Maize and soybeans production in integrated system under no-tillage with different pasture combinations and animal categories

The adoption of no-till system (NTS) combined with crop-livestock integration (CLI) has been a strategy promoted in Brazil, aiming to maximize areas yield and increase agribusiness profitability. This study aimed to evaluate grains yield and phytotechnical attributes from maize and soybean culture by CLI system under NTS after winter annual pure and diversified pastures with the absence or presence of grazing animals. The experiment was installed in Castro (Parana State, Brazil) on in a dystrophic Humic Rhodic Hapludox with a clay texture, using experimental design of randomized complete blocks in 4 x 2 factorial scheme with three replications. Treatments included four pasture combinations (diversified or pure) and animal categories (light and heavy) subjected or not to grazing animals during the winter. During 2008/09 and 2009/10 summers, the area was cultivated with soybeans and maize, respectively, with yield assessment of grains and phytotechnical attributes. Treatments did not alter the yield and weight of a thousand seeds (WTS) of soybeans. In maize culture, the grazing animal during the winter increased the plant population and grains yield, but gave slight decrease in WTS. Pasture combinations (diversified or pure) and animal categories (light and heavy) did not interfere in soybean culture, but benefited the maize crop.

Ontology for Data Representation in the Production of Cotton Fiber in Brazil

An important feature in computer systems developed for the agricultural sector is to satisfy the heterogeneity of data generated in different processes. Most problems related with this heterogeneity arise from the lack of standard for different computing solutions proposed. An efficient solution for that is to create a single standard for data exchange. The study on the actual process involved in cotton production was based on a research developed by the Brazilian Agricultural Research Corporation (EMBRAPA) that reports all phases as a result of the compilation of several theoretical and practical researches related to cotton crop. The proposition of a standard starts with the identification of the most important classes of data involved in the process, and includes an ontology that is the systematization of concepts related to the production of cotton fiber and results in a set of classes, relations, functions and instances. The results are used as a reference for the development of computational tools, transforming implicit knowledge into applications that support the knowledge described. This research is based on data from the Midwest of Brazil. The choice of the cotton process as a study case comes from the fact that Brazil is one of the major players and there are several improvements required for system integration in this segment.

DISTRIBUTION OF NITROGEN AMMONIUM SULFATE (N-15) SOIL-PLANT SYSTEM IN A NO-TILLAGE CROP SUCCESSION

DISTRIBUTION OF NITROGEN AMMONIUM SULFATE (N-15) SOIL-PLANT SYSTEM IN A NO-TILLAGE CROP SUCCESSION The N use by maize (Zea mays, L.) is affected by N-fertilizer levels. This study was conducted using a sandy-clay texture soil (Hapludox) to evaluate the efficiency of N use by maize in a crop succession, based on N-15-labeled ammonium sulfate (5.5 atom %) at different rates, and to assess the residual fertilizer effect in two no-tillage succession crops (signalgrass and corn). Two maize crops were evaluated, the first in the growing season 2006, the second in 2007, and brachiaria in the second growing season. The treatments consisted of N rates of 60, 120 and 180 kg ha(-1) in the form of labeled N-15 ammonium sulfate. This fertilizer was applied in previously defined subplots, only to the first maize crop (growing season 2006). The variables total accumulated N; fertilizer-derived N in corn plants and pasture; fertilizer-derived N in the soil; and recovery of fertilizer-N by plants and soil were evaluated. The highest uptake of fertilizer N by corn was observed after application of 120 kg ha(-1) N and the residual effect of N fertilizer on subsequent corn and Brachiaria was highest after application of 180 kg ha(-1) N. After the crop succession, soil N recovery was 32, 23 and 27 % for the respective applications of 60, 120 and 180 kg ha(-1) N.

An ice machine adapted into an autonomous photovoltaic system without batteries using a variable-speed drive

The adaptation of a commercially available ice machine for autonomous photovoltaic operation without batteries is presented. In this adaptation a 1040 W(p) photovoltaic array directly feeds a variable-speed drive and a 24 V(dc) source. The drive runs an induction motor coupled by belt-and-pulley to an open reciprocating compressor, while the dc source supplies a solenoid valve and the control electronics. Motor speed and refrigerant evaporation pressure are set aiming at continuously matching system power demand to photovoltaic power availability. The resulting system is a simple integration of robust, standard, readily available parts. It produces 27 kg of ice in a clear-sky day and has ice production costs around US$0.30/kg. Although a few machine features might be specific to Brazil, its technical and economical guidelines are applicable elsewhere. Copyright (C); 2010 John Wiley & Sons, Ltd.

