Sistema de previsão para o manejo da ferrugem asiática em soja

Asian soybean rust is the most important disease in soybean crop, having a high leaf damage potential. The use of disease forecasting systems may reduce the number of fungicide applications to its requirement and thus also reduces costs, risks of severe epidemics and environmental pollution. This work aimed to establish and test a forecasting system for the occurrence of Asian soybean rust in soybean, based on different meteorological variables and fungicide application intervals. The field experiment was carried out at UFFS - Campus Cerro Largo, with a completely randomized factorial design with 2 soybean genotypes, 6 management programs with 3 replications, totaling 36 plots. The genotypes SYN 1561 (no Inox®) and TMG 7363 RR (Inox®) were sown on November 22, 2018 and fungicide applications were performed to control Asian soybean rust, as indicated by the forecasting system for the 6 treatments: Calendarized application every 14 days from R1, control without spray, 11, 9, 7 and 5 severity values calculated. For this calculation, data were obtained in the UFFS - Campus Cerro Largo Automatic Wheather Station. Data were submitted to ANOVA by F test and means compared by Scott-Knott test at 5% probability of error. In the 11SVC and 9SVC treatments two fungicide sprays were performed, in the 7SVC treatment three sprays and in the 5SVC and in the Calendarized four sprays throughout the crop cycle, as the forecast system indicated. The higher area under the disease-progress curve, both in the upper and lower position of evaluation in the canopy, was observed in the control management programs in the no Inox® genotypes and there was no significant difference in the research between management programs and not genotypes. In both the Inox® and the no Inox® genotypes, management programs 9SVC had the highest, showing only two fungicide sprays at the right time allowed.A ferrugem asiática é a mais importante doença na cultura da soja, possuindo um alto potencial de dano nas folhas. A utilização de sistemas de previsão de doenças pode reduzir o número de aplicações de fungicidas, efetuando-as somente quando necessárias e, desta forma, também os custos para o produtor, os riscos de ocorrência de epidemias severas e a poluição ambiental. Este trabalho objetivou testar um sistema de previsão para a ocorrência de ferrugem asiática na soja, com base em variáveis meteorológicas e diferentes intervalos de aplicação de fungicidas. O experimento de campo foi realizado na UFFS - campus Cerro Largo, com o delineamento inteiramente casualizado e fatorial, com 2 genótipos de soja, 6 programas de manejo com 3 repetições, totalizando 36 unidades experimentais. Os genótipos SYN 1561 (não Inox®) e TMG 7363 RR (Inox®) foram semeadas dia 22/11/2018 e realizadas as aplicações de fungicidas para o controle da ferrugem asiática, conforme a indicação do sistema de previsão para cada tratamento: aplicação calendarizada a cada 14 dias a partir do estágio R1, testemunha sem aplicação, 11, 9, 7 e 5 valores de severidade calculada (VSC). Para o cálculo dos VSC, os dados foram obtidos na Estação Meteorológica Automática da UFFSCampus Cerro Largo. Os dados foram submetidos à ANOVA pelo teste F e as médias comparadas pelo teste de Scott-Knott em nível de 5% de probabilidade de erro. Nos tratamentos de 11VSC e 9VSC foram realizadas duas aplicações de fungicida, no tratamento 7VSC três aplicações e no 5VSC e no Calendarizado, quatro aplicações ao longo do ciclo, conforme o sistema de previsão indicou. A maior área abaixo da curva de progresso da doença, tanto da parte superior quanto inferior das plantas, ocorreu no programa de manejo testemunha do genótipo não Inox® e não houve diferença significativa de produtividade entre os programas de manejo e nem entre os genótipos. Tanto no genótipo Inox® quanto não Inox®, no programa de manejo 9VSC obtiveram-se as maiores médias de produtividade, mostrando que apenas duas aplicações de fungicidas no momento certo seriam suficientes para obter a proteção e produção auferidas com mais aplicações

Nonlinear regression models for estimating linseed growth, with proposals for data collection

Nonlinear regression models represent an alternative way to describe plant growth. In this study, we aimed to model the growth of linseed using four methods for data collection (longitudinal, mean, random, and cross-sectional) and fitting the logistic and Von Bertalanffy nonlinear regression models. The data came from experiments conducted between 2014 and 2020 in the municipality of Curitibanos, Santa Catarina, Brazil. The study had a randomized block design, with experimental units consisting of six lines, 5.0 m long and 3.0 m wide, containing the varieties and cultivars of linseed with four replicates. We performed weekly assessments of the number of secondary stems and plant height and measured total dry mass fortnightly. After tabulation, the data were analyzed using the four methods, and the logistic and Von Bertalanffy models were fitted. The logistic model for the plant height variable exhibited the best performance using the longitudinal, mean, and cross-sectional methods. It was an alternative approach that reduced the time and labor required to conduct the experiment

