Modelling annual grass weed seed dispersal in winter wheat, when influenced by hedges and directional wind

Accurate predictions of weed seed dispersal are important for spatial modelling of weed population dynamics. However there are few multi-year data sets available, and they are seldom analysed well. Here we gathered together and re-examined population growth and seed spread data from three grass weed species over 3 years. Using a new seed spread function in the simulation model SOMER it was possible to accurately parametrise population growth and seed spread to replicate the field data of Apera spica-venti (APESV) and Bromus sterilis (BROST). In contrast, the greatest increases in Alopecurus myosuroides (ALOMY) numbers occurred in the direction of machinery movement, which could not be predicted using this function. A probability-sum, exponential-type function gave an excellent fit to the field data for APESV and BROST, with changes in seed spread distances due to species differences, wind, and ‘shading’ from the hedge, accommodated by alterations in the scale, shape, and wind dispersal parameters. Here we describe a method of parametrising the probability function from within a stochastic simulation. Working within the simulation allowed empirical population size data sets to be successfully parameterised, without mathematical integration. This function is fully explained with stochastic simulated examples, and fitted to various two-dimensional longitudinal data sets. Enough detail to enable its parametrisation (including simplification) within a majority of spatial stochastic population models is included

Analysing the number of images needed to create robust variable spray maps

The targeted treatment of weeds is an expanding part of precision farming in many countries. Targeted weed treatments, using precision spray maps, reduce herbicide consumption, whilst still maintaining long term weed control. Assembling accurate spray maps is a vital part of this process. However, acceptable accuracy in spray maps is difficult to quantify, due in part to rapid technological advances in cameras, weed recognition software, and herbicide decision support systems (DSS). This research applied a DSS to repeated samples from field gathered weed data. Variability in the herbicide recommendations when different numbers of images were used for the same areas (polygons) within a field were examined. Type 2 errors (not recommending herbicide where it was needed), were analysed separately to type 1 errors (recommending herbicide where it was not needed). Type 2 errors were more common than type 1 errors in diagnosing herbicides to control Viola arvensis in Field 1, and Poaceae species in Field 2, and were also more common with systematically dispersed images compared to randomly dispersed images. In contrast, type 2 errors were less common than type 1 errors for Poaceae species in Field 1. Variability in herbicide recommendations differed for herbicides but was generally reduced (1) with greater numbers of images per polygon; (2) by using regularly arranged images; and (3) for datasets with greater ratios of ‘empty’ (not needing spray) polygons. Targeted treatments reduced herbicide use to 3–11% of the rate recommended for blanket spraying of the same weeds. High numbers of ‘empty’ polygons gave better results with lower relative percentages of type 1 errors. These results highlight the need to focus on reducing type 2 errors in spatial herbicide recommendations

Gender differences in fatigability and muscle activity responses to a short-cycle repetitive task

© 2016, The Author(s). Purpose: Epidemiological research has identified women to be more susceptible to developing neck–shoulder musculoskeletal disorders when performing low-force, repetitive work tasks. Whether this is attributable to gender differences in fatig ability and motor control is currently unclear. This study investigated the extent to which women differ from men in fatigability and motor control while performing a short-cycle repetitive task. Methods: 113 healthy young adults (58 women, 55 men) performed a standardized repetitive pointing task. The task was terminated when the subject’s perceived exertion reached 8 on the Borg scale. The time to task termination, and changes in means and cycle-to-cycle variabilities of surface electromyography signals from start to end of the task, were compared between women and men, for the upper trapezius, anterior deltoid, biceps and triceps muscles. Results: Women and men terminated the task after 6.5 (SD 3.75) and 7 (SD 4) min on average (p  >  0.05). All four muscles showed an increase of 25–35 % in average muscle activity with fatigue (no significant sex differences). However, men exhibited a higher increase than women in trapezius muscle variability with fatigue (31 vs. 7 %; p  <  0.05), and a decrease in biceps muscle variability where women had an increase (-23 vs. 12 %; p  <  0.05). Conclusions: Our results suggest that women and men may not differ in the ability to perform repetitive tasks at low-to-moderate force levels. However, differences in motor control strategies employed in task performance may explain gender differences in susceptibility to developing musculoskeletal disorders when performing repetitive work for prolonged periods in occupational life