930 resultados para harvest scheduling


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BACKGROUND: Pseudomonas tolaasii is a problematic pathogen of cultured mushrooms, forming dark brown 'blotches' on mushroom surfaces and causing spoilage during crop growth and post-harvest . Treating P. tolaasii infection is difficult, as other, commensal bacterial species such as Pseudomonas putida are necessary for mushroom growth, so treatments must be relatively specific. RESULTS: We have found that P. tolaasii is susceptible to predation in vitro by the δ-proteobacterium Bdellovibrio bacteriovorus. This effect also occurred in funga, where B. bacteriovorus was administered to post-harvest mushroom caps before and after administration of the P. tolaasii pathogen. A significant, visible improvement in blotch appearance, after incubation, was observed on administration of Bdellovibrio. A significant reduction in viable P. tolaasii cell numbers, recovered from the mushroom tissue, was detected. This was accompanied by a more marked reduction in blotch severity on Bdellovibrio administration. We found that there was in some cases an accompanying overgrowth of presumed-commensal, non-Pseudomonas bacteria on post-harvest mushroom caps after Bdellovibrio-treatment. These bacteria were identified (by 16SrRNA gene sequencing) as Enterobacter species, which were seemingly resistant to predation. We visualised predatory interactions occuring between B. bacteriovorus and P. tolaasii on the post-harvest mushroom cap surface by Scanning Electron Microscopy, seeing predatory invasion of P. tolaasii by B. bacteriovorus in funga. This anti-P. tolaasii effect worked well in post-harvest supermarket mushrooms, thus Bdellovibrio was not affected by any pre-treatment of mushrooms for commercial/consumer purposes. CONCLUSIONS: The soil-dwelling B. bacteriovorus HD100 preys upon and kills P. tolaasii, on mushroom surfaces, and could therefore be applied to prevent spoilage in post-harvest situations where mushrooms are stored and packaged for sale.

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• Background and Aims Earlier studies have suggested that the drying conditions routinely used by genebanks may not be optimal for subsequent seed longevity. The aim of this study was to compare the effect of hot-air drying with low temperature drying on subsequent seed longevity for 20 diverse rice accessions and to consider how factors related to seed production history might influence the results. • Methods Seeds were produced according to normal regeneration procedures at IRRI. They were harvested at different times (harvest date and days after anthesis (DAA), once for each accession) and dried either in a drying room (DR; 15% RH, 15°C), or in a flat-bed heated-air batch dryer (BD; 45°C, 8 h d-1) for up to 6 daily cycles followed by drying in the DR. Relative longevity was assessed by storage at 10.9% moisture content (m.c.) and 45°C. • Key Results Initial drying in the BD resulted in significantly greater longevity compared with the DR for 14 accessions (seed lots): the period of time for viability to fall to 50% for seeds dried in the BD as a percentage of that for seeds dried throughout in the DR varied between 1.3 and 372.2% for these 14 accessions. The seed lots that responded the most were harvested earlier in the season and at higher moisture content. Drying in the BD did not reduce subsequent longevity compared with DR drying for any of the remaining accessions. • Conclusions Seeds harvested at a m.c. where, according to the moisture desorption isotherm, they could still be metabolically active (>16.2%), may be in the first stage of the post-mass maturity, desiccation phase of seed development and able to increase longevity in response to hot-air drying. The genebank standards regarding seed drying for rice and, perhaps, for other tropical species should be reconsidered.

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An important step in breeding for nutritionally enhanced varieties is determining the effects of the post-harvest supply chain on phytochemicals and the changes in VOCs produced over time. TD- GC-TOF-MS was used and a technique for the extraction of VOCs from the headspace using portable tubes is described. Forty-two compounds were detected; 39 were identified by comparison to NIST libraries. Thirty-five compounds had not been previously reported in Eruca sativa. Seven accessions were assessed for changes in headspace VOCs over 7 days. Relative amounts of VOCs across 3 time points were significantly different - isothiocyanate-containing molecules being abundant on 'Day 0'. Each accession showed differences in proportions/types of volatiles produced on each day. PCA revealed a separation of VOC profiles according to the day of sampling. Changes in VOC profiles over time could provide a tool for assessment of shelf-life.

