The objective of this study was to determine if the presence of two ALS inhibiting herbicide residues in three Saskatchewan soils would result in an additive, synergistic, or antagonistic interaction. This was determined through field trials where herbicides were applied sequentially over the course of two years and through dose-response modelling. The herbicides examined in these experiments were imazamethabenz, flucarbazone-sodium, sulfosulfuron, and florasulam, each in combination with imazamox/imazethapyr. The phytotoxicity and persistence of the herbicides in soil was assessed using an Oriental mustard root inhibition bioassay. The determination of herbicide interaction was made through the comparison of the experimentally observed values to theoretically expected values derived from a mathematical equation.<p>The dose response curves created by placing incremental concentrations of these herbicides in soil were compared using the I50 parameter, which is the concentration resulting in a 50% reduction in root length. It appeared that soil organic matter followed by soil pH had the greatest effect in reducing herbicide residue phytotoxicity in the tested soils. Based on the bioassay analysis of sequentially applied ALS inhibiting herbicides, it is proposed that the phytotoxic effect of herbicide residues in soil result in additive injury effects rather than synergistic or antagonistic interactions.

The objective of this study was to determine if the presence of two ALS inhibiting herbicide residues in three Saskatchewan soils would result in an additive, synergistic, or antagonistic interaction. This was determined through field trials where herbicides were applied sequentially over the course of two years and through dose-response modelling. The herbicides examined in these experiments were imazamethabenz, flucarbazone-sodium, sulfosulfuron, and florasulam, each in combination with imazamox/imazethapyr. The phytotoxicity and persistence of the herbicides in soil was assessed using an Oriental mustard root inhibition bioassay. The determination of herbicide interaction was made through the comparison of the experimentally observed values to theoretically expected values derived from a mathematical equation.<p>The dose response curves created by placing incremental concentrations of these herbicides in soil were compared using the I50 parameter, which is the concentration resulting in a 50% reduction in root length. It appeared that soil organic matter followed by soil pH had the greatest effect in reducing herbicide residue phytotoxicity in the tested soils. Based on the bioassay analysis of sequentially applied ALS inhibiting herbicides, it is proposed that the phytotoxic effect of herbicide residues in soil result in additive injury effects rather than synergistic or antagonistic interactions.

Studies on relations between number of sessions and effect of psychotherapy have usually assumed a constant rate of change across different lengths of therapy, explained by a model called the dose-effect model. This assumption has been challenged by the good-enough level (GEL) model, which makes the prediction that the rate of change will vary as a function of total number of sessions. This study aimed to compare these models. We also assessed the relationship between reliable and clinically significant change (RCSI) and total dose of therapy. Participants were drawn from two datasets in the Swedish primary care (n = 640) and adult psychiatric care (n = 249). The participants made session-wise ratings on the Clinical Outcomes in Routine Evaluation-Outcome Measure (CORE-OM). Multilevel analyses indicated a better fit using the GEL-model, with some reservations concerning RCSI and patterns of change. The results may indicate a general lawful relationship that may have implications for future research, as well as psychotherapy practice and policy making.

O crescimento de investimentos em biotecnologia na agricultura tem sido um elemento primordial para a segurança alimentar global. Isso tem levado a uma reorganização da indústria mundial de sementes na busca por técnicas mais adequadas de cultivo, mecanização, uso de fertilizantes, defensivos agrícolas e a utilização de sementes. O Brasil por ser um dos ambientes mais sólidos nesse contexto tem contribuído com o crescimento e a diversificação da produção de sementes levando as lavouras brasileiras a atingirem um novo patamar de produtividade. Diferentes metodologias estatísticas têm sido utilizadas para analisar o comportamento da germinação de uma população de sementes. Entretanto, usar abordagens estatísticas que analisam os dados de germinação da melhor maneira possível permitirá uma maior confiabilidade dos resultados, bem como, ganho de informações pertinentes. Como em testes de germinação de sementes estuda-se o tempo até a ocorrência do evento, que envolve medidas repetidas feitas no mesmo lote e não se conhece o tempo exato da germinação da semente, propõe-se o uso de modelos de dose-resposta com censura intervalar, que permitem a interpretação biológica dos parâmetros usados para medir o processo germinativo e refletem o desenho experimental dos dados. Neste trabalho foram utilizadas duas metodologias estatísticas usuais na análise de dados de germinação de sementes e seus resultados foram comparados com os da abordagem de modelos dose-resposta com censura intervalar. Foram utilizados os modelos de dose-resposta Weibull 2 e log-logístico para explicar o processo germinativo de sementes de Brachiaria e Citrumelo Swingle respectivamente, com diferentes tempos de observação. Os experimentos foram realizados em delineamento inteiramente aleatorizado e os procedimentos dos testes de germinação de acordo com as Regras para Análise de Sementes (RAS). As conclusões obtidas a partir da análise dos dados por meio da metodologia proposta, em geral, divergiram das conclusões obtidas por abordagens tradicionais (modelos de regressão não-linear considerando a distribuição normal e índices de germinação com o uso da análise de variância) utilizadas para analisar dados de germinação. Os modelos de dose-resposta com censura intervalar apresentaram ajustes satisfatórios e sendo portanto uma análise mais adequada que as abordagens usuais. / The growth of investment in biotechnology in agriculture has been a vital element for global food security. This has led to a reorganization of the world seed industry in the seeking of the most appropriate techniques of cultivation, mechanization, use of fertilizers, pesticides and seeds. The Brazil for being one of the most solid in the world context of the seed industry has contributed to the growth and diversification of seed production, leading Brazilian crops to a new level of productivity. Different statistical methodologies have been used to analyze the germination behavior. However, using statistical approaches that analyze germination data as efficiently as possible will allow a greater reliability of the results, as well as relevant information gain. As in seed germination test studies the time until the occurrence of the event, involves repeated measurements on the same experimental unit and do not know the exact time of germination, we propose the use of dose-response models with interval censured that allow biological interpretation of parameters used to measure the germination process and reflect the experimental design of the germination data. In this work we used two methodologies of usual statistical analysis and their results were compared with those of the approach that uses the dose-response models with interval censured. We used the dose response models Weibull 2 and log-logistic to explain the process of seed germination of Brachiaria and Citrumelo Swingle with different observation times. The experiments were carried out in completely randomized design and testing procedures according to the rules for seed analysis (RAS). The conclusions obtained from the analysis of the data by the proposed methodology in general diverged from the conclusions obtained by traditional approaches (regression models nonlinear considering normal distribution and germination indices using analysis of variance) used to analyze data germination. The dose-response models with interval-censored showed satisfactory adjustments and therefore a more accurate analysis than the usual approaches.

