Gashaw Ayalew

Detection of glass contamination in horticultural peat with dual-energy X-ray absorptiometry (DXA)

The application of dual-energy X-ray absorptiometry (DXA) to the detection of glass contamination in horticultural peat was studied using contaminated peat specimens, imaged with X-ray energies of 40 and 70 kVp and without any physical disruption of the peat samples. The source was an uncollimated beam from an industrial X-ray non-destructive testing system. X-ray transmission characteristics of peat and glass were determined from chemical composition data using XCOM software. The DXA images were analysed for detectivity figure (DF), signal-to-noise ratio (SNR) and contrast. These quantities were compared with those of the unprocessed 40 kVp images. There was >75% detection of glass presence if thicker than 3 mm, but 100% detection of glass fragments thicker than 1 mm. It was not possible to distinguish between glass and stone. DF values were dependent on peat and glass type, and contrast more than doubled with the DXA-derived images compared with their 40 kVp counterparts. Comparison with reported figures for a luggage inspection system shows that this system performs better than expected for commercial security systems. Better DXA results may be possible using simultaneous energy detection, and such a multi-energy sensing system could allow glass/stone detection as part of peat quality assurance, and the determination of peat chemical composition.

Development of a prototype infrared reflectance moisture meter for milled peat

Abstract A prototype infrared reflectance moisture meter was designed, built and calibrated. Based on observations and statistical analyses, a reference waveband centred on 1800 nm and an absorption band centred on 1928 nm, were selected for measurement of wet weight basis moisture content in peat. The prototype was tested on three peat types (low-, medium-, and high-density peats) with mcwb ranging from ca. 33–63%. Analysis of covariance of the calibration data shows that the correlations existing in the three peat types differ at 5% significance level. Based on the computed standard error of estimate, the 95% confidence limits of the prototype moisture meter were ±2.75, ±1.75, and ±3.2% mcwb, respectively, for low-, medium-, and high-density peats. However, when all peat types were grouped together, the 95% confidence limit increased to ±5.3%. The peat industry requires a non-invasive moisture meter with an accuracy of ca. ±3.0% mcwb. This implies that in order to meet the industry requirement, it is necessary to be able to distinguish between peat types. This could be done satisfactorily by manual selection in many cases but the development of an automated system would further enhance the potential of this meter.

Implementation Protocol Utilising Radio Frequency Identification (RFID) and Biometric Identifiers; In the Context of Irish Bovine Traceability

1.1 Irish cattle traceability The Irish Department of Agriculture, Fisheries and Food (DAFF) is the authority responsible for the implementation of EC 1760/2000, which outlines the requirements for the identification and registration of bovine animals. Since the mid 1990’s computerised databases have been established specifically the Calf Birth Registration System and the Cattle Movement Monitoring System (CMMS) (DAFF, 2003). The CMMS was initiated to record all information on births, movement, deaths and disposals. Computer equipment linked to the central database was installed in abattoirs and export points to electronically record all animal movements to and/or from these premises. As the CMMS relies on paper records for notification of certain events such as, births (herd keepers have seven days to notify the Calf Birth Registration System) and on-farm deaths, it cannot be said that it is totally accurate at a given point in time. The figures from the official CMMS statistics reports published each year reflect this, out of which a summary of the herd population statistics for recent years can be seen in Table 1. The start of January figures are calculated by taking the population figure at the end of December for the year in question from the CMMS database and adding all the disposals (cattle slaughtered, exported and on-farm deaths) and subtracting all the births and imports that have been recorded on the CMMS for that year.

Comparison of Simple Shape Measures and Fourier Descriptors as applied to the Identification of Highinjury-risk Glass Contaminants in Horticultural Peat

Horticultural peat supplied for the domestic market is mainly hand manipulated by gardeners. For a glass contaminant to cause injury it must be angular (pointed) and must have a significant protrusion at its angular end. Identification of high-injury risk glass fragments must quantify angularity and protrusion. In this study, glass contaminants included in peat were detected using dual-energy X-ray absorptiometry (DXA), and ranking of various shapes according to risk of injury was carried out based upon visual assessment and compared to quantified shape measures. The shape measures investigated included compactness, eccentricity, radius of gyration, principal axes ratio, the product of angle of edge deflection and protrusion; and Zahn-Roskies Fourier shape measures (FSMs). Results showed that compactness performed best ( o =0.735, p<0.000001) with the lowest computational demand, followed by Zahn-Roskies Fourier shape measures ( o =-0.583, p<0.00001) and principal axes ratio ( o=0.563, p<0.00001). The use of compactness as a means of identification of risk of injury is feasible for online application.