ABSTRACT This study aimed to identify the correlations between traits of the groups stem cutting, seedling, stem, and root of cassava. Length, diameter, and weight of stem cutting (Group 1) were measured at each growing season (July, August, September, and October). A total of 300 cuttings were collected after sprouting and planted at seasons of September 22, October 7 and 19, and November 25. Plant height at planting, number of leaves at planting, and number of leaves at 7 days after planting were measured. The number of leaves at transplanting and plant height at transplanting were determined after acclimation (Group 2). Seedling transplanting was carried out on November 9 and 24 and December 3 and 26, and the traits stem (Group 3) and root (Group 4) yield were measured at harvest. Associations between the groups stem cutting and seedling were established by stem cutting diameter and weight, and height and number of leaves at planting. Seedling traits had the greatest influence on the number of buds per stem and stem diameter. Main stem branching height and stem diameter can be used for selecting plants with an indication of the best quality and yield of root traits.

ABSTRACT The flaxseed is little explored under Brazilian cultivation conditions, generating a gap in information about the appropriate management of the crop, in the country. Hence, the objective was to find the appropriate dose of nitrogen for the development of the variables: technical length, yield length, main stem diameter, number of grains per pod, plant grain yield, and plant dry mass of two flaxseed varieties, brown and golden, in places with subtropical and tropical climate in Brazil. The treatments consisted of a two-factor 2 x 6 experiment, consisting of two flax varieties (brown and golden) and six nitrogen doses (0; 30; 60; 90; 120 and 150 kg ha-1), in randomized blocks with four repetitions and three different environments: Santa Maria and Frederico Westphalen, in the state of Rio Grande do Sul, and Viçosa, in the state of Minas Gerais. The brown variety obtained greater technical and yield length compared to the golden variety, on the other hand, the golden variety showed a higher number of grains per capsule and higher plant grain yield compared to the brown variety, in the three environments. The plant dry mass increased linearly and proportionally to the increase in nitrogen doses in Santa Maria and Frederico Westphalen environments. Therefore, flaxseed responds differently to nitrogen supplementation according to the cultivation environment, showing wide variability. The different doses of nitrogen influenced the variables analyzed and the varieties of flaxseed differently, depending on the environment.

ABSTRACT Seedling production is an important step in growing vegetables. The study of relationships between variables has applications in practically all areas of study and is useful in identifying relationships among quality variables in vegetable seedlings. Thus, this work aims to estimate linear relationships between biometric variables in lettuce seedlings. The seedlings were grown in expanded polystyrene trays (n = 4) with 128 and 200 cells each. Leaf area, stem diameter, shoot height, length, area, volume of the root, dry and fresh shoot mass variables were measured and evaluated with Pearson's correlation analysis, multicollinearity diagnosis, condition number and the variance inflation factor, path analysis and canonical correlations. The results show linear relationships between the variables. For the 128 cell trays, there was a relationship between the total fresh mass and fresh shoot mass variables and between the total fresh mass and dry shoot mass variables. For the 200-cell trays, significant correlation was observed between the characters total fresh mass and fresh shoot mass variables and between root area and root volume variables, indicating that the greater the total fresh mass, the greater the fresh shoot mass and the greater the root area, the greater the root volume.

ABSTRACT The aim of this study was to evaluate, using logistic model, the differences in early production, production rate and total productivity of two strawberry cultivars with transplants from different origins grown in substrate. The experiment was carried out in a randomized block design (RBD), with two strawberry cultivars (Albion and Camarosa) and two origins of transplants (National and Imported), with four repetitions consisting of eight plants. For the variable fruit mass, the logistic model was adjusted as a function of the accumulated thermal sum, and from the partial derivatives of the adjusted function, the critical points of the model were estimated. The use of the Logistic model allows evaluating precocity and rate of fruit production efficiently and accurately. The cultivar Camarosa was the most productive compared to the Albion cultivar, presenting a shorter production cycle, with a high production peak. The Albion cultivar was earlier, presenting more constant production during the evaluated production cycle. The transplant's origin did not show significantly different results for the cultivars evaluated. The producer must choose the cultivar that will be used based on its performance and also based on consumer preferences and fruit demand.

