oil palm plantations in Southeast Asia. Ganoderma could potentially reduce the market share of palm oil for Malaysia. Currently Malaysia produces about 50% of the world’s supply of palm oil. Early, accurate, and non-destructive diagnosis of Ganoderma fungal infection is critical for management of this disease. Early disease management of Ganoderma could also prevent great losses in production and... S. Liaghat, S. Mansor, H. Shafri, S. Meon, R. Ehsani, S. Azam, N. Noh

2. Optimization Of Maize Yield: Relationship Between Management Zones, Hybrids And Plant Population

Corn is highly sensitive to variations in plant population and it is one of the most important practices influencing in grain yield. Knowledge about plant physiology and morphology allow understanding how the crop interacts with plant population variation. Considering that for each production system there is a population that optimizes the use of available resources it is necessary to manage plant population to reach maximum grain yield on each particular environment. This study... A.A. Anselmi, J.P. Molin, R. Khosla

3. Factors Related To Adoption Of Precision Agriculture Technologies In Southern Brazil

The adoption of technologies which allow the increase of food production with improving quality in addition to reduce the foot prints in the environment is important for agribusiness development. Precision Agriculture (PA) stands out as an option to aid the achievement of these goals. Brazil plays an important role to supply agricultural products and to demand technologies. However, research has focused on technical and economic implementation of PA technologies. Therefore, more information... A.A. Anselmi, L.C. Federizzi , C. Bredemeier, J.P. Molin

4. Positioning Strategy of Maize Hybrids Adjusting Plant Population by Management Zones

Choice of hybrid and accurate amount of plants per area determines grain yield and consequently net incomes. Local field adjustment in plant population is a strategy to manage spatial variability and optimize environmental resources that are not under farmer control (like soil type and water availability). This study aims to evaluate the response of hybrids by levels of plant population across management zones (MZ). Six different hybrids and five rates of plant populations were analyzed starting... A.A. Anselmi, J.P. Molin, M.T. Eitelwein, R. Trevisan, A. Colaço

5. Simulation of Curiosity and Exo Mars Rovers on Agriculture Terrain

Improving agricultural productivity is one of the biggest challenges Agriculture and Engineering face. A possible solution is the creation of soil databases and/or maps to apply precision agriculture techniques, aiming to produce more in the same land, using less agricultural supplies. This practice may be developed with the help of rovers applied to e.g. agricultural data collect, mapping, scouting and supply tasks. However, the rover needs to move and adapt to the terrain to obtain a real appropriate... J.F. Archila-diaz, M. Becker

6. Deep Learning-Based Corn Disease Tracking Using RTK Geolocated UAS Imagery

Deep learning-based solutions for precision agriculture have achieved promising results in recent times. Deep learning has been used to accurately classify different disease types and disease severity estimation as an initial stage for developing robust disease management systems. However, tracking the spread of diseases, identifying disease hot spots within cornfields, and notifying farmers using deep learning and UAS imagery remains a critical research gap. Therefore, in this study, high resolution,... A. Ahmad, V. Aggarwal, D. Saraswat, A. El gamal, G. Johal