Management of vomplex systems: Modeling the biological pest control

The aim of this paper is to study the cropping system as complex one, applying methods from theory of dynamic systems and from the control theory to the mathematical modeling of the biological pest control. The complex system can be described by different mathematical models. Based on three models of the pest control, the various scenarios have been simulated in order to obtain the pest control strategy only through natural enemies' introduction. © 2008 World Scientific Publishing Company.

Análise da sustentabilidade na bacia do Rio Corumbataí (SP)

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Comparison of different clean-up procedures for the determination of N-methylcarbamate insecticides in vegetable matrices by high-performance liquid chromatography with UV detection

Several clean-up procedures which included the use of glass chromatography columns (silica gel, alumina, Florisil, silanized Celite-charcoal), Sep-Pak cartridges and standard solutions were compared for the determination of the following N-methylcarbamate (NMC) insecticides: aldicarb, carbaryl, carbofuran, methomyl and propoxur. According to recovery results of the compounds after elution in a glass column, the most efficient systems employed 4.6% deactivated alumina and a silanized Celite-charcoal (4:1) as adsorbents, using dichloromethane-methanol (99:1) and toluene-acetonitrile (75:25) mixtures, respectively, as binary eluents. The recoveries of the compounds studied varied from 84 to 120%. Comparable recoveries (75-100%) for Sep-Pak cartridges in normal phase (NH2, CN) and reversed phase (C-8) were observed. Different temperatures were tested during the concentration step in a rotary evaporator, and we verified a strong influence of this parameter on the stability of some compounds, such as carbofuran and carbaryl. Recovery studies employing the best clean up procedures were performed at the Brazilian agricultural level in potato and carrot samples; Validation methodology of the US Food and Drug Administration was adapted for the N-methylcarbamate analysis. Their recoveries ranged between 79 and 93% with coefficients of variation of 2.3-8%. (C) 1998 Elsevier B.V. B.V.

CPITN: time and cost estimates for periodontal prevention and treatment procedures.

The aim of this study was to estimate the necessary time and cost for periodontal prevention and treatment in a working population from sugar and alcohol refineries in Araraquara, SP, Brazil. A stratified sample of 528 employees aged 18-64 from administrative, industrial and agricultural staffs was examined by one examiner, previously trained, according to the community periodontal index of treatment needs (CPITN). The time required for procedures and the cost was extrapolated to the total worker population. The results showed that the estimated time required for periodontal prevention/treatment was 4527 hours. Of this time, 1783 hours were required for oral hygiene instruction, 2531 for scaling, 151 for surgery and 62 for maintenance. The cost would be US $17,655 for hiring a dentist for 8 hours/day to provide oral hygiene instruction, scaling, surgery and maintenance. However, the cost would be US $9,028 for hiring a dentist for 4 hours/day to provide surgery and maintenance and a dental hygienist for 8 hours/day to provide scaling and oral hygiene instruction. Taking into account epidemiologic, technical and economic aspects, the decision relating to manpower should be this second option.

JSEG-based image segmentation in computer vision for agricultural mobile robot navigation

This project aims to apply image processing techniques in computer vision featuring an omnidirectional vision system to agricultural mobile robots (AMR) used for trajectory navigation problems, as well as localization matters. To carry through this task, computational methods based on the JSEG algorithm were used to provide the classification and the characterization of such problems, together with Artificial Neural Networks (ANN) for pattern recognition. Therefore, it was possible to run simulations and carry out analyses of the performance of JSEG image segmentation technique through Matlab/Octave platforms, along with the application of customized Back-propagation algorithm and statistical methods in a Simulink environment. Having the aforementioned procedures been done, it was practicable to classify and also characterize the HSV space color segments, not to mention allow the recognition of patterns in which reasonably accurate results were obtained.

ANN statistical image recognition method for computer vision in agricultural mobile robot navigation

The main application area in this project, is to deploy image processing and segmentation techniques in computer vision through an omnidirectional vision system to agricultural mobile robots (AMR) used for trajectory navigation problems, as well as localization matters. Thereby, computational methods based on the JSEG algorithm were used to provide the classification and the characterization of such problems, together with Artificial Neural Networks (ANN) for image recognition. Hence, it was possible to run simulations and carry out analyses of the performance of JSEG image segmentation technique through Matlab/Octave computational platforms, along with the application of customized Back-propagation Multilayer Perceptron (MLP) algorithm and statistical methods as structured heuristics methods in a Simulink environment. Having the aforementioned procedures been done, it was practicable to classify and also characterize the HSV space color segments, not to mention allow the recognition of segmented images in which reasonably accurate results were obtained. © 2010 IEEE.