ABSTRACT The cultivation of onion Allium cepa L. is of extreme economic importance globally, and, because of this, research must be constantly updated in order to increase productivity. This study was designed to estimate the optimal plot size, sample size and number of repetitions for experiments evaluating variables in the onion crop. Uniformity tests were carried in the years 2016 and 2017 in the experimental area of the Crop Science Department at Universidade Federal de Santa Maria, Santa Maria (RS), Brazil. Each plant was considered a basic experimental unit. Bulb mass, bulb height, and bulb diameter were measured for each basic experimental unit. The optimal plot size, sample size, and number of repetitions were estimated by the method of maximum curvature of the variation coefficient. For onion culture, the optimal plot size to evaluate the bulb mass, bulb height and bulb diameter is eight, six and six, respectively. The optimal sample size for evaluating the bulb mass of the onion crop is six plants, while for the height and diameter variables the optimal sample size is four plants in the direction of the row considering a semi-amplitude of the confidence interval (D%) equal to 20% of the average. Bulb mass variables require 10 repetitions to assess up to 20 treatments in a randomized block design for the least significant difference of the Tukey’s test, expressed as a percentage of the average of 35%. Bulb height and bulb diameter require just six repetitions for the same assessment.

RESUMO: O objetivo deste trabalho foi avaliar as relações entre os caracteres biométricos de mudas de tomate com os caracteres de produção obtidos ao final do ciclo da cultura, para determinar como a qualidade das mudas interfere na produtividade do tomate. O experimento foi conduzido em duas épocas de cultivo, em delineamento inteiramente casualizado, com quatro repetições e a unidade experimental composta por cinco plantas. Os tratamentos foram constituídos por mudas com diferentes idades, diferenciadas pelos dias após a semeadura (DAS): (15, 20, 25, 30, 35 e 40 DAS). Após cada avaliação das mudas, eram transplantadas para o local de produção definitivo, sendo avaliadas até o final do ciclo. Avaliaram-se os caracteres biométricos das mudas e os caracteres da produção de frutos. Análise de correlação de Pearson e componentes principais (PCA) foram realizados para determinar as relações entre os caracteres, análise de trilha para determinar os efeitos diretos e indiretos e análise de correlações canônicas entre os grupos de caracteres. Em todas as análises realizadas, foi identificada correlação fraca entre os caracteres biométricos das mudas (que avaliam a qualidade) com os caracteres da produção de frutos de tomate em cultivo em substrato.

ABSTRACT: This study evaluated the relationships between the biometric characters of tomato seedlings with the production characters obtained at the end of the crop cycle, to determine how the quality of seedlings interferes with tomato productivity. An experiment was carried out in two growing seasons, in a completely randomized design, with four replications and the experimental unit consisting of five plants. The treatments consisted of seedlings with different ages, differentiated by the days after sowing (DAS): (15, 20, 25, 30, 35, and 40 DAS). After each evaluation of the seedlings, they were transplanted to the definitive production site, being evaluated until the end of the cycle. Biometric characters of seedlings and characters of fruit production were evaluated. Pearson correlation analysis and principal components (PCA) were performed to determine the relationships between the characters, path analysis to determine the direct and indirect effects, and analysis of canonical correlations between the groups of characters. In all analyses performed, weak correlation between the biometric characters of the seedlings (which evaluate the quality) with the characters of tomato fruit production in substrate cultivation was identified.

RESUMO Modelos de crescimento de base biológica podem ser uma alternativa na identificação da resposta produtiva de hortaliças de múltiplas colheitas. Ao interpretar as estimativas dos parâmetros dos modelos, é possível estimar a produção total, a taxa de produção de frutos e o momento em que a cultura atinge seu potencial máximo de produção. Além disso, estimando intervalos de confiança, essas respostas podem ser comparadas entre genótipos ou entre diferentes tratamentos. Portanto, o objetivo do manuscrito foi apresentar uma revisão de literatura em um passo a passo para análise e interpretação do ciclo de produção de hortaliças de múltiplas colheitas, com base em regressão não linear. Todos os requisitos que devem ser atendidos neste tipo de análise foram apresentados detalhadamente, fornecendo o passo a passo necessário para análises de regressão não linear. A demonstração é realizada usando dados do cultivo de morango junto com os scripts R associados e a interpretação da saída da análise em um material suplementar. Esta abordagem pode permitir inferências mais relevantes do que análises tradicionais realizadas, através de um melhor exame e modelagem dos processos biológicos subjacentes.

ABSTRACT Biologically based growth models can be an alternative in identifying the productive response of multiple harvest vegetables. By interpreting the estimates of the parameters of the models, it is possible to estimate the total production, the rate of fruit production, and the moment when the crop reaches its maximum production potential. Besides, by estimating confidence intervals, these responses can be compared between genotypes or between different treatments. Therefore, the purpose of this manuscript is to present a literature review, and a detailed step-by-step, to interpreting the evolution of the production cycle of vegetables with multiple harvests crops based on non-linear regression. All the requirements that must be met in this type of analysis were presented in detail based on non-linear regression, providing the necessary steps for this type of analysis in details. Demonstration is given using data from strawberry cultivation along with the associated R scripts and interpretation of analysis output in material supplemental. This approach can allow for more relevant inferences than standard means analyses through better examination and modeling of the underlying biological processes.

