Assessment of “change in flexibility method” in structural health monitoring systems

The modern structural diagnosis process is rely on vibration characteristics to assess safer serviceability level of the structure. This paper examines the potential of change in flexibility method to use in damage detection process and two main practical constraints associated with it. The first constraint addressed in this paper is reduction in number of data acquisition points due to limited number of sensors. Results conclude that accuracy of the change in flexibility method is influenced by the number of data acquisition points/sensor locations in real structures. Secondly, the effect of higher modes on damage detection process has been studied. This addresses the difficulty of extracting higher order modal data with available sensors. Four damage indices have been presented to identify their potential of damage detection with respect to different locations and severity of damage. A simply supported beam with two degrees of freedom at each node is considered only for a single damage cases throughout the paper.

Damage assessment in reinforced concrete flexural members using modal strain energy based method

Damage assessment (damage detection, localization and quantification) in structures and appropriate retrofitting will enable the safe and efficient function of the structures. In this context, many Vibration Based Damage Identification Techniques (VBDIT) have emerged with potential for accurate damage assessment. VBDITs have achieved significant research interest in recent years, mainly due to their non-destructive nature and ability to assess inaccessible and invisible damage locations. Damage Index (DI) methods are also vibration based, but they are not based on the structural model. DI methods are fast and inexpensive compared to the model-based methods and have the ability to automate the damage detection process. DI method analyses the change in vibration response of the structure between two states so that the damage can be identified. Extensive research has been carried out to apply the DI method to assess damage in steel structures. Comparatively, there has been very little research interest in the use of DI methods to assess damage in Reinforced Concrete (RC) structures due to the complexity of simulating the predominant damage type, the flexural crack. Flexural cracks in RC beams distribute non- linearly and propagate along all directions. Secondary cracks extend more rapidly along the longitudinal and transverse directions of a RC structure than propagation of existing cracks in the depth direction due to stress distribution caused by the tensile reinforcement. Simplified damage simulation techniques (such as reductions in the modulus or section depth or use of rotational spring elements) that have been extensively used with research on steel structures, cannot be applied to simulate flexural cracks in RC elements. This highlights a big gap in knowledge and as a consequence VBDITs have not been successfully applied to damage assessment in RC structures. This research will address the above gap in knowledge and will develop and apply a modal strain energy based DI method to assess damage in RC flexural members. Firstly, this research evaluated different damage simulation techniques and recommended an appropriate technique to simulate the post cracking behaviour of RC structures. The ABAQUS finite element package was used throughout the study with properly validated material models. The damaged plasticity model was recommended as the method which can correctly simulate the post cracking behaviour of RC structures and was used in the rest of this study. Four different forms of Modal Strain Energy based Damage Indices (MSEDIs) were proposed to improve the damage assessment capability by minimising the numbers and intensities of false alarms. The developed MSEDIs were then used to automate the damage detection process by incorporating programmable algorithms. The developed algorithms have the ability to identify common issues associated with the vibration properties such as mode shifting and phase change. To minimise the effect of noise on the DI calculation process, this research proposed a sequential order of curve fitting technique. Finally, a statistical based damage assessment scheme was proposed to enhance the reliability of the damage assessment results. The proposed techniques were applied to locate damage in RC beams and slabs on girder bridge model to demonstrate their accuracy and efficiency. The outcomes of this research will make a significant contribution to the technical knowledge of VBDIT and will enhance the accuracy of damage assessment in RC structures. The application of the research findings to RC flexural members will enable their safe and efficient performance.

