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Tomato greenhouses are a crucial element in the Equadorian economy. Wireless sensor networks (WSNs) have received much attention in recent years in specialized applications such as precision farming. The energy consumption in WSNs is relevant nowadays for their adequate operation, and attention is being paid to analyzing the affecting factors, energy optimization techniques working on the network hardware or software, and characterizing the consumption in the nodes (especially in the ZigBee standard). However, limited information exists on the analysis of the consumption dynamics in each node, across different network technologies and communication topologies, or on the incidence of data transmission speed. The present study aims to provide a detailed analysis of the dynamics of the energy consumption for tomato greenhouse monitoring in Ecuador, in three types of WSNs, namely, ZigBee with star topology, ZigBee with mesh topology (referred to here as DigiMesh), and WiFi with access point topology. The networks were installed and maintained in operation with a line of sight between nodes and a 2-m length, whereas the energy consumption measurements of each node were acquired and stored in the laboratory. Each experiment was repeated ten times, and consumption measurements were taken every ten milliseconds at a rate of fifty thousand samples for each realization. The dynamics were scrutinized by analyzing the recorded time series using stochastic-process analysis methods, including amplitude probability functions and temporal autocorrelation, as well as bootstrap resampling techniques and representations of various embodiments with the so-called M-mode plots. Our results show that the energy consumption of each network strongly depends on the type of sensors installed in the nodes and on the network topology. Specifically, the CO2 sensor has the highest power consumption because its chemical composition requires preheating to start logging measurements. The ZigBee network is more efficient in energy saving independently of the transmission rate, since the communication modules have lower average consumption in data transmission, in contrast to the DigiMesh network, whose consumption is high due to its topology. Results also show that the average energy consumption in WiFi networks is the highest, given that the coordinator node is a Meshlium™ router with larger energy demand. The transmission duration in the ZigBee network is lower than in the other two networks. In conclusion, the ZigBee network with star topology is the most energy-suitable one when designing wireless monitoring systems in greenhouses. The proposed methodology for consumption dynamics analysis in tomato greenhouse WSNs can be applied to other scenarios where the practical choice of an energy-efficient network is necessary due to energy constrains in the sensor and coordinator nodes.

Environmental variables monitoring with wireless sensor networks (WSNs) is invaluable for precision agriculture applications. However, the effectiveness of existing low-power, conventional (e.g., ZigBee-type) radios in large-scale deployments is limited by power consumption, cost, and complexity constraints, while the existing WSN solutions employing nonconventional, scatter-radio principles have been restricted to communication ranges of up to a few meters. In this paper, the development of a novel analog scatter-radio WSN is presented, that employs semipassive sensor/tags in bistatic topology (i.e., carrier emitter placed in a different location from the reader), consuming <;1 mW of power, with communication range exceeding 100 m. The experimental results indicate that the multipoint surface fitting calibration, in conjunction with the employed two-phase filtering process, both provide a mean absolute error of 1.9% environmental relative humidity for a temperature range of 10 °C-50 °C. In addition, the energy consumption per measurement of the proposed environmental monitoring approach can be lower than that of conventional radio WSNs. Finally, the proposed approach operational characteristics are presented through a real-world network deployment in a tomato greenhouse. [ABSTRACT FROM PUBLISHER]

Greenhouse tomato growing processes are labor intensive, and the large numbers of workers involved in the various operations cause bottlenecks that affect costs and working efficiency. The main bottleneck points are in the trellising and harvesting stages, and in the transportation to the packinghouse. This study aimed to suggest improved working practices in tomato greenhouses by reducing manual labor. The study took place on a farm with 30 ha of tomato greenhouses located in southwest Israel. Work studies were conducted, and the working procedures were characterized. Two simulation models of the working procedures in tomato greenhouses were developed in ARENA and Microsoft Excel Visual Basic on the basis of statistical analysis of the work-study data. The Visual Basic simulation environment proved to be better suited to the agricultural environment. Several alternatives for the various work procedures were suggested and evaluated. The results indicate that fruit pickers should use a picking cart, progressing along the row in a batch advance method, and that longer rows are preferable and reduce working time. This could reduce manual labor by up to 32%. [ABSTRACT FROM AUTHOR]

