Search

Efficient and affordable plant phenotyping methods are an essential response to global climatic pressures. This study demonstrates the continued potential of consumer-grade photography to capture plant phenotypic traits in turfgrass and derive new calculations. Yet the effects of image corrections on individual calculations are often unreported. Turfgrass lysimeters were photographed over 8 weeks using a custom lightbox and consumer-grade camera. Subsequent imagery was analyzed for area of cover, color metrics, and sensitivity to image corrections. Findings were compared to active spectral reflectance data and previously reported measurements of visual quality, productivity, and water use. Results confirm that Red-Green-Blue imagery effectively measures plant treatment effects. Notable correlations were observed for corrected imagery, including between yellow fractional area with human visual quality ratings (r = -0.89), dark green color index with clipping productivity (r = 0.61), and an index combination term with water use (r = -0.60). The calculation of green fractional area correlated with Normalized Difference Vegetation Index (r = 0.91), and its RED reflectance spectra (r = -0.87). A new chromatic ratio correlated with Normalized Difference Red-Edge index (r = 0.90) and its Red-Edge reflectance spectra (r = -0.74), while a new calculation correlated strongest to Near-Infrared (r = 0.90). Additionally, the combined index term significantly differentiated between the treatment effects of date, mowing height, deficit irrigation, and their interactions ( p < 0.001). Sensitivity and statistical analyses of typical image file formats and corrections that included JPEG, TIFF, geometric lens distortion correction, and color correction were conducted. Findings highlight the need for more standardization in image corrections and to determine the biological relevance of the new image data calculations.

Aims: Exercise interventions positively affect numerous cardiometabolic risk factors. To better evaluate the health effects of exercise training, it may be more appropriate to evaluate risk factors together. The Metabolic Syndrome Severity Score (MetSSS) is a composite score representing cardiometabolic risk. Purpose: To evaluate the relationships between physical activity, neuromuscular fitness, exercise capacity, and the MetSSS in a heterogenous sample of people with complex chronic disease. Material and Methods: Fifty-three people with kidney or liver disease and at least one feature of the metabolic syndrome (MetS) were included. Pearson correlations were conducted between physical activity, neuromuscular fitness, exercise capacity, and the MetSSS. Linear regressions were performed for multi-level categorical variables. Independent variables with an association with MetSSS ( P ≤ 0.2) were included in a multiple regression analysis. Results: The 6-minute walk test (6MWT) distance was inversely and independently associated with MetSSS [standardized beta coefficient (β) = -0.31, P = 0.04]. No relationship was found between MetSSS and physical activity or neuromuscular fitness. Mean 6MWT in the highest tertile was 550 m (range: 505-620 m) and 346 m (range: 233-408 m) in the lowest. The analysis showed a medium-large between-group effect for the difference in MetSSS for the lowest and highest tertile of 6MWT [Eta squared (η 2 ) = 0.16, P = 0.01]. Conclusions: Exercise capacity was inversely and independently associated with MetSSS in people with complex chronic disease. Clinical trials with exercise interventions are needed to further investigate if improvements in exercise capacity result in clinically significant changes in the MetSSS.

Background: Diet and exercise are important components of treatment for complex chronic conditions, however access to allied health support is limited. When available, support is often siloed and fragmented. Digital health incorporating patient choice may help to align health care services with preferences and goals. This study evaluated the implementation of a ubiquitously accessible patient-centred digital health diet and exercise service., Methods: U-DECIDE was a single-centre, 26-week randomised controlled trial set in kidney and liver disease clinics in a tertiary hospital in Brisbane, Australia. Participants were adults with a complex chronic condition referred for dietetic consultation with at least one feature of the metabolic syndrome. All participants received a dietary consultation, an activity monitor and usual care. Intervention participants were offered one text message per week and access to additional digital health options (increased text message frequency, nutrition app, exercise app, group-based diet and/or exercise video consultations). The primary outcome of feasibility was determined by safety (study-related serious adverse events: SRSAEs), recruitment (≥ 50% eligible patients), retention (≥ 70%), exposure uptake (≥ 75% of intervention group had greater access to health professional contact than comparator) and video consultation adherence (≥ 80% attendance). Secondary outcomes included process evaluation metrics and clinical outcomes., Results: Of 67 participants (intervention n = 33, comparator n = 34), 37 (55%) were men, median (IQR) age was 51 (41-58) years. The most chosen digital health options were the nutrition app (n = 29, 88%) and exercise video consultations (n = 26, 79%). Only one participant chose no additional digital health options. The intervention group had no SRSAEs. The study exceeded targets for recruitment (52%), retention (81%) and exposure uptake (94%). Video consultation adherence was 42%. Engagement across digital health options was inconsistent., Conclusions: Digital health options incorporating patient choice were feasible and can be offered to people with complex chronic disease as a service model option., Trial Registration: Australia and New Zealand Trials Register: Trial Registration Number: ACTRN12620001282976. Registered 27th November 2020., (© 2024. The Author(s).)

