This year from 27th of January to 16th of March Dr. Renaldas Žydelis, junior researcher of Lithuanian Research Centre for Agriculture and Forestry (LAMMC), Institute of Agriculture, Department of Plant Nutrition and Agroecology had an internship in Agrifood Research and Technology Centre of Aragon, Spain.
The aim of the internship was to take over and transfer the most advanced crop modeling practice to the agribusiness and to use the gained knowledge to commercialize varieties and cultivation technologies under Lithuanian conditions. In order to achieve this goal, the possibilities of DSSAT model (Decision Support System for Agrotechnology Transfer) were assessed. The model was designed to simulate the yield of various agricultural crops and the possibilities to adapt them under Lithuanian conditions. Dr. Renaldas Žydelis introduced Spanish researchers Farida Dechmi and Ramon Isla with agronomic experiments carried out in LAMMC and the issues Lithuanian farmers most often face with.
The first prototype of the DSSAT model (CERES-Wheat/Maize) was developed in the 8th decade of the 20th c. In the United States. Since then, the models have been periodically updated and the latest version of this model (DSSAT 4.7) was released in 2017, November.
Currently the model can be applied to more than 40 different agricultural crops. Therefore, there are rather many possibilities to use this model in solving various agricultural issues.
Spanish researchers have shared their experience of working with this model and explained in detail how it could be applied, for instance, when choosing the most optimal cultivation technology, evaluating the influence of abiotic and biotic factors on yield reduction or assessing the nutritional needs of different plant varieties.
The DSSAT model has been optimized / adapted according to the data of maize experiments carried out in Lithuania. The model was calibrated using 3 years' (2015-2017) experimental data carried out by Dr. Renaldas Žydelis during his PhD studies in Lithuania: biomass and grain yield growth, leaf area, grain weight, soil moisture variation at different depths, variation of mineral nitrogen content, nitrogen uptake in plants, soil hydraulic properties, a detailed description of soil profile and other experimental results that best reflected maize vegetation in research period.
The model which was optimized during the internship according to the specific area of research and experimental variety was used to evaluate maize nutrition and the losses of nitrate leaching during vegetation. A reduction in grain yield due to water and nitrogen stress was also calculated. This model can be useful when solving the problems of farmers. However, it is very important to note that the models should be optimized according to the data of particular location and variety. The minimum data required for plant modeling include: meteorological data (maximum and minimum temperature, precipitation, wind speed, relative humidity, solar radiation), a detailed description of the soil profile (identified soil horizons and their water hydraulic properties, granulometric composition, soil density, hydraulic conductivity), periodic plant measurements (biomass and grain yield, leaf area, development stages, water content variation. Other required measurements depend on the set goals. With the previously mentioned measurement data plant models can be successfully applied to solve many different issues.
Source of funding – Agency for Science, Innovation and Technology (MITA)