Medidor de perdas na colheita de soja e trigo.

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População de plantas de soja no sistema de semeadura direta para o Centro-Sul do Estado do Paraná.

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Survival of pathogens on soybean debris under no-tillage and conventional tillage systems.

A study was conducted in the subtropical area of Southern Brazil to determine the survival of pathogens in soybean residues under conventional and no-tillage cultivation systems from March to September of 1998 and 1999. The pathogens most frequently isolated were Colletotrichum truncatum, Phomopsis spp., Cercospora kikuchii, Fusarium spp., Macrophomina phaseolina, and Rhizoctonia solani. Other fungi isolated were Myrothecium roridum, Penicillium sp., Chaetomium sp., Epicoccum sp., Corynespora cassiicola and Trichoderma sp. The percent of survival of each pathogen varied according to the month and the year. Survival of C. truncatum, Phomopsis spp. and C. kikuchii were significantly reduced (p<0.05) from the first to the last evaluation either on buried debris or maintained on the soil surface. On the other hand, M. phaseolina and Fusarium spp. were either not affected or favored by burying the debris. The frequency of recovery of Fusarium spp. increased specially in debris kept under the soil. The loss of biomass, measured by debris weight along the period of this study, showed a reduction of 44.4% in the conventional system and 34.9% in the no-tillage system in 1998, when rain was better distributed. In 1999, the reduction was 48.2% and 39.0% for the conventional and no-tillage system, respectively

Avaliação de perdas na colheita do trigo pelo método da armação de pano e copo medidor.

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Rendimento de graos em diferentes sistemas de preparo e manejo de solos.

Material e metodos: amostragem e avaliacao; Resultados e discussao: primeira etapa de 1978 ate 1986 - 17 cultivos; Segunda etapa: de 1987 ate 1990 - cultivos 18 a 23; Conclusoes e recomendacoes; Implicacoes praticas dos resultados experimentais.bitstream/item/60909/1/Documentos-61.pd

Rotação de culturas com a soja no norte do Estado do Paraná.

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Indicações técnicas para o cultivo do girassol.

Preparo do solo; Semeadura: profundidade, espacamento e densidade, epoca de semeadura; Cultivares; Calagem; Nutricao e adubacao: nitrogenio, fosforo, potassio; Controle de plantas daninhas; Insetos-pragas; Doencas do girassol: mancha de Alternaria, podridao e murcha de Esclerotinia, ferrugem, podridao de Macrophomina, seca da haste por Phomopsis sp.; Colheita e armazenagem; Custo de producao.bitstream/item/60518/1/Documentos-3.pd

Predicting attitudinal and behavioral responses to COVID-19 pandemic using machine learning

At the beginning of 2020, COVID-19 became a global problem. Despite all the efforts to emphasize the relevance of preventive measures, not everyone adhered to them. Thus, learning more about the characteristics determining attitudinal and behavioral responses to the pandemic is crucial to improving future interventions. In this study, we applied machine learning on the multinational data collected by the International Collaboration on the Social and Moral Psychology of COVID-19 (N = 51,404) to test the predictive efficacy of constructs from social, moral, cognitive, and personality psychology, as well as socio-demographic factors, in the attitudinal and behavioral responses to the pandemic. The results point to several valuable insights. Internalized moral identity provided the most consistent predictive contribution—individuals perceiving moral traits as central to their self-concept reported higher adherence to preventive measures. Similar results were found for morality as cooperation, symbolized moral identity, self-control, open-mindedness, and collective narcissism, while the inverse relationship was evident for the endorsement of conspiracy theories. However, we also found a non-neglible variability in the explained variance and predictive contributions with respect to macro-level factors such as the pandemic stage or cultural region. Overall, the results underscore the importance of morality-related and contextual factors in understanding adherence to public health recommendations during the pandemic.Peer reviewe

Predicting attitudinal and behavioral responses to COVID-19 pandemic using machine learning

At the beginning of 2020, COVID-19 became a global problem. Despite all the efforts to emphasize the relevance of preventive measures, not everyone adhered to them. Thus, learning more about the characteristics determining attitudinal and behavioral responses to the pandemic is crucial to improving future interventions. In this study, we applied machine learning on the multinational data collected by the International Collaboration on the Social and Moral Psychology of COVID-19 (N = 51,404) to test the predictive efficacy of constructs from social, moral, cognitive, and personality psychology, as well as socio-demographic factors, in the attitudinal and behavioral responses to the pandemic. The results point to several valuable insights. Internalized moral identity provided the most consistent predictive contribution—individuals perceiving moral traits as central to their self-concept reported higher adherence to preventive measures. Similar results were found for morality as cooperation, symbolized moral identity, self-control, open-mindedness, and collective narcissism, while the inverse relationship was evident for the endorsement of conspiracy theories. However, we also found a non-neglible variability in the explained variance and predictive contributions with respect to macro-level factors such as the pandemic stage or cultural region. Overall, the results underscore the importance of morality-related and contextual factors in understanding adherence to public health recommendations during the pandemic