Computerized analysis of seedling performance in evaluating the phytotoxicity of chemical treatment of soybean seeds

Abstract

Abstract: Chemical treatment of soybean seeds is very important to ensure successful crop establishment. However, problems such as phytotoxicity of product combinations that can reduce seed physiological performance require attention. The use of computational resources has shown potential in identifying phytotoxic effects and contributing to the steps of quality control of treated seeds. The aim of this study was to determine if computerized image analysis of seedlings enables the phytotoxicity of chemical treatment of soybean seeds to be assessed in an effective and simplified manner. Samples from two soybean seed lots were treated with fungicides, insecticides, micronutrients, and their combinations, as well as with polymer and drying powder (coatings). After chemical treatment, the seeds were evaluated for germination, first germination count, seedling emergence in sand, accelerated aging, and seedling performance with and without the correction of regions not automatically demarcated (Vigor-S). We found high correlation of the Vigor-S parameters with the traditional tests for detection of phytotoxic effects of chemical treatment, regardless of correction made in the system. Computerized image analysis of seedlings is an effective and highly sensitive resource for evaluating possible phytotoxicity effects due to chemical treatment of soybean seeds.

Keywords

• computer vision
• Glycine max L.
• image processing
• seed treatment
• Vigor-S system