Search Results (4)

Weed harrowing is commonly used to manage weeds in organic farming but is also applied in conventional farming to replace herbicides. Due to its whole-field application, weed harrowing after crop emergence has relatively poor selectivity and may cause crop damage. Weediness generally varies within a field. Therefore, there is a potential to improve the selectivity and consider the within-field variation in weediness. This paper describes a decision model for precision post-emergence weed harrowing in cereals based on experimental data in spring barley and nonlinear regression analysis. The model predicts the optimal weed harrowing intensity in terms of the tine angle of the harrow for a given weediness (in terms of percentage weed cover), a given draft force of tines, and the biological weed damage threshold (in terms of percentage weed cover). Weed cover was measured with near-ground RGB images analyzed with a machine vision algorithm based on deep learning techniques. The draft force of tines was estimated with an electronic load cell. The proposed model is the first that uses a weed damage threshold in addition to site-specific values of weed cover and soil hardness to predict the site-specific optimal weed harrow tine angle. Future field trials should validate the suggested model. Full article

The adoption of conservation agriculture (CA) techniques by farmers is changing the dynamics of weed communities in cereal fields and so potentially their spatial distribution. These changes can challenge the use of site-specific weed control, which is based on the accurate location of weed patches for spraying. We studied the effect of two types of CA (direct drilling and harrow-tilled to 20 cm) on weed patches in a three-year survey in four direct-drilled and three harrow-tilled commercial fields in Catalonia (North-eastern Spain). The area of the ground covered by weeds (hereafter called “weed cover”) was estimated at 96 to 122 points measured in each year in each field, in 50 cm × 50 cm quadrats placed in a 10 m × 10 m grid in spring. Bromus diandrus, Lolium rigidum, and Papaver rhoeas were the main weed species. The weed cover and degree of aggregation for all species varied both between and within fields, regardless of the kind of tillage. Under both forms of soil management all three were aggregated in elongated patterns in the direction of traffic. Bromus was generally more aggregated than Lolium, and both were more aggregated than Papaver. Patches were stable over time for only two harrow-tilled fields with Lolium and one direct-drilled field with Bromus, but not in the other fields. Spatial stability of the weeds was more pronounced in the direction of traffic. Herbicide applications, crop rotation, and traffic seem to affect weed populations strongly within fields, regardless of the soil management. We conclude that site-specific herbicides can be applied to control these species because they are aggregated, although the patches would have to be identified afresh in each season. Full article

Non-chemical weed control methods need to be directed towards a site-specific weeding approach, in order to be able to compete the conventional herbicide equivalents. A system for online weed control was developed. It automatically adjusts the tine angle of a harrow and creates different levels of intensity: from gentle to aggressive. Two experimental plots in a maize field were harrowed with two consecutive passes. The plots presented from low to high weed infestation levels. Discriminant capabilities of an ultrasonic sensor were used to determine the crop and weed variability of the field. A controlling unit used ultrasonic readings to adjust the tine angle, producing an appropriate harrowing intensity. Thus, areas with high crop and weed densities were more aggressively harrowed, while areas with lower densities were cultivated with a gentler treatment; areas with very low densities or without weeds were not treated. Although the weed development was relatively advanced and the soil surface was hard, the weed control achieved by the system reached an average of 51% (20%–91%), without causing significant crop damage as a result of harrowing. This system is proposed as a relatively low cost, online, and real-time automatic harrow that improves the weed control efficacy, reduces energy consumption, and avoids the usage of herbicide. Full article

Harrowing is often used to reduce weed competition, generally using a constant intensity across a whole field. The efficacy of weed harrowing in wheat and barley can be optimized, if site-specific conditions of soil, weed infestation and crop growth stage are taken into account. This study aimed to develop and test an algorithm to automatically adjust the harrowing intensity by varying the tine angle and number of passes. The field variability of crop leaf cover, weed density and soil density was acquired with geo-referenced sensors to investigate the harrowing selectivity and crop recovery. Crop leaf cover and weed density were assessed using bispectral cameras through differential images analysis. The draught force of the soil opposite to the direction of travel was measured with electronic load cell sensor connected to a rigid tine mounted in front of the harrow. Optimal harrowing intensity levels were derived in previously implemented experiments, based on the weed control efficacy and yield gain. The assessments of crop leaf cover, weed density and soil density were combined via rules with the aforementioned optimal intensities, in a linguistic fuzzy inference system (LFIS). The system was evaluated in two field experiments that compared constant intensities with variable intensities inferred by the system. A higher weed density reduction could be achieved when the harrowing intensity was not kept constant along the cultivated plot. Varying the intensity tended to reduce the crop leaf cover, though slightly improving crop yield. A real-time intensity adjustment with this system is achievable, if the cameras are attached in the front and at the rear or sides of the harrow. Full article