RESUMO O objetivo deste estudo foi identificar a resposta do ciclo produtivo de genótipos de abobrinha italiana cultivadas em condições de campo em duas épocas de cultivo por meio do modelo não linear logístico e seus pontos críticos. Para isso dois experimentos foram conduzidos em delineamento blocos ao acaso, com três genótipos (Caserta, PX13067051 e Tronco) e duas épocas de cultivo (primavera-verão e verão-outono) com oito repetições e a unidade experimental composta por 7 plantas. Ajustou-se o modelo não linear logístico para a variável massa de frutos, em função da soma térmica acumulada, e estimou-se os pontos críticos pelas derivadas parciais da função ajustada. Os pressupostos do modelo não linear não foram atendidos para nenhum genótipo em ambas as épocas avaliadas, e para contornar este problema foi realizado o ajuste por reamostragens bootstrap. Os resultados de não linearidade intrínseca e paramétrica confirmam a qualidade do ajuste do modelo. Pelos parâmetros e pontos críticos do modelo foi possível determinar que os genótipos de abobrinha italiana avaliados foram mais produtivos na primavera-verão. Os genótipos PX13067051 e Caserta apresentaram produtividade superior ao genótipo Tronco, além de serem mais precoces e apresentar maiores taxas de produção. O modelo de crescimento logístico e seus pontos críticos foram capazes de caracterizar o ciclo de produção dos genótipos de abobrinha italiana em diferentes épocas de cultivo, e permitiu que inferências fossem realizadas com vistas a diferenciar os genótipos e as épocas de cultivo avaliadas.

ABSTRACT This study aimed to identify the productive cycle response of Italian zucchini genotypes grown under field conditions in two growing seasons using the nonlinear logistic model and its critical points. Two randomized block experiments were conducted, with three genotypes (Caserta, PX13067051, and Tronco) and two growing seasons (spring-summer and summer-fall), with eight replicates and each experimental unit consisting of 7 plants. The logistic nonlinear model was adjusted for the fruit mass variable, as a function of the accumulated thermal sum, and the critical points were estimated by the partial derivatives of the adjusted function. Adjustment by bootstrap resampling was performed to address the violation of assumptions. The results of intrinsic and parametric nonlinearity confirm the quality of the model fit. This experiment demonstrated that the zucchini genotypes evaluated were more productive in the spring-summer growing season, using the parameters and critical points obtained from the logistic nonlinear model. Genotypes PX13067051 and Caserta showed superior productivity to the Tronco genotype, and also fruited earlier and at a higher rate of production. The logistic growth model and its critical points characterized the production cycle of the zucchini genotypes in different growing seasons and allowed inferences to be made to differentiate the genotypes and the growing seasons.

Abstract In agricultural experiments, measuring all plants that constitute an experimental unit is the most appropriate method for estimating averages. This study analyzed sample sizes (number of plants) for estimating averages of agronomic traits in cassava. The experiment for seedling production was conducted on four sowing dates: September 22, October 7, October 19, and November 25, 2017. The evaluated characters were plant height at planting, number of leaves at planting, number of leaves at 7 days after planting, number of leaves at transplanting, and plant height at transplanting. The seedlings were transplanted to the field on November 9, November 24, December 3, and December 26. Root characteristics and root yield were measured at harvest. The following statistics were measured: minimum, maximum, range, mean, median, variance, standard deviation, and coefficient of variation. The sample size was determined by resampling with replacement when the range of the 95% confidence interval (CI) was 10%, 20%, 30%, and 40% of the average estimate. Larger sample sizes were needed to estimate trait averages with a 95% CI range of 10% of the average estimate, i.e., when estimation accuracy was higher. In contrast, lower sample sizes were required to estimate averages of all characters in all planting times with a 95% CI range of 40%. For measuring seedling production and stem and root yield, 63 and 153 plants are sufficient to estimate averages when the range of the 95% confidence interval was 20%.