Nutritional status of Ugandan women living with HIV/AIDS : anthropometry and body composition assessment

Human immunodeficiency virus (HIV) that leads to acquired immune deficiency syndrome (AIDs) reduces immune function, resulting in opportunistic infections and later death. Use of antiretroviral therapy (ART) increases chances of survival, however, with some concerns regarding fat re-distribution (lipodystrophy) which may encompass subcutaneous fat loss (lipoatrophy) and/or fat accumulation (lipohypertrophy), in the same individual. This problem has been linked to Antiretroviral drugs (ARVs), majorly, in the class of protease inhibitors (PIs), in addition to older age and being female. An additional concern is that the problem exists together with the metabolic syndrome, even when nutritional status/ body composition, and lipodystrophy/metabolic syndrome are unclear in Uganda where the use of ARVs is on the increase. In line with the literature, the overall aim of the study was to assess physical characteristics of HIV-infected patients using a comprehensive anthropometric protocol and to predict body composition based on these measurements and other standardised techniques. The other aim was to establish the existence of lipodystrophy, the metabolic syndrome, andassociated risk factors. Thus, three studies were conducted on 211 (88 ART-naïve) HIV-infected, 15-49 year-old women, using a cross-sectional approach, together with a qualitative study of secondary information on patient HIV and medication status. In addition, face-to-face interviews were used to extract information concerning morphological experiences and life style. The study revealed that participants were on average 34.1±7.65 years old, had lived 4.63±4.78 years with HIV infection and had spent 2.8±1.9 years receiving ARVs. Only 8.1% of participants were receiving PIs and 26% of those receiving ART had ever changed drug regimen, 15.5% of whom changed drugs due to lipodystrophy. Study 1 hypothesised that the mean nutritional status and predicted percent body fat values of study participants was within acceptable ranges; different for participants receiving ARVs and the HIV-infected ART-naïve participants and that percent body fat estimated by anthropometric measures (BMI and skinfold thickness) and the BIA technique was not different from that predicted by the deuterium oxide dilution technique. Using the Body Mass Index (BMI), 7.1% of patients were underweight (<18.5 kg/m2) and 46.4% were overweight/obese (≥25.0 kg/m2). Based on waist circumference (WC), approximately 40% of the cohort was characterized as centrally obese. Moreover, the deuterium dilution technique showed that there was no between-group difference in the total body water (TBW), fat mass (FM) and fat-free mass (FFM). However, the technique was the only approach to predict a between-group difference in percent body fat (p = .045), but, with a very small effect (0.021). Older age (β = 0.430, se = 0.089, p = .000), time spent receiving ARVs (β = 0.972, se = 0.089, p = .006), time with the infection (β = 0.551, se = 0.089, p = .000) and receiving ARVs (β = 2.940, se = 1.441, p = .043) were independently associated with percent body fat. Older age was the greatest single predictor of body fat. Furthermore, BMI gave better information than weight alone could; in that, mean percentage body fat per unit BMI (N = 192) was significantly higher in patients receiving treatment (1.11±0.31) vs. the exposed group (0.99±0.38, p = .025). For the assessment of obesity, percent fat measures did not greatly alter the accuracy of BMI as a measure for classifying individuals into the broad categories of underweight, normal and overweight. Briefly, Study 1 revealed that there were more overweight/obese participants than