ABSTRACT Calcium and boron are important nutrients in pollen grain formation and seed production. As they are little mobile in plants, it is common to be supplied via foliar application. The objective of this research was to evaluate the production and quality of sweet pepper seeds with calcium and boron application directed to flowers and fruits. The experimental design was in randomized blocks, with seven replications. Four treatments were evaluated: isolated calcium (0.2%) application, isolated boron (0.1%) application, combined application of calcium (0.2%) and boron (0.1%), and the control without calcium and without boron. The characteristics evaluated were number of pollen grains, number of seeds per fruit; 1000 seed weight; physiological quality of seeds (germination, first germination count, and germination speed index) and protein (albumin, globulin, prolamine and glutelin) contents in seeds. Both the application of calcium and boron did not affect the physiological quality of the seeds. Boron application reduced seed production and the 1000 seed weight, while calcium application increased the number of pollen grains, seed production and seed albumin content, and, therefore, the application of calcium in the production of sweet pepper seeds is recommended.

RESUMO O cálcio e o boro são nutrientes importantes na formação do grão de pólen e na produção de sementes. Por serem pouco móveis nas plantas, é comum o fornecimento via aplicação foliar. Objetivou-se com este trabalho avaliar a produção e qualidade das sementes de pimentão em função da aplicação de cálcio e boro direcionado às flores e frutos. O delineamento experimental foi em blocos casualizados, com sete repetições. Foram avaliados quatro tratamentos: aplicação isolada de cálcio (0,2%), aplicação isolada de boro (0,1%), aplicação conjunta de cálcio (0,2%) e boro (0,1%) e o controle sem cálcio nem boro. Foram avaliadas as características número de grãos de pólen, número de sementes por fruto; massa de 1000 sementes; qualidade fisiológica das sementes (germinação, primeira contagem de germinação e índice de velocidade de germinação) e teores de proteínas (albumina, globulina, prolamina e glutelina) nas sementes. Tanto a aplicação de cálcio como de boro não afetaram a qualidade fisiológica das sementes. A aplicação de boro reduziu a produção de sementes e a massa de mil sementes, enquanto a de cálcio aumentou a produção de grãos de pólen e de sementes e o teor de albumina nas sementes e, portanto, recomenda-se a aplicação de cálcio na produção de sementes de pimentão.

ABSTRACT The increase of water usage for food production in recent years has triggered researches on ways to optimize the use of water and to reuse saline water. The present study analyzes the effects of reused saline water in the irrigation of radish culture and the construction of a fuzzy logical mathematic model so that producers may evaluate their production. The experiment, measuring the development of radish bulb at five saline water levels, was developed in a greenhouse in the Botucatu, Campus of the São Paulo State University (UNESP), Botucatu/SP, Brazil. Results showed that salinity caused reduction in fresh and dry matter of the bulb and affected ratings throughout the culture cycle. From the developed fuzzy model, it was possible to verify that the fuzzy modeling helps in the analysis of the experimental data and makes it possible to perform simulations capable of inferring points that were not experimentally determined.

ABSTRACT The low quality of the water currently used for irrigation purposes harms the quality of the products and can lead to a reduction in production. Thus, the objective of this work was to verify the effect of saline water in irrigation water, on biometric variables of pumpkin crop using a system based on fuzzy rules. The agronomic experimental part of this work was carried out in a greenhouse. The experimental design was in randomized blocks, with 5 doses of salinity (0, 1.25, 2.5, 3.75, and 5 dS m-1) and with 5 repetitions. The salinity doses and evaluations carried out throughout the cycle (days after transplanting) were defined as input variables in the mathematical model. For the output variables, the collected biometric responses were defined: number of leaves, number of flowers, leaf fresh mass, leaf dry mass, stem fresh mass, stem length, root fresh mass, and root length. After evaluation, the mathematical model was developed and its validation was carried out using statistical methods and Receiver Operating Characteristic Curves (ROC). It was observed that salinity affects the bush pumpkin crop with a reduction in the evaluated parameters. The mathematical model proved to be efficient for this evaluation.

