Abstract Background: The evaluation of selective herbicides for weed control in winter cereals is extremely important. Simple methods to evaluate alterations caused by herbicides in the growth and development of winter cereals can be performed with vegetation indices. Objective: Evaluate the potential of different vegetation indices by optical sensors to detect phytotoxicity caused by herbicides in winter cereals. Methods: The experiment was conducted under field conditions, in a randomized block design with four replications. Herbicides were sprayed when the plants were at Z24. The phytotoxicity was evaluated at 7, 14 and 21 days after treatment (DAT) and the normalized difference vegetation index (NDVI) and the normalized difference red edge index (NDRE) at 16, 22 and 37 DAT. Results: The herbicide 2,4-D was less phytotoxic to winter cereals, while metribuzin and saflufenacil caused higher percentages (up to 50%) of visible injuries. The NDRE discriminated more precisely than NDVI the variations in winter cereals, showing alteration in the chlorophyll content due to the phytotoxicity caused by the herbicides. The canonical correlation analysis found an inverse relationship between phytotoxicity and vegetation indices. Conclusions: The winter cereals studied were tolerant to herbicides, enabling the recovery of growth and development. The NDRE index was the most sensitive and showed greater potential in identifying injuries caused by herbicides. The canonical correlation analysis confirmed the inverse relationship between phytotoxicity and the reduction of vegetation indices.

RESUMO Objetivou-se neste estudo ajustar os modelos não lineares Gompertz e Logístico, para as massas de matéria fresca e seca de parte aérea e indicar o modelo que melhor descreve o crescimento de duas cultivares de centeio em cinco épocas de semeadura e caracterizar o crescimento das cultivares em relação às massas de matéria fresca e seca de parte aérea. Dez ensaios de uniformidade foram conduzidos com a cultura do centeio no ano de 2016. A partir do período que as plantas apresentavam uma folha expandida, iniciou-se, semanalmente, a coleta e avaliação de 10 plantas de cada ensaio. Em cada planta foram pesadas as massas de matéria fresca e seca de parte aérea. Foram ajustados os modelos Gompertz e Logístico em função da soma térmica acumulada, a partir das médias de cada caractere, em cada avaliação. Também, estimaram-se os parâmetros a, b e c para cada modelo e calculou-se o intervalo de confiança para cada parâmetro e os pontos de inflexão, aceleração máxima, desaceleração máxima e desaceleração assintótica. A qualidade do ajuste dos modelos foi verificada pelo coeficiente de determinação, critério de informação de Akaike e desvio padrão residual. Foi quantificada a não linearidade intrínseca e a não linearidade do efeito dos parâmetros. Ambos os modelos descrevem satisfatoriamente o comportamento das massas de matéria fresca e seca da parte aérea. O modelo Logístico descreve melhor o crescimento das cultivares de centeio. O crescimento das cultivares BRS Progresso e Temprano é distinto entre as épocas de semeadura. A cultivar BRS Progresso necessita menor soma térmica até atingir 50% de seu crescimento quando comparada com a cultivar Temprano.

ABSTRACT This study aimed to adjust the Gompertz and Logistic nonlinear models for the fresh and dry matter of aerial part and indicate the model that best describes the growth of two rye cultivars in five sowing seasons, as well as to characterize the growth of the cultivars regarding the fresh and dry matter of aerial part. Ten uniformity trials were conducted with the rye crop in 2016. A weekly sampling and evaluation of 10 plants per trial was performed from the time the plants presented one expanded leaf. For each plant, the fresh and dry matter of aerial part were weighed. The Gompertz and Logistic models were adjusted to the accumulated thermal time based on the measures of each trait in each assessment. Also the parameters a, b, and c for each model were estimated and calculated the interval of confidence for each parameter, as well as the inflection points, maximum acceleration, maximum deceleration and asymptotic deceleration. The quality of the model adjustments was verified using the coefficient of determination, Akaike information criterion, and residual standard deviation. The intrinsic nonlinearity and nonlinearity of the parameter effect was quantified. Both models satisfactorily describe the behavior of the fresh and dry matter of aerial part. The Logistic model best describes the growth of rye cultivars. The growth of the cultivars BRS Progresso and Temprano is distinct between sowing seasons. Cultivar BRS Progresso requires a lower thermal time until reaching 50% of its growth when compared to the Temprano cultivar.