Selection of the most efficient wavelength bands for discriminating weeds from crop

peer reviewedThe aim of this study was to select the best combination of filters for detecting various weed species located within carrot rows. In-field images were taken under artificial lighting with a multispectral device consisting of a black and white camera coupled with a rotating wheel holding 22 interference filters in the VIS-NIR domain. Measurements were performed over a period of 19 days, starting 1 week after crop emergence (early weeding can increase yields) and seven different weeds species were considered. The selection of the best filter combination was based on a quadratic discriminant analysis. The best combination of filters included three interference filters, respectively centred on 450, 550 and 700 nm. With this combination, the overall classification accuracy (CA) was 72%. When using only two filters, a slight degradation of the CA was noticed. When the classification results were reported on field images, a systematic misclassification of carrot cotyledons appears. Better results were obtained with a more advanced growth stage. (c) 2007 Elsevier B.V. All rights reserved

Development of a multi-spectral vision system for the detection of defects on apples

A method to sort 'Jonagold' apples based on the presence of defects was proposed. A multi-spectral vision system including four wavelength bands in the visible/NIR range was developed. Multi-spectral images of sound and defective fruits were acquired tending to cover the whole colour variability of this bicolour apple variety. Defects were grouped into four categories: slight defects, more serious defects, defects leading to the rejection of the fruit and recent bruises. Stem-ends/calyxes were detected using a correlation pattern matching algorithm. The efficiency of this method depended on the orientation of the stem-end/calyx according to the optical axis of the camera. Defect segmentation consisted in a pixel classification procedure based on the Bayes' theorem and non-parametric models of the sound and defective tissue. Fruit classification tests were performed in order to evaluate the efficiency of the proposed method. No error was made on rejected fruits and high classification rates were reached for apples presenting serious defects and recent bruises. Fruits with slight defects presented a more important misclassification rate but those errors fitted however the quality tolerances of the European standard. Considering an actual ratio of sound fruits of 90%, less than 2% of defective fruits were classified into the sound ones. (c) 2004 Elsevier Ltd. All rights reserved

Multidisciplinary Views on Applying Explicit and Implicit Motor Learning in Practice: An International Survey

Background A variety of options and techniques for causing implicit and explicit motor learning have been described in the literature. The aim of the current paper was to provide clearer guidance for practitioners on how to apply motor learning in practice by exploring experts' opinions and experiences, using the distinction between implicit and explicit motor learning as a conceptual departure point. Methods A survey was designed to collect and aggregate informed opinions and experiences from 40 international respondents who had demonstrable expertise related to motor learning in practice and/or research. The survey was administered through an online survey tool and addressed potential options and learning strategies for applying implicit and explicit motor learning. Responses were analysed in terms of consensus (>= 70%) and trends (>= 50%). A summary figure was developed to illustrate a taxonomy of the different learning strategies and options indicated by the experts in the survey. Results Answers of experts were widely distributed. No consensus was found regarding the application of implicit and explicit motor learning. Some trends were identified: Explicit motor learning can be promoted by using instructions and various types of feedback, but when promoting implicit motor learning, instructions and feedback should be restricted. Further, for implicit motor learning, an external focus of attention should be considered, as well as practicing the entire skill. Experts agreed on three factors that influence motor learning choices: the learner's abilities, the type of task, and the stage of motor learning (94.5%; n = 34/36). Most experts agreed with the summary figure (64.7%; n = 22/34). Conclusion The results provide an overview of possible ways to cause implicit or explicit motor learning, signposting examples from practice and factors that influence day-to-day motor learning decisions.published_or_final_versio

Using a Delphi technique to seek consensus regarding definitions, descriptions and classification of terms related to implicit and explicit forms of motor learning.