AGRICULTURAL BIRD PROBLEMS IN THE SOUTHEAST

Our chairman has wisely asked that we not spend all of our time here telling each other about our bird problems. In the Southeast, our difficulties with blackbirds are based upon the same bird habits that cause trouble elsewhere: they flock, they roost and they eat, generally taking advantage of the readily available handouts that today's agricul¬tural practices provide. Those of us on the receiving end of these de¬predations of course think that damage in our own particular area must be far the worst, anywhere. Because of the location of our meeting place today, perhaps it is worthwhile to point out that a report prepared by our Bureau's Washington office this year outlined the problem of blackbird damage to corn in the Middle Atlantic States, the Great Lakes Region and in Florida, and then followed with this statement--"An equally serious problem occurs in rice and grain sorghum fields of Arkansas, Mississippi, Texas and Louisiana." The report also men¬tions that the largest winter concentrations of blackbirds are found in the lower Mississippi Valley. Our 1963-64 blackbird-starling survey showed 43 principal roosts totaling approximately 100 million of these birds in Virginia, the Carolinas, Georgia, Alabama, Tennessee and Kentucky. We have our own birds during the summer plus the "tourist" birds from up here and elsewhere during the winter, and all of these birds must eat, so suffice it to say that we, too, have some bird problems in the Southeast. I'm sure you're more interested in what we're doing about them. To keep this in perspective also, please bear in mind that against the magnitude of these problems, our blackbird control research staff at Gainesville consists of 3 biologists, 1 biochemist and one technician. And unfortunately, none of us happens to be a miracle worker. I think, though, we have made great progress toward solving the bird problems in the Southeast for the man-hours that have been expended in this re¬search. My only suggestion to those who are impatient about not having more answers is that they examine the budget that has been set up for this work. Only then could we intelligently discuss what might be expected as a reasonable rate of research progress. When I think about what we have accomplished in a short span of time, with very small expenditure, I can assure you that I am very proud of our small research crew at Gainesville--and I say this quite sincerely. At the Gainesville station, we work under two general research approaches to the bird damage problem. These projects have been assigned to us. The first is research on management of birds, particularly blackbirds and starlings destructive to crops or in feedlots, and, secondly, the development and the adaptation of those chemical compounds found to be toxic to birds but relatively safe to mammals. These approaches both require laboratory and field work that is further subdivided into several specific research projects. Without describing the details of these now, I want to mention some of our recent results. From the results, I'm sure you will gather the general objectives and some of the procedures used.

Automatic segmentation of relevant textures in agricultural images

One important issue emerging strongly in agriculture is related with the automatization of tasks, where the optical sensors play an important role. They provide images that must be conveniently processed. The most relevantimage processing procedures require the identification of green plants, in our experiments they come from barley and corn crops including weeds, so that some types of action can be carried out, including site-specific treatments with chemical products or mechanical manipulations. Also the identification of textures belonging to the soil could be useful to know some variables, such as humidity, smoothness or any others. Finally, from the point of view of the autonomous robot navigation, where the robot is equipped with the imaging system, some times it is convenient to know not only the soil information and the plants growing in the soil but also additional information supplied by global references based on specific areas. This implies that the images to be processed contain textures of three main types to be identified: green plants, soil and sky if any. This paper proposes a new automatic approach for segmenting these main textures and also to refine the identification of sub-textures inside the main ones. Concerning the green identification, we propose a new approach that exploits the performance of existing strategies by combining them. The combination takes into account the relevance of the information provided by each strategy based on the intensity variability. This makes an important contribution. The combination of thresholding approaches, for segmenting the soil and the sky, makes the second contribution; finally the adjusting of the supervised fuzzy clustering approach for identifying sub-textures automatically, makes the third finding. The performance of the method allows to verify its viability for automatic tasks in agriculture based on image processing

Environmental variables modeling based on remote sensing data using time series analysis: forestry and agricultural applications

