Citrus canker and Huanglongbing (HLB) are citrus diseases that represent a serious threat to the citrus production worldwide and may cause large economic losses. In this work, we combined fluorescence imaging spectroscopy (FIS) and a machine learning technique to discriminate between these diseases and other ordinary citrus conditions that may be present at citrus orchards, such as citrus scab and zinc deficiency. Our classification results are highly accurate when discriminating citrus canker from citrus scab (97.8%), and HLB from zinc deficiency (95%). These results show that it is possible to accurately identify citrus diseases that present similar symptoms.
The overall objective of this work was to develop and evaluate computer vision and machine learning technique for classification of Huanglongbing-(HLB)-infected and healthy leaves using fluorescence imaging spectroscopy. The fluorescence images were segmented using normalized graph cut, and texture features were extracted from the segmented images using cooccurrence matrix. The extracted features were used as an input into the classifier, support vector machine (SVM). The classification results were evaluated based on classification accuracies and number of false positives and false negatives. The results indicated that the SVM could classify HLB-infected leaf fluorescence intensities with up to 90% classification accuracy. Though the fluorescence intensities from leaves collected in Brazil and the USA were different, the method shows potential for detecting HLB.
RESUMOEste estudo objetivou conhecer a percepção do surdo e dos profissionais da saúde no atendimento à saúde pública do surdo e como se dá a comunicação entre eles. Trata-se de uma revisão bibliográfica baseada na literatura em língua portuguesa, no período de 2013 a 2018, através de consulta as bases de dados da Capes, LILACS, SciELO e Google acadêmico. Constatou-se nas pesquisas analisadas que a percepção dos surdos e dos profissionais da saúde remete-se a falta de comunicação em Libras como maior obstáculo para um atendimento à saúde integral e humanizado. Concluiu-se que a comunicação é essencial para um atendimento de qualidade e precisa ser efetivada com políticas públicas que visem inserir nos planos curriculares das escolas e universidades na área da saúde, na formação técnica e superior, a disciplina Libras. Dessa forma, o surdo será assistido na saúde com respeito à sua identidade e cultura surda, e reconhecido como sujeito de direitos na sua dignidade humana. Palavras-chave: Surdos; Libras; Profissionais da saúde; atendimento à saúde; comunicação em Libras.
A Deus por me guiar e ajudar nos momentos de angústia e dificuldades, me revelando caminhos e oportunidades durante essa jornada.Ao meu orientador e amigo Prof. Dr. Luis Gustavo Marcassa, pelo seu suporte e apoio durante o desenvolvimento deste trabalho. Seus conhecimentos, sinceridade, opinião e nossas conversas me ajudaram a crescer profissionalmente e como pessoa.Aos meus pais, Carmo e Isabel, que tanto me apoiaram e incentivaram a continuar este trabalho, não me deixando abater pelas dificuldades encontradas. Pela confiança em meu sucesso. O apoio de vocês foi fundamental durante esta jornada. Amo muito vocês.À minha noiva, namorada e amiga, Denise, que nesta trajetória me apoiou de forma incondicional em minhas escolhas com sua paciência e amor. Nossas conversas me tornaram uma pessoa melhor. Sua confiança em meu trabalho me motivou em cada dia de angústia.
Chlorophyll content is a widely used parameter for nutritional status diagnosis in sugarcane. This study aimed to develop a predictive model of chlorophyll content in sugarcane seedlings using spectral imagery analysis within the electromagnetic spectrum visible range. The experiment was carried out in a split-plot design, with two fertilization rates and three sugarcane cultivars. For chlorophyll analysis, 144 leaves were collected from seedlings. Chlorophyll contents were extracted and measured by SPAD-502 meter. Spectral images within the range of 480 to 710 nm were analyzed using reflectance, absorbance (white source), and fluorescence (source at 405 and 470 nm) responses. Predictive models were developed using multivariate regression methods such as Principal Component Regression and Partial Least Squares Regression. We chose the best model through absorbance response using variable selection and the PLSR method (R2P = 0.718 and RMSEP = 7.665). The wavelengths of 480, 490, 500, 600, 630, and 640 nm were identified as the best for total chlorophyll content determination. The spectral image processing-based method can provide a chlorophyll measurement equivalent to SPAD, with the advantage of having a higher spatial coverage over the entire leaf area. Besides, it can also support automation of the chlorophyll measurement in greenhouses.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.