Author
Listed:
- Manuela Schieler
(Central Institute for Decision Support Systems in Crop Protection (ZEPP), Rüdesheimer Str. 60-68, 55545 Bad Kreuznach, Germany
Department of Biogeography, Faculty of Regional and Environmental Sciences, Trier University, Universitätsring 15, 54286 Trier, Germany)
- Natalia Riemer
(Department of Ecological Plant Protection, Faculty of Organic Agricultural Sciences, University of Kassel, Nordbahnhofstr. 1a, 37213 Witzenhausen, Germany)
- Benno Kleinhenz
(Central Institute for Decision Support Systems in Crop Protection (ZEPP), Rüdesheimer Str. 60-68, 55545 Bad Kreuznach, Germany)
- Helmut Saucke
(Department of Ecological Plant Protection, Faculty of Organic Agricultural Sciences, University of Kassel, Nordbahnhofstr. 1a, 37213 Witzenhausen, Germany)
- Michael Veith
(Department of Biogeography, Faculty of Regional and Environmental Sciences, Trier University, Universitätsring 15, 54286 Trier, Germany)
- Paolo Racca
(Central Institute for Decision Support Systems in Crop Protection (ZEPP), Rüdesheimer Str. 60-68, 55545 Bad Kreuznach, Germany)
Abstract
Many pests damage pea crops, which potentially leads to reduced quality and yield losses. Since pests occur at different phenological growth stages of pea crops, the prediction of growth stages, for example as BBCH stages, is beneficial. In this study, three models have been developed to simulate growth stages of grain and green pea crops, for the latter with early and late sowing dates. All data, such as BBCH stages and air temperature, were collected in Germany in a three-year study under practical farming conditions at 415 sample sites. For the development of each model, a Gompertz regression model based on the observed data was performed. The model validation suggests that each model precisely and reliably predicts pea crop growth stages for spring-sown peas. Amongst others, the RMSE Index for grain peas was 3.4; for green peas, early and late sowing dates, respectively, they were 3.4 and 4.5. SIMONTO-Pea (SIMulation of ONTOgenesis) is the first model that predicts detailed pea crop growth stages based on the BBCH scale. This innovation is especially beneficial for users such as advisors and farmers dealing with spring-sown pea crops as a decision support system in monitoring and pest management according to pea crop growth stages.
Suggested Citation
Manuela Schieler & Natalia Riemer & Benno Kleinhenz & Helmut Saucke & Michael Veith & Paolo Racca, 2023.
"SIMONTO-Pea: Phenological Models to Predict Crop Growth Stages in BBCH of Grain and Green Peas ( Pisum sativum ) for Temporal Pest Management,"
Agriculture, MDPI, vol. 14(1), pages 1-15, December.
Handle:
RePEc:gam:jagris:v:14:y:2023:i:1:p:15-:d:1305124
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