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Gimenez, L.M
Firozjaei, M.K
Wetterich, C
Alchnatis, V
Hanyabui, E
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Authors
Wetterich, C
Belasque Jr., J
Marcassa, L
Bernardi, A.C
Gimenez, L.M
Silva, C.A
Machado, P.L
Meron, M
Tsipris, J
Orlov, V
Alchnatis, V
Cohen, Y
Fathololoumi, S
Firozjaei, M.K
Biswas, A
Daggupati, P
Freire de Oliveira, M.F
Ortiz, B.V
Souza, J.B
Bao, Y
Hanyabui, E
Oliveira, M.F
Ortiz, B.V
Hanyabui, E
Costa Souza, J.B
Sanz-Saez, A
Luns Hatum de Almeida , S
Pilcon, C
Vellidis, G
Topics
Precision Horticulture
Precision A-Z for Practitioners
Remote Sensing Application / Sensor Technology
Proximal and Remote Sensing of Soils and Crops (including Phenotyping)
Artificial Intelligence (AI) in Agriculture
Type
Oral
Poster
Year
2010
2008
2024
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Filter results6 paper(s) found.

1. Fluorescence Imaging Spectroscopy Applied To Citrus Diseases

Diseases are one of the most serious threats for citrus production worldwide. Sao Paulo, Brazil and Florida, USA, are the most important citrus producers and, both, are making efforts for citrus diseases control. Citrus canker is one of the serious diseases, caused by the Xanthomonas citri subsp. citri bacteria, that infects citrus trees and relatives, causing a large economic loss in the citrus juice production. Another important disease affecting the citrus production worldwide is the Huanglongbing... C. Wetterich, J. Belasque jr., L. Marcassa

2. Variable Rate Application Of Potassium Fertilizer For Soybean Crop Growth In A No-till System

Variable rate application of fertilizer has the potential to improve nutrient use efficiency, improve economic returns, and reduce negative environmental impacts. The objective of this study was to evaluate the variable rate application of potassium fertilizer to soybean crop in a no-till system. The study was conducted on a 13-ha soybean grain field in Carambeí, State of Paraná, Brazil in a Typic Hapludox. The area has been under no-tillage for more than 10 years growing grains... A.C. Bernardi, L.M. Gimenez, C.A. Silva, P.L. Machado

3. Crop Water Stress Mapping for Site Specific Irrigation by Thermal Imagery and Artificial Reference Surfaces

Variable rate irrigation machines or solid set systems have become technically feasible; however, crop water status mapping is necessary as a blueprint to match irrigation quantities to site-specific crop water demands. Remote thermal sensing can provide these maps in sufficient detail and at a timely delivery. In a set of aerial and ground scans at the Hula Valley, Israel, digital crop water stress maps were generated using geo-referenced high- resolution thermal imagery and artificial reference... M. Meron, J. Tsipris, V. Orlov, V. Alchnatis, Y. Cohen

4. A Fusion Strategy to Map Corn Crop Residues

Access to post-harvest residue coverage information is crucial for agricultural management and soil conservation. The purpose of this study was to present a new approach based on an ensemble at the decision level for mapping the corn residue. To this end, a set of Landsat 8 imagery and field data including the Residue Cover Fraction (RCF) of corn (149 samples), were used. Firstly, a map of common spectral indices for RCF modeling was prepared based on the spectral bands. Then, the efficiency of... S. Fathololoumi, M.K. Firozjaei, A. Biswas, P. Daggupati

5. Towards a Digital Peanut Profile Board: a Deep Learning Approach

Artificial intelligence techniques, particularly deep learning, offer promising avenues for revolutionizing object detection and counting algorithms in the context of digital agriculture. The challenges faced by peanut farmers, particularly the precise determination of optimal maturity for digging, have prompted innovative solutions. Traditionally, peanut maturity assessment has relied on the Peanut Maturity Index (PMI), employing a manual classification process with the aid of a peanut profile... M.F. Freire de oliveira, B.V. Ortiz, J.B. Souza, Y. Bao, E. Hanyabui

6. Use of Crop and Drought Spectral Indices to Support Harvest Decisions of Peanut Fields in Alabama

Harvest efficiency expressed in quantity and quality of peanut fields could increase if farmers are provided with tools to support harvest decisions. Peanut farmers still rely on a visual and empiric method to assess the right time of peanut maturity but this method does not account for within-field variability of crop growth and maturity. The integration of spectral vegetation indices to assess drought, soil moisture, and crop growth to predict peanut maturity can help farmers strengthen decisions... M.F. Oliveira, B.V. Ortiz, E. Hanyabui, J.B. Costa souza, A. Sanz-saez, S. Luns hatum de almeida , C. Pilcon, G. Vellidis