Objective: The acceptability of being offered a choice from a suite of digital health service options to support optimal diet and exercise behaviors in adults with complex chronic conditions was evaluated. This study sought to understand many areas of acceptability including satisfaction, ease of use, usefulness and user appropriateness and perceived effectiveness., Methods: This mixed-methods study was embedded within a randomized-controlled feasibility trial providing digital health services managing diet and exercise for adults from specialist kidney and liver disease clinics. Post study surveys and semistructured interviews were used to determine patients' acceptability of the trial interventions. Quantitative (surveys) and qualitative (surveys and interviews) results were merged using integrative analysis and mapped to each construct of the modified version of the Theoretical Framework of Acceptability., Results: Seventeen interviews (intervention group) and 50 surveys ( n  = 24 intervention, n  = 26 comparator) completed from a possible 67 participants were analyzed. In the intervention group, the survey results revealed high areas of acceptability for the digital health services including overall support received, ease of use, timely advice and feeling safe. The interviews also revealed high areas of acceptability including convenience, ability to adopt healthier behaviors and having regular interactions with health professionals. However, the interviews also revealed lower areas of acceptability as a result of absence of individualization, low digital literacy, and limitations from life circumstances., Conclusions: Recipients of digital health services that supported diet and exercise interventions found these useful, effective, and safe. Individualized care, technical support and patient confidence remain important to improve the acceptability of digital health service interventions., Competing Interests: The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article., (© The Author(s) 2024.)

Active radiometric reflectance is useful to determine plant characteristics in field conditions. However, the physics of silicone diode-based sensing are temperature sensitive, where a change in temperature affects photoconductive resistance. High-throughput plant phenotyping (HTPP) is a modern approach using sensors often mounted to proximal based platforms for spatiotemporal measurements of field grown plants. Yet HTPP systems and their sensors are subject to the temperature extremes where plants are grown, and this may affect overall performance and accuracy. The purpose of this study was to characterize the only customizable proximal active reflectance sensor available for HTPP research, including a 10 °C increase in temperature during sensor warmup and in field conditions, and to suggest an operational use approach for researchers. Sensor performance was measured at 1.2 m using large titanium-dioxide white painted field normalization reference panels and the expected detector unity values as well as sensor body temperatures were recorded. The white panel reference measurements illustrated that individual filtered sensor detectors subjected to the same thermal change can behave differently. Across 361 observations of all filtered detectors before and after field collections where temperature changed by more than one degree, values changed an average of 0.24% per 1 °C. Recommendations based on years of sensor control data and plant field phenotyping agricultural research are provided to support ACS-470 researchers by using white panel normalization and sensor temperature stabilization.

