Carbon sequestration and nutrient reserves under differen t land use systems

This study evaluated the contribution of agroforestry (AFS) and traditional systems to carbon sequestration and nutrient reserves in plants, litter and soil. The study was carried out in the semiarid region of Brazil in a long-term experiment on an experimental farm of the goat and sheep section of the Brazilian Agricultural Research Corporation (Embrapa). Two agroforestry systems were investigated: agrosilvopastoral (ASP) and forest-pasture areas (SP) as well as traditional agriculture management (TM), two areas left fallow after TM (six fallow years - F6 and nine fallow years - F9) and one area of preserved Caatinga vegetation (CAT). Soil, litter and plants were sampled from all areas and the contents of C, N, P, K, Ca and Mg per compartment determined. The AFS (ASP and SP) had higher nutrient stocks than the traditional and intermediate stocks compared to the preserved Caatinga. In the ASP, a relevant part of the nutrients extracted by crops is returned to the system by constant inputs of litter, weeding of herbaceous vegetation and cutting of the legume crops. After fallow periods of six and nine years, carbon and nutrient stocks in the compartments soil, litter and herbaceous plants were similar to those of the preserved Caatinga (CAT), but still lower than under natural conditions in the woody vegetation.

Automatic and manual spray bar sections control

The use of precision farming tools in pesticide application technology can improve the techniques effectiveness during the spraying. Thus, this study aimed to compare automatic and manual systems to interrupt the syrup flow in the spray bar sections when applied in overlapped areas. The sprayings were carried out in eight places in completely randomized design. It was compared the spray consumption and the sprayed area in relation to the total area. The results indicated that in sprays performed with the automatic system there was an average savings of 17.2% of the sprayed volume. The sprayed area using the bar section's automatic control was an average 6.1% lower than the sprayed area with manual control.

The Application of Enterprise Architecture Approach to Military Concept Development–Case Study

Abstract—Concept development and experimentation (CD&E) plays an important role in driving strategic transformation in the military community. Defence architecture frameworks, such as the NATO architecture framework, are considered excellent means to support CD&E. There is not much empirical evidence, however, to indicate how enterprise architectures (EA) are applied in the military community or particularly in military CD&E. Consequently, this paper describes and discusses empirical application of the EA approach in CD&E. The research method in the paper is a case study. Situational method engineering (SiME) is used as a framework to adapt the EA approach to the case project of the paper. The findings of the paper suggest that the EA is applicable to CD&E work, although all aspects of the original concept could not be expressed in the EA model of the case project. The results also show that the SiME method can support in applying the EA framework to the CD&E in the case project.

Parasitism level by helminths and weight gain of calves kept in organic and conventional grazing

Sustainable production is a principle in which we must meet the needs of the present without compromising the capacity of future generations. Despite the successful development of pesticides against endo and ectoparasites found in domestic ruminants, these parasites are still the major problem of the herbivore production system. The purpose of this study was to know the population of gastrintestinal parasites and their influence on weight gain of calves kept in organic and conventional grazing. Thus, organic and conventional calves were randomly selected in 2008 and 2009. The fecal egg count (FEC) indentified the following genders of helminths: Haemonchus, Trichostrongylus, Oesophagostomum, Cooperia, Strongyloides, Trichuris and oocysts of Eimeria. There was no significant difference (p>0.05) between FEC in organic and conventional animals. Calves younger than 6 months showed significant higher infection (p<0.05) than calves between 7 and 12 months of age. The weight gain observed during the study was of 327g/day and 280g/day for conventional and organic systems animals, respectively. Consequently, the combination of sustainable practices of grazing associated with the selective application of anthelmintics may be a feasible alternative for nematode control in a conventional system and in transition to an organic one.

Weed control in young coffee plantations through post emergence herbicide application onto total area

