Compton scattering tomography for agricultural measurements

This paper presents a new approach in tomographic instrumentation for agriculture based on Compton scattering, which allows for the simultaneous measurements of density and moisture of soil samples. Compton tomography is a technique that can be used to obtain a spatial map of electronic density of samples. Quantitative results can be obtained by using a reconstruction algorithm that takes into account the absorption of incident and scattered radiation. Results show a coefficient of linear correlation better than 0.81, when comparison is made between soil density measurements based on this method and direct transmission tomography. For soil water contents, a coefficient of linear correlation better than 0.79 was found when compared with measurements obtained by time domain reflectrometry (TDR). In addition, a set of Compton scatter images are presented to illustrate the efficacy of this imaging technique, which makes possible improved spatial variability analysis of pre-established planes.

Design and development of the architecture of an agricultural mobile robot

Parameters such as tolerance, scale and agility utilized in data sampling for using in Precision Agriculture required an expressive number of researches and development of techniques and instruments for automation. It is highlighted the employment of methodologies in remote sensing used in coupled to a Geographic Information System (GIS), adapted or developed for agricultural use. Aiming this, the application of Agricultural Mobile Robots is a strong tendency, mainly in the European Union, the USA and Japan. In Brazil, researches are necessary for the development of robotics platforms, serving as a basis for semi-autonomous and autonomous navigation systems. The aim of this work is to describe the project of an experimental platform for data acquisition in field for the study of the spatial variability and development of agricultural robotics technologies to operate in agricultural environments. The proposal is based on a systematization of scientific work to choose the design parameters utilized for the construction of the model. The kinematic study of the mechanical structure was made by the virtual prototyping process, based on modeling and simulating of the tension applied in frame, using the.

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.

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.

Control and navigation of a rover for agricultural purposes

L’obiettivo di questa tesi è di descrivere e implementare via software un modello di rover autonomo per uso in ambito agricolo. La scelta di questo argomento deriva dal fatto che al laboratorio CASY dell’Università di Bologna è stato commissionato un robot che possa aiutare piccoli imprenditori agricoli a essere competitivi con i più grandi. Le funzionalità che il robot avrà, una volta ultimato, andranno dal tagliare l’erba allo spruzzare fertilizzante sugli alberi da frutto. Questa tesi si interessa del progetto del sistema di navigazione. Inizialmente viene introdotto il modello cinematico e in particolare la configurazione differential drive in cui il rover rientra. Successivamente viene elaborato un sistema di controllo basato sulla linearizzazione statica del feedback. Una volta completati il modello e il sistema di controllo si procede con la generazione di traiettoria: vengono analizzati e confrontati alcuni algoritmi per l’inseguimento di una traiettoria definita tramite waypoint. Infine è presentato un algoritmo per la navigazione all’interno di un campo di filari di alberi da frutto. Le uniche informazioni esterne disponibili in questo contesto sono le rilevazioni di sensori di distanza frontali e laterali, in quanto un GPS sarebbe troppo impreciso per gli scopi. Questa tesi costituisce la base per ulteriori sviluppi del progetto. In particolare la realizzazione di un programma di supervisione che stabilisca la modalità di moto da attuare e programmi specifici per le varie funzionalità agricole del rover.

Design and characterization of automated agricultural vehicle systems

Nowadays, technological advancements have brought industry and research towards the automation of various processes. Automation brings a reduction in costs and an improvement in product quality. For this reason, companies are pushing research to investigate new technologies. The agriculture industry has always looked towards automating various processes, from product processing to storage. In the last years, the automation of harvest and cultivation phases also has become attractive, pushed by the advancement of autonomous driving. Nevertheless, ADAS systems are not enough. Merging different technologies will be the solution to obtain total automation of agriculture processes. For example, sensors that estimate products' physical and chemical properties can be used to evaluate the maturation level of fruit. Therefore, the fusion of these technologies has a key role in industrial process automation. In this dissertation, ADAS systems and sensors for precision agriculture will be both treated. Several measurement procedures for characterizing commercial 3D LiDARs will be proposed and tested to cope with the growing need for comparison tools. Axial errors and transversal errors have been investigated. Moreover, a measurement method and setup for evaluating the fog effect on 3D LiDARs will be proposed. Each presented measurement procedure has been tested. The obtained results highlight the versatility and the goodness of the proposed approaches. Regarding the precision agriculture sensors, a measurement approach for the Moisture Content and density estimation of crop directly on the field is presented. The approach regards the employment of a Near Infrared spectrometer jointly with Partial Least Square statistical analysis. The approach and the model will be described together with a first laboratory prototype used to evaluate the NIRS approach. Finally, a prototype for on the field analysis is realized and tested. The test results are promising, evidencing that the proposed approach is suitable for Moisture Content and density estimation.

