ALBERT

Notes: Three years of experiments with spring barley showed significant differences in weed suppression ability among varieties. Weed dry matter in the most suppressive variety, Ida, was 48% lower than the mean weed dry matter of all varieties, whereas it was 31% higher in the least suppressive variety, Grit. Ranking varietal responses to weed competition in terms of grain yield loss corresponded well to ranking weed dry matter produced in crop weed mixtures. There was no correspondence between the varietal grain yields in pure stands and their competitiveness, suggesting that breeding to optimize both yielding and competitive ability may be possible. Non-linear regression models were fitted to canopy height and light interception data for each variety in all three years. The canopy height model provided a precise description of development and maximum canopy height of the varieties. A light interception model was developed to describe the light interception profiles of the varieties. A study of the estimated parameters showed significant correlation between weed dry matter, rate of canopy height development and the light interception profile. However, when estimates were standardized to eliminate the effect of year, there was no correlation between weed dry matter and the light interception profile parameters, indicating that varietal competitiveness was not related to this trait. A multiple regression analysis showed that a model comprising parameters of maximum canopy height, maximum light interception and temporal displacement of light interception provided a good description of the varietal differences.

Notes: For implementation of simple yield loss models into threshold-based weed management systems, a thorough validation is needed over a great diversity of sites. Yield losses by competition wsth Sinapis alba L. (white mustard) as a model weed, were studied in 12 experiments in sugar beet (Beta vulgaris L.) and in 11 experiments in spring wheat (Triticum aestivum L.). Most data sets were heller described by a model based on the relative leaf area of the weed than by a hyperbolic model based on weed density. This leaf area model accounted for (part of) the effect of different emerging times of the S. alba whereas the density model did not. A parameter that allows the maximum yield loss to be smaller than 100% was mostly not needed to describe the effects of weed competition. The parameter that denotes the competitiveness of the weed species with respect to the crop decreased the later the relative leaf area of the mustard was determined. This decrease could be estimated from the differences in relative growth rate of the leaf area of crop and S. alba. However, the accuracy of this estimation was poor. The parameter value of the leaf area model varied considerably between sites and years. The results strongly suggest that the predictive ability of the leaf area model needs to be improved before it can be applied in weed management systems. Such improvement would require additional information about effects of abiotic factors on plant development and morphology and the definition of a time window for predictions with an acceptable level of error.

Notes: Summary Stem thickness of the weed Solanum nigrum and the crop sugarbeet was determined with a He–Ne laser using a novel non-destructive technique measuring stem shadow. Thereafter, the stems were cut close to the soil surface with a CO2 laser. Treatments were carried out on pot plants, grown in the greenhouse, at two different growth stages, and plant dry matter was measured 2–5 weeks after treatment. The relationship between plant dry weight and laser energy was analysed using two different non-linear dose–response regression models; one model included stem thickness as a variable, the other did not. A binary model was also tested. The non-linear model incorporating stem thickness described the data best, indicating that it would be possible to optimize laser cutting by measuring stem thickness before cutting. The general tendency was that more energy was needed the thicker the stem. Energy uses on a field scale are discussed.

Notes: In dose-response experiments with the herbicide combinations MCPA+dichlorprop and ioxynil+mecoprop in barley, winter wheat, and winter rye varieties, oilseed rape (Brassica napus L.) was used as a substitute for weeds. The results showed a significant interaction between the competitive ability of varieties and herbicide performance. A negative exponential model with variety as categorical variable was used to analyse the data and to assess the competitive effect of the varieties on herbicide efficacy.A target level of 5 g weed dry matter m−2 in all varieties at the end of flowering was used to derive a varietal calibration factor of the herbicide dose. The results showed significant differences in calibration factors between species of winter wheat, barley, and rye, and between varieties of spring barley and winter wheat. In the winter wheat variety Sleipner it was necessary to use a 154% higher herbicide dose than in the winter barley variety Trixi, whereas in the winter rye variety Petkus II, herbicide dose could be reduced by 31% compared with Trixi. The differences between spring barley varieties were smallerbut significant. Competition entre culture et mauvaises herbes, et efficacité herbicide chez différentes espèces et variétés de céréales Dans des expériences dose-effet avec les combinaisons herbicides MCPA+dichlorprop et ioxynil+mécoprop dans différentes variétés d'orge, de blé d'hiver et de seigle d'hiver, le colza (Brassica napus L.) était utilisé comme modèle de mauvaise herbe. Les résultats ont montré une interaction significative entre l'aptitude à la concurrence des variétés et l'efficacité herbicide. Un modèle exponentiel négatif avec la variété comme variable catégorielle, a été utilisé pour analyser les données et pour déterminer l'effet de l'aptitude à la compétition des variétés sur l'efficacité herbicide.Un objectif de 5 g de matière sèche de mauvaise herbe par m2 pour toutes les variétés à la fin de la floraison a été utilisé pour déterminer un facteur de calibration varietal de la dose d'herbicide. Les résultats ont montré des différences significatives entre les facteurs de calibration déterminés pour les espèces blé d'hiver, orge et seigle, ainsi qu'entre les variétés d'orge de printemps et de blé d'hiver. Avec la variété de blé d'hiver Sleipner, U était nécessaire d'utiliser une dose d'herbicide supérieure de 154%à celle nécessaire pour la variété d'orge d'hiver Trixi, alors que dans le seigle d'hiver Petkus II, la dose herbicide pouvait ßtre réduite de 31 % par rapport à Trixi. Les différences entre variétés d'orge de printemps étaient plus faibles mais significatives. Konkurrenz zwischen Kulturpflanzen und Unkraut und Herbizidwirkung bei Getreidearten und -Sorten In Dosis-Wirkungs-Untersuchungen mit den Herbiziden MCPA+Dichlorprop und loxynil+Mecoprop wurde in Gersten-, Winterweizen- und Winterroggensorten Raps (Brassica napus L.) als Unkraut eingesetzt. Die Ergebnisse zeigten eine signifikante Wechselwirkung zwischen der Konkurrenzkraft von Sorten und der Herbizidwirkung. Ein negativ exponentielles Modell mil der Sorte als Kategorie wurde angewandt, um die Da ten zu analysieren und den Einfluß der Sorten auf die Herbizidwirksamkeit zubestimmen. Es wurde eine Zielgröße von 5 gm−2 Unkrauttrockenmasse in allen Sorten zum Endeder Blüte gesetzt, um einen sortenbezogenen Kalibrierungsfakt or für die Herbiziddosis zu erhalten. Es wurden signifikante Unterschiede der Kalibrierungsfaktoren zwischen den Getreidarten Winterweizen, Gerste und Roggen und zwischen den Sommergersten- und Winterweizensorten gefunden. Bei der Winterweizensorte Sleipner war es erforderlich, eine 154 % höhere Herbiziddosis als bei der Wintergerstensorte Trixi anzuwenden, während die Herbiziddosis bei der Winterroggensorte Petkus II im Vergleich zu Trixi um 31 % reduziert werden konnte. Die Unterschiede waren bei Sommergerstensorten geringer, jedoch signifikant.