This study was carried out to investigate the efficiency of several herbicides under field conditions, by post-emergence application onto the entire area, their effect on the control of weeds in young coffee plantations and commercial coffee and bean intercropping system, as well as on both crops. Seedlings of Coffea arabica cv. Red Catuaí with four to six leaf pairs were transplanted to the field and treated according to conventional agronomic practices. A bean and coffee intercropping system was established by sowing three lines of beans in the coffee inter-rows. At the time the herbicides were sprayed, the coffee plants had six to ten leaf pairs; the bean plants, three leaflets; and the weeds were at an early development stage. Fluazifop-p-butyl and clethodim were selective for coffee plants and controlled only Brachiaria plantaginea and Digitaria horizontalis efficiently. Broad-leaved weeds (Amaranthus retroflexus, Bidens pilosa, Coronopus didymus, Emilia sonchifolia, Galinsoga parviflora, Ipomoea grandifolia, Lepidium virginicum, and Raphanus raphanistrum) were controlled with high efficiency by sole applications of fomesafen, flazasulfuron, and oxyfluorfen, except B. pilosa, C. didymus, and R. raphanistrum for oxyfluorfen. Sequential applications in seven-day intervals of fomesafen + fluazifop-p-butyl, or clethodim, and two commercial mixtures of fomesafen + fluazifop-p-butyl simultaneously controlled both types of weed. Cyperus rotundus was only controlled by flazasulfuron. Except for fluazifop-p-butyl and clethodim, all herbicide treatments caused only slight injuries on younger coffee leaves. However, further plant growth was not impaired and coffee plant height and stem diameter were therefore similar in the treatments, as evaluated four months later. Fomesafen, fluazifop-p-butyl, and clethodim, at sole or sequential application, and the commercial mixtures of fomesafen + fluazifop-p-butyl were also highly selective for bean crop; thus at doses recommended for bean crop, these herbicides may be applied to control weeds in coffee and bean intercropping systems by spraying the entire area.

Effects of early compost application on no-till organic soybean

Weed control has always been an important issue in agriculture. With the advent of no-till systems, soil erosion was reduced but herbicide use was increased. Organic no-till systems try to adjust reduced erosion to the no use of herbicides. Nevertheless, this adjustment is limited by the cost of mechanical weed control. This cost may be reduced by improved cultural weed control with cover crops mulches. In this paper we report a study on the application of compost manure on an oats winter cover crop, preceding soybean, instead of on the soybean summer crop. Treatments comprised a control without compost manure, and compost manure doses of 4 and 8 Mg ha-1 applied either on oats in winter or soybean in summer, organized in a randomized block design, with five replications. In summer, plots were split into weed-controlled or not controlled subplots. The timing of application and the manure doses did not affect the oats biomass or the soybean performance. However, in summer, without water stress, the application of manure at 8 Mg ha-1 directly on soybean has reduced weed biomass in this crop.

Effects of irrigated rice sowing season and imazapyr + imazapic time of application on rice grain yield and red rice management

Irrigated rice sowing season and red rice competition are among the main factors affecting grain yield. The objective of this work was to evaluate the sowing date of irrigated rice and moments of application of the herbicide imazapyr + imazapic to control red rice management and irrigated rice grain yield. Eight experiments were performed at the following dates (09/30, 10/19, 11/08 and 12/01) for the 2010/2011 harvest season and (09/27, 10/17, 11/08 and 12/05) for the 2011/2012 harvest season. The treatments were: application of the herbicide imazapyr + imazapic at doses of 105+35 g ha-1 in pre-emergence (PRE); 52.5+17.5 g ha‑1 in pre-emergence and 52.5+17.5 g ha-1 in post-emergence (PRE + POST); and 105+35 g ha-1 in post- emergence (POST), and a control without application and no weeding. The cultivar Puitá Inta CL was used and a randomized block design with four replicates. A joint analysis of the experiments was carried out. There was less emergence of red rice and higher grain yield of the irrigated rice at the early periods (09/30/10 and 09/27/11), with 10,578 and 8,653 kg ha-1, respectively. At the end of the season (12/01/10 and 12/05/11), there was greater reduction of the red rice seed bank. Sowing at the beginning of the recommended period provided more irrigated rice grain yield. The application of imazapyr + imazapic at a dose of 52.5+17.5 g ha-1 in PRE + 52.5+17.5 g ha-1 POST, and 105+35 g ha-1 only in PRE and POST was effective in the control of red rice.

Institutional Repository ecosystem in Japan, IRDB and JAIRO Cloud

Poster at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

Weed Phytosociological and Floristic Survey in Agricultural Areas of Southwestern Goiás Region

The use of the Roundup Ready(r) technology and the cultivation of a second crop influence the floristic composition of weed communities in Brazilian Central-West region cropping systems. This study has aimed to diagnose the dominant weed species in southwestern Goiás in areas of genetically-modified and conventional soybeans, using phytosociological and floristic surveys. Weed sampling was obtained by collecting all the plants present within a 0.5 m hollow frame, randomly thrown 20 times in each of thirty-five agricultural areas in the 2012/2013 harvest. Field survey was carried out in three periods: before desiccation for soybean sowing, before postemergence herbicide in soybean first application and before postemergence herbicide application in late harvest. A total of 525 m2 was inventoried and 3,219 weeds were collected, which included 79 species, 58 genera and 28 families. Families Poaceae, Asteraceae, Euphorbiaceae, Fabaceae, Amaranthaceae, were the most representative in the survey. Species Cenchrus echinatus, Glycine max, Chamaesyce hirta, Commelina benghalensis, and Alternanthera tenella stood out in importance. The RR+millet soybean treatment had the highest number of species (44), while the conventional soybean + sorghum treatment had the lowest number of species (18). The highest number of species was recorded in first sampling period. Treatments conventional soybean + maize and conventional soybean + millet showed higher similarity (70%), while treatments RR soybean + millet and conventional soybean + sorghum showed the least (51%). Species of difficult control were recorded in all cultivation systems analyzed.

