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ORIGINAL PAPER
Multiple regression analysis model to predict and simulate winter rapeseed yield
1
Poznan University of Life Sciences, Institute of Biosystems Engineering, Faculty of Agronomy and Bioengineering ul. Wojska Polskiego 50, 60-627 Poznań, Poland
2
Koszalin University of Technology, Department of Agrobiotechnology, Faculty of Mechanical Engineering ul. Racławicka 15-17, 75-620 Koszalin, Poland
Journal of Research and Applications in Agricultural Engineering 2018;63(4):139-144
KEYWORDS
ABSTRACT
The aim of the work is to create a model for prediction and simulation of winter rapeseed yield. The model made it possible to perform a yield forecast on 30 June, directly before harvest in the current agrotechnical season. The prediction model was built using the multiple regression method (MLR). The model was based on meteorological data (air temperature and precipitation) and information about mineral fertilization. The data were collected from the years 2008-2017 from 291 production fields located in Poland, in the southern Opole region. The assessment of the quality of forecasts generated on the basis of the regression model was verified by determining prediction errors using RAE, RMS, MAE and MAPE error meters. An important feature of the created prediction model concerns the possibility of making the forecast in the current agrotechnical year on the basis of the current weather and fertilizer information.
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| eISSN: | 2719-423X |
| ISSN: | 1642-686X |
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