Developing Machine Vision in Tree-Fruit Applications-Fruit Count, Fruit Size and Branch Avoidance in Automated Harvesting.

Recent developments in affordable depth imaging hardware and the use of 2D Convolutional Neural Networks (CNN) in object detection and segmentation have accelerated the adoption of machine vision in a range of applications, with mainstream models often out-performing previous application-specific architectures. The need for the release of training and test datasets with any work reporting model development is emphasized to enable the re-evaluation of published work. An additional reporting need is the documentation of the performance of the re-training of a given model, quantifying the impact of stochastic processes in training. Three mango orchard applications were considered: the (i) fruit count, (ii) fruit size and (iii) branch avoidance in automated harvesting. All training and test datasets used in this work are available publicly. The mAP 'coefficient of variation' (Standard Deviation, SD, divided by mean of predictions using models of repeated trainings × 100) was approximately 0.2% for the fruit detection model and 1 and 2% for the fruit and branch segmentation models, respectively. A YOLOv8m model achieved a mAP50 of 99.3%, outperforming the previous benchmark, the purpose-designed 'MangoYOLO', for the application of the real-time detection of mango fruit on images of tree canopies using an edge computing device as a viable use case. YOLOv8 and v9 models outperformed the benchmark MaskR-CNN model in terms of their accuracy and inference time, achieving up to a 98.8% mAP50 on fruit predictions and 66.2% on branches in a leafy canopy. For fruit sizing, the accuracy of YOLOv8m-seg was like that achieved using Mask R-CNN, but the inference time was much shorter, again an enabler for the field adoption of this technology. A branch avoidance algorithm was proposed, where the implementation of this algorithm in real-time on an edge computing device was enabled by the short inference time of a YOLOv8-seg model for branches and fruit. This capability contributes to the development of automated fruit harvesting.

Fruit Sizing in Orchard: A Review from Caliper to Machine Vision with Deep Learning.

Forward estimates of harvest load require information on fruit size as well as number. The task of sizing fruit and vegetables has been automated in the packhouse, progressing from mechanical methods to machine vision over the last three decades. This shift is now occurring for size assessment of fruit on trees, i.e., in the orchard. This review focuses on: (i) allometric relationships between fruit weight and lineal dimensions; (ii) measurement of fruit lineal dimensions with traditional tools; (iii) measurement of fruit lineal dimensions with machine vision, with attention to the issues of depth measurement and recognition of occluded fruit; (iv) sampling strategies; and (v) forward prediction of fruit size (at harvest). Commercially available capability for in-orchard fruit sizing is summarized, and further developments of in-orchard fruit sizing by machine vision are anticipated.

The Use of Infrared Spectroscopy for the Quantification of Bioactive Compounds in Food: A Review.

Infrared spectroscopy (wavelengths ranging from 750-25,000 nm) offers a rapid means of assessing the chemical composition of a wide range of sample types, both for qualitative and quantitative analyses. Its use in the food industry has increased significantly over the past five decades and it is now an accepted analytical technique for the routine analysis of certain analytes. Furthermore, it is commonly used for routine screening and quality control purposes in numerous industry settings, albeit not typically for the analysis of bioactive compounds. Using the Scopus database, a systematic search of literature of the five years between 2016 and 2020 identified 45 studies using near-infrared and 17 studies using mid-infrared spectroscopy for the quantification of bioactive compounds in food products. The most common bioactive compounds assessed were polyphenols, anthocyanins, carotenoids and ascorbic acid. Numerous factors affect the accuracy of the developed model, including the analyte class and concentration, matrix type, instrument geometry, wavelength selection and spectral processing/pre-processing methods. Additionally, only a few studies were validated on independently sourced samples. Nevertheless, the results demonstrate some promise of infrared spectroscopy for the rapid estimation of a wide range of bioactive compounds in food matrices.

Phenolic Profiles of Ten Australian Faba Bean Varieties.