Abstract: Collaborative research was conducted in the south of France to assess constraints related to both climate heterogeneity and ventilation systems on the control potential of a Lecanicillium muscarium-based formulation against whiteflies in Mediterranean greenhouses. Four series of small-scale greenhouse trials were performed in 2001 and 2002. Two applications at 4–5 day intervals of Mycotal were conducted on young larvae of the greenhouse whitefly, Trialeurodes vaporariorum, at the rate recommended by the manufacturer (ca. 1010 viable spores per liter of water suspension). The climatic heterogeneity was taken into account by comparing the fungus-induced mortality of nymphs located on lateral row plants to that of nymphs on center row plants. In spite of significant differences in air flows (0.7–1.2 and 0.3ms−1, respectively) there was no effect on fungus efficacy (53–76% mortality). When comparing the influence of greenhouse equipment (sophisticated glasshouse vs. polyethylene-covered greenhouse), the fungus was not affected (89–96% mortality) in spite of significant differences in ventilation rates. The results confirmed that entomopathogenic Hyphomycetes have a strong potential for microbial control of whitefly larvae infesting tomato crops at moderate ambient humidity in Mediterranean greenhouses in spite of windy periods. These investigations confirmed that microclimatic conditions prevailing in the targeted insect habitat (under-leaf surface boundary layer) are greatly disconnected from that of both outside and inside the greenhouse. In northern Mediterranean greenhouses, non-stressed tomato crops provide unexpected favorable conditions for mycoinsecticide use against a phyllophagous insect. [Copyright &y& Elsevier]

Tomato greenhouses are a crucial element in the Equadorian economy. Wireless sensor networks (WSNs) have received much attention in recent years in specialized applications such as precision farming. The energy consumption in WSNs is relevant nowadays for their adequate operation, and attention is being paid to analyzing the affecting factors, energy optimization techniques working on the network hardware or software, and characterizing the consumption in the nodes (especially in the ZigBee standard). However, limited information exists on the analysis of the consumption dynamics in each node, across different network technologies and communication topologies, or on the incidence of data transmission speed. The present study aims to provide a detailed analysis of the dynamics of the energy consumption for tomato greenhouse monitoring in Ecuador, in three types of WSNs, namely, ZigBee with star topology, ZigBee with mesh topology (referred to here as DigiMesh), and WiFi with access point topology. The networks were installed and maintained in operation with a line of sight between nodes and a 2-m length, whereas the energy consumption measurements of each node were acquired and stored in the laboratory. Each experiment was repeated ten times, and consumption measurements were taken every ten milliseconds at a rate of fifty thousand samples for each realization. The dynamics were scrutinized by analyzing the recorded time series using stochastic-process analysis methods, including amplitude probability functions and temporal autocorrelation, as well as bootstrap resampling techniques and representations of various embodiments with the so-called M-mode plots. Our results show that the energy consumption of each network strongly depends on the type of sensors installed in the nodes and on the network topology. Specifically, the CO 2 sensor has the highest power consumption because its chemical composition requires preheating to start logging measurements. The ZigBee network is more efficient in energy saving independently of the transmission rate, since the communication modules have lower average consumption in data transmission, in contrast to the DigiMesh network, whose consumption is high due to its topology. Results also show that the average energy consumption in WiFi networks is the highest, given that the coordinator node is a Meshlium™ router with larger energy demand. The transmission duration in the ZigBee network is lower than in the other two networks. In conclusion, the ZigBee network with star topology is the most energy-suitable one when designing wireless monitoring systems in greenhouses. The proposed methodology for consumption dynamics analysis in tomato greenhouse WSNs can be applied to other scenarios where the practical choice of an energy-efficient network is necessary due to energy constrains in the sensor and coordinator nodes. [ABSTRACT FROM AUTHOR]