Motion Control of an Advanced Electric Implement for Agricultural Autonomous Vehicles

Nowadays, the development of intelligent and autonomous vehicles used to perform agricultural activities is essential to improve quantity and quality of agricultural productions. Moreover, with automation techniques it is possible to reduce the usage of agrochemicals and minimize the pollution. The University of Bologna is developing an innovative system for orchard management called ORTO (Orchard Rapid Transportation System). This system involves an autonomous electric vehicle capable to perform agricultural activities inside an orchard structure. The vehicle is equipped with an implement capable to perform different tasks. The purpose of this thesis project is to control the vehicle and the implement to perform an inter-row grass mowing. This kind of task requires a synchronized motion between the traction motors and the implement motors. A motion control system has been developed to generate trajectories and manage their synchronization. Two main trajectories type have been used: a five order polynomial trajectory and a trapezoidal trajectory. These two kinds of trajectories have been chosen in order to perform a uniform grass mowing, paying a particular attention to the constrains of the system. To synchronize the motions, the electronic cams approach has been adopted. A master profile has been generated and all the trajectories have been linked to the master motion. Moreover, a safety system has been developed. The aim of this system is firstly to improve the safety during the motion, furthermore it allows to manage obstacle detection and avoidance. Using some particular techniques obstacles can be detected and recovery action can be performed to overcome the problem. Once the measured force reaches the predefined force threshold, then the vehicle stops immediately its motion. The whole project has been developed by employing Matlab and Simulink. Eventually, the software has been translated into C code and executed on the TI Lauchpad XL board.

Antioxidant And Antiproliferative Activities Of Methanolic Extract From A Neglected Agricultural Product: Corn Cobs.

Neglected agricultural products (NAPs) are defined as discarded material in agricultural production. Corn cobs are a major waste of agriculture maize. Here, a methanolic extract from corn cobs (MEC) was obtained. MEC contains phenolic compounds, protein, carbohydrates (1.4:0.001:0.001). We evaluated the in vitro and in vivo antioxidant potential of MEC. Furthermore, its antiproliferative property against tumor cells was assessed through MTT assays and proteins related to apoptosis in tumor cells were examined by western blot. MEC showed no hydroxyl radical scavenger capacity, but it showed antioxidant activity in Total Antioxidant Capacity and DPPH scavenger ability assays. MEC showed higher Reducing Power than ascorbic acid and exhibited high Superoxide Scavenging activity. In tumor cell culture, MEC increased catalase, metallothionein and superoxide dismutase expression in accordance with the antioxidant tests. In vivo antioxidant test, MEC restored SOD and CAT, decreased malondialdehyde activities and showed high Trolox Equivalent Antioxidant Capacity in animals treated with CCl4. Furthermore, MEC decreased HeLa cells viability by apoptosis due an increase of Bax/Bcl-2 ratio, caspase 3 active. Protein kinase C expression increased was also detected in treated tumor cells. Thus, our findings pointed out the biotechnological potential of corn cobs as a source of molecules with pharmacological activity.