Although Australia is the largest exporter of faba bean globally, there is limited information available on the levels of bioactive compounds found in current commercial faba bean varieties grown in this country. This study profiled the phenolic acid and flavonoid composition of 10 Australian faba bean varieties, grown at two different locations. Phenolic profiling by HPLC-DAD revealed the most abundant flavonoid to be catechin, followed by rutin. For the phenolic acids, syringic acid was found in high concentrations (72.4-122.5 mg/kg), while protocatechuic, vanillic, p-hydroxybenzoic, chlorogenic, p-coumaric, and trans-ferulic acid were all found in low concentrations. The content of most individual phenolics varied significantly with the variety, while some effect of the growing location was also observed. This information could be used by food processors and plant breeders to maximise the potential health benefits of Australian-grown faba bean.

Do Steviol Glycosides Provide Ecological Fitness to Stevia rebaudiana through Impact on Dietary Preference of Plant Pests and Herbivores?

The impact of Stevia rebaudiana leaf on feeding preferences of an insect, a mite, and a mammal was investigated. The grasshopper, Valanga irregularis of the Acrididae family, avoided feeding on S. rebaudiana leaf, as evidenced by a decrease in animal weight. Increased mortality on S. rebaudiana feed was ascribed to feeding avoidance to the point of starvation. The extent of red spider mite ( Tetranychus urticae) damage was not proportional to leaf steviol glycoside (SG) concentration, a result ascribed to a feeding mechanism that avoids chlorenchyma cells that contain SGs. Guinea pigs ( Cavia porcellus) were presented with the choice between a control feed and feed amended to contain 5% sucrose or 0.02%, 4%, or 10% (dry weight) of S. rebaudiana leaf. Feed intake increased (39% above the control) for the diet involving high levels of SG amendment of feed (10% S. rebaudiana leaf). Encouragement of general mammalian herbivory may provide ecological fitness to S. rebaudiana if it is more tolerant of grazing pressure than other plants in its environment. Improvement in feed intake may have commercial implication for use of S. rebaudiana as an additive in stock feeds.

Mango Fruit Load Estimation Using a Video Based MangoYOLO-Kalman Filter-Hungarian Algorithm Method.

: Pre-harvest fruit yield estimation is useful to guide harvesting and marketing resourcing, but machine vision estimates based on a single view from each side of the tree ("dual-view") underestimates the fruit yield as fruit can be hidden from view. A method is proposed involving deep learning, Kalman filter, and Hungarian algorithm for on-tree mango fruit detection, tracking, and counting from 10 frame-per-second videos captured of trees from a platform moving along the inter row at 5 km/h. The deep learning based mango fruit detection algorithm, MangoYOLO, was used to detect fruit in each frame. The Hungarian algorithm was used to correlate fruit between neighbouring frames, with the improvement of enabling multiple-to-one assignment. The Kalman filter was used to predict the position of fruit in following frames, to avoid multiple counts of a single fruit that is obscured or otherwise not detected with a frame series. A "borrow" concept was added to the Kalman filter to predict fruit position when its precise prediction model was absent, by borrowing the horizontal and vertical speed from neighbouring fruit. By comparison with human count for a video with 110 frames and 192 (human count) fruit, the method produced 9.9% double counts and 7.3% missing count errors, resulting in around 2.6% over count. In another test, a video (of 1162 frames, with 42 images centred on the tree trunk) was acquired of both sides of a row of 21 trees, for which the harvest fruit count was 3286 (i.e., average of 156 fruit/tree). The trees had thick canopies, such that the proportion of fruit hidden from view from any given perspective was high. The proposed method recorded 2050 fruit (62% of harvest) with a bias corrected Root Mean Square Error (RMSE) = 18.0 fruit/tree while the dual-view image method (also using MangoYOLO) recorded 1322 fruit (40%) with a bias corrected RMSE = 21.7 fruit/tree. The video tracking system is recommended over the dual-view imaging system for mango orchard fruit count.

Do Steviol Glycosides Act Either as a Carbon Storage Pool or in Osmoregulation within Leaves of Stevia rebaudiana?

Steviol glycosides (SG) (with stevioside and rebaudioside A predominating) are present in wild-type Stevia rebaudiana, at approximately 10% of dry weight (dw), prompting a consideration of the autoecological role played by these compounds in terms of energy (C) storage and/or osmoregulation. The leaf starch pool was observed to change diurnally with respect to the light cycle (from 3.29% to 0.73% of leaf dw between dusk and dawn) and also to increase under constant light treatment (from 1.53% to 6.25% of leaf dw), while SG pools were relatively constant (around 6% w/dw). A similar trend was observed during exposure to elevated CO2 (800 ppm), with starch increasing (from 10% to 15% of leaf dw), while SG pool size was constant (around 12% w/dw). For plants subject to increasing water stress over several days, an increase in leaf sap osmolality was observed in the leaves of a severely stressed group (from -1 MPa to -3 MPa, after 2 days of treatment), while stevioside and rebaudioside A leaf concentration was relatively constant (around 16% w/dw). These results are not consistent with a role for SG as either a short-term C store or osmoregulator in S. rebaudiana.

