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Wang, J.M
Bouhlel, N
Sanches, G.M
Zamora, I
Won, K
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Authors
Wang, J.M
Li, C.M
Yang, X.M
Huang, W.M
Yang, H.M
Xu, X.M
Rossant, F
Orensanz, J
Boisgontier, D
Bouhlel, N
Lagarrigue, M
Castro, S.G
Kolln, O.T
Nakao, H.S
Franco, H.C
Braunbeck, O
Graziano Magalhães, P.S
Sanches, G.M
Zamora, I
Wulfsohn, D
Sanches, G.M
Kolln, O.T
Franco, H.C
Magalhaes, P.S
Duft, D.G
Sanches, G.M
Amaral, L.R
Pitrat, T
Brasco, T
Magalhaes, P.S
Duft, D.G
Franco, H.C
Sanches, G.M
Cardoso, T.F
Chagas, M.F
Luciano, A.C
Duft, D.G
Magalhães, P.S
Franco, H.C
Bonomi, A
Sanches, G.M
Magalhães, P.S
Franco, H.C
Remacre, A.Z
Michelon, G.K
Sanches, G.M
Valente, I.Q
Bazzi, C.L
de Menezes, P.L
Amaral, L.R
Magalhaes, P.G
Sanches, G.M
Otto, R
Pereira, F.R
Alahe, M
Kemeshi, J.O
Chang, Y
Won, K
Yang, X
Sher, M
Topics
Remote Sensing Applications in Precision Agriculture
Engineering Technologies and Advances
Precision Nutrient Management
Applications of UAVs (unmanned aircraft vehicle systems) in precision agriculture
Big Data Mining & Statistical Issues in Precision Agriculture
Proximal Sensing in Precision Agriculture
Precision Agriculture and Global Food Security
Site-Specific Nutrient, Lime and Seed Management
Decision Support Systems
In-Season Nitrogen Management
Edge Computing and Cloud Solutions
Type
Poster
Oral
Year
2012
2014
2016
2018
2022
2024
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Filter results11 paper(s) found.

1. Estimation of Leaf Nitrogen Concentration in Barley with In Situ Hyperspectral Measurements

Leaf nitrogen concentration (LNC), a good indicator of nitrogen status in crop, is of special significance to diagnose nutrient stress and guide nitrogen fertilization in fields. Due to its non-destructive and quick advantages, hyperspectral remote sensing plays a unique role... J.M. Wang, C.M. Li, X.M. Yang, W.M. Huang, H.M. Yang, X.M. Xu

2. Sound Based Detection Of Moths In Open Fields

Introduction   Open field farming of tomatoes suffers from the presence of harmful moths whose larvas are devastating. Detecting automatically the presence of moths allows regulating the use of pesticides, according to the actual population present in the field. Up to now, sex pheromone traps have been used, the number of captured insects giving some indication about the population. However, proper inspection of the traps is... F. Rossant, J. Orensanz, D. Boisgontier, N. Bouhlel, M. Lagarrigue

3. The Most Sensitive Growth Stage To Quantify Nitrogen Stress In Sugarcane Using Active Crop Canopy Sensor

The use of sensors that allow the application of nitrogen fertilizer at variable rate has been widely used by researchers in many agricultural crops, but without success in sugarcane, probably due to the difficulty of diagnosing the nutritional status of the crop for nitrogen (N). Active crop canopy sensors are based on the principle that the spectral reflectance curve of the leaves are modified by N level. Researchers in USA indicated that in-season N stress in corn can be detected... S.G. Castro, O.T. Kolln, H.S. Nakao, H.C. Franco, O. Braunbeck, P.S. Graziano magalhães, G.M. Sanches

4. The Use Of A Multirotor And High-Resolution Imaging For Precision Horticulture In Chile: An Industry Perspective

As part of the prototype development of a yield forecasting and precision agriculture service for Chilean horticulture, we evaluated the use of an eight-rotor Mikrokopter for high-resolution aerial imaging to support ground-based surveys. Specific considerations for UAV and communications performance under Chilean conditions are windy conditions, limited space for take-off and landing in orchards, tree height and plantation density, and the presence of high metal contents in soils. We discuss... I. Zamora, D. Wulfsohn

