Exploring genetic diversity and disease response of cultivated rice accessions (<Emphasis Type="Italic">Oryza</Emphasis> spp.) against <Emphasis Type="Italic">Pyricularia oryzae</Emphasis> under rainfed upland conditions in Benin

The main goal of this study is to gain insight into the relationship between the genetic profile of cultivated rice (Oryza spp.) accessions and their resistance to rice blast. Therefore, the genetic and phenotypic variability of a set of 350 cultivated rice accessions originating from Africa (Benin, Mali and Nigeria, Ivory Coast etc.) was examined. Seventy-seven fluorescent amplified fragment polymorphism (AFLP) markers were used to gain insight into the genetic variation and to classify the germplasm collection. In addition, the rice germplasm was assessed for its resistance to blast disease caused by Pyricularia oryzae in upland field conditions. Huge differences in responses of rice accessions to P. oryzae were observed, ranging from highly susceptible to highly resistant. Twelve percent of all accessions were highly resistant to P. oryzae. Based on their AFLP marker profile these highly resistant accessions could be separated from the other accessions. Stepwise regression revealed that the best prediction of the blast resistance level was achieved with a maximum number of 13 AFLP markers. Marker CTA22 was the most important for accurate prediction of blast resistance, this marker was present in all highly resistant accessions. It can be concluded that AFLP markers are a valuable tool to screen rice accessions for their susceptibility towards blast disease and that, based on a subset of markers, it is possible to predict the resistance to rice blast.     

The impact of high throughput sequencing on plant health diagnostics

High throughput sequencing informed diagnostics is revolutionising plant pathology. The application of this technology is most advanced in plant virology, where it is already becoming a front-line diagnostic tool and it is envisaged that for other types of pathogen and pests this will be the case in the near future. However, there are implications to deploying this technology due to a number of technical and scientific challenges. Firstly, interpretation of data and the assessment of plant health risk against a limited baseline of existing knowledge of the presence of pathogens in a given geographic region. Secondly, evidence of causality and the separation of pathogenic from commensal organisms in the sequence data, thirdly, the tension between the generation of a rapid sequence result with the necessary but laborious epidemiological characterisation in support of plant health risk assessment. Finally, the validation and accreditation of methods based on this rapidly evolving technology. These in turn present challenges for plant health policy and regulation. This review discusses the development of this technology, its application in plant health diagnostics, and explores the implications of applying this technology in the plant health setting.     

EuMIXFOR empirical forest mensuration and ring width data from pure and mixed stands of Scots pine (<Emphasis Type="Italic">Pinus sylvestris L.</Emphasis>) and European beech (<Emphasis Type="Italic">Fagus sylvatica L.</Emphasis>) through Europe

Key message

This data set provides unique empirical data from triplets of Scots pine ( Pinus sylvestris L.) and European beech ( Fagus sylvatica L.) across Europe. Dendrometric variables are provided for 32 triplets, 96 plots, 7555 trees and 4695 core samples. These data contribute to our understanding of mixed stand dynamics. Dataset access at   http://dx.doi.org/10.5061/dryad.8v04m . Associated metadata available at https://metadata-afs.nancy.inra.fr/geonetwork/apps/georchestra/?uuid=b3e098ca-e681-4910-9099-0e25d3b4cd52&hl=eng .