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Unpredictable flooding is a major constraint to rice production. It can occur at any growth stage. The effect of simulated flooding post-anthesis on yield and subsequent seed quality of pot-grown rice (Oryza sativa L.) plants was investigated in glasshouses and controlled-environment growth cabinets. Submergence post-anthesis (9-40 DAA) for 3 or 5 days reduced seed weight of japonica rice cv. Gleva, with considerable pre-harvest sprouting (up to 53%). The latter was greater the later in seed development and maturation that flooding occurred. Sprouted seed had poor ability to survive desiccation or germinate normally upon rehydration, whereas the effects of flooding on the subsequent air-dry seed storage longevity (p50) of the non-sprouted seed fraction was negligible. The indica rice cvs IR64 and IR64Sub1 (introgression of submergence tolerance gene Submergence1A-1) were both far more tolerant to flooding post-anthesis than cv. Gleva: four days’ submergence of these two near-isogenic cultivars at 10-40 DAA resulted less than 1% sprouted seeds. The presence of the Sub1A-1 allele in cv. IR64Sub1 was verified by gel electrophoresis and DNA sequencing. It had no harmful effect on loss in seed viability during storage compared with IR64 in both control and flooded environments. Moreover, the germinability and changes in dormancy during seed development and maturation were very similar to IR64. The efficiency of using chemical spray to increase seed dormancy was investigated in the pre-harvest sprouting susceptible rice cv. Gleva. Foliar application of molybdenum at 100 mg L-1 reduced sprouted seeds by 15-21% following 4 days’ submergence at 20-30 DAA. Analyses confirmed that the treatment did result in molybdenum uptake by the plants, and also tended to increase seed abscisic acid concentration. The latter was reduced by submergence and declined exponentially during grain ripening. The selection of submergence-tolerant varieties was more successful than application of molybdenum in reducing pre-harvest sprouting.

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BACKGROUND: The aim of this study was to characterise the mycoflora and the presence of fumonisin in sorghum grains, correlating the results with the environment and abiotic factors. RESULTS: Fifty samples (five collections of ten samples each) of sorghum were analysed. All samples were found to be contaminated with fungi, with higher frequencies of Cladosporium spp. (61.8%) and Helminthosporium spp. (33.4%). Fusarium verticillioides was isolated from 15.1% of the samples, with 38% of them being contaminated with fumonisin B(1) (FB(1)) at levels ranging from 50 to 368.78 ng g(-1). Regarding abiotic factors, temperature, water activity and rainfall showed a positive correlation with the frequency of F. verticillioides and FB(1) production. There was a significant positive correlation between relative air humidity and FB(1) production. The results obtained from sexual crosses between standard F mating tester strains and the isolated strains confirmed that the strains isolated were F. verticillioides. CONCLUSION: It can be concluded that the decrease in F. verticillioides and fumonisin contamination occurred owing to atypical climatic factors during the period of sorghum cultivation, when there was any occurrence of rain and the level of water activity of grains did not reach 0.58. (C) 2010 Society of Chemical Industry

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The evolution of commodity computing lead to the possibility of efficient usage of interconnected machines to solve computationally-intensive tasks, which were previously solvable only by using expensive supercomputers. This, however, required new methods for process scheduling and distribution, considering the network latency, communication cost, heterogeneous environments and distributed computing constraints. An efficient distribution of processes over such environments requires an adequate scheduling strategy, as the cost of inefficient process allocation is unacceptably high. Therefore, a knowledge and prediction of application behavior is essential to perform effective scheduling. In this paper, we overview the evolution of scheduling approaches, focusing on distributed environments. We also evaluate the current approaches for process behavior extraction and prediction, aiming at selecting an adequate technique for online prediction of application execution. Based on this evaluation, we propose a novel model for application behavior prediction, considering chaotic properties of such behavior and the automatic detection of critical execution points. The proposed model is applied and evaluated for process scheduling in cluster and grid computing environments. The obtained results demonstrate that prediction of the process behavior is essential for efficient scheduling in large-scale and heterogeneous distributed environments, outperforming conventional scheduling policies by a factor of 10, and even more in some cases. Furthermore, the proposed approach proves to be efficient for online predictions due to its low computational cost and good precision. (C) 2009 Elsevier B.V. All rights reserved.

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In this article we propose a 0-1 optimization model to determine a crop rotation schedule for each plot in a cropping area. The rotations have the same duration in all the plots and the crops are selected to maximize plot occupation. The crops may have different production times and planting dates. The problem includes planting constraints for adjacent plots and also for sequences of crops in the rotations. Moreover, cultivating crops for green manuring and fallow periods are scheduled into each plot. As the model has, in general, a great number of constraints and variables, we propose a heuristics based on column generation. To evaluate the performance of the model and the method, computational experiments using real-world data were performed. The solutions obtained indicate that the method generates good results.

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A lot sizing and scheduling problem prevalent in small market-driven foundries is studied. There are two related decision levels: (I the furnace scheduling of metal alloy production, and (2) moulding machine planning which specifies the type and size of production lots. A mixed integer programming (MIP) formulation of the problem is proposed, but is impractical to solve in reasonable computing time for non-small instances. As a result, a faster relax-and-fix (RF) approach is developed that can also be used on a rolling horizon basis where only immediate-term schedules are implemented. As well as a MIP method to solve the basic RF approach, three variants of a local search method are also developed and tested using instances based on the literature. Finally, foundry-based tests with a real-order book resulted in a very substantial reduction of delivery delays and finished inventory, better use of capacity, and much faster schedule definition compared to the foundry`s own practice. (c) 2006 Elsevier Ltd. All rights reserved.