Integrated sediment quality assessment in Paranagua Estuarine System, Southern Brazil

Sediment quality from Paranagua Estuarine System (PES), a highly important port and ecological zone, was evaluated by assessing three lines of evidence: (1) sediment physical-chemical characteristics; (2) sediment toxicity (elutriates, sediment-water interface, and whole sediment); and (3) benthic community structure. Results revealed a gradient of increasing degradation of sediments (i.e. higher concentrations of trace metals, higher toxicity, and impoverishment of benthic community structure) towards inner PES. Data integration by principal component analysis (PCA) showed positive correlation between some contaminants (mainly As, Cr, Ni, and Pb) and toxicity in samples collected from stations located in upper estuary and one station placed away from contamination sources. Benthic community structure seems to be affected by both pollution and natural fine characteristics of the sediments, which reinforces the importance of a weight-of-evidence approach to evaluate sediments of PES. (C) 2008 Elsevier Inc. All rights reserved.

Assessing the gain of biological data integration in gene networks inference

Background: A current challenge in gene annotation is to define the gene function in the context of the network of relationships instead of using single genes. The inference of gene networks (GNs) has emerged as an approach to better understand the biology of the system and to study how several components of this network interact with each other and keep their functions stable. However, in general there is no sufficient data to accurately recover the GNs from their expression levels leading to the curse of dimensionality, in which the number of variables is higher than samples. One way to mitigate this problem is to integrate biological data instead of using only the expression profiles in the inference process. Nowadays, the use of several biological information in inference methods had a significant increase in order to better recover the connections between genes and reduce the false positives. What makes this strategy so interesting is the possibility of confirming the known connections through the included biological data, and the possibility of discovering new relationships between genes when observed the expression data. Although several works in data integration have increased the performance of the network inference methods, the real contribution of adding each type of biological information in the obtained improvement is not clear. Methods: We propose a methodology to include biological information into an inference algorithm in order to assess its prediction gain by using biological information and expression profile together. We also evaluated and compared the gain of adding four types of biological information: (a) protein-protein interaction, (b) Rosetta stone fusion proteins, (c) KEGG and (d) KEGG+GO. Results and conclusions: This work presents a first comparison of the gain in the use of prior biological information in the inference of GNs by considering the eukaryote (P. falciparum) organism. Our results indicates that information based on direct interaction can produce a higher improvement in the gain than data about a less specific relationship as GO or KEGG. Also, as expected, the results show that the use of biological information is a very important approach for the improvement of the inference. We also compared the gain in the inference of the global network and only the hubs. The results indicates that the use of biological information can improve the identification of the most connected proteins.

Integration of spatial and temporal models to predict extreme water table depths

The objective of this work was to evaluate extreme water table depths in a watershed, using methods for geographical spatial data analysis. Groundwater spatio-temporal dynamics was evaluated in an outcrop of the Guarani Aquifer System. Water table depths were estimated from monitoring of water levels in 23 piezometers and time series modeling available from April 2004 to April 2011. For generation of spatial scenarios, geostatistical techniques were used, which incorporated into the prediction ancillary information related to the geomorphological patterns of the watershed, using a digital elevation model. This procedure improved estimates, due to the high correlation between water levels and elevation, and aggregated physical sense to predictions. The scenarios showed differences regarding the extreme levels - too deep or too shallow ones - and can subsidize water planning, efficient water use, and sustainable water management in the watershed.

