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Melnitchouck, A
Tavares, T.R
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Authors
Melnitchouck, A
Melnitchouck, A
Melnitchouck, A
Melnitchouck, A
Melnitchouck, A
Trevisan, R.G
Eitelwein, M.T
Ferraz, M.N
Tavares, T.R
Molin, J.P
Neves, D.C
Tavares, T.R
Molin, J.P
da Silva , T.R
de Carvalho , H.W
Topics
Precision Nutrient Management
Precision Nutrient Management
Remote Sensing Applications in Precision Agriculture
Precision Nutrient Management
Precision Crop Protection
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Type
Poster
Oral
Year
2012
2010
2014
2018
2022
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Authors

Filter results7 paper(s) found.

1. Comparative Analysis Of Different Approaches

The efficiency of variable rate seeding (VRS) was confirmed in various crops. It is proven that corn requires increasing seeding rates in high-yielding zones, whereas soybeans need lower rates. However, the data for wheat appeared to be controversial. The aim of our experiment was to determine the most efficient strategy for variable rate fertilization and seeding in spring wheat in the conditions of Canadian Prairies. Two approaches were tested: based on Normalize Difference Vegetation Index... A. Melnitchouck

2. Assessment Of Pod Ceal Dc™ Effect On Grain Yield In Beans Using Multi-spectral Satellite Imagery And Yield Data

Pod Ceal DC™ from BrettYoung creates an elastic membrane over pods in canola, beans etc., which results in controlling shatter before combining. To carry out this on-farm experiment, an irrigated field was divided in two parts according to the yielding potential and topographical characteristics to ensure equal conditions for both variants of the experiment. Grain beans were grown in the field using conventional technology. Pod Ceal DC™ was applied three weeks before harvesting on... A. Melnitchouck

3. Yield Limiting Factors In The Conditions Of Southern Alberta

The main goal of our experiment was to determine the main factors determining yield of green biomass of spring barley in the conditions of Southern Alberta. To analyze soil properties in the field, grid sampling was conducted at 1-ha grid. Soil samples were collected from the depths of 0…15 and 15…60 cm and analyzed for over 20 different characteristics including soil organic matter content, pH, cation exchange capacity (CEC), and the concentrations of macro- and micronutrients.... A. Melnitchouck

4. Determination of Optimal Number of Management Zones

... A. Melnitchouck

5. Multilayer And Multiyear Data Analysis In Precision Yield Planning

This work covers two separate field experiments. In the first one, the results of 1-ha grid soil analysis for soil organic matter (OM), pH, cation exchange capacity (CEC), nitrate N, P, K, S, Ca, Mg and soluble salts were compared with the results of yield mapping, biomass index from optical on-the-go sensors, as well as multispectral imagery analysis for the last 30 years.  As a result, it was found that none of the analyzed soil characteristics was predominant for determining yield.... A. Melnitchouck

6. Optimum Spatial Resolution for Precision Weed Management

The occurrence and number of herbicide-resistant weeds in the world has increased in recent years. Controlling these weeds becomes more difficult and raises production costs. Precision spraying technologies have been developed to overcome this challenge. However, these systems still have relatively high acquisition cost, requiring studies of the relation between the spatial distribution of weeds and the economically optimum spatial resolution of the control method. In this context, the objective... R.G. Trevisan, M.T. Eitelwein, M.N. Ferraz, T.R. Tavares, J.P. Molin, D.C. Neves

7. Predicting Secondary Soil Fertility Attributes Using XRF Sensor with Reduced Scanning Time in Samples with Different Moisture Content

To support future in situ/on-the-go applications using X-ray fluorescence (XRF) sensors for soil mapping, this study aimed at evaluating the XRF performance for predicting organic matter (OM), base saturation (V), and exchangeable (ex-) Mg, using a reduced analysis time (e.g., 4 s) in soil samples with different moisture contents. These attributes are considered secondary for XRF prediction because they do not present emission lines in the XRF spectrum. Ninety-nine soil samples... T.R. Tavares, J.P. Molin, T.R. Da silva , H.W. De carvalho