In Field Fruit Sizing Using A Smart Phone Application.

In field (on tree) fruit sizing has value in assessing crop health and for yield estimation. As the mobile phone is a sensor and communication rich device carried by almost all farm staff, an Android application ("FruitSize") was developed for measurement of fruit size in field using the phone camera, with a typical assessment rate of 240 fruit per hour achieved. The application was based on imaging of fruit against a backboard with a scale using a mobile phone, with operational limits set on camera to object plane angle and camera to object distance. Image processing and object segmentation techniques available in the OpenCV library were used to segment the fruit from background in images to obtain fruit sizes. Phone camera parameters were accessed to allow calculation of fruit size, with camera to fruit perimeter distance obtained from fruit allometric relationships between fruit thickness and width. Phone geolocation data was also accessed, allowing for mapping fruits of data. Under controlled lighting, RMSEs of 3.4, 3.8, 2.4, and 2.0 mm were achieved in estimation of avocado, mandarin, navel orange, and apple fruit diameter, respectively. For mango fruit, RMSEs of 5.3 and 3.7 mm were achieved on length and width, benchmarked to manual caliper measurements, under controlled lighting, and RMSEs of 5.5 and 4.6 mm were obtained in-field under ambient lighting.

Manure from biochar, bentonite and zeolite feed supplemented poultry: Moisture retention and granulation properties.

Feeding treatments were imposed in two feeding trials involving Cobb broiler and Bond Brown layer birds. Three feed additives (biochar, bentonite and zeolite) were supplied at four rates (0, 1, 2 and 4% w/w) in feed, as previously considered in the context of animal production, was considered in the context of Excreta chemical and water retention properties and granulation characteristics of decomposed excreta (manure) were characterised. At field capacity (- 0.01 MPa), manure produced from control and 4% bentonite diets contained significantly (p = 0.001) more water (at 1.93 and 2.44% v/v water, respectively) than zeolite and biochar treatments. Manure mesoporosity was significantly (p = 0.015) higher in 2 and 4% bentonite treatments than other feed additives. Fresh excreta from layer birds on the control diet contained 6% w/dw N and 35% C, which was decreased to 2.6% N and 28% C after decomposition, with C:N ratio changing from 5.9 to 12.1. Ammonia loss was higher from biochar and zeolite manures than control or bentonite, associated with higher pH in the biochar and zeolite manures. More N was unaccounted from bentonite manure than other treatments, presumably lost as N2O or N2, a result linked to its higher moisture content and its enhanced rate of denitrification. The highest proportion of granules in the size class desired for fertilizer spreading was achieved using decomposed manure from the 1 and 2% w/w biochar treatments of the broiler trial, and 1 and 2% zeolite and 4% biochar treatments of the layer trial. Thus the feed amendments improved poultry manure in specific ways.

Advances in techniques for assessment of microalgal lipids.

Microalgae are a varied group of organisms with considerable commercial potential as sources of various biochemicals, storage molecules and metabolites such as lipids, sugars, amino acids, pigments and toxins. Algal lipids can be processed to bio-oils and biodiesel. The conventional method to estimate algal lipids is based on extraction using solvents and quantification by gravimetry or chromatography. Such methods are time consuming, use hazardous chemicals and are labor intensive. For rapid screening of prospective algae or for management decisions (e.g. decision on timing of harvest), a rapid, high throughput, reliable, accurate, cost effective and preferably nondestructive analytical technique is desirable. This manuscript reviews the application of fluorescent lipid soluble dyes (Nile Red and BODIPY 505/515), nuclear magnetic resonance (NMR), Raman, Fourier transform infrared (FTIR) and near infrared (NIR) spectroscopy for the assessment of lipids in microalgae.

On-Tree Mango Fruit Size Estimation Using RGB-D Images.

