Studying standard and rheological quality parameters of winter wheat by Python visualisation

This study was carried out to present an innovative solution for interpreting large data sets in agri-statistics with the invocation of programmed visualisation. Moreover, following polyfactorial long-term experiment embodies a comprehensive 18 wheat quality parameters. The effect increasing dosages fertiliser (control, N90PK, N150PK) examined on 3 winter cultivars (KG Kunhalom, GK Csillag, Hybiza) two consecutive growing seasons (2018–2019). ecological conditions 2018 gave significantly higher yield, meanwhile 2019 augmented gluten spread, alveographic tenacity, deformation work, valorigraphic stability and group loaf volume. N90PK dosage enough realise yield potential as well. Fertilising improved 13 indices, namely crude protein, Zeleny index, wet content, extensibility, water absorption, number group, dough development time, stability, softening Considering cv. Hybiza performed better, while cvs. KG Kunhalom Csillag possessed better protein-linked postharvest attributes. One most important findings is that waffle chart, joint plot, correlation matrix complexradar Python provide very powerful tool agri-statistics. Also, results can potentially improve knowledge about cultivar-specific agronomy practice, connections between these