Resumen En experimentos agrícolas, medir todas las plantas que constituyen una unidad experimental es el método más apropiado para estimar promedios. Este estudio analizó tamaños de muestra (número de plantas) para estimar promedios de caracteres agronómicos en yuca. El experimento para la producción de plántulas se realizó en cuatro fechas de siembra: 22 de septiembre, 7 de octubre, 19 de octubre y 25 de noviembre de 2017. Los caracteres evaluados fueron la altura de la planta en la siembra, el número de hojas en la siembra, el número de hojas a los 7 días después de la siembra, el número de hojas en el trasplante y la altura de la planta en el trasplante. Las plántulas se trasplantaron al campo el 9 de noviembre, 24 de noviembre, 3 de diciembre y 26 de diciembre. Las características de la raíz y el rendimiento de la raíz se midieron en la cosecha. Se midieron las siguientes estadísticas: mínimo, máximo, rango, media, mediana, varianza, desviación estándar y coeficiente de variación. El tamaño de la muestra se determinó mediante remuestreo con reemplazo cuando el rango del intervalo de confianza (IC) de 95% fue de 10%, 20%, 30% y 40% de la estimación promedio. Se necesitaron tamaños de muestra más grandes para estimar los promedios de rasgos con un rango de IC de 95% de 10% de la estimación promedio; es decir, cuando la precisión de la estimación fue mayor. En contraste, se requirieron tamaños de muestra bajos para estimar promedios de los caracteres en los tiempos de siembra con un rango de IC de 95% de 40%. Para medir la producción de plántulas y rendimiento de tallos y raíces, 63 y 153 plantas son suficientes para estimar promedios cuando el rango del intervalo de confianza de 95% fue de 20%.

ABSTRACT. Tibraca limbativentris is considered one of the main species of insect pests in irrigated rice. This species can be found in plants in the vegetative and reproductive stages. This study aimed to select semivariogram models to estimate rice stem bug population densities by ordinary kriging. Two fields were used to survey the T. limbativentris population in Oryza sativa. A grid of 30 x 30 m was drawn, which generated 143 and 385 sample units for the first and second fields, respectively. Seven evaluations of two hundred plants per sampling unit were performed during cultivation. From the insect counts, the results were input into circular, spherical, pentaspherical, exponential, Gaussian, rational quadratic, cardinal sine, K-Bessel, J-Bessel, and stable semivariogram models via ordinary kriging interpolation and the best model was selected via cross-validation. Each assessment had a particular spatial structure and semivariogram model that best fit the experimental data.

ABSTRACT. Strawberry is an economically and socially important crop in several regions worldwide. Thus, studies that provide information on topics in strawberry growth are important and must be constantly updated. The aims of this study were to fit a logistic growth model to describe strawberry fruit production and to estimate the partial derivatives of the fitted model in order to estimate and interpret the critical points, in addition to using multivariate analyses. To do this, data on 16 treatments [combinations of two cultivars (Albion and Camarosa), two origins (national and imported), and four mixed organic substrates (70% crushed sugar cane residue + 30% organic compost, 70% crushed sugar cane residue + 30% commercial substrate, 70% burnt rice husk + 30% organic compost, and 70% burnt rice husk + 30% commercial substrate)] conducted in a randomized complete block design (RCBD) with four replicates were used. A logistic model was fitted to the accumulated fruit production stratified by treatment and replication. Partial derivatives related to the accumulated thermal sum were estimated in order to quantify the critical points of the model. Subsequently, a principal component analysis was performed. The results show that the use of growth models substantially increases the inferences that can be made about crop growth, and the multivariate analysis summarizes this information, simplifying its interpretation. Approaches such as those carried out in this study are still rarely used, but, compared to simpler models, they increase the amount of inferences that can be made and provide greater elucidation of the results.

ABSTRACT. A study was conducted during four growing seasons to investigate the rooting capacity and survival percentage of cassava seedlings from stem cuttings selected based on their number of leaves. The experimental design was a randomized block design with five replications in a factorial scheme (4 × 2 × 2), totalling 16 treatments. Treatments consisted of combinations of growing season (September 22, October 7 and 19, and November 25), stem cuttings smaller (15 to 19.99 mm) and larger (20 to 25 mm) than 20 mm in diameter, and number of leaves on the stem cuttings (3 to 5 and 6 to 8 leaves). The experiment was carried out during the four growing seasons in a Van der Hoeven greenhouse. The greenhouse, as well as the benches on which the treatments were placed, had a north-south orientation. The greenhouse has an automatic mist irrigation system, and the mean temperature was 25 °C. The plant height at planting, number of leaves at planting, and number of leaves at 7 days after planting were measured. The final number of leaves, final plant height, shoot dry matter, root dry matter, and total dry matter were measured after acclimatization. Stem cuttings between 20 and 25 mm in diameter should be used to produce cassava seedlings with the rapid multiplication method. Cuttings with 6 to 8 visible leaves should be collected, and the cuttings should be planted at the end of September.

