Produktion, skador och grenegenskaper hos 10-årig tall i ett kombinerat förbands- och avkommeförsök : Volume production, damages and branch properties in a 10-year old combined spacing and progeny trial of Scots pine

A Scots pine (Pinus sylvestris) progeny trial was established in 1990, in the southwestern part of Sweden. The offspring was from 30 plus trees. The trial is located on abandoned agricultural land and has a single tree block design with a variation in spacing. The trial has been damaged by voles. At a tree age of ten years, growth, damages and branch properties were estimated. An analysis of variance on height, diameter and stem volume shows significant difference between spacing and progenies as well as interactions between these factors. As indicated by a better annual height increment and fewer and thinner branches at each whorl the densest spacing has the highest potential to produce quality logs.There were also differences between progenies in growth and quality traits. Some progenies combined good growth and branch characters with low mortality, straight stems and few damages. Other progenies had superior volume production.

Protection of spruce seedlings against pine weevil attacks by treatment of seeds or seedlings with nicotinamide, nicotinic acid and jasmonic acid

Sustainable methods are required to protect newly planted tree seedlings from insect herbivore attack. To this end, here Norway spruce (Picea abies (L.) Karst.) seeds were treated with 2.5 mM nicotinamide (NIC), 2.5 mM nicotinic acid (NIA), 3 mM jasmonic acid (JA) or 0.2 mM 5-azacytidine (5-Aza), and 6-month-old seedlings grown from these seeds were planted at a reforestation area in central Sweden. Attack by pine weevils (Hylobius abietis) was reduced by 50 per cent by NIC treatment, 62.5 per cent by JA treatment and 25 per cent by 5-Aza treatment, when compared with seedlings grown from untreated seeds. Watering 18-month-old spruce seedlings with 2 mM NIC or 2 mM NIA did reduce attack during the first season in the field by 40 and 53 per cent, respectively, compared with untreated plants. Girdling was also reduced by the different treatments. Analysis of conifer seedlings treated with 5-Aza points at a possible involvement of epigenetic mechanisms in this defensive capacity. This is supported by a reduced level of DNA methylation in the needles of young spruce seedlings grown in a greenhouse from NIC-treated seeds. Seed treatment for seedling defense potentiation is simple, inexpensive and also a new approach for forestry with many potential applications.

Triggering Solar-Powered Vehicle Activated Signs using Self Organising Maps with K-means

Solar-powered vehicle activated signs (VAS) are speed warning signs powered by batteries that are recharged by solar panels. These signs are more desirable than other active warning signs due to the low cost of installation and the minimal maintenance requirements. However, one problem that can affect a solar-powered VAS is the limited power capacity available to keep the sign operational. In order to be able to operate the sign more efficiently, it is proposed that the sign be appropriately triggered by taking into account the prevalent conditions. Triggering the sign depends on many factors such as the prevailing speed limit, road geometry, traffic behaviour, the weather and the number of hours of daylight. The main goal of this paper is therefore to develop an intelligent algorithm that would help optimize the trigger point to achieve the best compromise between speed reduction and power consumption. Data have been systematically collected whereby vehicle speed data were gathered whilst varying the value of the trigger speed threshold. A two stage algorithm is then utilized to extract the trigger speed value. Initially the algorithm employs a Self-Organising Map (SOM), to effectively visualize and explore the properties of the data that is then clustered in the second stage using K-means clustering method. Preliminary results achieved in the study indicate that using a SOM in conjunction with K-means method is found to perform well as opposed to direct clustering of the data by K-means alone. Using a SOM in the current case helped the algorithm determine the number of clusters in the data set, which is a frequent problem in data clustering.