53 research outputs found
Estimating pearl millet leaf area and specific leaf area
Leaf area and specific leaf area (SLA) are important parameters in many agronomic and ecological processes, but can be difficult and expensive to measure. This study was made to test simplified methods of estimating pearl millet [Pennisetum glaucum (L.) R. Br.] leaf area and SLA. Leaf length, maximum width, area, and dry mass data were obtained 85 kg of acidic, P-deficient Betis sand (sandy, silicious, thermic Psammentic Paleustalf) and were treated with four P levels and two water treatments (stressed and nonstressed). Individual leaf area was estimated non-destructively with the following equations(...
Development of a New Soil Extractant for Simultaneous Phosphorus, Ammonium, and Nitrate Analysis
PossĂveis efeitos alelopaticos de Brachiaria decumbens sobre o crescimento inicial de limĂŁo cravo (Citrus limonia)
Optimierung des Entscheidungsverhaltens â Eine Evaluation der âbottom-upâ-Methode zum Wahrnehmungstraining
Das âQuiet Eyeâ des Experten â Zunehmende Inhibition alter-nativer Bewegungsvarianten?
Impairments of peripheral motion change detection during smooth pursuit eye movements
Introduction:
In team sports the ability to use peripheral vision is essential to track a number of players and the
ball. By using eye-tracking devices it was found that players either use fixations and saccades to
process information on the pitch or use smooth pursuit eye movements (SPEM) to keep track of
single objects (SchĂŒtz, Braun, & Gegenfurtner, 2011). However, it is assumed that peripheral vision
can be used best when the gaze is stable while it is unknown whether motion changes can be equally
well detected when SPEM are used especially because contrast sensitivity is reduced during SPEM
(SchĂŒtz, Delipetkose, Braun, Kerzel, & Gegenfurtner, 2007). Therefore, peripheral motion change
detection will be examined by contrasting a fixation condition with a SPEM condition.
Methods:
13 participants (7 male, 6 female) were presented with a visual display consisting of 15 white and 1
red square. Participants were instructed to follow the red square with their eyes and press a button
as soon as a white square begins to move. White square movements occurred either when the red
square was still (fixation condition) or moving in a circular manner with 6 °/s (pursuit condition). The
to-be-detected white square movements varied in eccentricity (4 °, 8 °, 16 °) and speed (1 °/s, 2 °/s, 4
°/s) while movement time of white squares was constant at 500 ms. 180 events should be detected in
total. A Vicon-integrated eye-tracking system and a button press (1000 Hz) was used to control for
eye-movements and measure detection rates and response times. Response times (ms) and missed
detections (%) were measured as dependent variables and analysed with a 2 (manipulation) x 3
(eccentricity) x 3 (speed) ANOVA with repeated measures on all factors.
Results:
Significant response time effects were found for manipulation, F(1,12) = 224.31, p < .01, ηp2 = .95,
eccentricity, F(2,24) = 56.43; p < .01, ηp2 = .83, and the interaction between the two factors, F(2,24) =
64.43; p < .01, ηp2 = .84. Response times increased as a function of eccentricity for SPEM only and
were overall higher than in the fixation condition. Results further showed missed events effects for
manipulation, F(1,12) = 37.14; p < .01, ηp2 = .76, eccentricity, F(2,24) = 44.90; p < .01, ηp2 = .79, the
interaction between the two factors, F(2,24) = 39.52; p < .01, ηp2 = .77 and the three-way interaction
manipulation x eccentricity x speed, F(2,24) = 3.01; p = .03, ηp2 = .20. While less than 2% of events
were missed on average in the fixation condition as well as at 4° and 8° eccentricity in the SPEM
condition, missed events increased for SPEM at 16 ° eccentricity with significantly more missed
events in the 4 °/s speed condition (1 °/s: M = 34.69, SD = 20.52; 2 °/s: M = 33.34, SD = 19.40; 4 °/s: M
= 39.67, SD = 19.40).
Discussion:
It could be shown that using SPEM impairs the ability to detect peripheral motion changes at the far
periphery and that fixations not only help to detect these motion changes but also to respond faster.
Due to high temporal constraints especially in team sports like soccer or basketball, fast reaction are
necessary for successful anticipation and decision making. Thus, it is advised to anchor gaze at a
specific location if peripheral changes (e.g. movements of other players) that require a motor
response have to be detected. In contrast, SPEM should only be used if a single object, like the ball in
cricket or baseball, is necessary for a successful motor response.
References:
SchĂŒtz, A. C., Braun, D. I., & Gegenfurtner, K. R. (2011). Eye movements and perception: A selective
review. Journal of Vision, 11, 1-30.