Background: The metabolic syndrome is common across many complex chronic disease groups. Advances in health technology have provided opportunities to support lifestyle interventions., Objective: The purpose of this study is to test the feasibility of a health technology-assisted lifestyle intervention in a patient-led model of care., Methods: The study is a single-center, 26-week, randomized controlled trial. The setting is specialist kidney and liver disease clinics at a large Australian tertiary hospital. The participants will be adults with a complex chronic condition who are referred for dietetic assessment and display at least one feature of the metabolic syndrome. All participants will receive an individualized assessment and advice on diet quality from a dietitian, a wearable activity monitor, and standard care. Participants randomized to the intervention group will receive access to a suite of health technologies from which to choose, including common base components (text messages) and optional components (online and mobile app-based nutrition information, an online home exercise program, and group-based videoconferencing). Exposure to the optional aspects of the intervention will be patient-led, with participants choosing their preferred level of engagement. The primary outcome will be the feasibility of delivering the program, determined by safety, recruitment rate, retention, exposure uptake, and telehealth adherence. Secondary outcomes will be clinical effectiveness, patient-led goal attainment, treatment fidelity, exposure demand, and participant perceptions. Primary outcome data will be assessed descriptively and secondary outcomes will be assessed using an analysis of covariance. This study will provide evidence on the feasibility of the intervention in a tertiary setting for patients with complex chronic disease exhibiting features of the metabolic syndrome., Results: The study was funded in 2019. Enrollment has commenced and is expected to be completed by June 2022. Data collection and follow up are expected to be completed by December 2022. Results from the analyses based on primary outcomes are expected to be submitted for publication by June 2023., Conclusions: The study will test the implementation of a health technology-assisted lifestyle intervention in a tertiary outpatient setting for a diverse group of patients with complex chronic conditions. It is novel in that it embeds patient choice into intervention exposure and will inform health service decision-makers in regards to the feasibility of scale and spread of technology-assisted access to care for a broader reach of specialist services., Trial Registration: Australian New Zealand Clinical Trial Registry ACTRN12620001282976; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=378337., International Registered Report Identifier (irrid): DERR1-10.2196/37556., (©Riley C C Brown, Dev K Jegatheesan, Marguerite M Conley, Hannah L Mayr, Jaimon T Kelly, Lindsey Webb, Amandine Barnett, Heidi M Staudacher, Nicola W Burton, Nicole M Isbel, Graeme A Macdonald, Katrina L Campbell, Jeff S Coombes, Shelley E Keating, Ingrid J Hickman. Originally published in JMIR Research Protocols (https://www.researchprotocols.org), 28.07.2022.)

Remote-sensing using normalized difference vegetation index (NDVI) has the potential of rapidly detecting the effect of water stress on field crops. However, this detection has typically been accomplished only after the stress effect led to significant changes in crop green biomass, leaf area index, angle and position, and few studies have attempted to estimate the uncertainties of the regression models. These have limited the informed interpretation of NDVI data in agricultural applications. We built a ground-based sensing cart and used it to calibrate the relationships between NDVI and leaf water potential (LWP) for wheat, corn, and cotton growing under field conditions. Both the methods of ordinary least-squares (OLS) and weighted least-squares (WLS) were employed in data analysis, and measurement errors in both LWP and NDVI were considered. We also used statistical resampling to test the effect of measurement errors of LWP on the uncertainties of model coefficients. Our data showed that obtaining a high value of the coefficient of determination did not guarantee a high prediction precision in the obtained regression models. Large prediction uncertainties were estimated for all three crops, and the regressions obtained were not always significant. The best models were obtained for cotton with a prediction uncertainty of 27%. We found that considering measurement errors for both LWP and NDVI led to reduced uncertainties in model coefficients. Also, reducing the sample size of LWP measurement led to significantly increased uncertainties in the coefficients of the linear models describing the LWP-NDVI relationship. Finally, potential strategies for reducing the uncertainty relative to the range of NDVI measurement are discussed., Competing Interests: The authors declare that they have no competing interests.