ABSTRACT Despite the advantages in production, mechanization may expose workers to high noise levels in the work environment, which is considered one of the main causes of work-related hearing loss. In this sense, this study aimed to analyze the spatial variability of noise generated by a self-propelled coffee harvester in an open area to define safe zones for operators and workers involved in coffee harvesting activities. The noise source used was an Electron Auto TDI self-propelled coffee harvester (model MWM D229-4), with a cabin manufactured in 2012 and a 67-hp 4-cylinder engine, working at 1200-rpm rotation. The noise level was measured by a digital decibel meter at points distributed within a regular 2.5 x 2.5 m sampling mesh (32.5 x 35.0 m area) surrounding the harvester in operation, which was configured according to the regulatory standard. Noise level spatial dependence was analyzed through geostatistics, characterizing structure and magnitude, and mapping spatial variability. Results showed that noise levels were above the limit established by relevant legislation (i.e., 85 dB), both for operators and employees at a distance of about 5.5 m from the generating source.

ABSTRACT In order to estimate the response of biometric variables in different irrigation depths in radish crop, as well as their relations in the development of the crop, a fuzzy mathematical analysis was carried out from irrigation with depths of different percentages of the crop evapotranspiration (ETc), using Gaussian pertinence functions for the input variable and triangular for the biometric output variables. Validations were performed using neural network models, smoothing splines and polynomial regression. The relation among the biometric variables was measured applying the Pearson correlation coefficient. The results showed that the fuzzy modeling presented superiority in the crop development estimate over the quadratic polynomial regression model, neural network and smoothing splines, because it achieved an average reduction of errors among the biometric variables, of 7.8% 94.6% and 9.2% for the RMSE in the respective models, as well as a better adjustment of the data with average R2 of the variables. The modeling with neural network showed inadequate agronomic behavior in data representation. Regarding biometric variables, the length and diameter of the tuberous root are inversely correlated, and the fresh phytomass of the tuberous root is correlated only with the fresh phytomass of the root.

ABSTRACT The productivity of a crop is related to the water demand inserted in its development. The measurement of water and its optimization directly influences the final costs of crop production for agricultural producers. In this sense, the objective of this study is evaluating the fuzzy modeling in estimating the productivity of the radish crop (fresh phytomass of the tuberous root) affected by different irrigation depths (25%, 50%, 75%, 100%, and 125%), based on evapotranspiration of the crop (ETc). To measure the results, two fuzzy systems (with triangular and Gaussian membership functions respectively) and a polynomial regression model were developed to perform model validation comparisons. The fuzzy modeling showed a better fit of the data compared to the polynomial regression model, with reduced errors (RMSE with values 6.3 and 6.9 in the fuzzy models versus 8.8 in the regression model) and higher correlation coefficient (0.54 and 0.5 fuzzy versus 0.1 regression). The triangular fuzzy model estimated the best crop yield (31.9 g of fresh phytomass) when using a 100% ETc depth. Also, the curve generated by the fuzzy model accurately represents all the productivity averages in each depth, in addition to this model presenting the smallest errors (compared to the triangular model and the regression model) and the highest R2. However, the Gaussian fuzzy model proved to be more efficient in representing the agronomic reality, as it does not have peaks and valleys, and it is a smooth model in both growth and degrowth.

ABSTRACT The present work aimed to develop mathematical fuzzy models to evaluate the effects of different doses of sewage sludge and irrigation with wastewater and potable water. Such models were elaborated from an experiment carried out at the Faculty of Agronomic Sciences, in the Department of Soil and Environmental Resources, from the Sao Paulo State University, in Brazil. The experiment was carried out in a randomized block design, in a 6 × 2 factorial scheme, with 6 doses of sewage sludge (0, 25, 50, 75, 100 and 125 of the recommended dose of N), and in the presence and absence of wastewater. In the development of the fuzzy model, the Mamdani method was used for the defuzzification. As input variables, the doses of sewage sludge and the types of water were used. For the output variables, it was sought to evaluate the biometric and developmental components of the culture. It can be inferred that the model developed presented a good fit when compared to the regression model, and that the use of sewage sludge may prove to be a potential future replacement of mineral nitrogen.