SchĂŒtz, A. C., Delipetkose, E., Braun, D. I., Kerzel, D., & Gegenfurtner, K. R. (2007). Temporal contrast
sensitivity during smooth pursuit eye movements. Journal of Vision, 7, 1-15
Peripheral vision in martial arts: How anchoring gaze helps athletes in Kung Fu and Tae Kwon Do
âQuiet Eyeâ-functions, an inhibition hypothesis and focus-specific inhibition processes in golf putting
Reduced foveal vision enhances peripheral monitoring and peripheral event detection
Introduction:
Although it seems plausible that sports performance relies on high-acuity foveal vision, it could be empirically shown that myoptic blur (up to +2 diopters) does not harm performance in sport tasks that require foveal information pick-up like golf putting (Bulson, Ciuffreda, & Hung, 2008). How myoptic blur affects peripheral performance is yet unknown. Attention might be less needed for processing visual cues foveally and lead to better performance because peripheral cues are better processed as a function of reduced foveal vision, which will be tested in the current experiment.
Methods:
18 sport science students with self-reported myopia volunteered as participants, all of them regularly wearing contact lenses. Exclusion criteria comprised visual correction other than myopic, correction of astigmatism and use of contact lenses out of Swiss delivery area. For each of the participants, three pairs of additional contact lenses (besides their regular lenses; used in the âplanoâ condition) were manufactured with an individual overcorrection to a retinal defocus of +1 to +3 diopters (referred to as â+1.00 Dâ, â+2.00 Dâ, and â+3.00 Dâ condition, respectively). Gaze data were acquired while participants had to perform a multiple object tracking (MOT) task that required to track 4 out of 10 moving stimuli. In addition, in 66.7 % of all trials, one of the 4 targets suddenly stopped during the
motion phase for a period of 0.5 s. Stimuli moved in front of a picture of a sports hall to allow for foveal processing. Due to the directional hypotheses, the level of significance for one-tailed tests on differences was set at α = .05 and posteriori effect sizes were computed as partial eta squares (ηÏ2).
Results:
Due to problems with the gaze-data collection, 3 participants had to be excluded from further analyses. The expectation of a centroid strategy was confirmed because gaze was closer to the centroid than the target (all p < .01). In comparison to the plano baseline, participants more often recalled all 4 targets under defocus conditions, F(1,14) = 26.13, p < .01, ηÏ2 = .65. The three defocus conditions differed significantly, F(2,28) = 2.56, p = .05, ηÏ2 = .16, with a higher accuracy as a function of a defocus increase and significant contrasts between conditions +1.00 D and +2.00 D (p = .03) and +1.00 D and +3.00 D (p = .03). For stop trials, significant differences could neither be found between plano baseline and defocus conditions, F(1,14) = .19, p = .67, ηÏ2 = .01, nor between the three defocus conditions, F(2,28) = 1.09, p = .18, ηÏ2 = .07. Participants reacted faster in â4 correct+buttonâ trials under defocus than under plano-baseline conditions, F(1,14) = 10.77, p < .01, ηÏ2 = .44. The defocus conditions differed significantly, F(2,28) = 6.16, p < .01, ηÏ2 = .31, with shorter response times as a function of a defocus increase and significant contrasts between +1.00 D and +2.00 D (p = .01) and +1.00 D and +3.00 D (p < .01).
Discussion:
The results show that gaze behaviour in MOT is not affected to a relevant degree by a visual overcorrection up to +3 diopters. Hence, it can be taken for granted that peripheral event detection was investigated in the present study. This overcorrection, however, does not harm the capability to peripherally track objects. Moreover, if an event has to be detected peripherally, neither response accuracy nor response time is negatively affected. Findings could claim considerable relevance for all sport situations in which peripheral vision is required which now needs applied studies on this topic.
References:
Bulson, R. C., Ciuffreda, K. J., & Hung, G. K. (2008). The effect of retinal defocus on golf putting. Ophthalmic and Physiological Optics, 28, 334-344
Functional Movement Analysis in Dance
Functional movement analysis is often adopted to better understand â and hence optimize â complex movement skills of athletes. This chapter aims to uncover the hitherto untouched potential of functional movement analyses for dancers. Both sports and dance involve complex movement skills acquired and refined over years of practice and training. The difference between dance and sports lies in the ultimate goal of this skill development: the dancer aims to âmaximizeâ his or her aesthetic effect, whereas the athlete regularly aims to maximize some objective performance criterion. Functional movement analysis was originally applied to sports, like gymnastics and athletics, and focused mainly on the mechanical principles underlying top-level sports movements. The deepened mechanical understanding has helped athletes improve many a gymnastic and athletic skill. The scope of functional movement analysis has broadened in recent years to also include the athlete performing a movement and the context in which this takes place. Accordingly, the analysis no longer exclusively focuses on the mechanics of a movement but further considers anatomical, physiological, and psychological factors. The present chapter aims to show that dance can benefit greatly from functional movement analysis, both in its original narrow conception and particularly in its current broader one. This claim rests on the central argument that maximizing aesthetic effects and maximizing motor performance are often very closely related in dance, so that many fruits of functional movement analysis currently only reaped by athletes are there for the taking for dancers as well
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