Conversion to soy on the Amazonian agricultural frontier increases streamflow without affecting stormflow dynamics

Large-scale soy agriculture in the southern Brazilian Amazon now rivals deforestation for pasture as the region`s predominant form of land use change. Such landscape-level change can have substantial consequences for local and regional hydrology, but these effects remain relatively unstudied in this ecologically and economically important region. We examined how the conversion to soy agriculture influences water balances and stormflows using stream discharge (water yields) and the timing of discharge (stream hydrographs) in small (2.5-13.5 km2) forested and soy headwater watersheds in the Upper Xingu Watershed in the state of Mato Grosso, Brazil. We monitored water yield for 1 year in three forested and four soy watersheds. Mean daily water yields were approximately four times higher in soy than forested watersheds, and soy watersheds showed greater seasonal variability in discharge. The contribution of stormflows to annual streamflow in all streams was low (< 13% of annual streamflow), and the contribution of stormflow to streamflow did not differ between land uses. If the increases in water yield observed in this study are typical, landscape-scale conversion to soy substantially alters water-balance, potentially altering the regional hydrology over large areas of the southern Amazon.

Historical carbon emissions and uptake from the agricultural frontier of the Brazilian Amazon

Tropical ecosystems play a large and complex role in the global carbon cycle. Clearing of natural ecosystems for agriculture leads to large pulses of CO(2) to the atmosphere from terrestrial biomass. Concurrently, the remaining intact ecosystems, especially tropical forests, may be sequestering a large amount of carbon from the atmosphere in response to global environmental changes including climate changes and an increase in atmospheric CO(2). Here we use an approach that integrates census-based historical land use reconstructions, remote-sensing-based contemporary land use change analyses, and simulation modeling of terrestrial biogeochemistry to estimate the net carbon balance over the period 1901-2006 for the state of Mato Grosso, Brazil, which is one of the most rapidly changing agricultural frontiers in the world. By the end of this period, we estimate that of the state`s 925 225 km(2), 221 092 km(2) have been converted to pastures and 89 533 km(2) have been converted to croplands, with forest-to-pasture conversions being the dominant land use trajectory but with recent transitions to croplands increasing rapidly in the last decade. These conversions have led to a cumulative release of 4.8 Pg C to the atmosphere, with similar to 80% from forest clearing and 20% from the clearing of cerrado. Over the same period, we estimate that the residual undisturbed ecosystems accumulated 0.3 Pg C in response to CO2 fertilization. Therefore, the net emissions of carbon from Mato Grosso over this period were 4.5 Pg C. Net carbon emissions from Mato Grosso since 2000 averaged 146 Tg C/yr, on the order of Brazil`s fossil fuel emissions during this period. These emissions were associated with the expansion of croplands to grow soybeans. While alternative management regimes in croplands, including tillage, fertilization, and cropping patterns promote carbon storage in ecosystems, they remain a small portion of the net carbon balance for the region. This detailed accounting of a region`s carbon balance is the type of foundation analysis needed by the new United Nations Collaborative Programmme for Reducing Emissions from Deforestation and Forest Degradation (REDD).

Greenhouse gas emissions from alternative futures of deforestation and agricultural management in the southern Amazon

The Brazilian Amazon is one of the most rapidly developing agricultural areas in the world and represents a potentially large future source of greenhouse gases from land clearing and subsequent agricultural management. In an integrated approach, we estimate the greenhouse gas dynamics of natural ecosystems and agricultural ecosystems after clearing in the context of a future climate. We examine scenarios of deforestation and postclearing land use to estimate the future (2006-2050) impacts on carbon dioxide (CO(2)), methane (CH(4)), and nitrous oxide (N(2)O) emissions from the agricultural frontier state of Mato Grosso, using a process-based biogeochemistry model, the Terrestrial Ecosystems Model (TEM). We estimate a net emission of greenhouse gases from Mato Grosso, ranging from 2.8 to 15.9 Pg CO(2)-equivalents (CO(2)-e) from 2006 to 2050. Deforestation is the largest source of greenhouse gas emissions over this period, but land uses following clearing account for a substantial portion (24-49%) of the net greenhouse gas budget. Due to land-cover and land-use change, there is a small foregone carbon sequestration of 0.2-0.4 Pg CO(2)-e by natural forests and cerrado between 2006 and 2050. Both deforestation and future land-use management play important roles in the net greenhouse gas emissions of this frontier, suggesting that both should be considered in emissions policies. We find that avoided deforestation remains the best strategy for minimizing future greenhouse gas emissions from Mato Grosso.