ABSTRACT Tomato, the most popular greenery, is characterized by being a demanding crop in water and when in prolonged and severe drought, has limitations in its growth and reduction in productivity. In addition, this vegetable is affected by excess salinity in the water, which causes leaf wilting, apex and leaf edges burn until their death. Such effects generally are studied using statistical analysis, but there are mathematical theories that allow finer adjustments, highlighting among them, the fuzzy logic. The objective of this study was to evaluate the effects on the growth and yield of hybrid tomato from different water tensions in the soil and different salinity doses in the irrigation at 120 days after sowing using fuzzy modeling. It was used data from an experiment that was conducted in the experimental area at the School of Agriculture of São Paulo State University (UNESP) in Botucatu-SP. The input variables of the fuzzy systems were irrigation and salinity, while the output variables elected were the biometric analysis and productivity that showed statistically significant differences. Analyses of the effects of irrigation and salinity were performed by means of three-dimensional graphics and the output variables contour maps. The variables studied here showed higher values, with exception of plant height for treatment with irrigation in field capacity and water salinity zero.

ABSTRACT It was used statistical techniques for the evaluation of agricultural experiments, but there are mathematical theories that allow finer adjustments, highlighting among them, the fuzzy logic. The objective of the study was characterizing a method of fuzzy modeling from an agronomic experiment. For this study it was used data from an experiment conducted at the School of Agriculture of São Paulo State University (UNESP) in Botucatu-SP. The system input variables based in fuzzy rules were soil water tension and doses of water salinity, being defined three fuzzy sets. The output variables was elected from the biometric and productivity analysis that showed statistically significant differences, namely, plant height, stem diameter, leaf area, green biomass, dry weight, number of fruits, average fruit weight and percentage of disabled fruits. For output variables 9 fuzzy sets were defined. From the adopted methodology, the model allowed extract directly from the data set a base of rules without the use of questionnaires to experts for its preparation. In addition, it will analyze intermediate regions at trial levels and weave other conclusions of the tomato growth and productivity, not limiting in this way only those observed with statistical analysis.

ABSTRACT: This study aimed to evaluate the effects of fertilization with composted sewage sludge and irrigation with drinking water (DW) and fertigation with wastewater (WW) in wheat crop using fuzzy rule-based system. The experiment was conducted in the Department of Soil and Environmental Resources, of FCA, UNESP - Botucatu, with factorial 6 × 2, which were applied 6 doses of sewage sludge (0, 50, 100, 150, 200 and 250% of nitrogen recommendation) and two types of effluents (treated water and sewage). In the developing of the system based in fuzzy rules, it was used the Mamdani inference method, where the input variables were sewage sludge doses and water types and the output variables used were the number of tillers, length and number spike per plant; number of spikelet per plant, grain mass per spike and dry mass of the aerial parts. It can be seen that the sewage sludge and the effluent contributed to the higher increase of production, and at 150% sludge dose occurred higher production.

O monitoramento da qualidade fisica e quimica do solo e importante para manter ou modificar o manejo incorreto do solo. Neste sentido, o objetivo deste trabalho foi avaliar as propriedades fisicas para monitorar a qualidade do solo em diferentes tipos de manejo. O delineamento experimental utilizado foi o inteiramente casualizado, com tres tratamentos: Area de vegetacao natural; Area com o cultivo de cultura perene e Area de pastagem degradada; com 5 repeticoes. Foram avaliadas as propriedades fisicas: densidade do solo, taxa de infiltracao de agua, resistencia do solo a penetracao e umidade gravimetrica do solo. nas camadas de solo: 0,00-0,10; 0,10-0,20 e 0,20-0,40m, respectivamente. Os dados foram analisados estatisticamente, utilizando o teste de Tukey a 5% para comparacao das medias. A resistencia a penetracao nao foi um bom indicador da qualidade do solo. Os resultados encontrados mostram que o manejo interfere na qualidade fisica do solo. Conclui-se que o tratamento vegetacao nativa apresenta melhor qualidade fisica do solo.

