Angel Ramon Sanchez Delgado

El cultivo de alfalfa utilizando agua de perforación, agua residual urbana y precipitaciones

The objective of this study was to analyse the production of alfalfa biomass, the efficiency of water use and the nutritional value of forage, inside an irrigation structure of an experimental facility that uses treated urban wastewater, artesian well water and rainfall, at the campus of the Universidad National de Rio Cuarto (Cordoba-Argentina). The irrigation treatment had a positive effect on the production of biomass of alfalfa. On an average 24% increase in production was observed when compared to dry-land farming. Regarding the quality of the irrigation water, statistical differences in production were observed, the irrigation with urban wastewater produced 19% more than that of well water. The efficiency of the water use by the crop increased when the irrigation was done using urban wastewater. The alfalfa irrigated with wastewater surpasses the nutritional values of the crop in normal field conditions: 39% more proteins, 14% more digestibility and equal percentage of metabolic energy. It is concluded that the urban wastewater represents possible water source for the alfalfa crop.

Determinación de indicadores de eutrofización en el embalse Río Tercero, Córdoba (Argentina)

Eutrophication is one of the most important environmental problems in lakes and reservoirs. Rio Tercero reservoir (Argentina) is affected by various human activities that impact negatively on the system. When generating a monitoring program of aquatic systems, one of the most important considerations is to define the most significant variables. Multivariate analysis was presented as an alternative tool. The aim of this study was to determine water quality and trophic status in Rio Tercero reservoir, in order to generate an adequate basis for management of water resources. Sampling campaigns were conducted during the years 2003 to 2006. Water quality parameters were measured. We determined the trophic status of the reservoir. Multivariate analysis was performed, generating a correlation matrix and a principal component analysis (PCA). The reservoir experienced a deterioration in water quality, from mesotrophic to eutrophic state. It was shown that there is positive correlation between chlorophyll-a and total phosphorus (r = 0.83), dissolved oxygen (r = 0.51) and temperature (r = 0.43). The PCA explained the 65.6% of the total variability of the data. Multivariate analysis established that the most significant variables were chlorophyll-a, total phosphorus and temperature, demonstrating that algal blooms should occur in spring and summer seasons. The results obtained allow to generate a preliminary program of monitoring and management applied to other aquatic resources.

Utilização de Técnicas de Inteligência Computacional na Predição de Dados Meteorológicos

O presente trabalho apresenta uma abordagem computacional para a predicao de um passo a frente em series de dados meteorologicos pertencentes as regioes de Paty do Alferes e Paracambi, situadas no estado do Rio de Janeiro (RJ). Para tanto, foram utilizados dois modelos de Redes Neurais Artificiais (RNAs): Perceptrons de Multiplas Camadas (MLP) e Funcao de Base Radial (RBF). Para confirmar o desempenho dos modelos foi realizada a predicao de variaveis horarias e mensais, que foram comparadas com resultados obtidos por modelos de Regressao Linear Multipla (RLM), confrontadas com os dados registrados pelas estacoes meteorologicas e analisadas por meio de tecnicas estatisticas, apresentando resultados favoraveis entre 91% a 96% de acerto para todos os casos. Alem disso, as previsoes tambem demonstraram uma forte correlacao linear com os dados registrados, mantendo-se entre 0,61 a 0,94. Como resultado, pode se destacar as RNAs como uma forte ferramenta para predicao dos dados meteorologicos analisados.

Binary programming for the simulation of crop rotation and animal transit in an integrated crop-livestock system

The aim of this study was to develop and implement a linear-programming model (LP) that provides as its result a schedule with the best selection of crops in each plot per period, and with the greatest weight gain for each animal. The linear-programming model was developed from empirical work carried out by Alvarenga and Gontijo Neto (2008) in an area of 24 hectares of Embrapa Milho e Sorgo, in Sete Lagoas, Minas Gerais (MG). For the computational implementation of the model, it was necessary to have data on agricultural suitability and animal weight gain for each period and for each plot. In order to test the developed mathematical model, values were randomly generated for agricultural suitability and for animal weight gain using the MATLAB solver. It was then possible to carry out the computational implementation of the linear-programming model in MATLAB. Two numerical trials were conducted, the first considering four periods, four plots and the transit of two animals, and the second with ten periods, four plots and the transit of three animals. The results show that the linear-programming model is consistent with the empirical work done by Alvarenga and Gontijo Neto (2008). The linear-programming model satisfies all the imposed constraints, maximises the weight gain of each animal, and provides the best selection of crops.

Application of Artificial Neural Networks (ANNs) in the Gap Filling of Meteorological Time Series

This study estimates and fills real flaws in a series of meteorological data belonging to four regions of the state of Rio de Janeiro. For this, an Artificial Neural Network (ANN) of Multilayer Perceptron (MLP) was applied. In order to evaluate its adequacy, the monthly variables of maximum air temperature and relative humidity of the period between 05/31/2002 and 12/31/2014 were estimated and compared with the results obtained by Multiple Linear Regression (MLR) and Regions Average (RA), and still faced with the recorded data. To analyze the estimated values and define the best model for filling, statistical techniques were applied such as correlation coefficient (r), Mean Percentage Error (MPE) and others. The results showed a high relation with the recorded data, presenting indexes between 0.94 to 0.98 of (r) for maximum air temperature and between 2.32% to 1.05% of (MPE), maintaining the precision between 97% A 99%. For the relative air humidity, the index (r) with MLP remained between 0.77 and 0.94 and (MPE) between 2.41% and 1.85%, maintaining estimates between 97% and 98%. These results highlight MLP as being effective in estimating and filling missing values.