in the general Ugandan population, the problem was associated with ART status and that BMI broader classification categories were maintained when compared with the gold standard technique. Study 2 hypothesized that the presence of lipodystrophy in participants receiving ARVs was not different from that of HIV-infected ART-naïve participants. Results showed that 112 (53.1%) patients had experienced at least one morphological alteration including lipohypertrophy (7.6%), lipoatrophy (10.9%), and mixed alterations (34.6%). The majority of these subjects (90%) were receiving ARVs; in fact, all patients receiving PIs reported lipodystrophy. Period spent receiving ARVs (t209 = 6.739, p = .000), being on ART (χ2 = 94.482, p = .000), receiving PIs (Fisher’s exact χ2 = 113.591, p = .000), recent T4 count (CD4 counts) (t207 = 3.694, p = .000), time with HIV (t125 = 1.915, p = .045), as well as older age (t209 = 2.013, p = .045) were independently associated with lipodystrophy. Receiving ARVs was the greatest predictor of lipodystrophy (p = .000). In other analysis, aside from skinfolds at the subscapular (p = .004), there were no differences with the rest of the skinfold sites and the circumferences between participants with lipodystrophy and those without the problem. Similarly, there was no difference in Waist: Hip ratio (WHR) (p = .186) and Waist: Height ratio (WHtR) (p = .257) among participants with lipodystrophy and those without the problem. Further examination showed that none of the 4.1% patients receiving stavudine (d4T) did experience lipoatrophy. However, 17.9% of patients receiving EFV, a non-nucleoside reverse transcriptase inhibitor (NNRTI) had lipoatrophy. Study 2 findings showed that presence of lipodystrophy in participants receiving ARVs was in fact far higher than that of HIV-infected ART-naïve participants. A final hypothesis was that the prevalence of the metabolic syndrome in participants receiving ARVs was not different from that of HIV-infected ART-naïve participants. Moreover, data showed that many patients (69.2%) lived with at least one feature of the metabolic syndrome based on International Diabetic Federation (IDF, 2006) definition. However, there was no single anthropometric predictor of components of the syndrome, thus, the best anthropometric predictor varied as the component varied. The metabolic syndrome was diagnosed in 15.2% of the subjects, lower than commonly reported in this population, and was similar between the medicated and the exposed groups (χ 21 = 0.018, p = .893). Moreover, the syndrome was associated with older age (p = .031) and percent body fat (p = .012). In addition, participants with the syndrome were heavier according to BMI (p = .000), larger at the waist (p = .000) and abdomen (p = .000), and were at central obesity risk even when hip circumference (p = .000) and height (p = .000) were accounted for. In spite of those associations, results showed that the period with disease (p = .13), CD4 counts (p = .836), receiving ART (p = .442) or PIs (p = .678) were not associated with the metabolic syndrome. While the prevalence of the syndrome was highest amongst the older, larger and fatter participants, WC was the best predictor of the metabolic syndrome (p = .001). Another novel finding was that participants with the metabolic syndrome had greater arm muscle circumference (AMC) (p = .000) and arm muscle area (AMA) (p = .000), but the former was most influential. Accordingly, the easiest and cheapest indicator to assess risk in this study sample was WC should routine laboratory services not be feasible. In addition, the final study illustrated that the prevalence of the metabolic syndrome in participants receiving ARVs was not different from that of HIV-infected ART-naïve participants.

