Operational performance of the mechanized and semi-mechanized potato harvest

Potato is an important crop plant throughout the world. Harvesting is a fundamental step in its production system. Maybe, it is the most complex and expensive operation. Thus, the objective of this work was to compare the cost of the mechanized and semi-mechanized harvest, the operational capacity and the production losses during the potato harvest process. The work was accomplished in a commercial farming, cultivated under pivot system, in the municipal district of Perdizes - MG, Brazil. A completely randomized design with two treatments was used: mechanized and semi-mechanized harvest. The mechanized harvest used a self-propelled harvester. In the semi-automated harvest, a digger mounted on tractor was used and the potato was manually harvested. It was concluded that the cost of mechanized harvest was 49.03% lower than the cost of semi-mechanized harvest. On average, the harvester had a work for 23 workers in manual harvest. Mechanized harvest showed losses of 2.35% of potato yield, while the semi-mechanized harvest showed losses of 6.32%.

Influência do resíduo de colheita de cana-de-açúcar sem queima sobre a eficiência dos herbicidas imazapic e imazapic + pendimethalin

Os resíduos deixados sobre o solo por ocasião da colheita mecanizada da cana-de-açúcar podem constituir-se em uma barreira física para a ação dos herbicidas no controle de plantas daninhas, quando aplicados em pré-emergência destas plantas sobre a palha da cana. em virtude disso, o presente trabalho teve por objetivos analisar e quantificar a interferência dessa camada de palha sobre o solo na ação dos herbicidas imazapic e imazapic + pendimethalin no controle de plantas daninhas em áreas onde a cana-de-açúcar foi colhida mecanicamente sem a queima da palhada previamente à colheita. Foram realizados dois ensaios simultâneos: um com a retirada da palha dois dias após a aplicação dos herbicidas e o outro com a manutenção desta, ambos conduzidos em casa de vegetação. O imazapic isolado foi aplicado nas dosagens de 0, 122,5 e 147 g i.a.ha-1 e em mistura com pendimethalin na dosagem de 75 + 1500 g i.a.ha-1, com simulação de chuvas nas intensidades de 30, 60 e 90 mm. Após análise dos resultados de biomassa seca, altura e número de folhas das plantas de Sorghum bicolor e Cyperus rotundus, além de nota visual e biomassa seca de Panicum maximum, Brachiaria plantaginea, Digitaria horizontalis, Amaranthus viridis, Ipomoea grandifolia e Brachiaria decumbens, constatou-se eficiência proporcional dos herbicidas à dosagem utilizada, independentemente da presença da palha, à exceção de Ipomoea grandifolia e Brachiaria decumbens, além de haver menor controle nos tratamentos submetidos à chuva de 90 mm. Esses resultados indicam boas perspectivas quanto à aplicação destes herbicidas em áreas de colheita mecanizada de cana-de-açúcar sem queima, para controle de plantas daninhas em condições de pré-emergência.

Avaliação de linhagens da população FCA planta baixa de mamona (Ricinus communis L.)

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Design and Pilot Study for an Efficient High-Throughput Automated Computer-Vision Guided Intelligent De-Calyxing Machine for Post-Harvest Strawberry Processing

Strawberries harvested for processing as frozen fruits are currently de-calyxed manually in the field. This process requires the removal of the stem cap with green leaves (i.e. the calyx) and incurs many disadvantages when performed by hand. Not only does it necessitate the need to maintain cutting tool sanitation, but it also increases labor time and exposure of the de-capped strawberries before in-plant processing. This leads to labor inefficiency and decreased harvest yield. By moving the calyx removal process from the fields to the processing plants, this new practice would reduce field labor and improve management and logistics, while increasing annual yield. As labor prices continue to increase, the strawberry industry has shown great interest in the development and implementation of an automated calyx removal system. In response, this dissertation describes the design, operation, and performance of a full-scale automatic vision-guided intelligent de-calyxing (AVID) prototype machine. The AVID machine utilizes commercially available equipment to produce a relatively low cost automated de-calyxing system that can be retrofitted into existing food processing facilities. This dissertation is broken up into five sections. The first two sections include a machine overview and a 12-week processing plant pilot study. Results of the pilot study indicate the AVID machine is able to de-calyx grade-1-with-cap conical strawberries at roughly 66 percent output weight yield at a throughput of 10,000 pounds per hour. The remaining three sections describe in detail the three main components of the machine: a strawberry loading and orientation conveyor, a machine vision system for calyx identification, and a synchronized multi-waterjet knife calyx removal system. In short, the loading system utilizes rotational energy to orient conical strawberries. The machine vision system determines cut locations through RGB real-time feature extraction. The high-speed multi-waterjet knife system uses direct drive actuation to locate 30,000 psi cutting streams to precise coordinates for calyx removal. Based on the observations and studies performed within this dissertation, the AVID machine is seen to be a viable option for automated high-throughput strawberry calyx removal. A summary of future tasks and further improvements is discussed at the end.

