Towards Spatial Decision Support System for Animals Traceability

Animal traceability is a very important question for several government and private institutions from many points of view: economical, sanitary, etc. Traditional systems are able to memorize the main bovine movements, or to capture the geolocation of an animal using RFID. Now it should be possible to envisage a new generation of traceability systems in which the different locations are automatically recorded several times per day for each animal. These systems should also be coupled with analysis techniques to help decision-makers to take decisions, validate and/or reformulate their hypothesis. In this chapter the authors present a spatial decision support system dedicated to the animal geolocation acquisitions and analysis of possible sanitary problems. Indeed, in case of sanitary alerts, the system is able to determine the animals which have been in contact with a diseased animal exploiting historical trajectories of animals. It is applied to traceability of beef cattle using the Brazilian production system as a case study. OTAG focuses on improving methods and geotechnologies for recording reliable and accurate data on beef production.

Pesticide Leaching Models in a Brazilian Agricultural Field Scenario

The use of Pesticide Leaching Models (PLM) for risk assessment may be an efficient and attractive way of assessing solutions to some agricultural and environmental problems. Many countries of the European Union and the USA have been using PLM for risk assessment already for a few decades. This chapter has the aim to present a successful application of two PLM (i.e. MACRO and PEARL) in a Brazilian very intensive agricultural area to simulate moisture profiles and the leaching of a water flow tracer (i.e. bromide) and the pesticides cyproconazole and thiamethoxam. Also attempts to summarize the available knowledge about the processes governing pesticide behavior in soil, types and classifications of PLM, the use of PLM for risk assessment at European Union, a theoretical description of PEARL and MACRO models and their testing in a Brazilian agricultural field scenario.

A Linear Optimization Approach for Increasing Sustainability in Vegetable Crop Production

This chapter is concerned with a set of optimization problems associated to crop rotation scheduling in the context of vegetable crop production according to some ecological criteria: no crop of the same botanic family is planted in sequence, green manure and fallow periods must be present in any schedule. A core mathematical model called the crop rotation scheduling model is proposed to represent these ecological criteria together with specific technical constraints associated to the growing of vegetable crops. Three optimization problems based on crop rotation schedules are written in detail in this chapter. For each problem, the authors present a general modeling framework and a solution methodology based on a technique known as column generation, which iteratively builds crop rotation plans for a number of plots. Some extensions are also presented, with the aim of incorporating additional characteristics found in production field conditions. This chapter ends with a brief discussion on a set of computational experiments and some suggestions for future research.

Mathematical-Modelling Simulation Applied to Help in the Decision-Making Process on Environmental Impact Assessment of Agriculture

The present chapter provides a brief explanation on some aspects involved in the development of models and mathematical-modelling simulations, to show their benefits to the decision-making process in the environmental impact assessment of agriculture. Aspects concerning the agroecosystems were also presented toward the sustainability of Brazilian agricultural production systems. Some applications which have been developed in Brazil were pointed out, as well as a specific case study conducted at the Guarani aquifer recharge area located in Ribeirão Preto, São Paulo state, in order to show the influence of input data on the results provided by CMLS94 simulator.

Study of Potential Climate for Sugarcane Production in the State of Rio Grande Do Sul, Brazil, By Means of Geoprocessing

A potential climate study for sugarcane of a sector of Rio Grande do Sul State, Brazil is presented here. GIS technology was applied for evaluation of the risk of frost and for integration of spatial data. The problem was focused in regional scale and in local scale (Municipality of Jaguari). Results showed that cultivation can be programmed in order to obtain physiological maturity before the period of risk of frost, thus avoiding low production. Spatial analysis of the information allows rapid perspective for productivity of sugarcane in a specific territory. The Municipality of Jaguari has large potential for cultivation of sugarcane because of the absence of the risk of frost. Its productivity allows for expansion into suitable neighboring areas. Also, geoprocessing combined with the study of climate and soil appears as a significant tool for interpreting the areas with aptitude for production of sugarcane or for the industry of sugar and alcohol.

