Damien Sirjacobs

Analysis of Soil Variability Measured with a Soil Strength Sensor

In the context of precision agriculture, the knowledge of soil strength variability at the field scale may be useful for improving site-specific tillage. Moreover, rapid and accurate sensing methods for soil physical properties determination would favourably replace labour-intensive, time-consuming and expensive soil sampling and analysis. This study aims at validating conclusions of a previous study which was conducted to develop and test a soil strength sensor in field conditions. The coupled acquisition of the sensors signals and the corresponding DGPS positions allowed establishment of maps for the three measured outputs, namely the horizontal force (Fx), the vertical force (Fz) and the moment (My). In order to study the relationships between measured forces and soil physical parameters, a series of soil properties were measured on soil cores collected in 10 reference plots. Significant correlations were found between Fx and the average resistance to cone penetration at 25 cm depth (r = 0.95) and between Fx and average soil moisture at 30 cm depth (r = −0.95). These relationships were similar to those found in the first study. This sensing method proved its capability to characterise within-field soil variability.

Consensus assessment of the contamination level of publicly available cyanobacterial genomes

Publicly available genomes are crucial for phylogenetic and metagenomic studies, in which contaminating sequences can be the cause of major problems. This issue is expected to be especially important for Cyanobacteria because axenic strains are notoriously difficult to obtain and keep in culture. Yet, despite their great scientific interest, no data are currently available concerning the quality of publicly available cyanobacterial genomes. As reliably detecting contaminants is a complex task, we designed a pipeline combining six methods in a consensus strategy to assess the contamination level of 440 genome assemblies of Cyanobacteria. Two methods are based on published reference databases of ribosomal genes (SSU rRNA 16S and ribosomal proteins), one is indirectly based on a reference database of marker genes (CheckM), and three are based on complete genome analysis. Among those genome-wide methods, Kraken and DIAMOND blastx share the same reference database that we derived from Ensembl Bacteria, whereas CONCOCT does not require any reference database, instead relying on differences in DNA tetramer frequencies. Given that all the six methods appear to have their own strengths and limitations, we used the consensus of their rankings to infer that >5% of cyanobacterial genome assemblies are highly contaminated by foreign DNA (i.e., contaminants were detected by 5 or 6 methods). Our results will help researchers to check the quality of publicly available genomic data before use in their own analyses. Moreover, we argue that journals should make mandatory the submission of raw read data along with genome assemblies in order to facilitate the detection of contaminants in sequence databases.