En la actualidad, el seguimiento de la dinámica de los procesos medio ambientales está considerado como un punto de gran interés en el campo medioambiental. La cobertura espacio temporal de los datos de teledetección proporciona información continua con una alta frecuencia temporal, permitiendo el análisis de la evolución de los ecosistemas desde diferentes escalas espacio-temporales. Aunque el valor de la teledetección ha sido ampliamente probado, en la actualidad solo existe un número reducido de metodologías que permiten su análisis de una forma cuantitativa. En la presente tesis se propone un esquema de trabajo para explotar las series temporales de datos de teledetección, basado en la combinación del análisis estadístico de series de tiempo y la fenometría. El objetivo principal es demostrar el uso de las series temporales de datos de teledetección para analizar la dinámica de variables medio ambientales de una forma cuantitativa. Los objetivos específicos son: (1) evaluar dichas variables medio ambientales y (2) desarrollar modelos empíricos para predecir su comportamiento futuro. Estos objetivos se materializan en cuatro aplicaciones cuyos objetivos específicos son: (1) evaluar y cartografiar estados fenológicos del cultivo del algodón mediante análisis espectral y fenometría, (2) evaluar y modelizar la estacionalidad de incendios forestales en dos regiones bioclimáticas mediante modelos dinámicos, (3) predecir el riesgo de incendios forestales a nivel pixel utilizando modelos dinámicos y (4) evaluar el funcionamiento de la vegetación en base a la autocorrelación temporal y la fenometría. Los resultados de esta tesis muestran la utilidad del ajuste de funciones para modelizar los índices espectrales AS1 y AS2. Los parámetros fenológicos derivados del ajuste de funciones permiten la identificación de distintos estados fenológicos del cultivo del algodón. El análisis espectral ha demostrado, de una forma cuantitativa, la presencia de un ciclo en el índice AS2 y de dos ciclos en el AS1 así como el comportamiento unimodal y bimodal de la estacionalidad de incendios en las regiones mediterránea y templada respectivamente. Modelos autorregresivos han sido utilizados para caracterizar la dinámica de la estacionalidad de incendios y para predecir de una forma muy precisa el riesgo de incendios forestales a nivel pixel. Ha sido demostrada la utilidad de la autocorrelación temporal para definir y caracterizar el funcionamiento de la vegetación a nivel pixel. Finalmente el concepto “Optical Functional Type” ha sido definido, donde se propone que los pixeles deberían ser considerados como unidades temporales y analizados en función de su dinámica temporal. ix SUMMARY A good understanding of land surface processes is considered as a key subject in environmental sciences. The spatial-temporal coverage of remote sensing data provides continuous observations with a high temporal frequency allowing the assessment of ecosystem evolution at different temporal and spatial scales. Although the value of remote sensing time series has been firmly proved, only few time series methods have been developed for analyzing this data in a quantitative and continuous manner. In the present dissertation a working framework to exploit Remote Sensing time series is proposed based on the combination of Time Series Analysis and phenometric approach. The main goal is to demonstrate the use of remote sensing time series to analyze quantitatively environmental variable dynamics. The specific objectives are (1) to assess environmental variables based on remote sensing time series and (2) to develop empirical models to forecast environmental variables. These objectives have been achieved in four applications which specific objectives are (1) assessing and mapping cotton crop phenological stages using spectral and phenometric analyses, (2) assessing and modeling fire seasonality in two different ecoregions by dynamic models, (3) forecasting forest fire risk on a pixel basis by dynamic models, and (4) assessing vegetation functioning based on temporal autocorrelation and phenometric analysis. The results of this dissertation show the usefulness of function fitting procedures to model AS1 and AS2. Phenometrics derived from function fitting procedure makes it possible to identify cotton crop phenological stages. Spectral analysis has demonstrated quantitatively the presence of one cycle in AS2 and two in AS1 and the unimodal and bimodal behaviour of fire seasonality in the Mediterranean and temperate ecoregions respectively. Autoregressive models has been used to characterize the dynamics of fire seasonality in two ecoregions and to forecasts accurately fire risk on a pixel basis. The usefulness of temporal autocorrelation to define and characterized land surface functioning has been demonstrated. And finally the “Optical Functional Types” concept has been proposed, in this approach pixels could be as temporal unities based on its temporal dynamics or functioning.

Woolliness assessment in peaches. Comparison between human and instrumental procedures and results

Woolliness, a negative attribute of sensory texture, is characterised by the lack of juiciness without variation of the tissue water content an incapacity of ripening although there is external ripe appearance. In this study, peaches cv Springcrest (early and soft flesh peaches) and Miraflores (late and hard flesh peaches) corresponding to three different maturity stages at harvest, stored 0, 1, 2, 3 and 4 weeks at 1 and 5°C have been tested by instrumental and sensory means. A Instrumental classification of woolliness has been compared to the sensory assessment. For Springcrest peaches the sensory results match with those found for the instrumental procedure. In this case , Woolliness appears after 2 weeks of storage at 5°C, changing abruptly from crispy to woolly. Miraflores peaches did not develop woolliness during storage. After comparing with sensory results, it is shown that a common instrumental scale may be appropriate to classify for woolliness all peach varieties.