Concentration and Dynamics of the Brazilian Agriculture

This chapter examines the measurement of motion in agriculture. Not only in Brazil, but in several Latin-American countries, important changes have been observed in the geographical distribution of the agricultural activity. They may take different forms, such as occupation of new areas or reallocation of particular products to areas that were already under some form of agriculture. Besides, in any year, for a given level of geographical subdivision, the distribution of a product shows spatial concentration; but the places which concentrate a substantial portion of the total production may change from year to year, and different subsets of the total territory occupied by a product may move at different speeds. Three distance measures will be introduced in order to assess the motion of individual products; two of them correspond to mathematical concepts, while the third one gives the terrestrial distance between national centers of gravity of the products.

Descriptive Methods and Compromise Programming for Promoting Agricultural Reuse of Treated Wastewater

The present chapter reports on a practical case of decision making in agricultural TWW reuse. The studied site concerns the Cebala TWW irrigated perimeter in Tunisia, located in North Africa. Crucially though in this perimeter is that TWW is under-exploited. Thus, the proposed research dwells on the future of this perimeter which could oscillate between hope and deadlock. In case of hope, shall we improve the quality of the resource and possibly move to the tertiary treatment? And in case of deadlock, shall we give up the TWW reuse or substitute it by a conventional resource? To make an evaluation of this experience, the authors first gave a general overview of the descriptive study in a dashboard. Contingent valuation method was used to assess qualitative data and gauge the intangible effects. Then, the authors presented a systemic multicriteria method deployed to make decision-making process easier. Such a method or technique, which is grounded on Lp metrics, is called Compromise Programming.

Zoning Based on Climate and Soil for Planting Eucalyptus in Southern Region of Rio Grande do Sul State, Brazil

Zoning based on climate and soil characteristics does not represent a full ecological-economic zoning procedure, as the Brazilian law establishes, but it is a positive step forward toward a sustainable use of natural resources. The Embrapa Temperate Climate Research Center has developed, with the collaboration of several entities from Brazil and Uruguay, a zoning procedure based on climate and soil for planting eucalyptus in southern region of Rio Grande do Sul State covering a total area greater than 3,5 million hectares. Three eucalyptus species were considered: Eucalyptus grandis W. Hill ex Maiden, Eucalyptus dunnii Maiden and Eucalyptus globulus Labill. Data were processed and integrated through statistical procedures and by using a GIS. The potential surface area for forestry surpasses 900,000 hectares, but a homogeneous exploitation of that territory is limited by legal restrictions.

Mining Climate and Remote Sensing Time Series to Improve Monitoring of Sugar Cane Fields

This chapter discusses how to take advantage of computational models to analyze and extract useful information from time series of climate data and remote sensing images. This kind of data has been used for researching on climate changes, as well as to help on improving yield forecasting of agricultural crops and increasing the sustainable usage of the soil. The authors present three techniques based on the Fractal Theory, data streams and time series mining: the FDASE algorithm, to identify correlated attributes; a method that combines intrinsic dimension measurements with statistical analysis, to monitor evolving climate and remote sensing data; and the CLIPSMiner algorithm applied to multiple time series of continuous climate data, to identify relevant and extreme patterns. The experiments with real data show that data mining is a valuable tool to help agricultural entrepreneurs and government on monitoring sugar cane areas, helping to make the production more useful to the country and to the environment.

A Mixed Integer Programming Approach for Sugar Cane Cultivation and Harvest Planning

The planning of agricultural cultivation and harvesting is a complex task. However, this area of study is still relatively young. This chapter focuses on the tactical and operational planning for sugar cane cultivation and harvesting which determines the best moment to harvest the fields, maximizing the total profit given by the sugar content within the cane. It considers resources such as cutting and transport crews, processing capacities in sugar cane mills, the use of maturation products and the application of vinasse on harvested fields. The mixed integer programming model extends the classical Packing formulation, adding a network flow structure to represent the harvest scheduling. All experiments were performed with real-world instances provided by a Brazilian sugar cane producer. The suggested solutions are discussed in terms of quality and use in practice.