Background: Obesity and chronic kidney disease (CKD) are highly prevalent worldwide and result in substantial health care costs. Obesity is a predictor of incident CKD and progression to kidney failure. Whether weight loss interventions are safe and effective to impact on disease progression and clinical outcomes, such as death remains unclear., Objectives: This review aimed to evaluate the safety and efficacy of intentional weight loss interventions in overweight and obese adults with CKD; including those with end-stage kidney disease (ESKD) being treated with dialysis, kidney transplantation, or supportive care., Search Methods: We searched the Cochrane Kidney and Transplant Register of Studies up to 14 December 2020 through contact with the Information Specialist using search terms relevant to this review. Studies in the Register are identified through searches of CENTRAL, MEDLINE, EMBASE, conference proceedings, the International Clinical Trials Register (ICTRP) Search Portal and ClinicalTrials.gov., Selection Criteria: Randomised controlled trials (RCTs) and quasi-RCTs of more than four weeks duration, reporting on intentional weight loss interventions, in individuals with any stage of CKD, designed to promote weight loss as one of their primary stated goals, in any health care setting., Data Collection and Analysis: Two authors independently assessed study eligibility and extracted data. We applied the Cochrane 'Risk of Bias' tool and used the GRADE process to assess the certainty of evidence. We estimated treatment effects using random-effects meta-analysis. Results were expressed as risk ratios (RR) for dichotomous outcomes together with 95% confidence intervals (CI) or mean differences (MD) or standardised mean difference (SMD) for continuous outcomes or in descriptive format when meta-analysis was not possible., Main Results: We included 17 RCTs enrolling 988 overweight or obese adults with CKD. The weight loss interventions and comparators across studies varied. We categorised comparisons into three groups: any weight loss intervention versus usual care or control; any weight loss intervention versus dietary intervention; and surgical intervention versus non-surgical intervention. Methodological quality was varied, with many studies providing insufficient information to accurately judge the risk of bias. Death (any cause), cardiovascular events, successful kidney transplantation, nutritional status, cost effectiveness and economic analysis were not measured in any of the included studies. Across all 17 studies many clinical parameters, patient-centred outcomes, and adverse events were not measured limiting comparisons for these outcomes. In studies comparing any weight loss intervention to usual care or control, weight loss interventions may lead to weight loss or reduction in body weight post intervention (6 studies, 180 participants: MD -3.69 kg, 95% CI -5.82 to -1.57; follow-up: 5 weeks to 12 months, very low-certainty evidence). In very low certainty evidence any weight loss intervention had uncertain effects on body mass index (BMI) (4 studies, 100 participants: MD -2.18 kg/m², 95% CI -4.90 to 0.54), waist circumference (2 studies, 53 participants: MD 0.68 cm, 95% CI -7.6 to 6.24), proteinuria (4 studies, 84 participants: 0.29 g/day, 95% CI -0.76 to 0.18), systolic (4 studies, 139 participants: -3.45 mmHg, 95% CI -9.99 to 3.09) and diastolic blood pressure (4 studies, 139 participants: -2.02 mmHg, 95% CI -3.79 to 0.24). Any weight loss intervention made little or no difference to total cholesterol, high density lipoprotein cholesterol, and inflammation, but may lower low density lipoprotein cholesterol. There was little or no difference between any weight loss interventions (lifestyle or pharmacological) compared to dietary-only weight loss interventions for weight loss, BMI, waist circumference, proteinuria, and systolic blood pressure, however diastolic blood pressure was probably reduced. Furthermore, studies comparing the efficacy of different types of dietary interventions failed to find a specific dietary intervention to be superior for weight loss or a reduction in BMI. Surgical interventions probably reduced body weight (1 study, 11 participants: MD -29.50 kg, 95% CI -36.4 to -23.35), BMI (2 studies, 17 participants: MD -10.43 kg/m², 95% CI -13.58 to -7.29), and waist circumference (MD -30.00 cm, 95% CI -39.93 to -20.07) when compared to non-surgical weight loss interventions after 12 months of follow-up. Proteinuria and blood pressure were not reported. All results across all comparators should be interpreted with caution due to the small number of studies, very low quality of evidence and heterogeneity across interventions and comparators., Authors' Conclusions: All types of weight loss interventions had uncertain effects on death and cardiovascular events among overweight and obese adults with CKD as no studies reported these outcome measures. Non-surgical weight loss interventions (predominately lifestyle) appear to be an effective treatment to reduce body weight, and LDL cholesterol. Surgical interventions probably reduce body weight, waist circumference, and fat mass. The current evidence is limited by the small number of included studies, as well as the significant heterogeneity and a high risk of bias in most studies., (Copyright © 2021 The Cochrane Collaboration. Published by John Wiley & Sons, Ltd.)

Field-based high-throughput plant phenotyping (FB-HTPP) has been a primary focus for crop improvement to meet the demands of a growing population in a changing environment. Over the years, breeders, geneticists, physiologists, and agronomists have been able to improve the understanding between complex dynamic traits and plant response to changing environmental conditions using FB-HTPP. However, the volume, velocity, and variety of data captured by FB-HTPP can be problematic, requiring large data stores, databases, and computationally intensive data processing pipelines. To be fully effective, FB-HTTP data workflows including applications for database implementation, data processing, and data interpretation must be developed and optimized. At the US Arid Land Agricultural Center in Maricopa Arizona, USA a data workflow was developed for a terrestrial FB-HTPP platform that utilized a custom Python application and a PostgreSQL database. The workflow developed for the HTPP platform enables users to capture and organize data and verify data quality before statistical analysis. The data from this platform and workflow were used to identify plant lodging and heat tolerance, enhancing genetic gain by improving selection accuracy in an upland cotton breeding program. An advantage of this platform and workflow was the increased amount of data collected throughout the season, while a main limitation was the start-up cost., Competing Interests: Competing interestsThe authors declare no conflicts of interest. Mention of trade names or commercial products in this publication is solely for the purpose of providing specific information and does not imply recommendation or endorsement by the USDA. The USDA is an equal opportunity employer., (© The Author(s) 2020.)

