Choice in the context of informal care-giving

Extending choice and control for social care service users is a central feature of current English policies. However, these have comparatively little to say about choice in relation to the informal carers of relatives, friends or older people who are disabled or sick. To explore the realities of choice as experienced by carers, the present paper reviews research published in English since 1985 about three situations in which carers are likely to face choices: receiving social services; the entry of an older person to long-term care; and combining paid work and care. Thirteen electronic databases were searched, covering both the health and social care fields. Databases included: ASSIA; IBSS; Social Care Online; ISI Web of Knowledge; Medline; HMIC Sociological Abstracts; INGENTA; ZETOC; and the National Research Register. The search strategy combined terms that: (1) identified individuals with care-giving responsibilities; (2) identified people receiving help and support; and (3) described the process of interest (e.g. choice, decision-making and self-determination). The search identified comparatively few relevant studies, and so was supplemented by the findings from another recent review of empirical research on carers' choices about combining work and care. The research evidence suggests that carers' choices are shaped by two sets of factors: one relates to the nature of the care-giving relationship; and the second consists of wider organisational factors. A number of reasons may explain the invisibility of choice for carers in current policy proposals for increasing choice. In particular, it is suggested that underpinning conceptual models of the relationship between carers and formal service providers shape the extent to which carers can be offered choice and control on similar terms to service users. In particular, the exercise of choice by carers is likely to be highly problematic if it involves relinquishing some unpaid care-giving activities

Near infrared spectroscopy as a rapid, non-invasive method for sandalwood oil determination

Fourier Transform (FT) - near infra-red spectroscopy (NIRS) was investigated as a non-invasive technique for predicting -santalol content in sandalwood chip samples. The correlation between the NIR spectral data and the a-santalol content from the GC-MS analysis was very high (R2 = 0.93). The feasibility study indicates that it is possible to use FT-NIRS to predict -santalol content in sandalwood chip samples. The technique of utilising NIRS technology for sandalwood quality and quantity determination needs to be further developed to be utilised as a tool for commercial applications

Near Infrared Spectroscopy as a rapid method\ud for sandalwood oil determination

The remaining chips from 295 sandalwood (S. austrocaledonicum) cores previously\ud analysed using GC-MS were scanned using Near infrared Spectroscopy\ud (NIRS). The correlation between the NIR spectral data and the a-santalol content\ud from the GC-MS analysis was very high (R2 = 0.9258). Such a high correspondence\ud between these two techniques indicates that it is possible to use NIRS to\ud predict a-santalol content in sandalwood chip samples. The relative advantages\ud of using NIRS for quantifying a-santalol content in raw sandalwood is discussed\ud in terms of its rapid and potentially inexpensive application to quality control for\ud processing and breeding new cultivars

Non-invasive assessment of internal quality attributes of whole avocado fruit by NIRS

The utility of Fourier Transform (FT) - near infra-red\ud spectroscopy (NIRS) was investigated as a non-invasive\ud technique for estimating percentage dry matter (%DM) of whole intact ‘Hass’ avocado fruit. Partial least square (PLS) regression models were developed from the diffuse reflectance spectra to predict %DM, taking into account effects of intra-seasonal variation and orchard conditions. The study found that combining three harvests (early, mid and late seasons) yielded a predictive model for %DM with Rv\ud 2=0.86, root mean square error of prediction (RMSEP)=1.18% for the DM in the range 18.2 – 35.0%. These results indicate the potential of FT-NIRS, in diffuse reflectance mode to non-invasively predict the %DM (and thus internal fruit quality) of whole ‘Hass’ avocado fruit

Prediction of hass avocado maturity via FT-NIRS

Most commercial quality classification systems for fruit and vegetables are based on external\ud features of the product, for example: shape, colour, size, weight and blemishes. For avocado fruit,\ud external colour is not a maturity characteristic. Also its smell is too weak, and appears later in its\ud maturity stage.1 Because maturity is a major component of avocado quality and palatability, it is\ud important to harvest mature fruit, so as to ensure that fruit will ripen properly and have acceptable\ud eating quality. Currently, commercial avocado maturity estimation is based on destructive\ud assessment of the percentage of Dry Matter (%DM), and sometimes percent oil, both of which\ud are highly correlated with maturity.2, 3 A rapid and non-destructive system that can accurately and\ud rapidly monitor internal quality attributes would allow the avocado industry to provide better,\ud more consistent eating quality fruit to the consumer, and thus improve industry competitiveness\ud and profitability.\ud The aim of this study was to assess the potential of FT-NIR diffuse reflectance spectroscopy as\ud an objective non-invasive method to determine Hass avocado maturity and thereby eating quality,\ud based on %DM, and its ability to predict over several growing seasons

Effects of seasonal variability on FT-NIR prediction of dry matter content for whole Hass avocado fruit

Fourier Transform (FT)-near infra-red spectroscopy (NIRS) was investigated as a non-invasive technique for estimating percentage (%) dry matter of whole intact 'Hass' avocado fruit. Partial least squares (PLS) calibration models were developed from the diffuse reflectance spectra to predict % dry matter, taking into account effects of seasonal variation. It is found that seasonal variability has a significant effect on model predictive performance for dry matter in avocados. The robustness of the calibration model, which in general limits the application for the technique, was found to increase across years (seasons) when more seasonal variability was included in the calibration set. The Rᵥ² and RMSEP for the single season prediction models predicting on an independent season ranged from 0.09 to 0.61 and 2.63 to 5.00, respectively, while for the two season models predicting on the third independent season, they ranged from 0.34 to 0.79 and 2.18 to 2.50, respectively. The bias for single season models predicting an independent season was as high as 4.429 but ≤ 1.417 for the two season combined models. The calibration model encompassing fruit from three consecutive years yielded predictive statistics of Rᵥ² = 0.89, RMSEP = 1.43% dry matter with a bias of -0.021 in the range 16.1-39.7% dry matter for the validation population encompassing independent fruit from the three consecutive years. Relevant spectral information for all calibration models was obtained primarily from oil, carbohydrate and water absorbance bands clustered in the 890-980, 1005-1050, 1330-1380 and 1700-1790 nm regions. These results indicate the potential of FT-NIRS, in diffuse reflectance mode, to non-invasively predict the % dry matter of whole 'Hass' avocado fruit and the importance of the development of a calibration model that incorporates seasonal variation