Fusarium wilt, a vascular syndrome in a wide range of plants, is caused by the pathogen Fusarium Oxysporum. The objective of this investigation was to evaluate the antifungal effect of four essential oils (EOs) (Plectranthus amboinicus, Syzygium aromaticum, Lippia alba, and Rosmarinus officinalis), which were obtained by using microwave-assisted hydrodistillation (MAH), against F. oxysporum. The yield obtained from P. amboinicus with the use of MAH was 0.2%, which was higher than that of a conventional extraction; its extraction time was also shorter. For concentrations of 100 and 300 μL/L, P. amboinicus caused an inhibition rate of 27.2 and 55.7%, respectively, while S. aromaticum caused an inhibition rate of 23.1 and 87.3%, respectively. It was observed that increasing the concentration also increased the % inhibition rate. The extracts of L. alba and R. officinalis caused an inhibition rate of 14.5 and 14.7% at 500 µL/L, respectively, at 10 days of incubation, while at this concentration, P. amboinicus and S. aromaticum achieved 100%. The major chemical compounds of P. amboinicus were carvacrol (41.20%), o-cymene (11.61%), caryophyllene (11.45%), α-bergamotene (7.71%), and caryophyllene oxide (4.62%), and these monoterpene hydrocarbons were responsible for the biological activity. The essential oil of P. amboinicus in appropriate concentrations is a potent antifungal agent that could be used for the control of F. oxysporum.

Mixed models are a useful tool for the analysis of sugarcane field trials in which sugarcane varieties are allocated in different locations and phenotypic traits are evaluated in the same experimental unit (plot) over time. One challenge to analyze these data is how to build a good mixed model when no experimental design is planned, because all sugarcane varieties in the area of influence of a sugar mill are planted in different years due to the age of the crop and there is no spatial information on all plots. The aim of this research was to examine and to determine the most appropriate mixed model for estimating cane stalk yield of sugarcane varieties when previously there was no planned experimental design. Cane stalk yields of 26 sugarcane genotypes harvested in 24 different locations and in different crop cycles (age) were analyzed. The randomized block nested design (plot within block) with ratoon crop as a class variable in the mixed model was the best for the mean comparisons in sugarcane genotype trials (Model 3), allowing a gain in information. The randomized block design approach helps to fit more general random effects, and the covariance structures helps to improve the performance of mixed model repeated measures. This study emphasizes the need to improve the process of finding a good enough mixed model, that is, how to define the mean structure and the best covariance structure for model sugarcane trials that enables more powerful and efficient parameter estimations. The results showed how a more appropriate mixed model might help avoid errors of judgment in sugarcane genotype recommendations for enhancing the productivity of the cane industry.