5. Translating Data into Knowledge - Precision Agriculture Database in a Sugarcane Production.

The advent of Information Technology in agriculture, surveying and data collection became a simple task, starting the era of "Big Data" in agricultural production. Currently, a large volume of data and information associated with the plant, soil and climate are collected quick and easily. These factors influence productivity, operating costs, investments and environment impacts. However, a major challenge for this area is the transformation of data and information... G.M. Sanches, O.T. Kolln, H.C. Franco, P.S. Magalhaes, D.G. Duft

6. Apparent Electrical Conductivity Sensors and Their Relationship with Soil Properties in Sugarcane Fields

One important tool within the technological precision agriculture (PA) package are the apparent electrical conductivity (ECa) sensors. This kind of sensor shows the ability in mapping soil physicochemical variability quickly, with high resolution and at low cost. However, the adoption of this technology in Brazil is not usual, particularly on sugarcane fields. A major issue for farmers is the applicability of ECa, how to convert ECa data in knowledge that may assist the producer in decision-making... G.M. Sanches, L.R. Amaral, T. Pitrat, T. Brasco, P.S. Magalhaes, D.G. Duft, H.C. Franco

7. Economic and Environmental Impacts in Sugarcane Production to Meet the Brazilian Ethanol Demands by 2030: The Role of Precision Agriculture

The agreement signed at COP-21 reaffirms the vital compromise of Brazil with sugarcane and ethanol production. To meet the established targets, the ethanol production should be 54 billion liters in 2030. From the agronomic standpoint, two alternatives are possible; increase the planted area and/or agricultural yield. The present study aimed to evaluate the economic and environmental impacts in sugarcane production meeting the established targets in São Paulo state. In this context, were... G.M. Sanches, T.F. Cardoso, M.F. Chagas, A.C. Luciano, D.G. Duft, P.S. Magalhães, H.C. Franco, A. Bonomi

8. Potential of Apparent Soil Electrical Conductivity to Describe Soil Spatial Variability in Brazilian Sugarcane Fields

The soil apparent electrical conductivity (ECa) has been highlighted in the literature as a tool with high potential to map the soil fertility of fields. However, sugarcane fields still lack results that show the applicability of this information to define the soil spatial variability and its fertility conditions. The objective of the present paper was to provide a comprehensive assessment of the relationship between ECa, evaluated by electromagnetic induction (EMI) sensor, and the spatial variability... G.M. Sanches, P.S. Magalhães, H.C. Franco, A.Z. Remacre

9. Optimized Soil Sampling Location in Management Zones Based on Apparent Electrical Conductivity and Landscape Attributes

One of the limiting factors to characterize the soil spatial variability is the need for a dense soil sampling, which prevents the mapping due to the high demand of time and costs. A technique that minimizes the number of samples needed is the use of maps that have prior information on the spatial variability of the soil, allowing the identification of representative sampling points in the field. Management Zones (MZs), a sub-area delineated in the field, where there is relative homogeneity in... G.K. Michelon, G.M. Sanches, I.Q. Valente, C.L. Bazzi, P.L. De menezes, L.R. Amaral, P.G. Magalhaes

10. Soil and Crop Factors to Site-specific Nitrogen Management on Sugarcane Fields

Nitrogen (N) is one of the most widely used fertilizers in crops and the most harmful to the environment. The increase fertilizers consumption, mainly N sources (one of the most widely fertilizer used in sugarcane fields), is one of the main factors underlying the sustainability of the entire production process. Currently, N recommendations in sugarcane are based only on the expected yield. However, there is little agronomic support for nitrogen (N) recommendations based on expected yield, despite... G.M. Sanches, R. Otto, F.R. Pereira

11. Securing Agricultural Data with Encryption Algorithms on Embedded GPU Based Edge Computing Devices

Smart Agriculture (SA) has captured the interest of both the agricultural business and the scientific community in recent years. Overall, SA aims to help the agricultural and food industry to avoid crop failures, loss of revenues as well as help farmers use inputs (such as fertilizers and pesticides) more efficiently by utilizing Internet of Things (IoT) devices and computing systems. However, rapid digitization and reliance on data-driven technologies create new security threats that can defeat... M. Alahe, J.O. Kemeshi, Y. Chang, K. Won, X. Yang, M. Sher