A comparison of alternative plant mixes for conservation bio-control by native beneficial arthropods in vegetable cropping systems in Queensland Australia.

Cucurbit crops host a range of serious sap-sucking insect pests, including silverleaf whitefly (SLW) and aphids, which potentially represent considerable risk to the Australian horticulture industry. These pests are extremely polyphagous with a wide host range. Chemical control is made difficult due to resistance and pollution, and other side-effects are associated with insecticide use. Consequently, there is much interest in maximising the role of biological control in the management of these sap-sucking insect pests. This study aimed to evaluate companion cropping alongside cucurbit crops in a tropical setting as a means to increase the populations of beneficial insects and spiders so as to control the major sap-sucking insect pests. The Population of beneficial and harmful insects, with a focus on SLW and aphids, and other invertebrates were sampled weekly oil four different crops which could be used for habitat manipulation: Goodbug Mix (GBM; a proprietary seed Mixture including self-sowing annual and perennial herbaceous flower species); lablab (Lablab purpureus L. Sweet); lucerne (Medicago sativa L.); and niger (Guizotia abyssinica (L.f.) Cass.). Lablab hosted the highest numbers of beneficial insects (larvae and adults of lacewing (Mallada signata (Schneider)), ladybird beetles (Coccinella transversalis Fabricius) and spiders) while GBM hosted the highest numbers of European bees (Apis mellifera Linnaeus) and spiders. Lucerne and niger showed little promise in hosting beneficial insects, but lucerne hosted significantly more spiders (double the numbers) than niger. Lucerne hosted significantly more of the harmful insect species of aphids (Aphis gossypii (Glover)) and Myzus persicae (Sulzer)) and heliothis (Heliothis armigera Hubner). Niger hosted significantly more vegetable weevils (Listroderes difficillis (Germar)) than the other three species. Therefore, lablab and GBM appear to be viable options to grow within cucurbits or as field boundary crops to attract and increase beneficial insects and spiders for the control of sap-sucking insect pests. Use of these bio-control strategies affords the opportunity to minimise pesticide usage and the risks associated with pollution.

Pond apple (Annona glabra L.) - Investigating novel mechanical control options

Pond apple usually occurs in swampy areas, but mechanical control may be a viable option in some locations during drier periods. Two machines, the Positrack™ and the Tracksaw™, have been trialled for initial kill rate, amount of follow-up control required, safety to field operators, cost-efficiency and selectivity (effect on native vegetation), compared to other control options. The Positrack™ is a tracked bobcat with a slasher-type attachment that cuts individual trees off near ground level and mulches them. It has no on-board herbicide application capability and requires an additional on-ground operator to apply herbicide by hand. The Tracksaw™ is a tracked mini-excavator with a chainsaw bar and spray applicator on the boom that cuts individual trees off near ground level and applies chemical immediately to the cut stump, requiring only a single operator. Initial trials were done in infestations of similar sizes and densities at the Daintree (Positrack™) and in Innisfail (Tracksaw™) in late 2009. Kill rates to date are 83% for Positrack™ mechanical, 95% for Positrack™ mechanical plus herbicide, and 78% for the Tracksaw™ combined treatment. If ongoing comparison proves either of these machines to be more cost effective, selective, and safer than traditional control methods, mechanical control methods may become more widely used.

Controls on trace metals in urban stream sediments : implications for pollution monitoring using sediment chemistry data

