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Methyl jasmonate (MJ) has potential to regulate fruit ripening and quality. ‘Yoho’ and ‘Jiro’ persimmons were sprayed with MJ (0, 2, 4, and 6 mM), four weeks before anticipated harvest to evaluate its effects on fruit colour and bioactive compounds. Preharvest MJ application significantly improved fruit colour with increased a*, b*, chroma, and colour index. The MJ 6 mM application had significantly enhanced soluble solids content (SSC), reduced total chlorophyll content in peel and pulp, and soluble and total tannins in persimmons. MJ treatments exhibited higher contents of total phenolics, flavonoids, carotenoids, and antioxidant activities. Additionally, MJ treatments enhanced the activities of shikimate dehydrogenase (SKDH), phenylalanine ammonia-lyase (PAL), catalase (CAT), superoxide dismutase (SOD), peroxidase (POD) and lipoxygenase (LOX) enzymes. Overall, pre-harvest MJ application at 6 mM four weeks before anticipated harvest could be useful for advancing colour and improving bioactive compounds in ‘Yoho’ and ‘Jiro’ persimmons.

Raspberries are highly perishable and have a short storage life. To extend its storage life, we evaluated the impact of preharvest melatonin (MEL) application (0, 50, 100, 200 mol L−1), three days before harvest, on the activities of oxidative and antioxidative enzymes and quality attributes in ‘Esperanza’ raspberries up to 10 d cold storage. The 200 mol L−1 MEL-treated raspberries exhibited a significant reduction in disease incidence while maintaining higher marketable fruit and activities of superoxide dismutase, glutathione reductase, dehydroascorbate reductase, monodehydroascorbate reductase, ascorbate peroxidase and catalase as compared to control. Additionally, it reduced activities of polyphenol oxidase, peroxidase and lipoxygenase enzymes and increased flavonoids and ascorbic acid levels. However, preharvest spray of 100 mol L−1 MEL mitigated fruit weight loss and maintained higher anthocyanins, and glutathione than control. In conclusion, MEL application (100–200 mol L−1), three days before harvest, supressed oxidative stress by maintaining higher activities of antioxidant enzymes in raspberries during 10 d of cold storage.

Chilling injury (CI) causes significant losses in fruits and vegetables during cold storage. CI symptoms exhibited as browning, off-flavour and sunken spots, reduced juice content, uneven ripening and softening in fresh horticultural produce. Application of melatonin (MT) effectively mitigates CI in cold-stored fruits and vegetables. This comprehensive review focuses at discussing symptoms, the mechanism of CI, regulation of melatonin-mediated chilling tolerance, and meta-analysis of CI reduction in horticultural produce. Melatonin mitigates CI, maintains quality of cold-stored horticultural produce by upregulating early hydrogen peroxide signalling, activities of antioxidant enzymes after inhibition of reactive oxygen species (ROS) accumulation, mitochondrial dysfunction, and membrane leakage.

Blackberries and raspberries, commonly known as Rubus berries, are commercially grown worldwide across different climates. Rubus berries contain wide array of phytochemicals, vitamins, dietary fibers, minerals, and unsaturated fatty acids. Nevertheless, these berries have short storage life which is the major constraint in their supply chains leading to higher postharvest losses. Inappropriate harvest handling, physical bruising, insect pests, and postharvest diseases lower the acceptability of fruit among consumers and other supply chain stakeholders. Additionally, the susceptibility to microbial decay, fruit softening, higher ethylene production, respiratory activity, and increased oxidation of anthocyanins, phenolics, and flavonoids considerably affects the marketability of Rubus berries at domestic and international markets. To date, several postharvest strategies such as cold storage, precooling, modified and controlled atmospheres, anti-ripening chemicals, edible coatings, biological agents, and nonchemical alternatives (heat treatment, ultrasound, irradiations, ozone) have been reported to prolong storage life, ensure food safety, and maintain the nutritional quality of Rubus berries. This review briefly encompasses multiple aspects including harvest maturity indices, regulation of fruit ripening, pre and postharvest factors affecting fruit quality, and an update on postharvest quality preservation by employing postharvest technologies to extend the storage life and maintaining the bioactive compounds in Rubus berries which are lacking in the literature. Accordingly, this review provides valuable information to the industry stakeholders and scientists offering relevant solutions, limitations in the application of certain technologies at commercial scale, highlighting research gaps, and paving the way forward for future investigations.