In-field mango fruit sizing is useful for estimation of fruit maturation and size distribution, informing the decision to harvest, harvest resourcing (e.g., tray insert sizes), and marketing. In-field machine vision imaging has been used for fruit count, but assessment of fruit size from images also requires estimation of camera-to-fruit distance. Low cost examples of three technologies for assessment of camera to fruit distance were assessed: a RGB-D (depth) camera, a stereo vision camera and a Time of Flight (ToF) laser rangefinder. The RGB-D camera was recommended on cost and performance, although it functioned poorly in direct sunlight. The RGB-D camera was calibrated, and depth information matched to the RGB image. To detect fruit, a cascade detection with histogram of oriented gradients (HOG) feature was used, then Otsu's method, followed by color thresholding was applied in the CIE L*a*b* color space to remove background objects (leaves, branches etc.). A one-dimensional (1D) filter was developed to remove the fruit pedicles, and an ellipse fitting method employed to identify well-separated fruit. Finally, fruit lineal dimensions were calculated using the RGB-D depth information, fruit image size and the thin lens formula. A Root Mean Square Error (RMSE) = 4.9 and 4.3 mm was achieved for estimated fruit length and width, respectively, relative to manual measurement, for which repeated human measures were characterized by a standard deviation of 1.2 mm. In conclusion, the RGB-D method for rapid in-field mango fruit size estimation is practical in terms of cost and ease of use, but cannot be used in direct intense sunshine. We believe this work represents the first practical implementation of machine vision fruit sizing in field, with practicality gauged in terms of cost and simplicity of operation.

Microplastics in water: Occurrence, fate and removal.

A global study on tap water samples has found that up to 83% of these contained microplastic fibres. These findings raise concerns about their potential health risks. Ingested microplastic particles have already been associated with harmful effects in animals, which raise concerns about similar outcomes in humans. Microplastics are ubiquitous in the environment, commonly found disposed in landfills and waste sites. Within indoor environments, the common sources are synthetic textiles, plastic bottles, and packaging. From the various point sources, they are globally distributed through air and water and can enter humans through various pathways. The finding of microplastics in fresh snow in the Antarctic highlights just how widely they are dispersed. The behaviour and health risks from microplastic particles are strongly influenced by their physicochemical properties, which is why their surfaces are important. Surface interactions are also important in pollutant transport via adsorption onto the microplastic particles. Our review covers the latest findings in microplastics research including the latest statistics in their abundance, their occurrence and fate in the environment, the methods of reducing microplastics exposure and their removal. We conclude by proposing future research directions into more effective remediation methods including new technologies and sustainable green remediation methods that need to be explored to achieve success in microplastics removal from waters at large scale.

Bioassay-Guided Fractionation of Pittosporum angustifolium and Terminalia ferdinandiana with Liquid Chromatography Mass Spectroscopy and Gas Chromatography Mass Spectroscopy Exploratory Study.

Bioprospecting native Australian plants offers the potential discovery of latent and novel bioactive compounds. The promising cytotoxic and antibacterial activity of methanolic extracts of Pittosporum angustifolium and Terminalia ferdinandiana led to further fractionation and isolation using our laboratory's bioassay-guided fractionation protocol. Hence, the aim of this study was to further evaluate the bioactivity of the fractions and subfractions and characterize bioactive compounds using liquid chromatography mass spectroscopy (LC-MS/MS) and gas chromatography MS (GC-MS). Compounds tentatively identified in P. angustifolium Fraction 1 using LC-ESI-QTOF-MS/MS were chlorogenic acid and/or neochlorogenic acid, bergapten, berberine, 8'-epitanegool and rosmarinic acid. GC-MS analysis data showed the presence of around 100 compounds, mainly comprising carboxylic acids, sugars, sugar alcohols, amino acids and monoalkylglycerols. Furthermore, the fractions obtained from T. ferdinandiana flesh extracts showed no cytotoxicity, except against HT29 cell lines, and only Fraction 2 exhibited some antibacterial activity. The reduced bioactivity observed in the T. ferdinandiana fractions could be attributed to the potential loss of synergy as compounds become separated within the fractions. As a result, the further fractionation and separation of compounds in these samples was not pursued. However, additional dose-dependent studies are warranted to validate the bioactivity of T. ferdinandiana flesh fractions, particularly since this is an understudied species. Moreover, LC-MS/GC-MS studies confirm the presence of bioactive compounds in P. angustifolium Fraction 1/subfractions, which helps to explain the significant acute anticancer activity of this plant. The screening process designed in this study has the potential to pave the way for developing scientifically validated phytochemical/bioactivity information on ethnomedicinal plants, thereby facilitating further bioprospecting efforts and supporting the discovery of novel drugs in modern medicine.