Contamination of urban streams is a rising topic worldwide, but the assessment and investigation of stormwater induced contamination is limited by the high amount of water quality data needed to obtain reliable results. In this study, stream bed sediments were studied to determine their contamination degree and their applicability in monitoring aquatic metal contamination in urban areas. The interpretation of sedimentary metal concentrations is, however, not straightforward, since the concentrations commonly show spatial and temporal variations as a response to natural processes. The variations of and controls on metal concentrations were examined at different scales to increase the understanding of the usefulness of sediment metal concentrations in detecting anthropogenic metal contamination patterns. The acid extractable concentrations of Zn, Cu, Pb and Cd were determined from the surface sediments and water of small streams in the Helsinki Metropolitan region, southern Finland. The data consists of two datasets: sediment samples from 53 sites located in the catchment of the Stream Gräsanoja and sediment and water samples from 67 independent catchments scattered around the metropolitan region. Moreover, the sediment samples were analyzed for their physical and chemical composition (e.g. total organic carbon, clay-%, Al, Li, Fe, Mn) and the speciation of metals (in the dataset of the Stream Gräsanoja). The metal concentrations revealed that the stream sediments were moderately contaminated and caused no immediate threat to the biota. However, at some sites the sediments appeared to be polluted with Cu or Zn. The metal concentrations increased with increasing intensity of urbanization, but site specific factors, such as point sources, were responsible for the occurrence of the highest metal concentrations. The sediment analyses revealed, thus a need for more detailed studies on the processes and factors that cause the hot spot metal concentrations. The sediment composition and metal speciation analyses indicated that organic matter is a very strong indirect control on metal concentrations, and it should be accounted for when studying anthropogenic metal contamination patterns. The fine-scale spatial and temporal variations of metal concentrations were low enough to allow meaningful interpretation of substantial metal concentration differences between sites. Furthermore, the metal concentrations in the stream bed sediments were correlated with the urbanization of the catchment better than the total metal concentrations in the water phase. These results suggest that stream sediments show true potential for wider use in detecting the spatial differences in metal contamination of urban streams. Consequently, using the sediment approach regional estimates of the stormwater related metal contamination could be obtained fairly cost-effectively, and the stability and reliability of results would be higher compared to analyses of single water samples. Nevertheless, water samples are essential in analysing the dissolved concentrations of metals, momentary discharges from point sources in particular.

Allelopathy for weed control in agricultural systems

Weeds are a hidden foe for crop plants, interfering with their functions and suppressing their growth and development. Yield losses of ∼34 are caused by weeds among the major crops, which are grown worldwide. These yield losses are higher than the losses caused by other pests in the crops. Sustainable weed management is needed in the wake of a huge decline in crop outputs due to weed pressure. A diversity in weed management tools ensures sustainable weed control and reduces chances of herbicide resistance development in weeds. Allelopathy as a tool, can be importantly used to combat the challenges of environmental pollution and herbicide resistance development. This review article provides a recent update regarding the practical application of allelopathy for weed control in agricultural systems. Several studies elaborate on the significance of allelopathy for weed management. Rye, sorghum, rice, sunflower, rape seed, and wheat have been documented as important allelopathic crops. These crops express their allelopathic potential by releasing allelochemicals which not only suppress weeds, but also promote underground microbial activities. Crop cultivars with allelopathic potentials can be grown to suppress weeds under field conditions. Further, several types of allelopathic plants can be intercropped with other crops to smother weeds. The use of allelopathic cover crops and mulches can reduce weed pressure in field crops. Rotating a routine crop with an allelopathic crop for one season is another method of allelopathic weed control. Importantly, plant breeding can be explored to improve the allelopathic potential of crop cultivars. In conclusion, allelopathy can be utilized for suppressing weeds in field crops. Allelopathy has a pertinent significance for ecological, sustainable, and integrated weed management systems.

Open source computer-vision based guidance system for UAVs on-board decision making

The use of UAVs for remote sensing tasks; e.g. agriculture, search and rescue is increasing. The ability for UAVs to autonomously find a target and perform on-board decision making, such as descending to a new altitude or landing next to a target is a desired capability. Computer-vision functionality allows the Unmanned Aerial Vehicle (UAV) to follow a designated flight plan, detect an object of interest, and change its planned path. In this paper we describe a low cost and an open source system where all image processing is achieved on-board the UAV using a Raspberry Pi 2 microprocessor interfaced with a camera. The Raspberry Pi and the autopilot are physically connected through serial and communicate via MAVProxy. The Raspberry Pi continuously monitors the flight path in real time through USB camera module. The algorithm checks whether the target is captured or not. If the target is detected, the position of the object in frame is represented in Cartesian coordinates and converted into estimate GPS coordinates. In parallel, the autopilot receives the target location approximate GPS and makes a decision to guide the UAV to a new location. This system also has potential uses in the field of Precision Agriculture, plant pest detection and disease outbreaks which cause detrimental financial damage to crop yields if not detected early on. Results show the algorithm is accurate to detect 99% of object of interest and the UAV is capable of navigation and doing on-board decision making.

New directions: Air pollution challenges for developing megacities like Delhi

Most major cities around the world experience periods of elevated air pollution levels, which exceed international health-based air quality standards (Kumar et al., 2013). Although it is a global problem, some of the highest air pollution levels are found in rapidly expanding cities in India and China. The sources, emissions, transformations and broad effects of meteorology on air pollution are reasonably well accounted in air quality control strategies in many developed cities; however these key factors remain poorly constrained in the growing cities of countries with emerging economies. We focus here on Delhi, one of the largest global population centres, which faces particular air pollution challenges, now and in the future.