EFECTOS DEL USO DE MANTA TÉRMICA SOBRE VARIABLES AMBIENTALES Y RENDIMIENTO DE UN CULTIVO DE LECHUGA

This study aims to evaluate the effect of protecting floating row covers on the behavior of environmental variables and the yield of a crop of lettuce. For it was sowed during two seasons autumn-winter cultivar of butterhead lettuce type (Lactuca sativa var. capitata) in germination trays of 128 cells with subsequent transplantation field performed at 37 (cycle 1) and 49 (cycle 2) days after sowing. The treatments were: 1)- Crop protected with floating row cover (MT); 2)- Control unprotected (T) in an experimental design in split plots with 3 repetitions. The plantation frame used was 0.35 m between rows and 0.25 m between plants and irrigation was made by a drip system. The effect of floating row cover on the transmissivity of photosynthetically active radiation (PAR), temperature and relative humidity, crop yield, heat summation in degree.days-1 from trasplant to harvest (oC.ddt-1) and efficiency of use of radiation (EUR) was evaluated. The results showed an average transmissivity of 63.1% RFA, temperature increase of minimum, average and maximum air 1.1; 2.0 and 3.1 °C respectively, and 4.3% relative humidity. The fresh weight yield (t ha-1) showed statistically significant differences between treatments, being 38.2 (MT); 15.5 (T) for cycle 1 and 33.8 (MT) and 14.7 (T) for cycle 2. The heat summation and EUR was higher in the treatment with floating row cover. Crop protection allows greater earlier maturity with significant performance improvements.

A NONLINEAR FEASIBILITY PROBLEM HEURISTIC

In this work we consider a region S ⊂ given by a finite number of nonlinear smooth convex inequalities and having nonempty interior. We assume a point x 0 is given, which is close in certain norm to the analytic center of S, and that a new nonlinear smooth convex inequality is added to those defining S (perturbed region). It is constructively shown how to obtain a shift of the right-hand side of this inequality such that the point x 0 is still close (in the same norm) to the analytic center of this shifted region. Starting from this point and using the theoretical results shown, we develop a heuristic that allows us to obtain the approximate analytic center of the perturbed region. Then, we present a procedure to solve the problem of nonlinear feasibility. The procedure was implemented and we performed some numerical tests for the quadratic (random) case.

CALIDAD DE PLÁNTULAS DE LECHUGA EN DIFERENTES VOLÚMENES DE CELDAS Y SU INFLUENCIA EN EL RENDIMIENTO - DOI: 10.13083/1414-3984/reveng.v23n6p575-583

In order to evaluate the quality of seedlings obtained in germination trays with different volumes of cells and their influence on the yield for a crop of lettuce for two production cycles autumn- winter, seeded cultivar type buttery (Lactuca sativa var. capitata) in a completely randomized design. The treatments were: 24 cm3/cell (128 cell/tray); 13 cm3/cell (200 cell/tray) y 7 cm3/cell (288 cell/tray). Leaf number, root length, seedling height, fresh and dry weight of shoot and roots were evaluated until the time of transplantation in field made at 37 and 49 days after planting for each production cycle. The results showed significant differences with a greater number of leaves, root length, seedling height, fresh and dry weight of the aerial parts and roots of seedlings obtained in 24 cm3 cells followed by 13 cm3 and finally 7 cm3. The quality of the lettuce seedlings is related to the volume of the cell plug trays, yielding subsequently better yields.

EMPLOYMENT OF RESOURCES ON ADEQUATE MEASURE: A COMPUTATIONAL TOOL FOR AGRICULTURAL OPTIMIZATION

O presente artigo foi apresentado oralmente no VII CNEG, sendo revisado e expandido. Ele descreve um projeto, que esta sendo desenvolvido como tese de doutoramento no programa de pos-graduacao binacional em Ciencia, Tecnologia e Inovacao em Agropecuaria – PPGCTIA / UFRRJ, cujo objetivo e a construcao de um codigo computacional, utilizando a filosofia “user friendly” (amiga do usuario), para otimizar a gestao do agronegocio, minimizando custos e aumentando a producao e ampliando as possibilidades de acesso mais facil mesmo a usuarios com pouca experiencia na utilizacao do computador. O sistema permitira escolher dentre as alternativas de producao disponiveis, a mais eficiente na utilizacao dos recursos produtivos que satisfacam certos objetivos preestabelecidos referentes ao solo, a umidade e meio ambiente em geral. Hoje em dia ja se dispoe de muita informacao tecnico-agricola, mas persiste um grande problema a ser enfrentado: como consolidar estas informacoes de forma clara e simples e transmiti-las, visando sua utilizacao, com a menor intermediacao possivel para o produtor? A necessidade de se reduzir a complexidade da gestao do agronegocio, foi o motor da investigacao sobre tecnicas de otimizacao agricola.

Maximization of the production and agricultural income with water and nitrogen constraints by using the interior points method

Com este trabalho, teve-se o objetivo de pesquisar o desempenho do metodo de pontos interiores (MPI), tipo trajetoria central, na maximizacao de funcoes-objetivo associadas a producao e a receita agricolas, com restricoes de agua e de nitrogenio. Para isso, foi desenvolvido um procedimento matematico que maximiza a producao e a receita liquida separadamente, em funcao da agua e do nitrogenio aplicados a cultura numa matriz bidimensional de restricoes, a partir de funcoes de produtividade para as culturas da aveia e da laranja-pera. O modelo foi caracterizado e, a partir dele, foram gerados resultados numericos para diferentes cenarios agricolas. Foi possivel concluir que a metodologia utilizada (MPI) foi capaz de maximizar as funcoes de produtividade e de receita, resultando na obtencao de valores semelhantes aos publicados na literatura, utilizando-se de programacao separavel.