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.

Comparison Between Automated And Microscopic Analysis In Body Fluids Cytology.

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Sensitivity and specificity of machine learning classifiers for glaucoma diagnosis using Spectral Domain OCT and standard automated perimetry

PURPOSE: To evaluate the sensitivity and specificity of machine learning classifiers (MLCs) for glaucoma diagnosis using Spectral Domain OCT (SD-OCT) and standard automated perimetry (SAP). METHODS: Observational cross-sectional study. Sixty two glaucoma patients and 48 healthy individuals were included. All patients underwent a complete ophthalmologic examination, achromatic standard automated perimetry (SAP) and retinal nerve fiber layer (RNFL) imaging with SD-OCT (Cirrus HD-OCT; Carl Zeiss Meditec Inc., Dublin, California). Receiver operating characteristic (ROC) curves were obtained for all SD-OCT parameters and global indices of SAP. Subsequently, the following MLCs were tested using parameters from the SD-OCT and SAP: Bagging (BAG), Naive-Bayes (NB), Multilayer Perceptron (MLP), Radial Basis Function (RBF), Random Forest (RAN), Ensemble Selection (ENS), Classification Tree (CTREE), Ada Boost M1(ADA),Support Vector Machine Linear (SVML) and Support Vector Machine Gaussian (SVMG). Areas under the receiver operating characteristic curves (aROC) obtained for isolated SAP and OCT parameters were compared with MLCs using OCT+SAP data. RESULTS: Combining OCT and SAP data, MLCs' aROCs varied from 0.777(CTREE) to 0.946 (RAN).The best OCT+SAP aROC obtained with RAN (0.946) was significantly larger the best single OCT parameter (p<0.05), but was not significantly different from the aROC obtained with the best single SAP parameter (p=0.19). CONCLUSION: Machine learning classifiers trained on OCT and SAP data can successfully discriminate between healthy and glaucomatous eyes. The combination of OCT and SAP measurements improved the diagnostic accuracy compared with OCT data alone.

Determination of banana fruit susceptibility to post-harvest diseases: wound anthracnose, quiescent anthracnose and crown rot

Introduction. This protocol aims at ( a) evaluating the resistance to post-harvest diseases within different genotypes of bananas, and ( b) comparing different origins of bananas ( geographic origin, physiological stage, etc.) for their susceptibility to post-harvest diseases. The principle, key advantages, starting plant material, time required and expected results are presented. Materials and methods. Materials required and details of the twelve steps of the protocol ( fruit sampling and inoculum preparation, wound anthracnose resistance study, quiescent anthracnose resistance study and crown-rot resistance study) are described. Results. Typical symptoms of the different diseases are obtained after artificial inoculation.

Methodology to forecast the harvest date of banana bunches

Introduction. This method is used to forecast the harvest date of banana bunches from as early as the plant shooting stage. It facilitates the harvest of bunches with the same physiological age. The principle, key advantages, time required and expected results are presented. Materials and methods. Details of the four steps of the method ( installation of the temperature sensor, tagging bunches at the flowering stage, temperature sum calculation and estimation of bunch harvest date) are described. Possible problems are discussed. Results. The application of the method allows drawing a curve of the temperature sum accumulated by the bunches which have to be harvested at exactly 900 degree-days physiological age.

Measurement of fungicide efficacy on post-harvest diseases: wound anthracnose, quiescent anthracnose, crown rot

Introduction. This protocol aims at evaluating (a) the efficacy of new fungicides for the control of post-harvest diseases, (b) the efficacy of various application methods for the chemical control of post-harvest diseases, and (c) the quality of the fungicide solution during the same packing day where this solution is recycled. The principle, key advantages, starting plant material, time required and expected results are presented. Materials and methods. Materials required and details of the eighteen steps of the protocol (fruit sampling and inoculum preparation, wound anthracnose study, quiescent anthracnose study, and crown-rot study) are described. Results. Comparison between untreated control bananas and bananas treated with fungicide allows the calculation of the fungicide treatment efficacy.

Automated supervised classification of variable stars in the CoRoT programme Method and application to the first four exoplanet fields

Aims. In this work, we describe the pipeline for the fast supervised classification of light curves observed by the CoRoT exoplanet CCDs. We present the classification results obtained for the first four measured fields, which represent a one-year in-orbit operation. Methods. The basis of the adopted supervised classification methodology has been described in detail in a previous paper, as is its application to the OGLE database. Here, we present the modifications of the algorithms and of the training set to optimize the performance when applied to the CoRoT data. Results. Classification results are presented for the observed fields IRa01, SRc01, LRc01, and LRa01 of the CoRoT mission. Statistics on the number of variables and the number of objects per class are given and typical light curves of high-probability candidates are shown. We also report on new stellar variability types discovered in the CoRoT data. The full classification results are publicly available.

