A multidisciplinary study of biodeteriorated Celje Ceiling, a tempera painting on canvas

Interdisciplinary investigations of damaged cultural heritage objects have nowadays become standard practise. Numerous techniques in various fields may generate large amounts data, difficult to interpret. Machine learning was applied data collected from samples a painting build predictive model potential further biodeterioration and consequent damage the paintings. We used this strategy for deteriorated 17th century Celje Ceiling, tempera wooden frame, covering 143 m 2 ceiling. An interdisciplinary approach, monitoring microclimatic conditions wood moisture content, examinations using UV VIS photography, analyses paint layers decay products by Raman FTIR spectroscopy, SEM-EDS, protein binders ELISA, assess current condition painting. Data 535 painting's were subjected analysis machine methods. Moulding, main cause biodeterioration, found be strongly influenced position room related conditions. The presence coating layer, pigments, such as goethite, ultramarine kaolinite, had important role mould development well. mainly currently non-active, presumably xerophilic Aspergillus species, determined microscopy, cultivation amplicon sequencing. • Four century-old painting, Cieling, ceiling analysed multidisciplinary approach. Microclimatic chamber monitored over three years. obtained create deterioration. Microscopy, culture-dependent -independent methods microbial contamination selected parts