Risk analysis for UAV safe operations: a rationalization for an agricultural environment

The road to the automation of the agricultural processes passes through the safe operation of the autonomous vehicles. This requirement is a fact in ground mobile units, but it still has not well defined for the aerial robots (UAVs) mainly because the normative and legislation are quite diffuse or even inexistent. Therefore, to define a common and global policy is the challenge to tackle. This characterization has to be addressed from the field experience. Accordingly, this paper presents the work done in this direction, based on the analysis of the most common sources of hazards when using UAV's for agricultural tasks. The work, based on the ISO 31000 normative, has been carried out by applying a three-step structure that integrates the identification, assessment and reduction procedures. The present paper exposes how this method has been applied to analyze previous accidents and malfunctions during UAV operations in order to obtain real failure causes. It has allowed highlighting common risks and hazardous sources and proposing specific guards and safety measures for the agricultural context.

Storabelity of melon for different ripeness stages at harvest. Selection of instrumental procedures for quality assessment.

The consumption of melon (Cucumis melo L.) has been, until several years ago, regional, seasonal and without commercial interest. Recent commercial changes and world wide transportation have changed this situation. Melons from 3 different ripeness stages at harvest and 7 cold storage periods have been analysed by destructive and non destructive tests. Chemical, physical, mechanical (non destructive impact, compression, skin puncture and Magness- Taylor) and sensory tests were carried out in order to select the best test to assess quality and to determine the optimal ripeness stage at harvest. Analysis of variance and Principal Component Analysis were performed to study the data. The mechanical properties based on non-destructive Impact and Compression can be used to monitor cold storage evolution. They can also be used at harvest to segregate the highest ripeness stage (41 days after anthesis DAA) in relation to less ripe stages (34 and 28 DAA).Only 34 and 41 DAA reach a sensory evaluation above 50 in a scale from 0-100.

Ranking factors affecting emissions of GHG from incubated agricultural soils

Agriculture significantly contributes to global greenhouse gas (GHG) missions and there is a need to develop effective mitigation strategies. The efficacy of methods to reduce GHG fluxes from agricultural soils can be affected by a range of interacting management and environmental factors. Uniquely, we used the Taguchi experimental design methodology to rank the relative importance of six factors known to affect the emission of GHG from soil: nitrate (NO3?) addition, carbon quality (labile and non-labile C), soil temperature, water-filled pore space (WFPS) and extent of soil compaction. Grassland soil was incubated in jars where selected factors, considered at two or three amounts within the experimental range, were combined in an orthogonal array to determine the importance and interactions between factors with a L16 design, comprising 16 experimental units. Within this L16 design, 216 combinations of the full factorial experimental design were represented. Headspace nitrous oxide (N2O), methane (CH4) and carbon dioxide (CO2) concentrations were measured and used to calculate fluxes. Results found for the relative influence of factors (WFPS and NO3? addition were the main factors affecting N2O fluxes, whilst glucose, NO3? and soil temperature were the main factors affecting CO2 and CH4 fluxes) were consistent with those already well documented. Interactions between factors were also studied and results showed that factors with Little individual influence became more influential in combination. The proposed methodology offers new possibilities for GHG researchers to study interactions between influential factors and address the optimized sets of conditions to reduce GHG emissions in agro-ecosystems, while reducing the number of experimental units required compared with conventional experimental procedures that adjust one variable at a time.

The Valuation of Agricultural Land and the Influence of Government Payments. Factor Markets Working Paper No. 10, December 2011

This study gives an overview of the theoretical foundations, empirical procedures and derived results of the literature identifying determinants of land prices. Special attention is given to the effects of different government support policies on land prices. Since almost all empirical studies on the determination of land prices refer either to the net present value method or the hedonic pricing approach as a theoretical basis, a short review of these models is provided. While the two approaches have different theoretical bases, their empirical implementation converges. Empirical studies use a broad range of variables to explain land values and we systematise those into six categories. In order to investigate the influence of different measures of government support on land prices, a meta-regression analysis is carried out. Our results reveal a significantly higher rate of capitalisation for decoupled direct payments and a significantly lower rate of capitalisation for agri-environmental payments, as compared to the rest of government support. Furthermore, the results show that taking theoretically consistent land rents (returns to land) and including non-agricultural variables like urban pressure in the regression implies lower elasticities of capitalisation. In addition, we find a significant influence of the land type, the data type and estimation techniques on the capitalisation rate.