Optical sensors combined with machine learning algorithms have led to significant advances in seed science. These advances have facilitated the development of robust approaches, providing decision-making support in the seed industry related to the marketing of seed lots. In this study, a novel approach for seed quality classification is presented. We developed classifier models using Fourier transform near-infrared (FT-NIR) spectroscopy and X-ray imaging techniques to predict seed germination and vigor. A forage grass (Urochloa brizantha) was used as a model species. FT-NIR spectroscopy data and radiographic images were obtained from individual seeds, and the models were created based on the following algorithms: linear discriminant analysis (LDA), partial least squares discriminant analysis (PLS-DA), random forest (RF), naive Bayes (NB), and support vector machine with radial basis (SVM-r) kernel. In the germination prediction, the models individually reached an accuracy of 82% using FT-NIR data, and 90% using X-ray data. For seed vigor, the models achieved 61% and 68% accuracy using FT-NIR and X-ray data, respectively. Combining the FT-NIR and X-ray data, the performance of the classification model reached an accuracy of 85% to predict germination, and 62% for seed vigor. Overall, the models developed using both NIR spectra and X-ray imaging data in machine learning algorithms are efficient in quickly, non-destructively, and accurately identifying the capacity of seed to germinate. The use of X-ray data and the LDA algorithm showed great potential to be used as a viable alternative to assist in the quality classification of U. brizantha seeds.

The present study tested the ecological apparency hypothesis in a Brazilian rural community. It used the use value to test the information gained through three types of calculations (UV change , UV general , UV potential ). A vegetation inventory was performed in two areas near Capivara, Paraí-ba, Brazil, and 112 informants were interviewed. For the hypothesis test, the Spearman correlation coefficient was used to correlate the phytosociological (vegetation) and ethnobotanical data (use value). The study recorded 25 useful species in the first site and 20 in the second site. Positive correlations were found in the first site, between the UV g to basal area and dominance, and between the UV c and basal area, dominance, and importance value. In the second site, between the UV g and both basal area and dominance and between UV c and basal area, density, and dominance. Apparency explained the local importance of useful plants in construction, technology, and fuel, but was not explanative of medicine. Also, important responses were observed for the different use values.

Successive cycles of water absorption and loss favor weathering deterioration, one of the main factors that affect the quality of soybean seeds. This study evaluated the physiological, physical, and morpho-anatomical changes in soybean seeds under weathering deterioration at the pre-harvest phase. Six soybean cultivars (BMX Apolo, DM 6563, NS 5959, NA 5909, BMX Potência, and TMG 1175) were produced in a greenhouse and underwent weathering deterioration through a rainfall simulation system, applying 0, 60, 120, and 180 mm of precipitation at pre-harvest phase. Each rainfall level was divided into two applications at an interval of 72 h: 60 mm (30 + 30), 120 mm (60 + 60), and 180 mm (90 + 90). After harvest, the seeds were evaluated for germination, vigor, physical and morpho-anatomical properties. Weathering deterioration induced by simulated rainfall at the pre-harvest phase contributes to the reduction in soybean seed germination and vigor and is conditioned by the soybean genotype. The increase in intensity of simulated rainfall led to a more significant weathering damage in seeds, as evidenced by the X-ray and tetrazolium test. Cultivars DM 6563 and BMX Potência were more susceptible, while NA 5909 was less susceptible to weathering deterioration (especially at the highest level; 120 mm and 180 mm). Anatomical changes caused by weathering deterioration lead to cell compaction and rupture, mainly in the cell layers of the hourglass and parenchyma, forming intracellular spaces. The presence of weathering damage caused a reduction in physiological soybean seed quality.

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Cavidades secretoras são constantemente citadas entre espécies da família Myrtaceae. As cavidades secretoras possuem origens diversas, podendo ser oriundas do afastamento de células (esquizógena), de morte celular programada (lisígena) ou da combinação destes dois processos (esquizolisígena). Este trabalho descreve a ontogenia das cavidades presentes nas folhas de onze espécies da família Myrtaceae. Foram utilizados ápices vegetativos de espécimes ocorrentes na região dos municípios de Itutinga e Sete Lagoas, Minas Gerais. As amostras foram fixadas em FAA70, estocadas em etanol 70%, desidratadas em série etílica e incluídas em metacrilato. Cortes transversais e longitudinais de 6 a 8 µm de espessura foram obtidos em micrótomo rotativo de avanço automático. Os cortes foram corados com Azul de Toluidina para caracterização estrutural. Lâminas permanentes foram montadas com resina sintética. As cavidades apontam para uma origem no meristema fundamental, apresentando paredes finas e citoplasma denso, e com intensa atividade de divisão celular, originando de forma precoce o epitélio secretor com células caracteristicamente achatadas. O afastamento das células no interior da cavidade ocorre conseguinte à formação do epitélio secretor. Ao final do processo de formação, as cavidades passam por um evento de apoptose, em que células do seu interior são degradadas, caracterizando a esquizolisigenia.