Published onlineJournal ArticleResearch Support, Non-U.S. Gov'tBACKGROUND: Motor learning is central to domains such as sports and rehabilitation; however, often terminologies are insufficiently uniform to allow effective sharing of experience or translation of knowledge. A study using a Delphi technique was conducted to ascertain level of agreement between experts from different motor learning domains (i.e., therapists, coaches, researchers) with respect to definitions and descriptions of a fundamental conceptual distinction within motor learning, namely implicit and explicit motor learning. METHODS: A Delphi technique was embedded in multiple rounds of a survey designed to collect and aggregate informed opinions of 49 international respondents with expertise related to motor learning. The survey was administered via an online survey program and accompanied by feedback after each round. Consensus was considered to be reached if ≥70% of the experts agreed on a topic. RESULTS: Consensus was reached with respect to definitions of implicit and explicit motor learning, and seven common primary intervention strategies were identified in the context of implicit and explicit motor learning. Consensus was not reached with respect to whether the strategies promote implicit or explicit forms of learning. DISCUSSION: The definitions and descriptions agreed upon may aid translation and transfer of knowledge between domains in the field of motor learning. Empirical and clinical research is required to confirm the accuracy of the definitions and to explore the feasibility of the strategies that were identified in research, everyday practice and education.Stichting Alliantie Innovatie (Innovation Alliance Foundation)RAAK-internationa

Multidisciplinary Views on Applying Explicit and Implicit Motor Learning in Practice: An International Survey.

Published onlineJournal ArticleResearch Support, Non-U.S. Gov'tBACKGROUND: A variety of options and techniques for causing implicit and explicit motor learning have been described in the literature. The aim of the current paper was to provide clearer guidance for practitioners on how to apply motor learning in practice by exploring experts' opinions and experiences, using the distinction between implicit and explicit motor learning as a conceptual departure point. METHODS: A survey was designed to collect and aggregate informed opinions and experiences from 40 international respondents who had demonstrable expertise related to motor learning in practice and/or research. The survey was administered through an online survey tool and addressed potential options and learning strategies for applying implicit and explicit motor learning. Responses were analysed in terms of consensus (≥ 70%) and trends (≥ 50%). A summary figure was developed to illustrate a taxonomy of the different learning strategies and options indicated by the experts in the survey. RESULTS: Answers of experts were widely distributed. No consensus was found regarding the application of implicit and explicit motor learning. Some trends were identified: Explicit motor learning can be promoted by using instructions and various types of feedback, but when promoting implicit motor learning, instructions and feedback should be restricted. Further, for implicit motor learning, an external focus of attention should be considered, as well as practicing the entire skill. Experts agreed on three factors that influence motor learning choices: the learner's abilities, the type of task, and the stage of motor learning (94.5%; n = 34/36). Most experts agreed with the summary figure (64.7%; n = 22/34). CONCLUSION: The results provide an overview of possible ways to cause implicit or explicit motor learning, signposting examples from practice and factors that influence day-to-day motor learning decisions.Stichting Innovatie Alliantie (Innovation Alliance Foundation)RAAK-internationa

Multispectral images of peach related to firmness and maturity at harvest

wo multispectral maturity classifications for red soft-flesh peaches (‘Kingcrest’, ‘Rubyrich’ and ‘Richlady’ n = 260) are proposed and compared based on R (red) and R/IR (red divided by infrared) images obtained with a three CCD camera (800 nm, 675 nm and 450 nm). R/IR histograms were able to correct the effect of 3D shape on light reflectance and thus more Gaussian histograms were produced than R images. As fruits ripened, the R/IR histograms showed increasing levels of intensity. Reference measurements such as firmness and visible spectra also varied significantly as the fruit ripens, firmness decreased while reflectance at 680 nm increased (chlorophyll absorption peak)

Overview of effects of motor learning strategies in neurological and geriatric populations: a systematic mapping review

Systematic review protocol under review. Review Stage at time of this submission - Data analysis.This protocol was registered with the International Platform of Registered Systematic Review and Meta-Analysis Protocols (INPLASY) on 14 March 2024 and was last updated on 14 March 2024.Regieorgaan SI