The use of seeds with high physiological quality allows rapid growth and establishment of seedlings in the field to be obtained. Therefore, the accuracy of the information obtained during the determination of the physiological quality of seeds is of great importance. The objective was to use generalized linear models, investigating which link function (Probit, Logit and Complementary log-log) is suitable to predict T50 and uniformity during germination of soybean and corn seeds. To perform the experiments, we used seeds from five commercial hybrids and/or cultivars of corn and soybean. The germination speed was calculated by counting the germinated seeds and the results were expressed in the form of proportions. Germination uniformity was calculated by the difference in the times required for germination. The best model was selected according to the criteria of the test of Deviance, AIC and BIC. The Logit model showed accurate results for most cultivars. The evaluation of germination in the form of proportions considering the assumption of binomial response is satisfactory, and the choice of the link function is dependent on the characteristics of each lot and/or species evaluated. The use of this methodology makes it possible to estimate any germination time and uniformity.

Microwaves have been applied to the drying of seeds of several species due to their maintenance of the quality of the seeds and reduction of time and costs. However, few is known about the effect of microwaves on the increase of the physiological quality of soybean seeds and especially their effects on longevity. Therefore, the use of microwaves as magneto-priming in soybean seeds was the object of study in this work. For this purpose, two soybean cultivars were selected and submitted to the ultra-high frequency (UHF) microwave exposure of 2.45 GHz, in the wavelength of 11 cm, and power of 0.2 W/g, for 15 min. The results showed that this condition of exposure to the microwave brought benefits in both cultivars after treatment. Incremental improvements were observed in the germinability indexes, the seedling length, the water absorption by the seeds, the fresh mass, dry mass, and longevity. The genes related to seed germination and longevity showed superior expression (HSFA3, HSP21, HSP17.6b, EXP, ABI3) with magneto-priming treatment. The data found ensure the use of the technique as a viable option for pre-treatment as magneto-priming in soybean seeds in order to improve seed quality.

The use of electromagnetic energy for drying seeds has been shown to be a promising alternative. However, studies show that the technique still lacks careful evaluation due to the sensitivity of soybean seeds to damage caused using microwaves. Studies have shown that the use of microwaves during drying can be safe in seeds of soybeans, corn, and beans, among others. These studies recognize that drying using microwaves has a great potential for savings in the drying process, as it considerably reduces the drying time. This work aimed to evaluate the immediate damage caused in soybean seeds subjected to drying at temperatures of 40, 50, and 60 °C, with power of 0, 0.5, and 1 W/g at a frequency of 2.45 GHz. The results of the vigor and germination tests showed that the action of microwaves on seeds was not only safe and more efficient but also brought about increases in seed germination and vigor. However, the process must be judicious and obey precise indices of power and temperature to not cause damage to the seeds.

This study aims to evaluate the behavior of seed longevity in soybean, maize, and tomato stored under controlled conditions using Logistic and Boltzmann sigmoidal models. Additionally, it seeks to determine the performance of these models in predicting $P_{50}$, $P_{85}$, and $P_{25}$. The models were fitted to the experimental longevity data, and their performance in predicting the percentiles was evaluated. The Logistic model showed better performance in predicting $P_{50}$ (time for viability to drop to 50%), $P_{85}$ (time for viability to drop to 85%), and $P_{25}$ (time for viability to drop to 25%), estimating the parameters more frequently within the experimental range (obtained from the initial viability data). The results of this study suggest that some cultivars exhibited different patterns in deterioration rates, with some showing abrupt declines in viability, highlighting differences in the speed and nature of seed deterioration. The Logistic model proved to be superior, with an accuracy of 83% in estimating the $P_{85}$ and $P_{25}$ percentiles, while the Boltzmann model achieved an accuracy of 54%. The tomato cultivar Gaucho showed the greatest loss in germination, reaching $P_{25}$ quickly, while the soybean cultivar M 7119 IPRO and maize cultivar MAM06 maintained high germination for a longer period. These findings emphasize the importance of using viability percentiles to optimize storage practices, minimize economic losses, and prevent genetic erosion in conservation programs. Modeling seed longevity using sigmoidal models can significantly contribute to determining various viability percentiles, supporting storage practices and providing valuable insights for strategic decision-making in seed management, proving useful in both commercial and species conservation contexts.

O presente trabalho teve como objetivo determinar o tamanho de amostra mínimo para avaliar o desempenho de semeadoras de precisão com sementes de soja para experimentos em laboratório. O ensaio foi conduzido sobre esteira carpetada conforme instruções da International Organization for Standardization. Para compor os tratamentos, foram combinados quatro mecanismos dosadores de sementes com quatro velocidades periféricas do disco dosador em esquema fatorial 4x4 com três repetições. Para cada tratamento, foram coletados 280 espaçamentos entre sementes, de um total de 13440 ao longo do experimento. Para determinar os tamanhos de amostra, foram utilizados três métodos de determinação: intensidade de amostragem, bootstrap e comparação das médias do percentual de espaçamentos aceitáveis. Pode-se concluir que o método bootstrap é o mais confiável para determinar o tamanho de amostra em experimentos para avaliação de desempenho de semeadoras. Por este método, foi possível reduzir em pelo menos 25% o tamanho original de amostra de 250 espaçamentos entre sementes.