While logging is banned in many endangered forests around the world, that hasn't stopped some companies from logging the area and then lying about the origin of the wood. However, the tree's chemicals may soon disable the group.
One reason for timber fraud testing is that timber often travels through many countries before being sold. In other words, even though the seller may be in a country where logging is permitted, the wood may have originally been harvested in another country where the trees are protected.
With this in mind, scientists from the University of the Netherlands and the Wageningen Research Center set out to collect wood samples from 991 trees in central Africa and Borneo. Samples were taken from three different tree species, red meranti, azobe and thali, which are the most commonly collected.
The researchers then analyzed the chemical composition of each sample using a mass spectrometer, measuring the ratio of elements such as calcium to magnesium. Each tree species has been found to have a specific "chemical fingerprint" of its geographic region of origin. In fact, even trees of the same species only 50 kilometers (31 miles) apart have different fingerprints.
The scientists then developed a machine learning algorithm to match the fingerprints of the wood sample with the already available fingerprints of the tree type in the area. When tested by researchers, the algorithm was found to be 86% to 98% accurate for identifying wood from parts of central Africa and 88% for wood from Borneo. In blinded independent tests, accuracy in Central Africans ranged from 70% to 72%, although this number may increase with further technological advances.
This study was conducted as part of the Timtrace project, which also includes universities and research institutes in Cameroon, the Republic of Congo, Gabon and Indonesia. An article recently published in Environmental Research Letters explains it.
Source: Wageningen University and Research.
