Genome-wide association studies for methane production in dairy cattle

© 2019 by the authors. Licensee MDPI, Basel, Switzerland. Genomic selection has been proposed for the mitigation of methane (CH4) emissions by cattle because there is considerable variability in CH4 emissions between individuals fed on the same diet. The genome-wide association study (GWAS) represents an important tool for the detection of candidate genes, haplotypes or single nucleotide polymorphisms (SNP) markers related to characteristics of economic interest. The present study included information for 280 cows in three dairy production systems in Mexico: 1) Dual Purpose (n = 100), 2) Specialized Tropical Dairy (n = 76), 3) Familiar Production System (n = 104). Concentrations of CH4 in a breath of individual cows at the time of milking (MEIm) were estimated through a system of infrared sensors. After quality control analyses, 21,958 SNPs were included. Associations of markers were made using a linear regression model, corrected with principal component analyses. In total, 46 SNPs were identified as significant for CH4 production. Several SNPs associated with CH4 production were found at regions previously described for quantitative trait loci of composition characteristics of meat, milk fatty acids and characteristics related to feed intake. It was concluded that the SNPs identified could be used in genomic selection programs in developing countries and combined with other datasets for global selection

RESEARCH INTO THE METHODS OF ANALYSING THE PRODUCTIVITY INDICATORS OF TRANSPORT TERMINALS

The measurement of terminal productivity is the issue of extreme importance to both terminal owners and management and customers. As the sector of transport is highly intensive in terms of investments into the infrastructure, the productivity of a terminal may play a crucial role in competing with other terminals. Productivity is defined in terms of inputs and output. The majority of the available studies, wherein this issue is addressed, are generally focused on the determination of functional dependence between inputs and output using the method of regressive analysis. The present article provides an insight into the Data Envelopment Analysis method as a tool for measuring productivity. This technique enables a rather accurate evaluation of terminal productivity by means of comparative analysis, which, in fact, appears to be the only feasible alternative in cases where statistic data required for performing regressive analysis is lacking