Maximising environmental pressure-response relationship signals from diatom-based metabarcoding in rivers.

DNA metabarcoding has been performed on a large number of river phytobenthos samples collected from the UK, using rbcL primers optimised for diatoms. Within this dataset the composition of non-diatom sequence reads was studied and the effect of including these in models for evaluating the nutrient gradient was assessed. Whilst many non-diatom taxonomic groups were detected, few contained the full diversity expected in riverine environments. This may be due to the performance of the current primers in characterising the wider phytobenthic community and influenced by the sampling method employed, as both were developed specifically for diatoms. Nevertheless, the study identified considerable diversity in some groups, e.g. Eustigmatophyceae and a wider distribution than previously thought for freshwater Phaeophyceae. These results offer a strong case for the benefits of metabarcoding for expanding knowledge of aquatic biodiversity in the UK and elsewhere. Many of the ASVs associated with non-diatoms showed significant pressure responses; however, models that included non-diatoms had similar predictive strength to those based on diatoms alone. Whilst limitations of the primers for assessing non-diatoms may play a role in explaining these results, the diatoms provide a strong signal along the nutrient gradient and other algae, therefore, add little unique information. We recommend that future developments should use ASVs to calculate metrics, with links to reference databases made as a final step to generate lists of taxa to support interpretation. Any further exploration of the potential of non-diatoms would benefit from access to a well-curated reference database, similar to diat.barcode. Such a database does not yet exist, and we caution against the indiscriminate use of NCBI GenBank as a taxonomic resource as many rbcL sequences deposited have not been curated.

An integrated spatio-temporal view of riverine biodiversity using environmental DNA metabarcoding.

Anthropogenically forced changes in global freshwater biodiversity demand more efficient monitoring approaches. Consequently, environmental DNA (eDNA) analysis is enabling ecosystem-scale biodiversity assessment, yet the appropriate spatio-temporal resolution of robust biodiversity assessment remains ambiguous. Here, using intensive, spatio-temporal eDNA sampling across space (five rivers in Europe and North America, with an upper range of 20-35 km between samples), time (19 timepoints between 2017 and 2018) and environmental conditions (river flow, pH, conductivity, temperature and rainfall), we characterise the resolution at which information on diversity across the animal kingdom can be gathered from rivers using eDNA. In space, beta diversity was mainly dictated by turnover, on a scale of tens of kilometres, highlighting that diversity measures are not confounded by eDNA from upstream. Fish communities showed nested assemblages along some rivers, coinciding with habitat use. Across time, seasonal life history events, including salmon and eel migration, were detected. Finally, effects of environmental conditions were taxon-specific, reflecting habitat filtering of communities rather than effects on DNA molecules. We conclude that riverine eDNA metabarcoding can measure biodiversity at spatio-temporal scales relevant to species and community ecology, demonstrating its utility in delivering insights into river community ecology during a time of environmental change.

BotanicX-AI: Identification of Tomato Leaf Diseases Using an Explanation-Driven Deep-Learning Model.

Early and accurate tomato disease detection using easily available leaf photos is essential for farmers and stakeholders as it help reduce yield loss due to possible disease epidemics. This paper aims to visually identify nine different infectious diseases (bacterial spot, early blight, Septoria leaf spot, late blight, leaf mold, two-spotted spider mite, mosaic virus, target spot, and yellow leaf curl virus) in tomato leaves in addition to healthy leaves. We implemented EfficientNetB5 with a tomato leaf disease (TLD) dataset without any segmentation, and the model achieved an average training accuracy of 99.84% ± 0.10%, average validation accuracy of 98.28% ± 0.20%, and average test accuracy of 99.07% ± 0.38% over 10 cross folds.The use of gradient-weighted class activation mapping (GradCAM) and local interpretable model-agnostic explanations are proposed to provide model interpretability, which is essential to predictive performance, helpful in building trust, and required for integration into agricultural practice.