Changes in soil organic carbon storage under different agricultural management systems in the Southwest Amazon Region of Brazil

The Cerrado and Amazon regions of Brazil are probably the largest agricultural frontier of the world, and Could be a sink or source for C depending on the net effect of land use change and subsequent management on soil organic C pools. We evaluated the effects of agricultural management systems on soil organic C (SOC) stocks in the Brazilian states of Rondonia and Mato Grosso, and derived regional specific factors for soil C stock change associated with different management systems. We used 50 observations (data points) in this study, including 42 dealing with annual cropping practices and 8 dealing with perennial cropping, and analyzed the data in linear mixed-effect models. No tillage (NT) systems in Cerrado areas increased SOC Storage by 1.08 +/- 0.06 relative to SOC stocks under native conditions, while SOC storage increased by a modest factor of 1.01 +/- 0.17 in Cerradao and Amazon Forest conditions. Full tillage (FT) had negative effect on SOC storage relative to NT, decreasing SOC stocks by a factor of 0.94 +/- 0.04. but did not significantly reduce SOC stocks relative to native levels when adopted in the Cerrado region. Perennial cropping had a minimal impact on SOC stocks, estimated at a factor Value of 0.98 +/- 0.14, suggesting these systems maintain about 98% of the SOC stock found under native vegetation. The results Suggest that NT adoption may be increasing SOC with land use change from native vegetation to cropland management in the Cerrado region of Brazil. (C) 2009 Elsevier B.V. All rights reserved.

Carbon sequestration in agricultural soils in the Cerrado region of the Brazilian Amazon

The introduction of crop management practices after conversion of Amazon Cerrado into cropland influences soil C stocks and has direct and indirect consequences on greenhouse gases (GHG) emissions. The aim of this study was to quantify soil C sequestration, through the evaluation of the changes in C stocks, as well as the GHG fluxes (N(2)O and CH(4)) during the process of conversion of Cerrado into agricultural land in the southwestern Amazon region, comparing no-tillage (NT) and conventional tillage (CT) systems. We collected samples from soils and made gas flux measurements in July 2004 (the dry season) and in January 2005 (the wet season) at six areas: Cerrado, CT cultivated with rice for 1 year (1CT) and 2 years (2CT), and NT cultivated with soybean for 1 year (1NT), 2 years (2NT) and 3 years (3NT), in each case after a 2-year period of rice under CT. Soil samples were analyzed in both seasons for total organic C and bulk density. The soil C stocks, corrected for a mass of soil equivalent to the 0-30-cm layer under Cerrado, indicated that soils under NT had generally higher C storage compared to native Cerrado and CT soils. The annual C accumulation rate in the conversion of rice under CT into soybean under NT was 0.38 Mg ha(-1) year(-1). Although CO(2) emissions were not used in the C sequestration estimates to avoid double counting, we did include the fluxes of this gas in our discussion. In the wet season, CO(2) emissions were twice as high as in the dry season and the highest N(2)O emissions occurred under the NT system. There were no CH(4) emissions to the atmosphere (negative fluxes) and there were no significant seasonal variations. When N(2)O and CH(4) emissions in C-equivalent were subtracted (assuming that the measurements made on 4 days were representative of the whole year), the soil C sequestration rate of the conversion of rice under CT into soybean under NT was 0.23 Mg ha(-1) year(-1). Although there were positive soil C sequestration rates, our results do not present data regarding the full C balance in soil management changes in the Amazon Cerrado. (C) 2008 Elsevier B.V. All rights reserved.

Arsenic and Chromium in Brazilian Agricultural Supplies

Arsenic (As) and chromium (Cr) contents were measured in agricultural supplies used at different farms in Sao Paulo State, Brazil. The highest mass fractions of As were found in thermophosphates, reaching levels of 4 mg/kg. The highest mass fractions of Cr (21 g/kg) were found in calcium magnesium silicate, while the thermophosphates also presented high values reaching approximately 1 g/kg. The levels of As were within Brazilian guidelines, but the values of Cr in thermophosphates exceeded the levels permitted in Brazil. The As content in fertilizers may be considered safe (5 mg/kg) in terms of environmental pollution. However, the Cr content in calcium magnesium silicate following continuous use may constitute a significant problem in Brazil due to potentially increasing levels of this metal in soils.