ARTIFICIAL INTELLIGENCE AND MULTIPLE MODELS APPLIED TO PHYTOSANITARY AND NUTRITIONAL ASPECTS THAT INTERFER IN THE PHYSIOLOGICAL POTENTIAL OF SOYBEAN SEEDS
The objective of this work was to evaluate the interference of physical, nutritional, sanitary and genetic aspects in the quality of seeds. The experimental design used was randomized blocks, using 55 soybean F6 genotypes, with 4 replications. In this study, thousand seeds mass, germinated seeds, accelerated aging, tetrazolium, phytosanitary indicators (Aspergillus flavus,Cercospora kikuchii,Fusarium graminearum,Fusarium semisectum and Bacteriosis), seed nutritional indicators (nitrogen, phosphorus, potassium, calcium, magnesium, sulfur, boron, copper, iron, manganese, zinc, sodium and molybdenum). The physiological quality of the seeds is negatively affected by the health aspects of Cercospora kikuchii, Aspergillus flavus, Fusarium semictectum and Bacteriosis, in addition, nutritional aspects also act negatively due to the presence of salts, and positive due to the levels of P. Likewise, Zn, Mo and K are correlated as strong indicators of seed vigor levels. The developed genotypes have excellent behavior towards pathogens and seed nutrition, contributing to high quality seed production.