Gaso, Deborah Berger, Andres Kooistra, Lammert de Wit, Allard
Yield forecasting has been extensively tackled by the use of crop growth models, however its implementation at field scale still faces numerous constrains due to the lack of input data required and uncertainties in parameter value. Current accessibility of remote sensing data with global coverage and free access offers a great opportunity to enhanc...
Andrianasolo, Fety Deswarte, Jean-Charles Jorant, Amaury
Phenological stages are widely used in crop models as starting points for most processes based on leaf, biomass and yield growth. In soft wheat in particular, the appearance of the last leaf on the main shoot is a mandatory stage for crop protection strategy, since this stage alone, contributes to up to half of the carbon allocated to the grain. We...
Delhez, Laura Dumont, Clément Vandewattyne, Félix Longdoz, Bernard
A process-based model which simulates carbon, nitrogen and water cycle at a plot scale has been recently developed at Gembloux Agro-Bio Tech. Adapted to different agroecosystems, this model is mainly oriented towards the estimation of greenhouse gas exchanges. The model, named TADA (Terrestrial Agroecosystems Dynamics Analysis), is based on the mec...
Banakar, Ahmad Khafajeh, Hamid Minaei, Saeid Delavar, Majid
Greenhouse is an environment where variables such as: climate, nutritional and biological conditions can be controlled. Therefore, the greenhouse allows horticultural crops to grow in the off-season and also affect plant growth to achieve optimal conditions for different stages of crop growth (Janoudi., 1993). The purpose of a greenhouse constructi...
Fallah, Mohammad Hossein, Zare Ahmad, Nezami Hamid, Khazaie Mehdi, Nassiri Gerrit, Hoogenboom
Process-based crop models can integrate the complex interactions of soil properties, climatic conditions, management practices, and crop genetic characteristics. They differ in the way they simulate soil-plant-atmosphere processes, in detail of describing crop growth, water use and soil water balances, also in the number of parameters and inputs re...
ten Den, Tamara van de Wiel, Inge de Wit, Allard van Evert, Frits Van Ittersum, Martin Reidsma, Pytrik
WOFOST is a generic crop model which has been applied for many crops including potatoes (de Wit et al., 2018). However, some of the crop parameter sets require revision as they are outdated. For example, for potato the values for important parameters were derived from cultivar Bintje (Wang et al., 2018). Bintje was popular in the 1960s to 1980s but...
Silva, Joao de Wit, A.J.W. Rijk, B. Supit, I. Reidsma, Pytrik van Ittersum, M.K.
Crop models are key tools for agricultural research (van Ittersum et al., 2003). Despite the wide range of model applications, little attention has been paid to model calibration (Seidel et al., 2018). Detailed field trials are needed for this purpose but these are costly and barely conducted, and thus model parameters tend to become outdated. This...
Kimball, Bruce Boote, Kenneth Hatfield, Jerry Ahuja, Laj Stockle, Claudio Archontoulis, Sotirios Baron, Christian Basso, Bruno Bertuzzi, Patrick Constantin, Julie
...
Crop yield can be affected by crop water use (evapotranspiration, ET) and vice versa, so when trying to simulate one or the other, it can be important to simulate both well. Method: To determine how well 29 maize growth models can simulate ET, an inter-comparison study was initiated under the umbrella of AgMIP (Agricultural Model Inter-Comparison a...
Kersebaum, Kurt-Christian Wallor, Evelyn Coucheney, Elsa Hoffmann, Munir Neira, Anuschka Lewan, Elisabet
Field scale variability of soil texture contributes to the site-specific performance of water dynamics, nitrogen turnover and crop development in the soil-plant-atmosphere system. In agricultural practice, management recommendations that operate on the basis of spatially and temporally variable soil states are rarely considered, even though, having...
Kemanian, Armen Hoffman, Alexis Chris, Forest
An ingenious statistical analysis by Schlenker and Roberts (2009) of the county-level grain yield of cotton, corn and soybean in response to climate showed that these non-controlled experiments contain valuable and somewhat hidden information. Critically, these authors identified a temperature range over which grain yields increase (≈10 to 29°C for...