Strigolactone analogues induce suicidal seed germination of Striga spp. in soil

Striga hermonthica and Striga asiatica are obligate root parasites that cause serious problems in the production of staple cereal crops in Africa. Because of the high levels of infestation, there is an urgent need to control these weeds. A potentially useful control option is depletion of the soil seed bank by suicidal germination, which involves germination of the seeds in the absence of host plants. Suicidal germination is often mentioned in the literature, but not considered realistic, because of the alleged untimely decomposition of the stimulants in the soil, despite the fact that some encouraging results were reported around 1980. The alleged instability has prevented active research in this direction for the past 20–25 years. Five newly designed synthetic germination stimulants were investigated as candidates for suicidal germination. An important issue is the persistence of these stimulants in soil. Packets with Striga spp. seeds were put in pots with soil and then treated with aqueous solutions of the stimulants. All five compounds induced germination under these conditions, with percentages varying between 18% and 98% depending on stimulant and species. There were no noticeable signs of decomposition of the stimulants. The best performing stimulant is derived from 1-tetralone. We conclude that synthetic strigolactones analogues have excellent prospects for use in combating parasitic weeds. Further testing will be needed to evaluate whether such prospects can be realised in the field.

An investigation to enhance understanding of the stimulation of weed seedling emergence by soil disturbance

Enhanced understanding of soil disturbance effects on weed seedling recruitment will help guide improved management approaches. Field experiments were conducted at 16 site-years at 10 research farms across Europe and North America to (i) quantify superficial soil disturbance (SSD) effects on Chenopodium album emergence and (ii) clarify adaptive emergence behaviour in frequently disturbed environments. Each site-year contained factorial combinations of two seed populations (local and common, with the common population studied at all site-years) and six SSD timings [0, 50, 100, 150, 200 day-degrees (d°C, base temperature 3°C) after first emergence from undisturbed soil]. Analytical units in this study were emergence flushes. Flush magnitudes (maximum weekly emergence per count flush) and flush frequencies (flushes year 1) were compared between disturbed and undisturbed seedbanks. One year after burial, SSD promoted seedling emergence relative to undisturbed seedbanks by increasing flush magnitude rather than increasing flush frequency. Two years after burial, SSD promoted emergence through increased flush magnitude and flush frequency. The promotional effects of SSD on emergence were strongest within 500 d°C following SSD; however, low levels of SSDinduced emergence were detected as late as 3000 d°C following SSD. Accordingly, stale seedbed practices that eliminate weed seedlings should occur within 500 d°C of disturbance, because few seedlings emerge after this time. However, implementation of stale seedbed practices will probably cause slight increases in weed population densities throughout the year. Compared with the common population, local populations exhibited reduced variance in total emergence measured within sites and across SSD treatments, suggesting that C. album adaptation to local pedo-climatic conditions involves increased consistency in SSD-induced emergence.

Designing a sampling scheme to reveal correlations between weeds and soil properties at multiple spatial scales

Weeds tend to aggregate in patches within fields and there is evidence that this is partly owing to variation in soil properties. Because the processes driving soil heterogeneity operate at different scales, the strength of the relationships between soil properties and weed density would also be expected to be scale-dependent. Quantifying these effects of scale on weed patch dynamics is essential to guide the design of discrete sampling protocols for mapping weed distribution. We have developed a general method that uses novel within-field nested sampling and residual maximum likelihood (REML) estimation to explore scale-dependent relationships between weeds and soil properties. We have validated the method using a case study of Alopecurus myosuroides in winter wheat. Using REML, we partitioned the variance and covariance into scale-specific components and estimated the correlations between the weed counts and soil properties at each scale. We used variograms to quantify the spatial structure in the data and to map variables by kriging. Our methodology successfully captured the effect of scale on a number of edaphic drivers of weed patchiness. The overall Pearson correlations between A. myosuroides and soil organic matter and clay content were weak and masked the stronger correlations at >50 m. Knowing how the variance was partitioned across the spatial scales we optimized the sampling design to focus sampling effort at those scales that contributed most to the total variance. The methods have the potential to guide patch spraying of weeds by identifying areas of the field that are vulnerable to weed establishment.