The Fourteenth Data Release of the Sloan Digital Sky Survey: First Spectroscopic Data from the Extended Baryon Oscillation Spectroscopic Survey and from the Second Phase of the Apache Point Observatory Galactic Evolution Experiment

The fourth generation of the Sloan Digital Sky Survey (SDSS-IV) has been in operation since 2014 July. This paper describes the second data release from this phase, and the 14th from SDSS overall (making this Data Release Fourteen or DR14). This release makes the data taken by SDSS-IV in its first two years of operation (2014–2016 July) public. Like all previous SDSS releases, DR14 is cumulative, including the most recent reductions and calibrations of all data taken by SDSS since the first phase began operations in 2000. New in DR14 is the first public release of data from the extended Baryon Oscillation Spectroscopic Survey; the first data from the second phase of the Apache Point Observatory (APO) Galactic Evolution Experiment (APOGEE-2), including stellar parameter estimates from an innovative data-driven machine-learning algorithm known as "The Cannon"; and almost twice as many data cubes from the Mapping Nearby Galaxies at APO (MaNGA) survey as were in the previous release (N = 2812 in total). This paper describes the location and format of the publicly available data from the SDSS-IV surveys. We provide references to the important technical papers describing how these data have been taken (both targeting and observation details) and processed for scientific use. The SDSS web site (www.sdss.org) has been updated for this release and provides links to data downloads, as well as tutorials and examples of data use. SDSS-IV is planning to continue to collect astronomical data until 2020 and will be followed by SDSS-V

Next-generation sequencing and its potential impact on food microbial genomics

Recent efforts of researchers to elucidate the molecular mechanisms of biological systems have been revolutionized greatly with the use of high throughput and cost-effective techniques such as next generation sequencing (NGS). Application of NGS to microbial genomics is not just limited to predict the prevalence of microorganisms in food samples but also to elucidate the molecular basis of how microorganisms respond to different food-associated conditions, which in turn offers tremendous opportunities to predict and control the growth and survival of desirable or undesirable microorganisms in food. Concurrently, NGS has facilitated the development of new genome-assisted approaches for correlating genotype and phenotype. The aim of this review is to provide a snapshot of the various possibilities that these new technologies are opening up in area of food microbiology, focusing the discussion mainly on lactic acid bacteria and yeasts associated with fermented food. The contribution of NGS to a system level understanding of food microorganisms is also discussed