Bioassay Guided Fractionation Protocol for Determining Novel Active Compounds in Selected Australian Flora.

A large variety of unique and distinct flora of Australia have developed exceptional survival methods and phytochemicals and hence may provide a significant avenue for new drug discovery. This study proposes a bioassay guided fractionation protocol that maybe robust and efficient in screening plants with potential bioactive properties and isolating lead novel compounds. Hence, five native Australian plants were selected for this screening process, namely Pittosporum angustifolium (Gumbi gumbi), Terminalia ferdinandiana (Kakadu plum, seeds (KPS), and flesh (KPF)), Cupaniopsis anacardioides (Tuckeroo, seeds (TKS) and flesh (TKF)), Podocarpus elatus (Illawarra plum, seeds (IPS) and flesh (IPF)) and Pleiogynium timoriense (Burdekin plum, seeds (BPS) and flesh (BPF)). The methanolic extracts of the plants samples were analysed for Total phenolic content (TPC) and antioxidant capacity measure by FRAP. The highest values were found in the KPF which were 12,442 ± 1355 mg GAE/ 100 g TPC and 16,670 ± 2275 mg TXE/100 g antioxidant capacity. Extracts of GGL was deemed to be most potent with complete cell inhibition in HeLa and HT29, and about 95% inhibition in HuH7 cells. Comparative activity was also seen for KPS extract, where more than 80% cell inhibition occurred in all tested cell lines. Dose-dependent studies showed higher SI values (0.72-1.02) in KPS extracts than GGL (0.5-0.73). Microbial assays of the crude extracts were also performed against five bacterial strains commonly associated with causing food poisoning diseases were selected (Gram positive-Staphylococcus aureus and Gram negative-Escherichia coli, Salmonella typhi and Pseudomonas aeruginosa bacteria). KPF extracts were effective in suppressing microbial growth of all tested bacterial strains except for P. aeruginosa, while TKS and TKF were only slightly effective against S. aureus. Due to the potential of the GGL crude extract to completely inhibit the cells compared to KPS, it was further fractionated and tested against the cell lines. HPLC phenolic profiling of the crude extracts were performed, and numerous peak overlaps were evident in the fruit extracts. The KPF extracts demonstrated the strongest peaks which was coherent with the fact that it had the highest TPC and antioxidant capacity values. A high occurrence of t-ferulic acid in the GGL extracts was found which may explain the cytotoxic activity of GGL extracts. Peaks in KPS and KPF extracts were tentatively identified as gallic acid, protocatechuic acid, 4-hydroxybenzoic acid and syringic acid and possibly ellagic acid. HPLC time-based fractionation of the GGL extract (F1-F5) was performed and Dose dependent cytotoxic effects were determined. It was construed that F1, having the highest SI value for HeLa, HT29 and HuH7 (1.60, 1.41 and 1.67, respectively) would be promising for further fractionation and isolation process.

Antioxidative and therapeutic potential of selected Australian plants: A review.