Assessment of traffic noise level before and after freeway widening using traffic microsimulation and a refined classic noise prediction method

In this paper, a refined classic noise prediction method based on the VISSIM and FHWA noise prediction model is formulated to analyze the sound level contributed by traffic on the Nanjing Lukou airport connecting freeway before and after widening. The aim of this research is to (i) assess the traffic noise impact on the Nanjing University of Aeronautics and Astronautics (NUAA) campus before and after freeway widening, (ii) compare the prediction results with field data to test the accuracy of this method, (iii) analyze the relationship between traffic characteristics and sound level. The results indicate that the mean difference between model predictions and field measurements is acceptable. The traffic composition impact study indicates that buses (including mid-sizedtrucks) and heavy goods vehicles contribute a significant proportion of total noise power despite their low traffic volume. In addition, speed analysis offers an explanation for the minor differences in noise level across time periods. Future work will aim at reducing model error, by focusing on noise barrier analysis using the FEM/BEM method and modifying the vehicle noise emission equation by conducting field experimentation.

Physiotherapists have accurate expectations of their patients’ future health-related quality of life after first assessment in a subacute rehabilitation setting

BACKGROUND Expectations held by health professionals and their patients are likely to affect treatment choices in subacute inpatient rehabilitation settings for older adults. There is a scarcity of empirical evidence evaluating whether health professionals expectations of the quality of their patients' future health states are accurate. METHODS A prospective longitudinal cohort investigation was implemented to examine agreement (kappa coefficients, exact agreement, limits-of-agreement, and intraclass-correlation coefficients) between physiotherapists' (n = 23) prediction of patients' discharge health-related quality of life (reported on the EQ-5D-3L) and the actual health-related quality of life self-reported by patients (n = 272) at their discharge assessment (using the EQ-5D-3L). The mini-mental state examination was used as an indicator of patients' cognitive ability. RESULTS Overall, 232 (85%) patients had all assessment data completed and were included in analysis. Kappa coefficients (exact agreement) ranged between 0.37-0.57 (58%-83%) across EQ-5D-3L domains in the lower cognition group and 0.53-0.68 (81%-85%) in the better cognition group. CONCLUSIONS Physiotherapists in this subacute rehabilitation setting predicted their patients' discharge health-related quality of life with substantial accuracy. Physiotherapists are likely able to provide their patients with sound information regarding potential recovery and health-related quality of life on discharge. The prediction accuracy was higher among patients with better cognition than patients with poorer cognition.

Assessment of cone beam CT registration for prostate radiation therapy : fiducial marker and soft tissue methods

Introduction This investigation aimed to assess the consistency and accuracy of radiation therapists (RTs) performing cone beam computed tomography (CBCT) alignment to fiducial markers (FMs) (CBCTFM) and the soft tissue prostate (CBCTST). Methods Six patients receiving prostate radiation therapy underwent daily CBCTs. Manual alignment of CBCTFM and CBCTST was performed by three RTs. Inter-observer agreement was assessed using a modified Bland–Altman analysis for each alignment method. Clinically acceptable 95% limits of agreement with the mean (LoAmean) were defined as ±2.0 mm for CBCTFM and ±3.0 mm for CBCTST. Differences between CBCTST alignment and the observer-averaged CBCTFM (AvCBCTFM) alignment were analysed. Clinically acceptable 95% LoA were defined as ±3.0 mm for the comparison of CBCTST and AvCBCTFM. Results CBCTFM and CBCTST alignments were performed for 185 images. The CBCTFM 95% LoAmean were within ±2.0 mm in all planes. CBCTST 95% LoAmean were within ±3.0 mm in all planes. Comparison of CBCTST with AvCBCTFM resulted in 95% LoA of −4.9 to 2.6, −1.6 to 2.5 and −4.7 to 1.9 mm in the superior–inferior, left–right and anterior–posterior planes, respectively. Conclusions Significant differences were found between soft tissue alignment and the predicted FM position. FMs are useful in reducing inter-observer variability compared with soft tissue alignment. Consideration needs to be given to margin design when using soft tissue matching due to increased inter-observer variability. This study highlights some of the complexities of soft tissue guidance for prostate radiation therapy.

A national satellite-based land-use regression model for air pollution exposure assessment in Australia

Land-use regression (LUR) is a technique that can improve the accuracy of air pollution exposure assessment in epidemiological studies. Most LUR models are developed for single cities, which places limitations on their applicability to other locations. We sought to develop a model to predict nitrogen dioxide (NO2) concentrations with national coverage of Australia by using satellite observations of tropospheric NO2 columns combined with other predictor variables. We used a generalised estimating equation (GEE) model to predict annual and monthly average ambient NO2 concentrations measured by a national monitoring network from 2006 through 2011. The best annual model explained 81% of spatial variation in NO2 (absolute RMS error=1.4 ppb), while the best monthly model explained 76% (absolute RMS error=1.9 ppb). We applied our models to predict NO2 concentrations at the ~350,000 census mesh blocks across the country (a mesh block is the smallest spatial unit in the Australian census). National population-weighted average concentrations ranged from 7.3 ppb (2006) to 6.3 ppb (2011). We found that a simple approach using tropospheric NO2 column data yielded models with slightly better predictive ability than those produced using a more involved approach that required simulation of surface-to-column ratios. The models were capable of capturing within-urban variability in NO2, and offer the ability to estimate ambient NO2 concentrations at monthly and annual time scales across Australia from 2006–2011. We are making our model predictions freely available for research.

