A novel method for area frame stratification based on geospatial crop planting frequency data layers
This paper proposes a novel method for land cover area frame stratification based on corn planting frequency and percent cultivation. South Dakota U.S. geospatial crop frequency (2008-2013) and cultivation (2013) data layers created from NASS Cropland Data Layers are utilized to develop a novel area sampling frame (ASF) stratification design. Eight corn planting frequency strata are derived using a k-means clustering method based on mean corn planting frequency calculated at the NASS ASF primary sampling unit level. The corn planting frequency strata are then sub stratified based on percent cultivation, which, together, provide more crop specific information than the current NASS ASF based on percent cultivation alone. Using 2014 Farm Service Agency Common Land Unit Data as in situ validation, it is found that this novel ASF design predicts crop specific planting patterns well. These results indicate that the new stratification method has potential to improve ASF accuracy, efficiency and crop estimates.
CropScape: A Web service based application for exploring and disseminating US conterminous geospatia
The Cropland Data Layer (CDL) contains crop and other specific land cover classifications obtained using remote sensing for the conterminous United States. This raster-formatted and geo-referenced product has been widely used in such applications as disaster assessments, land cover and land use research, agricultural sustainability studies, and agricultural production decision-making. The traditional CDL data distribution channels include paper thematic maps, email data requests, CD/DVD media, and ftp bulk downloading. To effectively and efficiently meet the growing needs of our customers, CropScape (the name invented for a new interactive Web CDL exploring system) was developed to query, visualize, disseminate, and analyze CDL data geospatially through standard geospatial Web services in a publicly accessible online environment. CropScape not only offers the online functionalities of interactive map operations, data customization and downloading, crop acreage statistics, charting and graphing, and multitemporal change analysis as well in an interoperable manner, but also provides Web geoprocessing services such as automatic data delivery and on-demand crop statistics for uses in other applications. This system delivers dynamic user experiences with its comprehensive capabilities in an open geospatial context, and facilitates delivery and analysis of geospatial cropland information for decision support and various research endeavors. More than 17,000 users around the world have visited CropScape in its first 5months of availability.
Genetics of the phenotypic evolution in sheep: a molecular look at diversity-driving genes
Background After domestication, the evolution of phenotypically-varied sheep breeds has generated rich biodiversity. This wide phenotypic variation arises as a result of hidden genomic changes that range from a single nucleotide to several thousands of nucleotides. Thus, it is of interest and significance to reveal and understand the genomic changes underlying the phenotypic variation of sheep breeds in order to drive selection towards economically important traits. Review Various traits contribute to the emergence of variation in sheep phenotypic characteristics, including coat color, horns, tail, wool, ears, udder, vertebrae, among others. The genes that determine most of these phenotypic traits have been investigated, which has generated knowledge regarding the genetic determinism of several agriculturally-relevant traits in sheep. In this review, we discuss the genomic knowledge that has emerged in the past few decades regarding the phenotypic traits in sheep, and our ultimate aim is to encourage its practical application in sheep breeding. In addition, in order to expand the current understanding of the sheep genome, we shed light on research gaps that require further investigation. Conclusions Although significant research efforts have been conducted in the past few decades, several aspects of the sheep genome remain unexplored. For the full utilization of the current knowledge of the sheep genome, a wide practical application is still required in order to boost sheep productive performance and contribute to the generation of improved sheep breeds. The accumulated knowledge on the sheep genome will help advance and strengthen sheep breeding programs to face future challenges in the sector, such as climate change, global human population growth, and the increasing demand for products of animal origin.