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NIBIOs ansatte publiserer flere hundre vitenskapelige artikler og forskningsrapporter hvert år. Her finner du referanser og lenker til publikasjoner og andre forsknings- og formidlingsaktiviteter. Samlingen oppdateres løpende med både nytt og historisk materiale. For mer informasjon om NIBIOs publikasjoner, besøk NIBIOs bibliotek.

2024

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Sammendrag

Common scab (CS) is a major bacterial disease causing lesions on potato tubers, degrading their appearance and reducing their market value. To accurately grade scab-infected potato tubers, this study introduces “ScabyNet”, an image processing approach combining color-morphology analysis with deep learning techniques. ScabyNet estimates tuber quality traits and accurately detects and quantifies CS severity levels from color images. It is presented as a standalone application with a graphical user interface comprising two main modules. One module identifies and separates tubers on images and estimates quality-related morphological features. In addition, it enables the extraction of tubers as standard tiles for the deep-learning module. The deep-learning module detects and quantifies the scab infection into five severity classes related to the relative infected area. The analysis was performed on a dataset of 7154 images of individual tiles collected from field and glasshouse experiments. Combining the two modules yields essential parameters for quality and disease inspection. The first module simplifies imaging by replacing the region proposal step of instance segmentation networks. Furthermore, the approach is an operational tool for an affordable phenotyping system that selects scab-resistant genotypes while maintaining their market standards.

Sammendrag

Scots pine (Pinus sylvestris L.) is a commercially important forest tree species in many Eurasian countries. Its wood has been commonly utilized for production of construction timber. In Sweden, a breeding program was launched in 1950s to improve Scots pine trees to better suit industrial requirements. The emphasis was mainly put on improving stem volume, vitality, stem straightness and branching characteristics whilst wood quality was neglected. However, since some of the important wood quality traits are negatively correlated with the prioritized volume production, the continuation of such an approach could in a long run lead to irreversible deterioration of wood quality. In our study, we focused on wood quality traits that are relevant for construction timber – wood density, stiffness, strength, grain angle and sawn-board shape stability (crook, bow and twist). We linked wood quality traits nondestructively assessed on standing trees with those measured on sawn boards. We estimated narrow-sense heritabilities, genetic correlations and correlated responses to selection with the aim of identifying reliable techniques for wood quality assessment on standing trees and proposing suitable strategies for incorporating wood quality traits into the breeding program. We have concluded that standing-tree drilling resistance, acoustic velocity and grain angle are good predictors of wood density, wood stiffness & strength, and sawn-board twisting, respectively. Taking into account the long-term development on wood market, we are proposing an inclusion of wood density in the breeding program, in the way that it will be retained at the current levels rather than increased, which would also positively affect wood stiffness and strength. Furthermore, we are suggesting to consider grain angle as a breeding trait although more research is needed to unravel its underlying biological mechanism.