The Catlin Seaview Survey – kilometre-scale seascape assessment, and monitoring of coral reef ecosystems

1.Marine ecosystems provide critically important goods and services to society, and hence their accelerated degradation underpins an urgent need to take rapid, ambitious and informed decisions regarding their conservation and management. 2.The capacity, however, to generate the detailed field data required to inform conservation planning at appropriate scales is limited by time and resource consuming methods for collecting and analysing field data at the large scales required. 3.The ‘Catlin Seaview Survey’, described here, introduces a novel framework for large-scale monitoring of coral reefs using high-definition underwater imagery collected using customized underwater vehicles in combination with computer vision and machine learning. This enables quantitative and geo-referenced outputs of coral reef features such as habitat types, benthic composition, and structural complexity (rugosity) to be generated across multiple kilometre-scale transects with a spatial resolution ranging from 2 to 6 m2. 4.The novel application of technology described here has enormous potential to contribute to our understanding of coral reefs and associated impacts by underpinning management decisions with kilometre-scale measurements of reef health. 5.Imagery datasets from an initial survey of 500 km of seascape are freely available through an online tool called the Catlin Global Reef Record. Outputs from the image analysis using the technologies described here will be updated on the online repository as work progresses on each dataset. 6.Case studies illustrate the utility of outputs as well as their potential to link to information from remote sensing. The potential implications of the innovative technologies on marine resource management and conservation are also discussed, along with the accuracy and efficiency of the methodologies deployed.

The clinical utility of the Cornell Scale for Depression in Dementia as a routine assessment in nursing homes

Objective To examine the clinical utility of the Cornell Scale for Depression in Dementia (CSDD) in nursing homes. Setting 14 nursing homes in Sydney and Brisbane, Australia. Participants 92 residents with a mean age of 85 years. Measurements Consenting residents were assessed by care staff for depression using the CSDD as part of their routine assessment. Specialist clinicians conducted assessment of depression using the Semi-structured Clinical Diagnostic Interview for DSM-IV-TR Axis I Disorders for residents without dementia or the Provisional Diagnostic Criteria for Depression in Alzheimer Disease for residents with dementia to establish expert clinical diagnoses of depression. The diagnostic performance of the staff completed CSDD was analyzed against expert diagnosis using receiver operating characteristic (ROC) curves. Results The CSDD showed low diagnostic accuracy, with areas under the ROC curve being 0.69, 0.68 and 0.70 for the total sample, residents with dementia and residents without dementia, respectively. At the standard CSDD cutoff score, the sensitivity and specificity were 71% and 59% for the total sample, 69% and 57% for residents with dementia, and 75% and 61% for residents without dementia. The Youden index (for optimizing cut-points) suggested different depression cutoff scores for residents with and without dementia. Conclusion When administered by nursing home staff the clinical utility of the CSDD is highly questionable in identifying depression. The complexity of the scale, the time required for collecting relevant information, and staff skills and knowledge of assessing depression in older people must be considered when using the CSDD in nursing homes.

Assessment of the effects of CT dose in averaged x-ray CT images of a dose-sensitive polymer gel

The signal-to-noise ratio achievable in x-ray computed tomography (CT) images of polymer gels can be increased by averaging over multiple scans of each sample. However, repeated scanning delivers a small additional dose to the gel which may compromise the accuracy of the dose measurement. In this study, a NIPAM-based polymer gel was irradiated and then CT scanned 25 times, with the resulting data used to derive an averaged image and a "zero-scan" image of the gel. Comparison between these two results and the first scan of the gel showed that the averaged and zero-scan images provided better contrast, higher contrast-to- noise and higher signal-to-noise than the initial scan. The pixel values (Hounsfield units, HU) in the averaged image were not noticeably elevated, compared to the zero-scan result and the gradients used in the linear extrapolation of the zero-scan images were small and symmetrically distributed around zero. These results indicate that the averaged image was not artificially lightened by the small, additional dose delivered during CT scanning. This work demonstrates the broader usefulness of the zero-scan method as a means to verify the dosimetric accuracy of gel images derived from averaged x-ray CT data.