Oxalic acid (OA) is a unique organic acid that commonly occurs in plants with distinct functions in modulating metabolic processes. To date, the role of OA has primarily been studied in the deactivation of copper-containing preservatives, detoxification of aluminium toxicity and remediation of organic pollutants. During the last two decades, OA has been considered as an antioxidant compound with focus on its potential to enhance crop yield, improve fruit quality, boost nutritional profile, and delay postharvest senescence in fruit and vegetables. It has been established that pre- and postharvest OA application delays ripening and senescence by down-regulating physiological processes such as water loss, ethylene production and respiration. OA treatment controlled adverse storage effects including chilling injury, enzymatic browning, as well as flesh softening by lowering oxidative stress. OA application has also been found to reduce decay in fresh fruit and vegetables by inducing systemic resistance against pathogens, decontamination from surficial microbial load and pesticide residues. Additionally, OA treatments have shown to effectively improve enzymatic and non-enzymatic antioxidants and maintain attributes for eating quality. Effectively, OA application has been deemed to be a potentially food-safe natural and suitable alternative to synthetic chemicals for up-regulating bioactive compounds in harvested fruit and vegetables and extending storability within the postharvest supply chain. This extensive review covers aspects of OA including its: history, chemistry, biosynthesis in plants, quantification in fruit and vegetables, crosstalk with ripening physiology, past attempts and recent advancements in storage life extension, safety as well as quality management of fruit and vegetables.

Objective To investigate the Australian general public's perception of appropriate medical scenarios that warrants a call to an emergency ambulance. Methods An online survey asked participants to identify the likely medical treatment pathway they would take for 17 hypothetical medical scenarios. The number and type of non-emergency scenarios (n = 8) participants incorrectly suggested were appropriate to place a call for an emergency ambulance were calculated. Participants included Australian residents (aged >18 years) who had never worked as an Australian registered medical doctor, nurse or paramedic. Results From a sample of 5264 participants, 40% suggested calling an emergency ambulance for a woman in routine labour was appropriate. Other medical scenarios which were most suggested by participants to warrant an emergency ambulance call was ‘Lego in ear canal’ (11%), ‘Older person bruising’ (8%) and ‘Flu’ (7%). Women, people aged 56+ years, those without a university qualification, with lower household income and with lower emotional wellbeing were more likely to suggest calling an emergency ambulance was appropriate for non-emergency scenarios. Conclusions Although emergency healthcare system (EHS) capacity not increasing at the same rate as demand is the biggest contributor to EHS burden, non-urgent medical situations for which other low-acuity healthcare pathways may be appropriate does play a small role in adding to the overburdening of the EHS. This present study outlines a series of complaints and demographic characteristics that would benefit from targeted educational interventions that may aid in alleviating ambulance service attendances to low-acuity callouts.

Digital camera monitoring has revolutionised survey designs in many fields, as an important source of information. The extended sampling coverage offered by this monitoring scheme makes it preferable compared to other traditional methods of survey. However, data obtained from digital camera monitoring are often highly variable, and characterized by sparse periods of zero counts, interspersed with missing observations due to outages. In practice, missing data of relatively shorter duration are mostly observed and are often imputed using interpolation techniques, ignoring long-term trends leading to inherent estimation biases. In this study, we investigated time series forecasting methods that adequately handle intermittency and produced plausible estimates for imputation and forecasting purposes. The study utilised a yearlong digital camera monitoring data set of hourly counts of powerboat launches at three boat ramps in Western Australia. Several time series forecasting methods were evaluated and the accuracies of their point estimates of forecasts for various lead times in hours of up to one week were assessed using cross-validation techniques. Intermittent demand forecasting techniques, including Croston's method and Syntetos-Boylan Approximation (SBA) models, and count data forecasting methods including autoregressive conditional Poisson (ACP) models, integer-valued moving average (INMA) models, and integer-valued autoregressive (INAR) models were evaluated. ACP and INAR models performed better than intermittent demand forecasting techniques for short forecast horizons and provided some evidence of their sufficiency in predicting the dynamics in recreational boating activities. This result established that, in as much as intermittency may be a key feature for a given dataset, it should not override the systemic characteristics of data in the application of forecasting techniques. Our results provide plausible estimates for short-term missing data and forecasts fo