O crescimento de investimentos em biotecnologia na agricultura tem sido um elemento primordial para a segurança alimentar global. Isso tem levado a uma reorganização da indústria mundial de sementes na busca por técnicas mais adequadas de cultivo, mecanização, uso de fertilizantes, defensivos agrícolas e a utilização de sementes. O Brasil por ser um dos ambientes mais sólidos nesse contexto tem contribuído com o crescimento e a diversificação da produção de sementes levando as lavouras brasileiras a atingirem um novo patamar de produtividade. Diferentes metodologias estatísticas têm sido utilizadas para analisar o comportamento da germinação de uma população de sementes. Entretanto, usar abordagens estatísticas que analisam os dados de germinação da melhor maneira possível permitirá uma maior confiabilidade dos resultados, bem como, ganho de informações pertinentes. Como em testes de germinação de sementes estuda-se o tempo até a ocorrência do evento, que envolve medidas repetidas feitas no mesmo lote e não se conhece o tempo exato da germinação da semente, propõe-se o uso de modelos de dose-resposta com censura intervalar, que permitem a interpretação biológica dos parâmetros usados para medir o processo germinativo e refletem o desenho experimental dos dados. Neste trabalho foram utilizadas duas metodologias estatísticas usuais na análise de dados de germinação de sementes e seus resultados foram comparados com os da abordagem de modelos dose-resposta com censura intervalar. Foram utilizados os modelos de dose-resposta Weibull 2 e log-logístico para explicar o processo germinativo de sementes de Brachiaria e Citrumelo Swingle respectivamente, com diferentes tempos de observação. Os experimentos foram realizados em delineamento inteiramente aleatorizado e os procedimentos dos testes de germinação de acordo com as Regras para Análise de Sementes (RAS). As conclusões obtidas a partir da análise dos dados por meio da metodologia proposta, em geral, divergiram das conclusões obtidas por abordagens tradicionais (modelos de regressão não-linear considerando a distribuição normal e índices de germinação com o uso da análise de variância) utilizadas para analisar dados de germinação. Os modelos de dose-resposta com censura intervalar apresentaram ajustes satisfatórios e sendo portanto uma análise mais adequada que as abordagens usuais. / The growth of investment in biotechnology in agriculture has been a vital element for global food security. This has led to a reorganization of the world seed industry in the seeking of the most appropriate techniques of cultivation, mechanization, use of fertilizers, pesticides and seeds. The Brazil for being one of the most solid in the world context of the seed industry has contributed to the growth and diversification of seed production, leading Brazilian crops to a new level of productivity. Different statistical methodologies have been used to analyze the germination behavior. However, using statistical approaches that analyze germination data as efficiently as possible will allow a greater reliability of the results, as well as relevant information gain. As in seed germination test studies the time until the occurrence of the event, involves repeated measurements on the same experimental unit and do not know the exact time of germination, we propose the use of dose-response models with interval censured that allow biological interpretation of parameters used to measure the germination process and reflect the experimental design of the germination data. In this work we used two methodologies of usual statistical analysis and their results were compared with those of the approach that uses the dose-response models with interval censured. We used the dose response models Weibull 2 and log-logistic to explain the process of seed germination of Brachiaria and Citrumelo Swingle with different observation times. The experiments were carried out in completely randomized design and testing procedures according to the rules for seed analysis (RAS). The conclusions obtained from the analysis of the data by the proposed methodology in general diverged from the conclusions obtained by traditional approaches (regression models nonlinear considering normal distribution and germination indices using analysis of variance) used to analyze data germination. The dose-response models with interval-censored showed satisfactory adjustments and therefore a more accurate analysis than the usual approaches.