Experimental plan for carrot culture

ABSTRACT: The carrotculture stands out on the world stage due to its nutritional characteristics and economic importance, an aspect that demands the constant development of research aiming greater productivity. Thus, this study proposed an experimental plan, determining the estimates of plot size, sample size, and number of repetitions, with the purpose of increasing the precision and reliability of the results of the experiments with the carrot crop. Six uniformity trials were conducted, using three cultivars in two growing seasons (Season: 2019 and 2021).Each plant was considered a basic experimental unit and in each BEU, the variables shoot height, root length, shoot fresh mass, root fresh mass, and root diameter were measured. The size of the plot, sample, and the number of repetitions was estimated by the method of maximum curvature of the coefficient of variation. The results recommend that for experiments with the carrot crop, plots with twelve plants should be used. For a sampling of carrot plants in the plot, samples of eleven plants must be used in the direction of the row, considering a semi-amplitude of the confidence interval (D%) equal to 20% of the mean, with a confidence level of 95%. For a minimum significant difference in the Tukey test expressed as a percentage of the 50% mean, plots of twelve plants per crop row, with eight replicates, are recommended

Estimativa de área foliar em genótipos de girassol

The leaf area is considered a criterion indicative of productivity. Based on this, methods are easy to perform, non-destructive and fast, which make it possible to estimate this leaf area with precision, thus having high degree of importance, due to enable the observation and evaluation of plant growth in field conditions during the entire cycle. In this present work, the objective was to estimate the leaf area of five genotypes of sunflower in function of the linear measures taken from limbo, and the number of leaves per plant. The experiment was conducted at the experimental area of the Federal University Border South in the period from October 2015 to February 2016. The areas of the limbos, the leaf were determined by direct method and were measured from the length along the main fitting and the width perpendicular to the insertion of limbo in the petiole. For the total area, in addition to the direct method, has been used a destructive method in which the sheets were cut into disks, obtaining regressions for the genotypes and concluded that the best model is the one that uses the product of the linear dimensions, but the models that use only the width are satisfactory in addition to reducing the working time.A área foliar é considerada um critério indicativo de produtividade. Com base nisso, existem métodos de fácil execução, não destrutivos e rápidos, que possibilitam estimar essa área foliar com precisão, assim possuindo alto grau de importância, devido possibilitar a observação e a avaliação do crescimento das plantas em condições de campo durante todo ciclo. Nesse presente trabalho, objetivou-se estimar a área foliar de cinco genótipos de girassol, em função das medidas lineares realizadas do limbo foliar e métodos destrutivos do número de folhas por planta. O experimento foi conduzido na área experimental da Universidade Federal Fronteira Sul no período de outubro/2015 a fevereiro/2016. As áreas dos limbos foliares foram determinadas por método direto e foram mensurados a partir do comprimento ao longo da nervura principal e a largura de forma perpendicular à inserção do limbo no pecíolo. Para área total, além do método direto, foi utilizado um método destrutivo em que as folhas foram cortadas em discos, obtendo regressões para os genótipos e concluindo que o melhor modelo é o que utiliza o produto das dimensões lineares, porém os modelos que utilizam somente a largura são satisfatórios além de reduzir o tempo de trabalho

Thermal risk for common beans due to high temperatures in three counties of Rio Grande do Sul state

Common beans are an important protein source for human diet. Much cultivated in small farms it is considered a subsistence crop, employing little cultivation technology. It presents a high susceptibility to temperatures above 28 °C in reproductive periods, causing abortion of plant parts due to the high temperature triggering the plant ethylene synthesis. The agroclimatic zoning for culture does not emphasis on air temperature, which affects the crop. With these assumptions, the aim of this work was to evaluate the high temperature thermal risk for the bean crop in Cruz Alta, Passo Fundo and São Luiz Gonzaga. From the maximum air temperature data obtained since 1961, we obtained the average frequency of days at which the maximum air temperature was equal or greater than 28 °C in ten-day periods. The bigger thermal risk was found in the third ten-day period of January and in the last ten-day period of December. Passo Fundo showed the better thermal conditions for bean crop. São Luiz Gonzaga, even during periods not indicated for the culture, during winter, still showed happen at least one day of thermal risk