It is important to monitor the physical quality and soil chemistry to maintain or modify the incorrect soil management. In this sense, the objective of this study was to evaluate the physical properties to monitor soil quality in different types of management. The experimental design was completely randomized, with three treatments: natural vegetation area; area with perennial crop cultivation and degraded pasture area; with 5 replications. The following physical properties were evaluated: soil density, water infiltration rate, soil penetration resistance and gravimetric soil moisture, in soil depths: 0.00 to 0.10; 0,20-0,40m and 0.10-0.20, respectively. We analysed data statistically by using the 5% Tukey test for comparison of means. The penetration resistance was not a good indicator of soil quality. The results show that the management interferes with the soil physical quality. We conclude that the treatment has improved physical native vegetation soil quality.

Monitoreo de la calidad del suelo y la quimica fisica es importante para mantener o modificar la direccion incorrecta del suelo. En este sentido, el objetivo de este estudio fue evaluar las propiedades fisicas para controlar la calidad del suelo en diferentes tipos de gestion. El diseno experimental fue completamente al azar, con tres tratamientos: area de vegetacion natural; Area con cultivos perennes y zona de pastos decapitados; con 5 repeticiones. las propiedades fisicas se evaluaron: la densidad del suelo, la tasa de infiltracion de agua, resistencia a la penetracion del suelo y la humedad del suelo gravimetrico. en capas de suelo: 0.00 0,10; 0,10-0,20 y 0,20-0,40m, respectivamente. Los datos fueron analizados estadisticamente mediante la prueba de Tukey al 5% para la comparacion de medias. La resistencia a la penetracion no fue un buen indicador de la calidad del suelo. Los resultados muestran que la administracion interfiere con la calidad fisica del suelo. Llegamos a la conclusion de que el tratamiento vegetacion nativa ha mejorado la calidad del suelo.

A lógica fuzzy admite infinitos valores lógicos intermediários entre o falso e o verdadeiro. Com esse princípio, foi elaborado neste trabalho um sistema baseado em regras fuzzy, que indicam o índice de massa corporal de animais ruminantes com objetivo de obter o melhor momento para o abate. O sistema fuzzy desenvolvido teve como entradas as variáveis massa e altura, e a saída um novo índice de massa corporal, denominado Índice de Massa Corporal Fuzzy (IMC Fuzzy), que poderá servir como um sistema de detecção do momento de abate de bovinos, comparando-os entre si através das variáveis linguísticas )Muito BaixaM, ,BaixaB, ,MédiaM, ,AltaA e Muito AltaM. Para a demonstração e aplicação da utilização deste sistema fuzzy, foi feita uma análise de 147 vacas da raça Nelore, determinando os valores do IMC Fuzzy para cada animal e indicando a situação de massa corpórea de todo o rebanho. A validação realizada do sistema foi baseado em uma análise estatística, utilizando o coeficiente de correlação de Pearson 0,923, representando alta correlação positiva e indicando que o método proposto está adequado. Desta forma, o presente método possibilita a avaliação do rebanho, comparando cada animal do rebanho com seus pares do grupo, fornecendo desta forma um método quantitativo de tomada de decisão para o pecuarista. Também é possível concluir que o presente trabalho estabeleceu um método computacional baseado na lógica fuzzy capaz de imitar parte do raciocínio humano e interpretar o índice de massa corporal de qualquer tipo de espécie bovina e em qualquer região do País.

The fuzzy logic admits infinite intermediate logical values between false and true. With this principle, it developed in this study a system based on fuzzy rules, which indicates the body mass index of ruminant animals in order to obtain the best time to slaughter. The controller developed has as input the variables weight and height, and as output a new body mass index, called Fuzzy Body Mass Index (Fuzzy BMI), which may serve as a detection system at the time of livestock slaughtering, comparing one another by the linguistic variables "Very Low", "Low", "Average ", "High" and "Very High". For demonstrating the use application of this fuzzy system, an analysis was made with 147 Nellore beeves to determine Fuzzy BMI values for each animal and indicate the location of body mass of any herd. The performance validation of the system was based on a statistical analysis using the Pearson correlation coefficient of 0.923, representing a high positive correlation, indicating that the proposed method is appropriate. Thus, this method allows the evaluation of the herd comparing each animal within the group, thus providing a quantitative method of farmer decision. It was concluded that this study established a computational method based on fuzzy logic that mimics part of human reasoning and interprets the body mass index of any bovine species and in any region of the country.