Mapping Indicators of Machinery Utilization Predicted by an Artificial Neural Network

A methodology is presented to generate digital maps containing values of Mechanization Indicators (Mechanization Index and Machinery Energy Ratio), predicted without direct calculation, using a multilayered ANN model. The inputs to the ANN model were simple data obtained from local databases.Complementarily there were processed digital maps related to parameters on land slope, farm size, soil texture, water supply for crop production and distribution of the land productivity potential for the main crops in the region of study.Overlapping among the generated maps assisted to analyze the mechanization conditions in every production unit of the Mexican State of Guanajuato, in order to estimate the intensity and suitability of mechanization as well as to identify which farms in the region would benefit more from machinery use.The developed methodology can facilitate the analysis to prioritize areas for the introduction or replacement of agricultural machinery.It is concluded that the present methodology would be a good tool to assess mechanization sustainability of agricultural activities; this in turn providing policy-makers and planners with tools with which to judge the best use of land in the near future. Planning the intensity and suitability of mechanization using this approach would contribute to optimize the use of inputs from oil sources

The Seventeenth Data Release of the Sloan Digital Sky Surveys: Complete Release of MaNGA, MaStar and APOGEE-2 Data

This paper documents the seventeenth data release (DR17) from the Sloan Digital Sky Surveys; the fifth and final release from the fourth phase (SDSS-IV). DR17 contains the complete release of the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey, which reached its goal of surveying over 10,000 nearby galaxies. The complete release of the MaNGA Stellar Library (MaStar) accompanies this data, providing observations of almost 30,000 stars through the MaNGA instrument during bright time. DR17 also contains the complete release of the Apache Point Observatory Galactic Evolution Experiment 2 (APOGEE-2) survey which publicly releases infra-red spectra of over 650,000 stars. The main sample from the Extended Baryon Oscillation Spectroscopic Survey (eBOSS), as well as the sub-survey Time Domain Spectroscopic Survey (TDSS) data were fully released in DR16. New single-fiber optical spectroscopy released in DR17 is from the SPectroscipic IDentification of ERosita Survey (SPIDERS) sub-survey and the eBOSS-RM program. Along with the primary data sets, DR17 includes 25 new or updated Value Added Catalogs (VACs). This paper concludes the release of SDSS-IV survey data. SDSS continues into its fifth phase with observations already underway for the Milky Way Mapper (MWM), Local Volume Mapper (LVM) and Black Hole Mapper (BHM) surveys