Effect of the Quality Property of Table Grapes in Cold Chain Logistics-Integrated WSN and AOW

Quality Monitoring and Analysis of Xinjiang ‘Korla’ Fragrant Pear in Cold Chain Logistics and Home Storage with Multi-Sensor Technology

Korla fragrant pear is prestigious for its special texture and unique flavor but suffers storage and supply chain difficulties for its deterioration-prone properties. In order to improve the storage quality of Korla fragrant pears during the whole cold chain from the orchard to the customers, the paper deeply researches multiple influencing factors of cold chain logistics and home storage of Korla fragrant pears with multi-sensor technology (MST), such as the temperature, relative humidity, concentrations of oxygen (O2), carbon dioxide (CO2) and ethylene (C2H4). Cold chain logistics are assessed by sensory evaluation and physiological index measurement, and home storage environments are classified by using back propagation neural network (BPNN) in both refrigerators and ordinary rooms. Experimental results show that the MST-based detectors can improve the accuracy of continuous sensor data acquisition, such that the preservation quality of Korla fragrant pears is effectively enhanced by data analysis on gas contents, firmness, pH, and total soluble solids. These results indicate that Korla fragrant pears stored in refrigerators have a higher acceptance for customers.

Smart System for the Optimization of Logistics Performance of the Pruning Biomass Value Chain

Agricultural pruning biomass is one of the important resources in Europe for generating renewable energy. However, utilization of the agricultural residues requires development of efficient and effective logistics systems. The objective of this study was to develop smart logistics system (SLS) appropriate for the management of the pruning biomass supply chain. The paper describes the users’ requirement of SLS, defines the technical and functional requirements and specifications for the development of SLS, and determines relevant information/data to be documented and managed by the SLS. This SLS has four major components: (a) Smart box, a sensor unit that enables measurement of data such as relative humidity, temperature, geographic positions; (b) On-board control unit, a unit that performs route planning and monitors the recordings by the smart box; (c) Information platform, a centralized platform for data storing and sharing, and management of pruning supply chain and traceability; and (d) Central control unit, an interface linking the Information platform and On-board control unit that serves as a point of administration for the whole pruning biomass supply chain from harvesting to end user. The SLS enables the improvement of performance of pruning biomass supply chain management and product traceability leading to a reduction of product loss, increased coordination of resources utilisation and quality of solid biofuel supply, increased pruning marketing opportunity, and reduction of logistics cost. This SLS was designed for pruning biomass, but could also be adapted for any type of biomass-to-energy initiatives.

Effectiveness of Metarhizium anisopliae and Entomopathogenic Nematodes to Control Oryctes rhinoceros Larvae in the Rainy Season

BACKGROUND AND OBJECTIVE

Metarhizium anisopliae (MET) and entomopathogenic nematodes (EPN) are microorganisms that attack the larvae of Oryctes rhinoceros. The effects of MET, EPN and the combination of both on the O. rhinoceros larvae were studied during the rainy season in Jepara Indonesia. This study aimed to determine the effectiveness of Metarhizium anisopliae and entomopathogenic nematodes to control Oryctes rhinoceros larvae in the rainy season.

MATERIALS AND METHODS

There were four level doses of MET, four level doses of EPN and four mixture of MET and EPN. The experiment used 72 containers that were placed in the garden with coconut palm shade. Five kilograms of organic soil that was mixed with biological control agents (MET, EPN and MET+EPN) and ten O. rhinoceros larvae 3rd instar were put in each other container. The data were analyzed by descriptive analysis.

RESULTS

Every larvae mortality was observed once a week and observations are for 8 weeks. The result showed that the larval mortality due to MET treatment occurred on 2nd-7th week. Meanwhile, the larval mortality due to EPN treatment took place on 2nd-8th weeks and the larval mortality due to MET+EPN treatment occurred on 1st-5th weeks.

CONCLUSION

The combination of MET and EPN was simultaneously effective to control O. rhinoceros larvae than separate use of MET or EPN. Result of this study showed that using two agents of biocontrol was more effective, so that it can be beneficial for controlling O. rhinoceros larvae in the field.