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Simard, M
Jeong, D
Girona, J
Bűdi, K
Bastos, L
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Authors
Panneton, B
Simard, M
Leroux, G.D
Longchamps, L
Zarco-Tejada, P.J
Gonzalez-Dugo, V
Girona, J
Fereres, E
Bellvert, J
Bastos, L
Ferguson, R.B
Milics, G
Szabó, S
Bűdi, K
Takács, A
Láng, V
Zsebo, S
Swe, K.M
Kim, Y
Jeong, D
Lee, S
Chung, S
Kabir, M.S
Bastos, L
Ferguson, R.B
Topics
Precision Crop Protection
Remote Sensing Applications in Precision Agriculture
Sensor Application in Managing In-season Crop Variability
Site-Specific Nutrient, Lime and Seed Management
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
In-Season Nitrogen Management
Type
Poster
Oral
Year
2012
2014
2016
2018
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Filter results6 paper(s) found.

1. Development of a Quick Diagnosis Method to Target Fields with Better Potential for Site-Specific Weed Management

Site-specific weed management appears as an innovative way of saving herbicides in crop while maintaining yield. This can potentially lead economic and ecological benefits. However, it was reported in the literature that savings range from 1 % to 94 % from one field to the other. This implies that certain fields... B. Panneton, M. Simard, G.D. Leroux, L. Longchamps

2. Detection Of Fruit Tree Water Status In Orchards From Remote Sensing Thermal Imagery

In deciduous fruit trees there is a growing need of using water status indicators for scheduling irrigation and adopt regulated deficit irrigation (RDI) strategies taking into account spatial variability of orchards. RDI strategies have been successfully adopted for many fruit trees as a means for reducing water use and because yield and quality at harvest are not sensitive to water stress at some developmental stages. Although water status is generally monitored by measuring tree... P.J. Zarco-tejada, V. Gonzalez-dugo, J. Girona, E. Fereres, J. Bellvert

3. Active and Passive Crop Canopy Sensors As Tools for Nitrogen Management in Corn

The objectives of this research were to (i) assess the correlation between active and passive crop canopy sensors’ vegetation indices at different corn growth stages and (ii) assess sidedress variable rate nitrogen (N) recommendation accuracy of active and passive sensors compared to the agronomic optimum N rate (AONR). The experiment was conducted near Central City, Nebraska on a Novina sandy loam planted to corn on 15 April 2015. The experiment was a randomized complete-block design with... L. Bastos, R. Ferguson

4. Increasing Corn (Zea Mays L.) Profitability by Site-Specific Seed and Nutrient Management in Igmand-Kisber Basin, Hungary

Variable Rate Technology (VRT) in seeding and nutrient management has been developed in order to apply crop inputs variably. Farm equipment is widely available to manage in-field variability in Hungary, however, defining management zones, seed rates and amounts of nutrients is still a challenge. An increasing number of growers in Hungary have started adopting precision agriculture technology; however, data on profitability concerning site-specific seeding and nitrogen management is not widely... G. Milics, S. Szabó, K. Bűdi, A. Takács, V. Láng, S. Zsebo

5. Sensor Comparison for Yield Monitoring Systems of Small-Sized Potato Harvesters

Yield monitoring of potato in real time during harvesting would be useful for farmers, providing instant yield and income information. In the study, potentials of candidate sensors were evaluated with different yield measurement techniques for yield monitoring system of small-sized potato harvesters. Mass-based (i.e., load cell) and volume-based (i.e., CCD camera) sensors were selected and tested under laboratory conditions. For mass-based sensing, an impact plate instrumented with load cells... K.M. Swe, Y. Kim, D. Jeong, S. Lee, S. Chung, M.S. Kabir

6. Active and Passive Sensor Comparison for Variable Rate Nitrogen Determination and Accuracy in Irrigated Corn

The objectives of this research were to (i) compare active and passive crop canopy sensors’ sidedress variable rate nitrogen (VRN) derived from different vegetation indices (VI) and (ii) assess VRN recommendation accuracy of active and passive sensors as compared to the agronomic optimum N rate (AONR) in irrigated corn. This study is comprised of six site-years (SY), conducted in 2015, 2016 and 2017 on different soil types (silt loam, loam and sandy loam) and with a range of preplant-applied... L. Bastos, R.B. Ferguson