Proceedings :: International Society of Precision Agriculture

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Korsaeth, A

Klein, R.N

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Authors

Isaksson, T

Korsaeth, A

Øvergaard, S

Klein, R.N

Golus, J.A

Topics

Remote Sensing Applications in Precision Agriculture

Guidance, Auto Steer, and GPS Systems

Type

Poster

Oral

Year

2012

2010

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Filter results2 paper(s) found.
1. Using GPS-RTK In Crop Variety And Hybrid Evaluations The traditional methods used by many to conduct research in crop variety and hybrid evaluations is to blank plant the area, flag the area, or use a physical marker. All of these have disadvantages. In blank planting it may be difficult to plant exactly in the same rows, and can dry the soil and affect seed germination if soil water is limited. Blank planting also destroys crop residues and with skip-row residues are destroyed in the unplanted rows.This method is used for many plots in cooperator’s... R.N. Klein, J.A. Golus Download paper
2. Remote NIR-Sensor Fusion with Weather Data for Improved Prediction of Wheat Yield Models Prediction models for grain yield based on remote sensing data are commonly shown to perform reasonably well for one single cropping season. The model performances often drop, however, when data from more years is included. This may be caused by biased data, resulting from diverging growth conditions from year to year, which affects... T. Isaksson, A. Korsaeth, S. Øvergaard Download paper

Filter results2 paper(s) found.

1. Using GPS-RTK In Crop Variety And Hybrid Evaluations

The traditional methods used by many to conduct research in crop variety and hybrid evaluations is to blank plant the area, flag the area, or use a physical marker. All of these have disadvantages. In blank planting it may be difficult to plant exactly in the same rows, and can dry the soil and affect seed germination if soil water is limited. Blank planting also destroys crop residues and with skip-row residues are destroyed in the unplanted rows.This method is used for many plots in cooperator’s... R.N. Klein, J.A. Golus

Download paper

2. Remote NIR-Sensor Fusion with Weather Data for Improved Prediction of Wheat Yield Models

Prediction models for grain yield based on remote sensing data are commonly shown to perform reasonably well for one single cropping season. The model performances often drop, however, when data from more years is included. This may be caused by biased data, resulting from diverging growth conditions from year to year, which affects... T. Isaksson, A. Korsaeth, S. Øvergaard

Download paper