Application of elements of probability theory and mathematical techniques in crop production

The paper is concerned with key aspects of applying probability theory and mathematical techniques to crop production. Special attention is given to simulation of seeding planning using stochastic processes, risk assessment by means of probability distributions, crop yield management on the basis of statistical models, and product quality control involving methods of mathematical statistics. Focus areas are key distributions with examples of their use for seeding planning, plant protection, and drought analysis. Practical algorithms are provided to test hypotheses and simulate regressions. A diagram of precision agriculture is proposed, from data collection through statistics and simulation to evidence-based managerial decisions. The methodology enhances production stability and minimizes losses from uncertainty.