Dissecting Phaseolus vulgaris Innate Immune System against Colletotrichum lindemuthianum Infection

Background: The genus Colletotrichum is one of the most economically important plant pathogens, causing anthracnose on a wide range of crops including common beans (Phaseolus vulgaris L.). Crop yield can be dramatically decreased depending on the plant cultivar used and the environmental conditions. This study aimed to identify potential genetic components of the bean immune system to provide environmentally friendly control measures against this fungus. Methodology and Principal Findings: As the common bean is not amenable to reverse genetics to explore functionality and its genome is not fully curated, we used putative Arabidopsis orthologs of bean expressed sequence tag (EST) to perform bioinformatic analysis and experimental validation of gene expression to identify common bean genes regulated during the incompatible interaction with C. lindemuthianum. Similar to model pathosystems, Gene Ontology (GO) analysis indicated that hormone biosynthesis and signaling in common beans seem to be modulated by fungus infection. For instance, cytokinin and ethylene responses were up-regulated and jasmonic acid, gibberellin, and abscisic acid responses were down-regulated, indicating that these hormones may play a central role in this pathosystem. Importantly, we have identified putative bean gene orthologs of Arabidopsis genes involved in the plant immune system. Based on experimental validation of gene expression, we propose that hypersensitive reaction as part of effector-triggered immunity may operate, at least in part, by down-regulating genes, such as FLS2-like and MKK5-like, putative orthologs of the Arabidopsis genes involved in pathogen perception and downstream signaling. Conclusions/Significance: We have identified specific bean genes and uncovered metabolic processes and pathways that may be involved in the immune response against pathogens. Our transcriptome database is a rich resource for mining novel defense-related genes, which enabled us to develop a model of the molecular components of the bean innate immune system regulated upon pathogen attack.

Active crop sensor to detect variability of nitrogen supply and biomass on sugarcane fields

Nitrogen management has been intensively studied on several crops and recently associated with variable rate on-the-go application based on crop sensors. Such studies are scarce for sugarcane and as a biofuel crop the energy input matters, seeking high positive energy balance production and low carbon emission on the whole production system. This article presents the procedure and shows the first results obtained using a nitrogen and biomass sensor (N-Sensor (TM) ALS, Yara International ASA) to indicate the nitrogen application demands of commercial sugarcane fields. Eight commercial fields from one sugar mill in the state of Sao Paulo, Brazil, varying from 15 to 25 ha in size, were monitored. Conditions varied from sandy to heavy soils and the previous harvesting occurred in May and October 2009, including first, second, and third ratoon stages. Each field was scanned with the sensor three times during the season (at 0.2, 0.4, and 0.6 m stem height), followed by tissue sampling for biomass and nitrogen uptake at ten spots inside the area, guided by the different values shown by the sensor. The results showed a high correlation between sensor values and sugarcane biomass and nitrogen uptake, thereby supporting the potential use of this technology to develop algorithms to manage variable rate application of nitrogen for sugarcane.

Stochastic simulation of time-series models combined with geostatistics to predict water-table scenarios in a Guarani Aquifer System outcrop area, Brazil

Stochastic methods based on time-series modeling combined with geostatistics can be useful tools to describe the variability of water-table levels in time and space and to account for uncertainty. Monitoring water-level networks can give information about the dynamic of the aquifer domain in both dimensions. Time-series modeling is an elegant way to treat monitoring data without the complexity of physical mechanistic models. Time-series model predictions can be interpolated spatially, with the spatial differences in water-table dynamics determined by the spatial variation in the system properties and the temporal variation driven by the dynamics of the inputs into the system. An integration of stochastic methods is presented, based on time-series modeling and geostatistics as a framework to predict water levels for decision making in groundwater management and land-use planning. The methodology is applied in a case study in a Guarani Aquifer System (GAS) outcrop area located in the southeastern part of Brazil. Communication of results in a clear and understandable form, via simulated scenarios, is discussed as an alternative, when translating scientific knowledge into applications of stochastic hydrogeology in large aquifers with limited monitoring network coverage like the GAS.