Assessment and application of clustering techniques to atmospheric particle number size distribution for the purpose of source apportionment

Long-term measurements of particle number size distribution (PNSD) produce a very large number of observations and their analysis requires an efficient approach in order to produce results in the least possible time and with maximum accuracy. Clustering techniques are a family of sophisticated methods which have been recently employed to analyse PNSD data, however, very little information is available comparing the performance of different clustering techniques on PNSD data. This study aims to apply several clustering techniques (i.e. K-means, PAM, CLARA and SOM) to PNSD data, in order to identify and apply the optimum technique to PNSD data measured at 25 sites across Brisbane, Australia. A new method, based on the Generalised Additive Model (GAM) with a basis of penalised B-splines, was proposed to parameterise the PNSD data and the temporal weight of each cluster was also estimated using the GAM. In addition, each cluster was associated with its possible source based on the results of this parameterisation, together with the characteristics of each cluster. The performances of four clustering techniques were compared using the Dunn index and Silhouette width validation values and the K-means technique was found to have the highest performance, with five clusters being the optimum. Therefore, five clusters were found within the data using the K-means technique. The diurnal occurrence of each cluster was used together with other air quality parameters, temporal trends and the physical properties of each cluster, in order to attribute each cluster to its source and origin. The five clusters were attributed to three major sources and origins, including regional background particles, photochemically induced nucleated particles and vehicle generated particles. Overall, clustering was found to be an effective technique for attributing each particle size spectra to its source and the GAM was suitable to parameterise the PNSD data. These two techniques can help researchers immensely in analysing PNSD data for characterisation and source apportionment purposes.

Assessment of antenna characteristic effects on pedestrian and cyclists travel-time estimation based on Bluetooth and WiFi MAC addresses

Monitoring pedestrian and cyclists movement is an important area of research in transport, crowd safety, urban design and human behaviour assessment areas. Media Access Control (MAC) address data has been recently used as potential information for extracting features from people’s movement. MAC addresses are unique identifiers of WiFi and Bluetooth wireless technologies in smart electronics devices such as mobile phones, laptops and tablets. The unique number of each WiFi and Bluetooth MAC address can be captured and stored by MAC address scanners. MAC addresses data in fact allows for unannounced, non-participatory, and tracking of people. The use of MAC data for tracking people has been focused recently for applying in mass events, shopping centres, airports, train stations etc. In terms of travel time estimation, setting up a scanner with a big value of antenna’s gain is usually recommended for highways and main roads to track vehicle’s movements, whereas big gains can have some drawbacks in case of pedestrian and cyclists. Pedestrian and cyclists mainly move in built distinctions and city pathways where there is significant noises from other fixed WiFi and Bluetooth. Big antenna’s gains will cover wide areas that results in scanning more samples from pedestrians and cyclists’ MAC device. However, anomalies (such fixed devices) may be captured that increase the complexity and processing time of data analysis. On the other hand, small gain antennas will have lesser anomalies in the data but at the cost of lower overall sample size of pedestrian and cyclist’s data. This paper studies the effect of antenna characteristics on MAC address data in terms of travel-time estimation for pedestrians and cyclists. The results of the empirical case study compare the effects of small and big antenna gains in order to suggest optimal set up for increasing the accuracy of pedestrians and cyclists’ travel-time estimation.

