The development of rural territories in the European Union (EU) plays an essential role, and agricultural development can largely contribute to this process. To project agricultural trends, a number of models have been developed in the EU, while in Latvia the LASAM model was developed in 2016 to generate projections for agricultural sector development in Latvia until 2050. In 2017, LASAM was extended by a module for socio-economic assessment that allows projecting productivity for various types of farming. The research aim is to develop a model for productivity simulation for various specialisation types of farms in order to project their development in Latvia. To achieve the aim, two specific research tasks were set: 1) to develop a model for productivity simulation for various specialisation types of farms in Latvia; 2) to identify the key results of the simulation of productivity for various specialisation types of farms in Latvia. The research found that in the period 2005 – 2016 the value added of agriculture tended to slightly increase in Latvia, whereas an opposite trend was observed for the number of persons employed in agriculture, which tended to decrease in the period of analysis. Both trends determine the agricultural productivity trend as well. A projection of productivity measured as value added per AWU for various farming types in Latvia by means of the LASAM model has revealed that it is different, and the highest level of productivity in 2030 and 2050 is projected for granivores as well as field crop farms.

Production of cereals is mostly processed by operating the machinery. Operation of machinery influences the yield, i.e. also the income on one side, but it is also one of the biggest sources of expenses from the other side. Increasing the yearly operation time and amount of work of the machinery leads to decreasing costs per unit. Increasing the yearly amount of work is limited by agrotechnical terms. The crop yield depends on the time and duration of field work, and affects the farm income. The methods and formulae to prognosticate the averageoptimum yearly operation time of farm's machinery, i.e. also farm's cereal-growing area was composed by the author, concerning biological, technical and economical factors and relations, affecting cereal production. Farm profit and profitability were used as optimization criteria.