Application Volumes and Sizes of Droplets for the Application of Diquat Herbicide in the Control of Eichhornia crassipes

The objective of this study was to evaluate the efficiency of application and the efficacy of control of water hyacinth (Eichhornia crassipes) with the use of the diquat herbicide done with two application volumes associated to three droplets classes. Three experiments were conducted; in the first, the application efficiency was evaluated; in the second, the control efficiency and; in the third, the droplet spectrum. They were conducted in a completely randomized design with five, four and six replicates, respectively. The treatments were arranged in a 2 x 3 factorial design, with two application volumes (100 and 200 L ha-1) and three droplets classes (fine, extremely coarse and ultra-coarse) to the first and second experiment and the third comprised two diquat concentrations in spray solution (2 and 4 g i.a. L-1) and three droplets classes (fine, extremely coarse and ultra-coarse). The application efficiency was determined by the coverage by droplets, spray deposition and active ingredient of the herbicide (diquat). The efficacy was measured by the control and the percentage of plants with regrowth at 50 days after application. The spectrum of droplets produced per each nozzle model used to obtain the droplets classes were analyzed. According to the parameters analyzed, using the droplets classes extremely thick and ultra thick can provide greater certainty in the application of diquat in the aquatic environment associated with the deposition of the active and sufficient coverage to control Eichhornia crassipes with both application volumes

Preparing for CRIS: Challenges and Opportunities for Systems Integration at Finnish Universities

Poster at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

Adaptive Markov chain Monte Carlo and Bayesian filtering for state space models

This thesis is concerned with the state and parameter estimation in state space models. The estimation of states and parameters is an important task when mathematical modeling is applied to many different application areas such as the global positioning systems, target tracking, navigation, brain imaging, spread of infectious diseases, biological processes, telecommunications, audio signal processing, stochastic optimal control, machine learning, and physical systems. In Bayesian settings, the estimation of states or parameters amounts to computation of the posterior probability density function. Except for a very restricted number of models, it is impossible to compute this density function in a closed form. Hence, we need approximation methods. A state estimation problem involves estimating the states (latent variables) that are not directly observed in the output of the system. In this thesis, we use the Kalman filter, extended Kalman filter, Gauss–Hermite filters, and particle filters to estimate the states based on available measurements. Among these filters, particle filters are numerical methods for approximating the filtering distributions of non-linear non-Gaussian state space models via Monte Carlo. The performance of a particle filter heavily depends on the chosen importance distribution. For instance, inappropriate choice of the importance distribution can lead to the failure of convergence of the particle filter algorithm. In this thesis, we analyze the theoretical Lᵖ particle filter convergence with general importance distributions, where p ≥2 is an integer. A parameter estimation problem is considered with inferring the model parameters from measurements. For high-dimensional complex models, estimation of parameters can be done by Markov chain Monte Carlo (MCMC) methods. In its operation, the MCMC method requires the unnormalized posterior distribution of the parameters and a proposal distribution. In this thesis, we show how the posterior density function of the parameters of a state space model can be computed by filtering based methods, where the states are integrated out. This type of computation is then applied to estimate parameters of stochastic differential equations. Furthermore, we compute the partial derivatives of the log-posterior density function and use the hybrid Monte Carlo and scaled conjugate gradient methods to infer the parameters of stochastic differential equations. The computational efficiency of MCMC methods is highly depend on the chosen proposal distribution. A commonly used proposal distribution is Gaussian. In this kind of proposal, the covariance matrix must be well tuned. To tune it, adaptive MCMC methods can be used. In this thesis, we propose a new way of updating the covariance matrix using the variational Bayesian adaptive Kalman filter algorithm.