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In 2006 the Route load balancing algorithm was proposed and compared to other techniques aiming at optimizing the process allocation in grid environments. This algorithm schedules tasks of parallel applications considering computer neighborhoods (where the distance is defined by the network latency). Route presents good results for large environments, although there are cases where neighbors do not have an enough computational capacity nor communication system capable of serving the application. In those situations the Route migrates tasks until they stabilize in a grid area with enough resources. This migration may take long time what reduces the overall performance. In order to improve such stabilization time, this paper proposes RouteGA (Route with Genetic Algorithm support) which considers historical information on parallel application behavior and also the computer capacities and load to optimize the scheduling. This information is extracted by using monitors and summarized in a knowledge base used to quantify the occupation of tasks. Afterwards, such information is used to parameterize a genetic algorithm responsible for optimizing the task allocation. Results confirm that RouteGA outperforms the load balancing carried out by the original Route, which had previously outperformed others scheduling algorithms from literature.

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The aim of task scheduling is to minimize the makespan of applications, exploiting the best possible way to use shared resources. Applications have requirements which call for customized environments for their execution. One way to provide such environments is to use virtualization on demand. This paper presents two schedulers based on integer linear programming which schedule virtual machines (VMs) in grid resources and tasks on these VMs. The schedulers differ from previous work by the joint scheduling of tasks and VMs and by considering the impact of the available bandwidth on the quality of the schedule. Experiments show the efficacy of the schedulers in scenarios with different network configurations.

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The problem of scheduling a parallel program presented by a weighted directed acyclic graph (DAG) to the set of homogeneous processors for minimizing the completion time of the program has been extensively studied as academic optimization problem which occurs in optimizing the execution time of parallel algorithm with parallel computer.In this paper, we propose an application of the Ant Colony Optimization (ACO) to a multiprocessor scheduling problem (MPSP). In the MPSP, no preemption is allowed and each operation demands a setup time on the machines. The problem seeks to compose a schedule that minimizes the total completion time.We therefore rely on heuristics to find solutions since solution methods are not feasible for most problems as such. This novel heuristic searching approach to the multiprocessor based on the ACO algorithm a collection of agents cooperate to effectively explore the search space.A computational experiment is conducted on a suit of benchmark application. By comparing our algorithm result obtained to that of previous heuristic algorithm, it is evince that the ACO algorithm exhibits competitive performance with small error ratio.

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The introduction of a new technology High Speed Downlink Packet Access (HSDPA) in the Release 5 of the 3GPP specifications raises the question about its performance capabilities. HSDPA is a promising technology which gives theoretical rates up to 14.4 Mbits. The main objective of this thesis is to discuss the system level performance of HSDPAMainly the thesis exploration focuses on the Packet Scheduler because it is the central entity of the HSDPA design. Due to its function, the Packet Scheduler has a direct impact on the HSDPA system performance. Similarly, it also determines the end user performance, and more specifically the relative performance between the users in the cell.The thesis analyzes several Packet Scheduling algorithms that can optimize the trade-off between system capacity and end user performance for the traffic classes targeted in this thesis.The performance evaluation of the algorithms in the HSDPA system are carried out under computer aided simulations that are assessed under realistic conditions to predict the results as precise on the algorithms efficiency. The simulation of the HSDPA system and the algorithms are coded in C/C++ language

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The multiprocessor task graph scheduling problem has been extensively studied asacademic optimization problem which occurs in optimizing the execution time of parallelalgorithm with parallel computer. The problem is already being known as one of the NPhardproblems. There are many good approaches made with many optimizing algorithmto find out the optimum solution for this problem with less computational time. One ofthem is branch and bound algorithm.In this paper, we propose a branch and bound algorithm for the multiprocessor schedulingproblem. We investigate the algorithm by comparing two different lower bounds withtheir computational costs and the size of the pruned tree.Several experiments are made with small set of problems and results are compared indifferent sections.

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The automated timetabling and scheduling is one of the hardest problem areas. This isbecause of constraints and satisfying those constraints to get the feasible and optimizedschedule, and it is already proved as an NP Complete (1) [1]. The basic idea behind this studyis to investigate the performance of Genetic Algorithm on general scheduling problem underpredefined constraints and check the validity of results, and then having comparative analysiswith other available approaches like Tabu search, simulated annealing, direct and indirectheuristics [2] and expert system. It is observed that Genetic Algorithm is good solutiontechnique for solving such problems and later analysis will prove this argument. The programis written in C++ and analysis is done by using variation in various parameters.

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In order to achieve the high performance, we need to have an efficient scheduling of a parallelprogram onto the processors in multiprocessor systems that minimizes the entire executiontime. This problem of multiprocessor scheduling can be stated as finding a schedule for ageneral task graph to be executed on a multiprocessor system so that the schedule length can be minimize [10]. This scheduling problem is known to be NP- Hard.In multi processor task scheduling, we have a number of CPU’s on which a number of tasksare to be scheduled that the program’s execution time is minimized. According to [10], thetasks scheduling problem is a key factor for a parallel multiprocessor system to gain betterperformance. A task can be partitioned into a group of subtasks and represented as a DAG(Directed Acyclic Graph), so the problem can be stated as finding a schedule for a DAG to beexecuted in a parallel multiprocessor system so that the schedule can be minimized. Thishelps to reduce processing time and increase processor utilization. The aim of this thesis workis to check and compare the results obtained by Bee Colony algorithm with already generatedbest known results in multi processor task scheduling domain.