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Resultado 1-10 de 69.
Ano de publicaçãoTítuloAutor(es)
2020Co-inoculation of Bradyrhizobium japonicum and Azospirillum brasilense on the physiological quality of soybean seedsLIBÓRIO, P. H. da S.; BARBARO-TORNELI, I. M.; NOGUEIRA, M. A.; UNEDA-TREVISOLI, S. H.
2020UAV-based thermal imaging in the assessment of water status of soybean plants.CRUSIOL, L. G. T.; NANNI, M. R.; FURLANETTO, R. H.; SIBALDELLI, R. N. R.; CEZAR, E.; MERTZ-HENNING, L. M.; NEPOMUCENO, A. L.; NEUMAIER, N.; FARIAS, J. R. B.
2020Intracultivar selection for seed quality of soybeans in an ultra-low-density selection model (Honeycomb Selection Designs)LOPES, K. B. de A.; PIPOLO, A. E.; BAZZO, J. H. B.; ZUCARELI, C.
2020Phosphate Fertilizer in Soybean-Wheat Cropping System Under No-Till ManagementMOREIRA, A.; MORAES, L. A. C.; PETINELI, R.
2022Interaction of Mechanical Damage and Chemical Treatment and Its Effects on Soybean Seed Physiological Quality.COPPO, C.; BRACCINI, A. L.; HENNING, F. A.; PEREIRA, R. C.; SILBA, B. G.; OLIVEIRA, S. M.; SANTOS, R. F.; BASTIANI, G. G.; CATELAN, L. C.; PROTZEK, H. M. C.; BORGES, Y. M.
2021Genome-wide association study for resistance to the Meloidogyne javanica causing root-knot nematode in soybean.ALEKCEVETCH, J. C.; PASSIANOTTO, A. L. de L.; FERREIRA, E. G. C.; SANTOS, A. B. dos; SILVA, D. C. G. da; DIAS, W. P.; BELZILE, F.; ABDELNOOR, R. V.; MARCELINO-GUIMARÃES, F. C.
2020Physiological quality of soybean seeds submitted to chemical treatment and storage times.BRZEZINSKI, C. R.; ABATI, J.; WERNER, F.; HENNING, F. A.; HENNING, A. A.; ZUCARELI, C.
2021Classification of soybean genotypes assessed under different water availability and at different phenological stages using leaf-based hyperspectral reflectance.CRUSIOL, L. G. T.; NANNI, M. R.; FURLANETTO, R. H.; SIBALDELLI, R. N. R.; CEZAR, E.; SUN, L.; FOLONI, J. S. S.; MERTZ-HENNING, L. M.; NEPOMUCENO, A. L.; NEUMAIER, N.; FARIAS, J. R. B.
2020Physiological potential of soybean industrially treated with different spray volumes and dry powder.ABATI, J.; BRZEZINSKI, C. R.; ZUCARELI, C.; WERNER, F.; HENNING, A. A.; HENNING, F. A.
2023Using brainwave patterns recorded from plant pathology experts to increase the reliability of ai-based plant disease recognition system.MEIR, Y.; BARBEDO, J. G. A.; KEREN, O.; GODOY, C. V.; AMEDI, N.; SHALOM, Y.; GEVA, A. B.
Resultado 1-10 de 69.

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