Decision making and decision support in service systems

This thesis is a literature study that develops a conceptual model of decision making and decision support in service systems. The study is related to the Ä-Logi, Intelligent Service Logic for Welfare Sector Services research project, and the objective of the study is to develop the necessary theoretical framework to enable further research based on the research project results and material. The study first examines the concepts of service and service systems, focusing on understanding the characteristics of service systems and their implications for decision making and decision support to provide the basis for the development of the conceptual model. Based on the identified service system characteristics, an integrated model of service systems is proposed that views service systems through a number of interrelated perspectives that each offer different, but complementary, implications on the nature of decision making and the requirements for decision support in service systems. Based on the model, it is proposed that different types of decision making contexts can be identified in service systems that may be dominated by different types of decision making processes and where different types of decision support may be required, depending on the characteristics of the decision making context and its decision making processes. The proposed conceptual model of decision making and decision support in service systems examines the characteristics of decision making contexts and processes in service systems, and their typical requirements for decision support. First, a characterization of different types of decision making contexts in service systems is proposed based on the Cynefin framework and the identified service system characteristics. Second, the nature of decision making processes in service systems is proposed to be dual, with both rational and naturalistic decision making processes existing in service systems, and having an important and complementary role in decision making in service systems. Finally, a characterization of typical requirements for decision support in service systems is proposed that examines the decision support requirements associated with different types of decision making processes in characteristically different types of decision making contexts. It is proposed that decision support for the decision making processes that are based on rational decision making can be based on organizational decision support models, while decision support for the decision making processes that are based on naturalistic decision making should be based on supporting the decision makers’ situation awareness and facilitating the development of their tacit knowledge of the system and its tasks. Based on the proposed conceptual model a further research process is proposed. The study additionally provides a number of new perspectives on the characteristics of service systems, and the nature of decision making and requirements for decision support in service systems that can potentially provide a basis for further discussion and research, and support the practice alike.

Formal development of resilient distributed systems

Resilience is the property of a system to remain trustworthy despite changes. Changes of a different nature, whether due to failures of system components or varying operational conditions, significantly increase the complexity of system development. Therefore, advanced development technologies are required to build robust and flexible system architectures capable of adapting to such changes. Moreover, powerful quantitative techniques are needed to assess the impact of these changes on various system characteristics. Architectural flexibility is achieved by embedding into the system design the mechanisms for identifying changes and reacting on them. Hence a resilient system should have both advanced monitoring and error detection capabilities to recognise changes as well as sophisticated reconfiguration mechanisms to adapt to them. The aim of such reconfiguration is to ensure that the system stays operational, i.e., remains capable of achieving its goals. Design, verification and assessment of the system reconfiguration mechanisms is a challenging and error prone engineering task. In this thesis, we propose and validate a formal framework for development and assessment of resilient systems. Such a framework provides us with the means to specify and verify complex component interactions, model their cooperative behaviour in achieving system goals, and analyse the chosen reconfiguration strategies. Due to the variety of properties to be analysed, such a framework should have an integrated nature. To ensure the system functional correctness, it should rely on formal modelling and verification, while, to assess the impact of changes on such properties as performance and reliability, it should be combined with quantitative analysis. To ensure scalability of the proposed framework, we choose Event-B as the basis for reasoning about functional correctness. Event-B is a statebased formal approach that promotes the correct-by-construction development paradigm and formal verification by theorem proving. Event-B has a mature industrial-strength tool support { the Rodin platform. Proof-based verification as well as the reliance on abstraction and decomposition adopted in Event-B provides the designers with a powerful support for the development of complex systems. Moreover, the top-down system development by refinement allows the developers to explicitly express and verify critical system-level properties. Besides ensuring functional correctness, to achieve resilience we also need to analyse a number of non-functional characteristics, such as reliability and performance. Therefore, in this thesis we also demonstrate how formal development in Event-B can be combined with quantitative analysis. Namely, we experiment with integration of such techniques as probabilistic model checking in PRISM and discrete-event simulation in SimPy with formal development in Event-B. Such an integration allows us to assess how changes and di erent recon guration strategies a ect the overall system resilience. The approach proposed in this thesis is validated by a number of case studies from such areas as robotics, space, healthcare and cloud domain.

Priming the Governance System for Climate Change Adaptation: The Application of a Social Ecological Inventory (SEI) to Engage Actors in Niagara, Canada

Adaptive systems of governance are increasingly gaining attention in respect to complex and uncertain social-ecological systems. Adaptive co-management is one strategy to make adaptive governance operational and holds promise with respect to community climate change adaptation as it facilitates participation and learning across scales and fosters adaptive capacity and resilience. Developing tools which hasten the realization of such approaches are growing in importance. This paper describes explores the Social Ecological Inventory (SEI) as a tool to 'prime' a regional climate change adaptation network. The SEI tool draws upon the social-ecological systems approach in which social and ecological systems are considered linked. SEIs bridge the gap between conventional stakeholder analysis and biological inventories and take place through a six phase process. A case study describes the results of applying an SEI to prime an adaptive governance network for climate change adaptation in the Niagara Region of Canada. Lessons learned from the case study are discussed and highlight how the SEI catalyzed the adaptive co-management process in the case. Future avenues for SEIs in relation to climate change adaptation emerge from this exploratory work and offer opportunities to inform research and adaptation planning.