© 2021 Informa UK Limited, trading as Taylor & Francis Group. Living with a long-term medical condition is associated with heightened risk for mental health and psychosocial difficulties, but further research is required on this risk for children and adolescents with a rare disease in the educational setting. The aim of this study is to describe parents’ perceptions of the psychosocial impact of rare diseases on their school-aged children in Western Australia. A cross-sectional survey of 41 parents of school-aged children and adolescents diagnosed with a rare disease completed an online questionnaire. Questions related to their perceptions of health-related stigma, bullying, social competencies and mental health difficulties faced by their child. Results showed that stigmatisation was experienced by 75.6% of participants, and almost half (46.4%) reported their child was bullied. In this sample, parents reported high sensory (vision and hearing) abilities, but low to moderate self-care competence in relation to social activities and peer relations. Almost half of the respondents (43.9%) reported mental health difficulties among their children. Children and adolescents with a rare disease have unique psychological and social issues. These findings highlight the need for greater efforts to meet the diverse psychosocial, physical and emotional needs of children diagnosed with a rare disease who attend mainstream schools in Western Australia.

© 2020 The Authors. Meteorological Applications published by John Wiley & Sons Ltd on behalf of the Royal Meteorological Society. Analysis of high-resolution data offers greater opportunity to understand the nature of data variability, behaviours, trends and to detect small changes. Climate studies often require complete time series data which, in the presence of missing data, means imputation must be undertaken. Research on the imputation of high-resolution temporal climate time series data is still at an early phase. In this study, multiple approaches to the imputation of missing values were evaluated, including a structural time series model with Kalman smoothing, an autoregressive integrated moving average (ARIMA) model with Kalman smoothing and multiple linear regression. The methods were applied to complete subsets of data from 12 month time series of hourly temperature, humidity and wind speed data from four locations along the coast of Western Australia. Assuming that observations were missing at random, artificial gaps of missing observations were studied using a five-fold cross-validation methodology with the proportion of missing data set to 10%. The techniques were compared using the pooled mean absolute error, root mean square error and symmetric mean absolute percentage error. The multiple linear regression model was generally the best model based on the pooled performance indicators, followed by the ARIMA with Kalman smoothing. However, the low error values obtained from each of the approaches suggested that the models competed closely and imputed highly plausible values. To some extent, the performance of the models varied among locations. It can be concluded that the modelling approaches studied have demonstrated suitability in imputing missing data in hourly temperature, humidity and wind speed data and are therefore recommended for application in other fields where high-resolution data with missing values are common.

Afrifa‐Yamoah, E., Mueller, U. A., Taylor, S. M., & Fisher, A. J. (2020). Missing data imputation of high‐resolution temporal climate time series data. Meteorological Applications, 27(1), e1873. https://doi.org/10.1002/met.1873

Afrifa-Yamoah, E., & Mueller, U. A. (2022). Modeling digital camera monitoring count data with intermittent zeros for short-term prediction. Heliyon, e08774 https://doi.org/10.1016/j.heliyon.2022.e08774

Afrifa-Yamoah, E., & Mueller, U. A. (2022). Modeling digital camera monitoring count data with intermittent zeros for short-term prediction. Heliyon, e08774 https://doi.org/10.1016/j.heliyon.2022.e08774