Precision Agriculture Applied to Harvesting Operations through the Exploitation of Numerical Simulation.

When it comes to harvesting operations, precision agriculture needs to consider both combine harvester technology and the precise execution of the process to eliminate harvest losses and minimize out-of-work time. This work aims to propose a complete control framework defined by a two-layer-based algorithm and a simulation environment suitable for quantitative harvest loss, time, and consumption analyses. In detail, the path-planning layer shows suitable harvesting techniques considering field boundaries and irregularities, while the path-tracking layer presents a vision-guided Stanley Lateral Controller. In order to validate the developed control framework, challenging driving scenarios were created using IPG-CarMaker software to emulate wheat harvesting operations. Results showed the effectiveness of the designed controller to follow the reference trajectory under regular field conditions with zero harvest waste and minimum out-of-work time. Whereas, in presence of harsh road irregularities, the reference trajectory should be re-planned by either selecting an alternative harvesting method or overlapping the harvester header by some distance to avoid missing crops. Quantitative and qualitative comparisons between the two harvesting techniques as well as a relationship between the level of irregularities and the required overlap will be presented. Eventually, a Driver-in-the-loop (DIL) framework is proposed as a methodology to compare human and autonomous driving.

Survival Rate and Transcriptional Response upon Infection with the Generalist Parasite Beauveria bassiana in a World-Wide Sample of Drosophila melanogaster.

The ability to cope with infection by a parasite is one of the major challenges for any host species and is a major driver of evolution. Parasite pressure differs between habitats. It is thought to be higher in tropical regions compared to temporal ones. We infected Drosophila melanogaster from two tropical (Malaysia and Zimbabwe) and two temperate populations (the Netherlands and North Carolina) with the generalist entomopathogenic fungus Beauveria bassiana to examine if adaptation to local parasite pressures led to differences in resistance. Contrary to previous findings we observed increased survival in temperate populations. This, however, is not due to increased resistance to infection per se, but rather the consequence of a higher general vigor of the temperate populations. We also assessed transcriptional response to infection within these flies eight and 24 hours after infection. Only few genes were induced at the earlier time point, most of which are involved in detoxification. In contrast, we identified more than 4,000 genes that changed their expression state after 24 hours. This response was generally conserved over all populations with only few genes being uniquely regulated in the temperate populations. We furthermore found that the American population was transcriptionally highly diverged from all other populations concerning basal levels of gene expression. This was particularly true for stress and immune response genes, which might be the genetic basis for their elevated vigor.

Inferring genealogical processes from patterns of Bronze-Age and modern DNA variation in Sardinia.

The ancient inhabitants of a region are often regarded as ancestral, and hence genetically related, to the modern dwellers (for instance, in studies of admixture), but so far, this assumption has not been tested empirically using ancient DNA data. We studied mitochondrial DNA (mtDNA) variation in Sardinia, across a time span of 2,500 years, comparing 23 Bronze-Age (nuragic) mtDNA sequences with those of 254 modern individuals from two regions, Ogliastra (a likely genetic isolate) and Gallura, and considering the possible impact of gene flow from mainland Italy. To understand the genealogical relationships between past and present populations, we developed seven explicit demographic models; we tested whether these models can account for the levels and patterns of genetic diversity in the data and which one does it best. Extensive simulation based on a serial coalescent algorithm allowed us to compare the posterior probability of each model and estimate the relevant evolutionary (mutation and migration rates) and demographic (effective population sizes, times since population splits) parameters, by approximate Bayesian computations. We then validated the analyses by investigating how well parameters estimated from the simulated data can reproduce the observed data set. We show that a direct genealogical continuity between Bronze-Age Sardinians and the current people of Ogliastra, but not Gallura, has a much higher probability than any alternative scenarios and that genetic diversity in Gallura evolved largely independently, owing in part to gene flow from the mainland.