BAT (Berry Analysis Tool): A high-throughput image interpretation tool to acquire the number, diameter, and volume of grapevine berries

QTL-analysis (quantitative trait loci) and marker development rely on efficient phenotyping techniques. Objectivity and precision of a phenotypic data evaluation is crucial but time consuming. In the present study a high-throughput image interpretation tool was developed to acquire automatically number, size, and volume of grape berries from RGB (red-green-blue) images. Individual berries of one cluster were placed on a black construction (300 x 300 mm) to take a RGB image from the top. The image interpretation of one dataset with an arbitrary number of images runs automatically using the BAT (Berry-Analysis-Tool) developed in MATLAB. For validation of results, the number of berries was counted and their size was measured using a digital calliper. A measuring cylinder was used to determine reliably the berry volume by displacement of water. All placed berries could be counted by BAT 100 % correctly. Manual ratings compared with BAT ratings showed strong correlation of r = 0.96 for mean berry diameter/image and r = 0.98 for cluster volume.

Weight Loss by Telemonitoring of Nutrition and Physical Activity in Patients with Metabolic Syndrome for 1 Year

Objective: Mobile technology can improve lifestyle programs, but the monitoring techniques and carer feedback need to be optimized. To this end, we investigated the efficacy of telemonitoring physical activity and nutrition over 12 months in patients with metabolic syndrome in a randomized, parallel-group, open trial. Methods: Screening all over Germany yielded 184 patients with metabolic syndrome. All patients attended a single 2-hour instruction meeting in their region concerning a combination diet and the importance of physical activity. Thereafter they were randomized into a control group (controls, n = 62) or one of 2 different intervention groups. Both intervention groups were issued accelerometers, which measured physical activity, recorded daily weight and calorie intake, and transmitted these data to a central server for use by patient carers. In the Active Body Control Program of University of Magdeburg (ABC) intervention group (n = 60), information and motivation was ensured by weekly letters. In the 4sigma telephone coaching (4S) intervention group (n = 58), this was accomplished by monthly telephone calls from the carers. Clinical and biochemical data for all patients were collected at 0, 4, 8, and 12 months without any regular face-to-face meetings between patients and carers. The primary endpoint w Results: After 12 months the dropout rates in the control, 4S, and ABC groups were respectively 35%, 17%, and 18%. The adjusted relative weight losses after 12 months were respectively 3.7%, 8.6%, and 11.4% (all p < 0.000 versus baseline). ABC was more effective than 4S (p = 0.041); 43% of the patients completing the study in the ABC group lost more than 15% of their baseline weight. The diagnosis of metabolic syndrome was no longer applicable in 58% of the cases in the ABC group, in 41% of the 4S group, and in 33% of the controls. Conclusions: Telemonitoring of physical activity and nutrition markedly improves weight loss and markers of metabolic syndrome. © 2014, © American College of Nutrition Published by Taylor & Francis Group, LLC