Improved assessment of aerosol absorption using OMI-MODIS joint retrieval

The Ozone Monitoring Instrument (OMI) aboard EOS-Aura and the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard EOS-Aqua fly in formation as part of the A-train. Though OMI retrieves aerosol optical depth (AOD) and aerosol absorption, it must assume aerosol layer height. The MODIS cannot retrieve aerosol absorption, but MODIS aerosol retrieval is not sensitive to aerosol layer height and with its smaller pixel size is less affected by subpixel clouds. Here we demonstrate an approach that uses MODIS-retrieved AOD to constrain the OMI retrieval, freeing OMI from making an a priori estimate of aerosol height and allowing a more direct retrieval of aerosol absorption. To predict near-UV optical depths using MODIS data we rely on the spectral curvature of the MODIS-retrieved visible and near-IR spectral AODs. Application of an OMI-MODIS joint retrieval over the north tropical Atlantic shows good agreement between OMI and MODIS-predicted AODs in the UV, which implies that the aerosol height assumed in the OMI-standard algorithm is probably correct. In contrast, over the Arabian Sea, MODIS-predicted AOD deviated from the OMI-standard retrieval, but combined OMI-MODIS retrievals substantially improved information on aerosol layer height (on the basis of validation against airborne lidar measurements). This implies an improvement in the aerosol absorption retrieval, but lack of UV absorption measurements prevents a true validation. Our study demonstrates the potential of multisatellite analysis of A-train data to improve the accuracy of retrieved aerosol products and suggests that a combined OMI-MODIS-CALIPSO retrieval has large potential to further improve assessments of aerosol absorption.

Rapid assessment of genotype-by-environment interactions and heritability for growth rate in aquaculture species using in vitro fertilisation and DNA tagging

Commercial environments may receive only a fraction of expected genetic gains for growth rate as predicted from the selection environment This fraction is the result of undesirable genotype-by-environment interactions (G x E) and measured by the genetic correlation (r(g)) of growth between environments. Rapid estimates of genetic correlation achieved in one generation are notoriously difficult to estimate with precision. A new design is proposed where genetic correlations can be estimated by utilising artificial mating from cryopreserved semen and unfertilised eggs stripped from a single female. We compare a traditional phenotype analysis of growth to a threshold model where only the largest fish are genotyped for sire identification. The threshold model was robust to differences in family mortality differing up to 30%. The design is unique as it negates potential re-ranking of families caused by an interaction between common maternal environmental effects and growing environment. The design is suitable for rapid assessment of G x E over one generation with a true 0.70 genetic correlation yielding standard errors as low as 0.07. Different design scenarios were tested for bias and accuracy with a range of heritability values, number of half-sib families created, number of progeny within each full-sib family, number of fish genotyped, number of fish stocked, differing family survival rates and at various simulated genetic correlation levels

Application of commercially available, low-cost, miniaturised NIR spectrometers to the assessment of the sugar content of intact fruit

Recent decreases in costs, and improvements in performance, of silicon array detectors open a range of potential applications of relevance to plant physiologists, associated with spectral analysis in the visible and short-wave near infra-red (far-red) spectrum. The performance characteristics of three commercially available ‘miniature’ spectrometers based on silicon array detectors operating in the 650–1050-nm spectral region (MMS1 from Zeiss, S2000 from Ocean Optics, and FICS from Oriel, operated with a Larry detector) were compared with respect to the application of non-invasive prediction of sugar content of fruit using near infra-red spectroscopy (NIRS). The FICS–Larry gave the best wavelength resolution; however, the narrow slit and small pixel size of the charge-coupled device detector resulted in a very low sensitivity, and this instrumentation was not considered further. Wavelength resolution was poor with the MMS1 relative to the S2000 (e.g. full width at half maximum of the 912 nm Hg peak, 13 and 2 nm for the MMS1 and S2000, respectively), but the large pixel height of the array used in the MMS1 gave it sensitivity comparable to the S2000. The signal-to-signal standard error ratio of spectra was greater by an order of magnitude with the MMS1, relative to the S2000, at both near saturation and low light levels. Calibrations were developed using reflectance spectra of filter paper soaked in range of concentrations (0–20% w/v) of sucrose, using a modified partial least squares procedure. Calibrations developed with the MMS1 were superior to those developed using the S2000 (e.g. coefficient of correlation of 0.90 and 0.62, and standard error of cross-validation of 1.9 and 5.4%, respectively), indicating the importance of high signal to noise ratio over wavelength resolution to calibration accuracy. The design of a bench top assembly using the MMS1 for the non-invasive assessment of mesocarp sugar content of (intact) melon fruit is reported in terms of light source and angle between detector and light source, and optimisation of math treatment (derivative condition and smoothing function).