Market transparency and collusion: on the UK agricultural tractor registration exchange

We review the decision by the European Commission in the case of the UK Agricultural Registration Exchange. We propose a theoretical model, offering a basis for some of the intuitive arguments used by the Commission on the anti-competitive role of information exchange in the case of price and non price collusion. Market transparency on non price data is shown to be a collusion facilitating device which may achieve stability in otherwise unstable cartels.

Mitigation options for sediment and phosphorus loss from winter-sown arable crops

Sediment and P inputs to freshwaters from agriculture are a major problem in the United Kingdom (UK). This study investigated mitigation options for diffuse pollution losses from arable land. Field trials were undertaken at the hillslope scale over three winters at three UK sites with silt (Oxyaquic Hapludalf), sand (Udic Haplustept), and clay (Typic Haplaquept) soils. None of the mitigation treatments was effective in every year trialled, but each showed overall average reductions in losses. Over five site years, breaking up the compaction in tramlines (tractor wheel tracks) using a tine reduced losses of sediment and P to losses similar to those observed from areas without tramlines, with an average reduction in P loss of 1.06 kg TP ha(-1) Compared to traditional plowing, TP losses under minimum tillage were reduced by 0.30 kg TT ha(-1) over five site years, TP losses under contour cultivation were reduced by 0.30 kg TP ha(-1) over two site years, and TP losses using in-field barriers were reduced by 0.24 kg TP ha(-1) over two site years. In one site year, reductions in losses due to crop residue incorporation were nor significant. Each of the mitigation options trialled. is associated with a small cost at the farm-scale of up to 5 pound ha(-1), or with cost savings. The results indicate that each of the treatments his the potential to be a cost-effective mitigation option, but that tramline management is the most promising treatment, because tramlines dominate sediment and P transfer in surface runoff from arable hillslopes.

Proof of concept of automated mapping of weeds in arable fields

The project investigated whether it would be possible to remove the main technical hindrance to precision application of herbicides to arable crops in the UK, namely creating geo-referenced weed maps for each field. The ultimate goal is an information system so that agronomists and farmers can plan precision weed control and create spraying maps. The project focussed on black-grass in wheat, but research was also carried out on barley and beans and on wild-oats, barren brome, rye-grass, cleavers and thistles which form stable patches in arable fields. Farmers may also make special efforts to control them. Using cameras mounted on farm machinery, the project explored the feasibility of automating the process of mapping black-grass in fields. Geo-referenced images were captured from June to December 2009, using sprayers, a tractor, combine harvesters and on foot. Cameras were mounted on the sprayer boom, on windows or on top of tractor and combine cabs and images were captured with a range of vibration levels and at speeds up to 20 km h-1. For acceptability to farmers, it was important that every image containing black-grass was classified as containing black-grass; false negatives are highly undesirable. The software algorithms recorded no false negatives in sample images analysed to date, although some black-grass heads were unclassified and there were also false positives. The density of black-grass heads per unit area estimated by machine vision increased as a linear function of the actual density with a mean detection rate of 47% of black-grass heads in sample images at T3 within a density range of 13 to 1230 heads m-2. A final part of the project was to create geo-referenced weed maps using software written in previous HGCA-funded projects and two examples show that geo-location by machine vision compares well with manually-mapped weed patches. The consortium therefore demonstrated for the first time the feasibility of using a GPS-linked computer-controlled camera system mounted on farm machinery (tractor, sprayer or combine) to geo-reference black-grass in winter wheat between black-grass head emergence and seed shedding.