Objective: The objective of this study is to document the patterns of usage regarding intradialytic parenteral nutrition (IDPN) within in-center hemodialysis units in Australia., Design and Methods: This study used purposive non-probabilistic sampling to obtain details of the proportion of units using IDPN; formulations used; infusion rates; and barriers and enablers to usage. All participants were practicing renal dietitians in Australia. The participants were recruited from professional nephrology networks and completed a cross-sectional self-administered online survey., Results: A total of 68 responses were received, representing 41% of dialysis units in Australia. Half did not use IDPN at all, and one-third (38.2%) used it regularly. The most common IDPN formulations used were triple phase bags (48.3%) and lipid-only infusions (22.6%). Variation in practice was seen regarding maximum infusion rates for some formulations. Costs for IDPN were borne by dialysis units (74%) or pharmacy (16%). Barriers to the use of IDPN included bureaucratic hurdles and misconceptions about IDPN as an effective form of nutrition support. The presence of a protocol, support from medical and other staff, and dietitian experience were enablers to the use IDPN., Conclusions: IDPN use in Australia is not uncommon. This survey extends the small evidence base about the practice of IDPN and identified some important variations in practice. Some barriers to IDPN use could be overcome with further training to support staff. Enablers to IDPN use include protocols with defined responsibilities and access to experienced clinicians., (Copyright © 2019 National Kidney Foundation, Inc. All rights reserved.)

Many systems for field-based, high-throughput phenotyping (FB-HTP) quantify and characterize the reflected radiation from the crop canopy to derive phenotypes, as well as infer plant function and health status. However, given the technology's nascent status, it remains unknown how biophysical and physiological properties of the plant canopy impact downstream interpretation and application of canopy reflectance data. In that light, we assessed relationships between leaf thickness and several canopy-associated traits, including normalized difference vegetation index (NDVI), which was collected via active reflectance sensors carried on a mobile FB-HTP system, carbon isotope discrimination (CID), and chlorophyll content. To investigate the relationships among traits, two distinct cotton populations, an upland ( Gossypium hirsutum L.) recombinant inbred line (RIL) population of 95 lines and a Pima ( G. barbadense L.) population composed of 25 diverse cultivars, were evaluated under contrasting irrigation regimes, water-limited (WL) and well-watered (WW) conditions, across 3 years. We detected four quantitative trait loci (QTL) and significant variation in both populations for leaf thickness among genotypes as well as high estimates of broad-sense heritability (on average, above 0.7 for both populations), indicating a strong genetic basis for leaf thickness. Strong phenotypic correlations (maximum r = -0.73) were observed between leaf thickness and NDVI in the Pima population, but not the RIL population. Additionally, estimated genotypic correlations within the RIL population for leaf thickness with CID, chlorophyll content, and nitrogen discrimination ([Formula: see text] = -0.32, 0.48, and 0.40, respectively) were all significant under WW but not WL conditions. Economically important fiber quality traits did not exhibit significant phenotypic or genotypic correlations with canopy traits. Overall, our results support considering variation in leaf thickness as a potential contributing factor to variation in NDVI or other canopy traits measured via proximal sensing, and as a trait that impacts fundamental physiological responses of plants.

Physical activity recommendations for children in several countries advise that all young people should accumulate at least 60 min of moderate to vigorous physical activity every day. Perceiving physical activity intensity, however, can be a difficult task for children and it is not clear whether children can identify their levels of moderate to vigorous physical activity in accordance with the recommended guidelines. This study aimed to (1) explore whether children can identify time spent in moderate to vigorous physical activity; and (2) investigate whether heart rate biofeedback would improve children's ability to estimate time spent in moderate to vigorous physical activity. Thirty seven children (15 boys and 22 girls, mean age 12.6 years) wore data recording Polar E600 heart rate monitors during eight physical education lessons. At the end of each lesson children's estimated time in zone was compared to their actual time in zone. During a six lesson Intervention phase, one class was assigned to a biofeedback group whilst the other class acted as the control group and received no heart rate biofeedback. Post-Intervention, students in the biofeedback group were no better than the control group at estimating time spent in zone (mean relative error of estimation biofeedback group: Pre-Intervention 41±32% to Post-Intervention 28±26%; control group: Pre-Intervention 40±39% to Post-Intervention 31±37%). Thus it seems that identifying time spent in moderate to vigorous physical activity remains a complex task for children aged 11-13 even with the help of heart rate biofeedback., (Copyright © 2010 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.)