Resumo: O objetivo deste trabalho foi avaliar a época ideal de colheita de dez genótipos de cana-de-açúcar (Saccharum officinarum) para o processamento e a qualidade de açúcar mascavo. O experimento foi realizado em delineamento de blocos ao acaso, em arranjo fatorial 3x10, em parcelas subdivididas, com três épocas de colheita e dez genótipos de cana-de-açúcar, no estado de São Paulo, Brasil. Os parâmetros qualitativos de açúcar mascavo foram avaliados pelo teste de Scott-Knott, a 5% de probabilidade. A época de colheita em setembro, conhecida como meio de safra, é a mais adequada para a produção de açúcar mascavo, em razão dos maiores valores de ºBrix da cana, ºBrix do caldo, valor pol do mascavo e açúcares totais redutores nesse período. A colheita dos genótipos de cana-de-açúcar em junho-julho é a mais favorável para a produção de açúcar mascavo quanto às características de coloração a*, b*, L* e croma; no entanto, é também o período de produção de açúcar mascavo com menores teores de açúcar. A terceira época de colheita (novembro) é a menos recomenda para a produção de açúcar mascavo, em razão dos maiores valores de fibra e pureza. O genótipo mais adequado para a produção e a qualidade de açúcar mascavo é o 'IACSP04-704'.

Abstract: The objective of this work was to evaluate the optimal harvest time of ten genotypes of sugarcane (Saccharum officinarum) for the processing and quality of brown sugar. The experiment was carried out in a randomized complete block design in a 3x10 factorial arrangement in split plots, with three harvest times and ten sugarcane genotypes, in the state of São Paulo, Brazil. The qualitative parameters of brown sugar were evaluated by Scott-Knott’s test, at 5% probability. The harvest season in September, known as the middle of the harvest, is the most suitable for the production of brown sugar due to the higher of ºBrix values of cane, ºBrix of the broth, pol of brown sugar, and total reducing sugars in this period. The harvesting of the sugarcane genotypes in June-July is the most favorable for the production of brown sugar for the color characteristics a*, b*, L*, and chroma; however, it is also the period of production of brown sugar with a lower sugar content. The third harvest season (November) is the least recommended for brown sugar production due to the higher fiber and purity values. The most suitable genotype for brown sugar production and quality is 'IACSP04-704'.

Abstract Kriging is a method that estimates values in places not sampled from different interpolators, therefore, widely used to predict the spatial distribution of organisms. However, the different interpolators may vary in performance depending on the organism under study or the area evaluated. The aimed study to compare the ordinary kriging and inverse of distance weighted interpolation methods, applied to the spatial distribution of population density of Tibraca limbativentris in irrigated rice. This study was carried out in Santa Maria, RS, Brazil, in two fields with areas of 1.3 ha and 6.2 ha, respectively. Seven evaluations of the population density of T. limbativentris were carried out, corresponding to the period from sowing to maturation. In these areas the adults of T. limbativentris were quantified and the sum used for the statistical and geostatistical analysis. The sample population of T. limbativentris was submitted to different semivariograms, which were selected through cross-validation. The sample population of T. limbativentris was submitted to different semivariograms, selected by means of cross-validation. Once selected, semivariograms were used in both tested interpolation methods. From the results it was concluded that the ordinary kriging interpolation method performed better in all evaluations performed in both areas. Therefore, we recommend its use for estimating the population density and spatial distribution of T. limbativentris in the irrigated rice throughout the crop phenology. Using appropriate interpolation methods, localized management can be used, reducing costs for controlling this pest and increasing the sustainability of the environment.

ABSTRACT The objective of this paper was to evaluate the quality of water drained after the use of the knife-roller (an implement used to incorporate rice residues after harvest), the partial global warming potential (pGWP) and straw decomposition as a result of postharvest field management of irrigated rice. The experiments were conducted during the 2018 and 2019 offseason and the treatments consisted of several water drainage periods (0, 3, 6, 9 and 12 days) after a field pass with a knife-roller. In addition, a nonflooded harvest treatment without straw management was included. Analysis of drainage water three days after a pass with the kniferoller showed a reduction in total soluble solids by 94% compared to zero days. Nitrogen and soluble phosphorus were not influenced by the treatments. However, potassium levels increased as the drainage period increased, which is related to the period between harvest and drainage. As the electrical conductivity is influenced by the concentration of ions, it showed the same response curve as the potassium levels and, for pH, there were small oscillations influenced by the temperature. The total CH4 emission and the pGWP were higher when the water depth remained for a longer period. However, the N2O emissions were higher in the absence of soil submersion. Water should be drained three days after a pass with the knife-roller in order to reduce potassium loss and suspended solids as well as pGWP. The use of the knife-roller accelerated the process of straw decomposition in relation to the unmanaged straw treatment.