ETHNOPHARMACOLOGICAL RELEVANCE: Numerous common pharmaceuticals, including anti-cancer, antiviral and antidiabetic drugs, are derived from traditional plant-derived medicines. With approximately 25,000 species of flora occurring in Australia that are adapted to the harsh environment, there is a plethora of novel compounds awaiting research in the context of their medicinal properties. Anecdotal accounts of plant-based medicines used by the Australian Aboriginal and Torres Strait Islander peoples clearly illustrates high therapeutic activity. AIM: This review aims to demonstrate the medicinal potentials of selected native Australian plants based on scientific data. Furthermore, it is anticipated that work presented here will contribute towards enhancing our knowledge of native plants from Australia, particularly in the prevention and potential treatment of disease types such as cancer, microbial and viral infections, and diabetes. This is not meant to be a comprehensive study, rather it is meant as an overview to stimulate future research in this field. METHODS: The EBSCOhost platform which included PubMed, SciFinder, Web of Knowledge, Scopus, and ScienceDirect databases were searched for papers using the keywords: medicinal plants, antioxidative, antimicrobial, antibacterial, anticancer, anti-tumor, antiviral or antidiabetic, as well as Australian, native, traditional and plants. The selection criteria for including studies were restricted to articles on plants used in traditional remedies which showed antioxidative potential and therapeutic properties such as anticancer, antimicrobial, antiviral and antidiabetic activity. RESULTS: Some plants identified in this review which showed high Total Phenolic Content (TPC) and antioxidative capacity, and hence prominent bioactivity, included Tasmannia lanceolata (Poir.) A.C. Sm., Terminalia ferdinandiana Exell, Eucalyptus species, Syzygium species, Backhousia citriodora F.Muell., Petalostigma species, Acacia species, Melaleuca alternifolia (Maiden & Betche) Cheel, Eremophila species, Prostanthera rotundifolia R.Br., Scaevola spinescens R. Br. and Pittosporum angustifolium Lodd. The majority of studies found polar compounds such as caffeic acid, coumaric acid, chlorogenic acid, quercetin, anthocyanins, hesperidin, kaempferol, catechin, ellagic acid and saponins to be the active components responsible for the therapeutic effects. Additionally, mid to non-polar volatile organic compounds such as meroterpenes (serrulatanes and nerol cinnamates), monoterpenes (1,8-cineole and myodesert-1-ene), sesquiterpenes, diterpenes and triterpenes, that are known only in Australian plants, have also shown therapeutic properties related to traditional medicine. CONCLUSION: Australian plants express a diverse range of previously undescribed metabolites that have not been given full in vitro assessment for human health potential. This review has included a limited number of plant species of ethnomedicinal significance; hundreds of plants remain in need of exploration and detailed study. Future more elaborate studies are therefore required to screen out and purify lead bioactive compounds against numerous other disease types. This will not only improve our knowledge on the phytochemistry of Australian native flora, but also provide a platform to understand their health-promoting and bioactive effects for pharmaceutical interventions, nutraceuticals, cosmetics, and as functional foods. Finally, plant-derived natural compounds (phytochemicals), as well as plant-based traditional remedies, are significant sources for latent and novel drugs against diseases. Extensive investigation of native medicinal plants may well hold the key to novel drug discoveries.

Natural product-derived phytochemicals as potential agents against coronaviruses: A review.

Coronaviruses are responsible for a growing economic, social and mortality burden, as the causative agent of diseases such as severe acute respiratory syndrome (SARS), Middle East respiratory syndrome (MERS), avian infectious bronchitis virus (IBV) and COVID-19. However, there is a lack of effective antiviral agents for many coronavirus strains. Naturally existing compounds provide a wealth of chemical diversity, including antiviral activity, and thus may have utility as therapeutic agents against coronaviral infections. The PubMed database was searched for papers including the keywords coronavirus, SARS or MERS, as well as traditional medicine, herbal, remedy or plants, with 55 primary research articles identified. The overwhelming majority of publications focussed on polar compounds. Compounds that show promise for the inhibition of coronavirus in humans include scutellarein, silvestrol, tryptanthrin, saikosaponin B2, quercetin, myricetin, caffeic acid, psoralidin, isobavachalcone, and lectins such as griffithsin. Other compounds such as lycorine may be suitable if a therapeutic level of antiviral activity can be achieved without exceeding toxic plasma concentrations. It was noted that the most promising small molecules identified as coronavirus inhibitors contained a conjugated fused ring structure with the majority being classified as being polyphenols.

An assessment of quality costs within electronic adverse incident reporting and recording systems: a case study.

PURPOSE: There are three main objectives of the research presented in this paper: to examine the challenges of using an electronic adverse incident recording and reporting system; to assess the method of using a prevention appraisal and failure model; and to identify the benefits of using quality costs in conjunction with incident reporting systems. DESIGN/METHODOLOGY/APPROACH: Action diary, documentation and triangulation are used to obtain an understanding of the challenges and critical success factors in using quality costing within an adverse incident recording and reporting system. FINDINGS: The paper provides healthcare professionals with the critical success factors for developing quality costing into an electronic adverse incident recording and reporting system. This approach would provide clinicians, managers and directors with information on patient safety issues following the effective use of data from an electronic adverse incident reporting and recording system. ORIGINALITY/VALUE: This paper makes an attempt of using a prevention, appraisal and failure model (PAF) within a quality-costing framework in relation to improving patient safety within an electronic adverse incident reporting and recording system.