Notes: The spatial cross-correlation between weed species densities and six soil properties within fields was analysed using cross-semivariograms. The survey was carried out in three successive years in two fields. The most consistent relationship between weed species density (numbers m−2) and soil properties was negative cross-correlation between the density of Viola arvensis Murray and clay content. This correlation was found in both fields; however, the range of spatial dependence varied between fields. In one of the fields, the density of Lamium purpureum L. was positively cross-correlated with the phosphorus content in the soil in all years. The density of Veronica spp. and Poa annua L. was negatively cross-correlated with pH in all three years. Other spatial cross-correlations that were found in this study were inconsistent over time or field site. The densities of some of the weed species were spatially cross-correlated with more than one soil property. The results showed that the range of spatial dependence varied not only between fields, but also between weed species and soil properties, as well as between years. This study indicates that the weed pattern is field-specific and that the spatial variation in soil properties within a field is one of several factors affecting weed patchiness.

Notes: Stems of Chenopodium album. and Sinapis arvensis. and leaves of Lolium perenne. were cut with a CO2 laser or with a pair of scissors. Treatments were carried out on greenhouse-grown pot plants at three different growth stages and at two heights. Plant dry matter was measured 2 to 5 weeks after treatment. The relationship between dry weight and laser energy was analysed using a non-linear dose–response regression model. The regression parameters differed significantly between the weed species. At all growth stages and heights S. arvensis was more difficult to cut with a CO2 laser than C. album. When stems were cut below the meristems, 0.9 and 2.3 J mm−1 of CO2 laser energy dose was sufficient to reduce by 90% the biomass of C. album and S. arvensis respectively. Regrowth appeared when dicotyledonous plant stems were cut above meristems, indicating that it is important to cut close to the soil surface to obtain a significant effect. When cutting L. perenne plants with 2-true leaves at a height of 2 cm from the soil surface with a laser, the biomass decreased significantly compared with plants cut by scissors, indicating a delay in regrowth. This delay was not observed for the dicotyledonous plants nor for the other growth stages of L. perenne.

Notes: Information on temporal and spatial variation in weed seedling populations within agricultural fields is very important for weed population assessment and management. Most of all, it allows a potential reduction in herbicide use, when post-emergence herbicides are only applied to field sections with weed infestation levels higher than the economic weed threshold; a review of such work is provided. This paper presents a system for site-specific weed control in sugarbeet (Beta vulgaris L.), maize (Zea mays L.), winter wheat (Triticum aestivum L.) and winter barley (Hordeum vulgare L.), including online weed detection using digital image analysis, computer-based decision making and global positioning systems (GPS)-controlled patch spraying. In a 4-year study, herbicide use with this map-based approach was reduced in winter cereals by 60% for herbicides against broad-leaved weeds and 90% for grass weed herbicides. In sugarbeet and maize, average savings for grass weed herbicides were 78% in maize and 36% in sugarbeet. For herbicides against broad-leaved weeds, 11% were saved in maize and 41% in sugarbeet.

Notes: A sugarbeet field experiment was conducted in 1999 and 2000 to measure beet yield where Sinapis arvensis or Lolium perenne were growing in the crop row at 2, 4 or 8 cm from the beet plants. The weeds were removed by cutting once in the growing season in either late May, mid-June or early July. The number of neighbouring beet plants to every target beet plant was recorded. Projected leaf cover of a subset of the data with non-cut weeds was analysed by using image analysis to investigate whether this could be used to predict beet yield loss early in the growing season. Increasing the distance between beet and weed from 2 to 8 cm increased the beet yield significantly by an average of 20%, regardless of weed species. The dry weight of non-cut and re-growing weeds at harvest time decreased when cutting was postponed to the period between mid-June and early July. The number of neighbours described a sigmoidal yield decline of the single beet plants. Results from image analysis showed that approximately 33 g of beet yield was lost in October/November for each per cent relative projected leaf cover of the weeds in May, despite variation in growing conditions. The results are discussed in relation to potentials for robotic in-row weed control.