RESUMO Este trabalho objetivou identificar comprimentos de ondas com base na reflectância foliar (400-1050 nm), visando à estimativa da severidade do mofo-branco em cultivos de feijão para diferentes datas. Foram implantados dois experimentos em períodos de outono / inverno. Utilizou- -se da regressão por Mínimos Quadrados Parciais (PLS) para a definição do conjunto de comprimentos de onda que melhor estime a severidade da doença numa determinada data. Para uso desse método, as observações foram previamente divididas em dois subgrupos: o primeiro (calibração) foi utilizado para a construção do modelo, e o segundo subgrupo, para testar o modelo definido. Medidas de Raiz do Erro Médio Quadrático (RMSE) e de correlação entre valores medidos e preditos da severidade da doença foram utilizadas para avaliar os modelos. Medidas de erro e de correlação entre valores medidos e preditos do índice de severidade da doença foram utilizadas para estabelecer os comprimentos de onda que melhor estimam a doença nas diferentes datas. O índice médio de severidade de doença em cada experimento foi de 5,8% e de 7,4%, considerados baixos. Faixas espectrais de transição entre as bandas azul e verde, entre as bandas verde e vermelha e entre as bandas vermelha e infravermelha mostraram-se mais sensíveis à estimativa da doença. Outras regiões espectrais também apresentaram comprimentos de onda com potencial para determinar a severidade da doença, tais como: o vermelho, verde e infravermelho próximo.

ABSTRACT This study aimed to identify wavelengths based on leaf reflectance (400-1050 nm) to estimate white mold severity in common beans at different seasons. Two experiments were carried out, one during fall and another in winter. Partial Least Squares (PLS) regression was used to establish a set of wavelengths that better estimates the disease severity at a specific date. Therefore, observations were previously divided in two sub-groups. The first one (calibration) was used for model building and the second subgroup for model testing. Error measurements and correlation between measured and predicted values of disease severity index were employed to provide the best wavelengths in both seasons. The average indexes of each experiment were of 5.8% and 7.4%, which is considered low. Spectral bands ranged between blue and green, green and red, and red and infrared, being most sensitive for disease estimation. Beyond the transition ranges, other spectral regions also presented wavelengths with potential to determine the disease severity, such as red, green, and near infrared.

Common bean is an economically, nutritionally, and socially important crop. It is grown in distinct regions and different seasons around the world by subsistence level farmers with low-technology input as well as by farmers that use high input technologies. One important factor that can limit the bean growing and drastically affect grain yields is the high number of destructive pathogens that attack and cause serious damage to the crop. Among them is bean rust, incited by the fungus Uromyces appendiculatus. This disease is distributed throughout the world, but it effectively causes major production problems in humid tropical and subtropical regions. In Brazil, rust causes major losses in south, southeast, and central regions of the country. Bean rust control by resistant cultivars is an easy and economical strategy to be used in association to other rust management practices. Pyramiding of different race-specific resistance genes in association with other genes conferring adult plant resistance, slow rusting, and reduced pustule size can prolong the lifespan of a common bean cultivar by creating a more durable resistance complex against the rust pathogen. This review manuscript presents an overview on bean rust and reports some breeding efforts aiming to develop rust resistant cultivars in Brazil.