AUTOMATED DETERMINATION OF [Fe/H] AND [C/Fe] FROM LOW-RESOLUTION SPECTROSCOPY

We develop an automated spectral synthesis technique for the estimation of metallicities ([Fe/H]) and carbon abundances ([C/Fe]) for metal-poor stars, including carbon-enhanced metal-poor stars, for which other methods may prove insufficient. This technique, autoMOOG, is designed to operate on relatively strong features visible in even low- to medium-resolution spectra, yielding results comparable to much more telescope-intensive high-resolution studies. We validate this method by comparison with 913 stars which have existing high-resolution and low- to medium-resolution to medium-resolution spectra, and that cover a wide range of stellar parameters. We find that at low metallicities ([Fe/H] less than or similar to -2.0), we successfully recover both the metallicity and carbon abundance, where possible, with an accuracy of similar to 0.20 dex. At higher metallicities, due to issues of continuum placement in spectral normalization done prior to the running of autoMOOG, a general underestimate of the overall metallicity of a star is seen, although the carbon abundance is still successfully recovered. As a result, this method is only recommended for use on samples of stars of known sufficiently low metallicity. For these low- metallicity stars, however, autoMOOG performs much more consistently and quickly than similar, existing techniques, which should allow for analyses of large samples of metal-poor stars in the near future. Steps to improve and correct the continuum placement difficulties are being pursued.

Harvest-ironman: heavy armature, and not its defensive secretions, protects a harvestman against a spider

Natural selection has caused prey species to evolve distinct defensive mechanisms. One of such mechanisms was the evolution of noxious or distasteful chemicals, which have appeared independently in a number of vertebrates and invertebrates. In detailed analyses of arthropod behaviour, scent gland secretions have consistently been shown to be responsible for repelling specific predators. Because using such chemicals is costly, animals with alternative cheaper defences are expected not to release such secretions when alternative options exist. In this study, we sought to determine the defensive mechanisms of the harvestman Discocyrtus invalidus, a heavy bodied species that bears a pair of repugnatorial glands. The spider Enoploctenus cyclothorax was used as the predator, and the cricket Gryllus sp. was used as a control. In a first set of experiments, the harvestmen were preyed upon significantly less than the crickets. In two other experiments, we found that harvestmen did not use their scent gland secretions to deter the predator. Moreover, results of a fourth experiment revealed that these spiders are not repelled by defensive secretions. Discocyrtus invalidus has a thick cuticle on the entire body: scanning electron micrographs revealed that only the mouth, the articulations of appendages and the tips of the legs are not covered by a hard integument. In a fifth experiment, we found that these spiders had difficulty piercing the harvestmen body. This is the first experimental evidence that a chemically defended arachnid does not use its scent gland secretions to repel a much larger predator but instead relies on its heavily built body. (c) 2010 The Association for the Study of Animal Behaviour. Published by Elsevier Ltd. All rights reserved.

Fault Detection in Power Distribution Systems Using Automated Integration of Computational Intelligence Tools

The main purpose of this paper is to present architecture of automated system that allows monitoring and tracking in real time (online) the possible occurrence of faults and electromagnetic transients observed in primary power distribution networks. Through the interconnection of this automated system to the utility operation center, it will be possible to provide an efficient tool that will assist in decisionmaking by the Operation Center. In short, the desired purpose aims to have all tools necessary to identify, almost instantaneously, the occurrence of faults and transient disturbances in the primary power distribution system, as well as to determine its respective origin and probable location. The compilations of results from the application of this automated system show that the developed techniques provide accurate results, identifying and locating several occurrences of faults observed in the distribution system.

Optimized harvest scheduling in eucalyptus plantations under operational, spatial and climatic constraints

The representation of sustainability concerns in industrial forests management plans, in relation to environmental, social and economic aspects, involve a great amount of details when analyzing and understanding the interaction among these aspects to reduce possible future impacts. At the tactical and operational planning levels, methods based on generic assumptions usually provide non-realistic solutions, impairing the decision making process. This study is aimed at improving current operational harvesting planning techniques, through the development of a mixed integer goal programming model. This allows the evaluation of different scenarios, subject to environmental and supply constraints, increase of operational capacity, and the spatial consequences of dispatching harvest crews to certain distances over the evaluation period. As a result, a set of performance indicators was selected to evaluate all optimal solutions provided to different possible scenarios and combinations of these scenarios, and to compare these outcomes with the real results observed by the mill in the study case area. Results showed that it is possible to elaborate a linear programming model that adequately represents harvesting limitations, production aspects and environmental and supply constraints. The comparison involving the evaluated scenarios and the real observed results showed the advantage of using more holistic approaches and that it is possible to improve the quality of the planning recommendations using linear programming techniques.