In the work based on agroecological and technological testing of varieties of grain crops of domestic and foreign breeding, winter triticale in particular, conducted on the experimental field of the Smolensk State Agricultural Academy between 2015 and 2019, we present the methodology and results of processing the experimental data used for constructing the neural network model. Neural networks are applicable for solving tasks that are difficult for computers of traditional design and humans alike. Those are processing large volumes of experimental data, automation of image recognition, approximation of functions and prognosis. Neural networks include analyzing subject areas and weight coefficients of neurons, detecting conflict samples and outliers, normalizing data, determining the number of samples required for teaching a neural network and increasing the learning quality when their number is insufficient, as well as selecting the neural network type and decomposition based on the number of input neurons. We consider the technology of initial data processing and selecting the optimal neural network structure that allows to significantly reduce modeling errors in comparison with neural networks created with unprepared source data. Our accumulated experience of working with neural networks has demonstrated encouraging results, which indicates the prospects of this area, especially when describing processes with large amounts of variables. In order to verify the resulting neural network model, we have carried out a computational experiment, which showed the possibility of applying scientific results in practice.

The article analyzes and presents data on the growth and development of the Phoenix fiber flax variety during the growing season, depending on the type and ratio of mineral fertilizers. The object of research was the variety of fiber flax Phoenix. The use of the tested types of mineral fertilizers made it possible to obtain a yield of flax straw up to 9.49 t/ha and seeds up to 0.34 t/ha. In general, the most effective was the use of fertilizers in option 11 (pre-sowing application of NPK(S) 8:20:30(2) + 0.3B at a dose of 200 kg/ha + Ammophos NP 12:52 at a dose of 133 kg/ha + Kalimag 38 at a dose of 137 kg/ha + top dressing in the herringbone phase ammonium nitrate 34.6 at a dose of 59 kg/ha + trace elements), where the level of yield relative to the control increased by an average of 100% for straw and 70% for seeds. All yield data are confirmed by the elements of its structure. Thus, plant height ranged from 68 to 91 cm, technical length - from 54 to 70 cm, number of plants before harvesting - 1232-1616 pcs/ha, seed weight per plant - 0.16-0.22 g, straw weight - 0.40-0.60 g.