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The search for time and human subjectivity reduction in the analysis of the physiologic potential of seeds has brought forward the use of computerized systems as an alternative. The goal of this research was to assess the effectiveness of the GroundEye equipment in the characterization of soybean seeds vigor by using the image analysis technique in comparison to the information provided by vigor tests recommended to soybean seeds. Sixteen lots of two soybean varieties were used — variety 98Y12 and P98Y70, characterized by the following tests: germination test, accelerated ageing test, cold test, tetrazolium test, and seedling emergence in the field. The image analysis was performed using the GroundEye software to obtain the vigor index and the average length of seedlings and roots for a later comparison with the results of the accelerated ageing test and the manual measurement of the average length of seedlings and roots. GroundEye has demonstrated efficiency in the determination of vigor of soybean seeds and has reduced the time needed to obtain the results in six days, being indicated in the quality control programs established by soybean seeds production companies.

Investigating the distribution modeling of Spondias tuberosa , as well as its phenotypic diversity, is critical for species conservation and tree improvement initiatives. This species holds great importance in bioeconomy, yet there is limited knowledge to address its production. Utilizing predictive distribution modeling, we can identify areas in Sergipe with a high likelihood of the natural occurrence of S. tuberosa , which is crucial for targeted conservation efforts. Comprehensive phenotypic characterization was conducted on a natural population, selecting individuals and examining traits ranging from tree architecture to fruit biometry, and including information on seed conservation under storage conditions. The findings revealed substantial variance in germination rates and seedling vigor related to the duration of endocarp storage, although no significant differences were observed in overall germination success across different storage times. However, prolonged storage resulted in an increase in abnormal seedlings and deteriorated seeds. The integration of phenotypic data and predictive modeling provides a robust framework for understanding ecological dynamics and supports sustainable management practices for S. tuberosa , aligning with bioeconomic goals. This research underscores the importance of maintaining phenotypic variability within populations, which is vital for the adaptive capacity of species to changing environmental conditions and for enhancing local bioeconomies.