Abstract: Spring cereals are important agricultural crops in Northern Europe. The short growing season in this region necessitates early sowing. The earliest possible date is often determined by the soil water content, which usually decreases during and after snowmelt at rates varying with the weather and the soil characteristics. Tillage and sowing operations on soils with too high a water content can lead to soil compaction, increased soil erosion, and losses of nutrients and soil organic matter. Rainfall intensity also affects crop emergence, through its potentially negative effects on surface capping. The objective of this study was to determine the earliest possible sowing date of spring cereals for representative soil and climate scenarios in southeastern Norway. Criteria were set for pre-sowing tillage operations and sowing, based on the water content in differ soil layers and the incidence of rainfall. To determine the day of the year when these criteria were first met, the soil water content during the spring was simulated with the soil module in DSSAT v4.5. These simulations were performed for contrasting soil types and climate scenarios representing the period 1961-90 and 2046-65 respectively. For each combination of soil and climate, one hundred simulations with individual weather data were performed. The results provide information about the timing and variability of the optimal planting date for the current and projected climate in South Eastern Norway. No Label

Abstract: This study deals with observed and simulated growth, development and yield of the fresh-market Thomas F1 tomato bush cultivar (Solanum lycopersicum L.) grown under open field conditions at farm scale in the Elbe lowland. The CROPGRO-Tomato model used in this study is part of the DSSAT V4.5 software. The model has been calibrated with growth analyses data from field experiments, agronomic evidence (GC UPRAVY software) and the most currently available data from the literature sources of cardinal temperatures for tomato phenology, fruit growth and photosynthesis (Tb – base temperature; Topt1 – the lowest temperature at which maximum rate is attained; Topt2 – the upper temperature at which maximum rate is sustained; Tmax – maximum temperature). The sampling plants were collected a once 14 days for analysis of basic physiological parameters: LAI (Leaf area index), LAR (Leaf Area Ratio), C (Crop Growth Rate), RGRw (Relative Growth Rate) and NAR (Net Assimilation Rate). Phenology observation was done weakly. Meteorological, soil and agro-technical parameters across the fields were monitored. The treatments were well-irrigated and well-fertilised, and therefore, no water or N stress was present.Parameters affecting leaf growth, dry biomass productions, and dry biomass of leaves, stem and generative organs from planting to harvest were calibrated against the observed data. Phenological development and growth processes such as leaf expansion and fruit growth depend on cardinal temperatures. Leaf area expansion depends on the new leaf mas produced and specific leaf area, which is influenced by light, temperature, root N uptake, and plant water status. Starting date for the simulation corresponds with transplanting date of the crop in the field, which was set at day 141. The simulation period ended at day 273, a reasonable estimate for the date when plants are stopped in practice. Initial input dry biomass at Mochov farm (Suchdol) was set to 2.25 (2.88), 1.71 (2.5) and 0.01 (0.78) grams for leaves, stem and generative organs, respectively. No Label

Abstract: Agrimod serves as a central knowledge hub for information on agricultural modelling activities worldwide. The vision is to unite the agricultural modelling community by providing a platform whereby models can be showcased, their applications discussed and new collaborations built, streamlining the process by which new modelling activities are developed. Agrimod covers spatial scales from cells to globe, temporal scales from minutes to centuries. There is a limitless coverage of research issues, bounded only by their relevance to agriculture, as the platform is open-ended: details about models, data or case studies can be up-dated; issues or concepts can be raised and discussed. The scope is limited only by the willingness of users to participate. No Label