Reference model for implementing an MRP system in a highly diverse component and seasonal lean production environment

Companies are currently choosing to integrate logics and systems to achieve better solutions. These combinations also include companies striving to join the logic of material requirement planning (MRP) system with the systems of lean production. The purpose of this article was to design an MRP as part of the implementation of an enterprise resource planning (ERP) in a company that produces agricultural implements, which has used the lean production system since 1998. This proposal is based on the innovation theory, theory networks, lean production systems, ERP systems and the hybrid production systems, which use both components and MRP systems, as concepts of lean production systems. The analytical approach of innovation networks enables verification of the links and relationships among the companies and departments of the same corporation. The analysis begins with the MRP implementation project carried out in a Brazilian metallurgical company and follows through the operationalisation of the MRP project, until its production stabilisation. The main point is that the MRP system should help the company's operations with regard to its effective agility to respond in time to demand fluctuations, facilitating the creation process and controlling the branch offices in other countries that use components produced in the matrix, hence ensuring more accurate estimates of stockpiles. Consequently, it presents the enterprise knowledge development organisational modelling methodology in order to represent further models (goals, actors and resources, business rules, business process and concepts) that should be included in this MRP implementation process for the new configuration of the production system.

Computational framework to support integration of biomolecular and clinical data within a translational approach

Background The use of the knowledge produced by sciences to promote human health is the main goal of translational medicine. To make it feasible we need computational methods to handle the large amount of information that arises from bench to bedside and to deal with its heterogeneity. A computational challenge that must be faced is to promote the integration of clinical, socio-demographic and biological data. In this effort, ontologies play an essential role as a powerful artifact for knowledge representation. Chado is a modular ontology-oriented database model that gained popularity due to its robustness and flexibility as a generic platform to store biological data; however it lacks supporting representation of clinical and socio-demographic information. Results We have implemented an extension of Chado – the Clinical Module - to allow the representation of this kind of information. Our approach consists of a framework for data integration through the use of a common reference ontology. The design of this framework has four levels: data level, to store the data; semantic level, to integrate and standardize the data by the use of ontologies; application level, to manage clinical databases, ontologies and data integration process; and web interface level, to allow interaction between the user and the system. The clinical module was built based on the Entity-Attribute-Value (EAV) model. We also proposed a methodology to migrate data from legacy clinical databases to the integrative framework. A Chado instance was initialized using a relational database management system. The Clinical Module was implemented and the framework was loaded using data from a factual clinical research database. Clinical and demographic data as well as biomaterial data were obtained from patients with tumors of head and neck. We implemented the IPTrans tool that is a complete environment for data migration, which comprises: the construction of a model to describe the legacy clinical data, based on an ontology; the Extraction, Transformation and Load (ETL) process to extract the data from the source clinical database and load it in the Clinical Module of Chado; the development of a web tool and a Bridge Layer to adapt the web tool to Chado, as well as other applications. Conclusions Open-source computational solutions currently available for translational science does not have a model to represent biomolecular information and also are not integrated with the existing bioinformatics tools. On the other hand, existing genomic data models do not represent clinical patient data. A framework was developed to support translational research by integrating biomolecular information coming from different “omics” technologies with patient’s clinical and socio-demographic data. This framework should present some features: flexibility, compression and robustness. The experiments accomplished from a use case demonstrated that the proposed system meets requirements of flexibility and robustness, leading to the desired integration. The Clinical Module can be accessed in http://dcm.ffclrp.usp.br/caib/pg=iptrans webcite.

Nitrogen fertilizer (15N) leaching in a central pivot fertigated coffee crop

Nitrogen has a complex dynamics in the soil-plant-atmosphere system. N fertilizers are subject to chemical and microbial transformations in soils that can result in significant losses. Considering the cost of fertilizers, the adoption of good management practices like fertigation could improve the N use efficiency by crops. Water balances (WB) were applied to evaluate fertilizer N leaching using 15N labeled urea in west Bahia, Brazil. Three scenarios (2008/2009) were established: i) rainfall + irrigation the full year, ii) rainfall only; and iii) rainfall + irrigation only in the dry season. The water excess was considered equal to the deep drainage for the very flat area (runoff = 0) with a water table located several meters below soil surface (capillary rise = 0). The control volume for water balance calculations was the 0 - 1 m soil layer, considering that it involves the active root system. The water drained below 1 m was used to estimate fertilizer N leaching losses. WB calculations used the mathematic model of Penman-Monteith for evapotranspiration, considering the crop coefficient equal to unity. The high N application rate associated to the high rainfall plus irrigation was found to be the main cause for leaching, which values were 14.7 and 104.5 kg ha-1 for the rates 400 and 800 kg ha-1 of N, corresponding to 3.7 and 13.1 % of the applied fertilizer, respectively.