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The daylily gall midge, Contarinia quinquenotata (Loew) (Diptera: Cecidomyiidae), is an ornamental pest of daylilies, Hemerocallis spp. Linneas (Asphodelaceae). Originally native to Asia, this pest was accidentally introduced to western North America, and it is believed to occur throughout other parts of North America even though its presence has not been confirmed. Using an online survey of gardeners across Canada’s “Maritimes” (the region that includes the provinces of New Brunswick, Nova Scotia, and Prince Edward Island), we determined that symptoms of the pest occurred at multiple sites across Nova Scotia, but we received no reports from Prince Edward Island or New Brunswick. Sequencing the cytochrome c oxidase 1 gene of the samples submitted by community scientists, we confirmed the daylily gall midge occurs at multiple sites across Nova Scotia. A common garden study that included 517 daylily varieties found that yellow-flowering varieties were almost twice as likely to be affected as nonyellow varieties. Early-flowering varieties were more likely to be attacked than later-flowering varieties. For each day that the date at first flowering was delayed, the likelihood of gall midge attack decreased by 16%. To avoid or mitigate damage where the daylily gall midge occurs, selecting late-flowering varieties with nonyellow flowers can be a useful complement to destructing infested flower buds.

Almost all applications of remotely sensed imagery require generic algorithms for image feature extraction and classification to gain the required information. Therefore the GMOSS project defined a work package Feature recognition to serve the application work packages in their need to derive information for their tasks. For this purpose an important task is the definition of terms, nomenclature and the creation of a feature catalogue which describes significant features as well as the ability and means to detect these features. The work performed in this work package covers a very wide area and reaches from basic image processing algorithms used in pre-processing steps to highly sophisticated automated, object-based classification and detection methods and its evaluation regarding to performance and robustness. In principle two basic operations will be covered by the feature recognition work package. Classification should provide good and robust background knowledge of the basic land-cover within a certain area whereas object detection techniques are specialized on finding one specific feature or object in a defined area.

Weeds have relatively long life cycles and satisfactory control measures can often be undertaken over a longer period than those for many other pests. Consequently, emphasis has been placed on the effects of environmental factors on weed control and selectivity rather than on level of infestation. An overall view of the interaction of weather and herbicide performance may be obtained by considering field results and meteorological data, but in order to rank the importance of individual weather factors it is usually necessary to vary one environmental factor while the others are held constant From field experience it is generally accepted that certain weather criteria must be met for successful application results, but it is less widely appreciated that environmental factors before and after spraying may exert a major influence on herbicide activity. Results illustrate the way in which environmental factors influence spray interception and herbicide entry, movement and phytotoxic activity in the plant. The use of this type of information to increase herbicide reliability and flexibility of use is discussed.

2-Chloroethylphosphonic acid applied to foliage or soil released dormant buds from apical dominance in aerial shoots and rhizomes of Agropyron repens. The aerial shoots had scale-like leaves and shortened internodes with adventitious roots at the nodes. The treated plants had a dwarf appearance and had increased peroxidase activity.