Induced plant volatiles allow sensitive monitoring of plant health status in greenhouses

A novel approach to support the inspection of greenhouse crops is based on the measurement of volatile organic compounds emitted by unhealthy plants.This approach has attracted some serious interest over the last decade. In pursuit of this interest, we performed several experiments at the laboratory-scale to pinpoint marker volatiles that can be used to indicate certain health problems. In addition to these laboratory experiments, pilot and model studies were performed in order to verify the validity of these marker volatiles under real-world conditions. This paper provides an overview of results and gives an outlook on the use of plant volatiles for plant health monitoring.Key words: plant health, volatiles, plant pathogens, plant infection     

Effect of man-made electromagnetic fields on common <i>Brassicaceae Lepidium sativum</i> (cress d’Alinois) seed germination: a preliminary replication study

Under high levels of radiation (70-100 µW/m2 =175 mV/m), seeds of Brassicaceae Lepidium sativum (cress d’Alinois) never germinated. In fact, the first step of seeds’ germination ‒ e.g. imbibitions of germinal cells ‒ could not occur under radiation, while inside the humid compost such imbibitions occurred and roots slightly developed. When removed from the electromagnetic field, seeds germinated normally. The radiation was, thus, most likely the cause of the non-occurrence of the seeds’ imbibitions and germination.     

Modelling tropical fire ant (<Emphasis Type="Italic">Solenopsis geminata</Emphasis>) dynamics and detection to inform an eradication project

Invasive species threaten endangered species worldwide and substantial effort is focused on their control. Eradication projects require critical resource allocation decisions, as they affect both the likelihood of success and the overall cost. However, these complex decisions must often be made within data-poor environments. Here we develop a mathematical framework to assist in resource allocation for invasive species control projects and we apply it to the proposed eradication of the tropical fire ant (Solenopsis geminata) from the islands of Ashmore Reef in the Timor Sea. Our framework contains two models: a population model and a detection model. Our stochastic population model is used to predict ant abundance through time and allows us to estimate the probability of eradication. Using abundance predictions from the population model, we use the detection model to predict the probability of ant detection through time. These models inform key decisions throughout the project, which include deciding how many baiting events should take place, deciding whether to invest in detector dogs and setting surveillance effort to confirm eradication following control. We find that using a combination of insect growth regulator and toxins are required to achieve a high probability of eradication over 2 years, and we find that using two detector dogs may be more cost-effective than the use of lure deployment, provided that they are used across the life of the project. Our analysis lays a foundation for making decisions about control and detection throughout the project and provides specific advice about resource allocation.     

Cytoplasmic dynein could be key to understanding neurodegeneration

A new mouse mutation, Sprawling, highlights an essential role for the dynein heavy chain in sensory neuron function, but it lacks the ability of other known heavy-chain mutations to ameliorate neurodegeneration due to defective superoxide dismutase.