This study was conducted to investigate changes in immunoglobulin G (IgG) concentration, nutrient content, and microbial communities of fresh and heat-treated Holstein colostrum collected from a colostrum bank operated by a local agricultural technology center in Gyeongsangbuk-do, South Korea. Of the 16 colostrum samples, 8 were heated at 60℃ for 30 min under a pressure of 0.9–1 bar. The colostrum samples were stored at −70℃ until use, at which time they were thawed at 50–55℃ in a water bath to analyze IgG levels, chemical composition, and microbiome, which was identified by 16S rRNA gene sequencing using the Illumina MiSeq-PE250 platform. The IgG concentrations were similar in fresh and heat-treated colostrum. The fat, protein, and lactose contents also did not differ in these samples. However, somatic cell count (SCC) was lower in heat-treated colostrum than those in fresh colostrum (p<0.05). At the phylum level for the microbiome of fresh colostrum, Proteobacteria (44.16%) was the most abundant taxa, followed by Bacteroidota (33.26%), Firmicutes (10.04%), Actinobacteriota (7.14%), and a marginal difference in the order of abundance was observed in heat-treated colostrum. At the genus level, bacteria belonging to Sphingomonas, Delftia, Ochrobactrum, Simplicispira, and Lactobacillus were more abundant (p<0.05) in the heat-treated colostrum, while the abundance of Acinetobacter in the fresh colostrum was four times more (p<0.05) than that in the heat-treated colostrum. Our results demonstrated that heating does not affect IgG level and colostrum composition but reduces SCC (p<0.05), suggesting that heat-treated colostrum can potentially be put to further use (e.g., feeding Hanwoo calves) without compromising its quality. Differences in the microbiome between the fresh and heat-treated colostrum were limited. Further studies are required to extensively investigate the quality and safety of colostrum collected from dairy farms to ensure better utilization and processing at a local agricultural technology center.

We have developed an algorithm for tracking coronal mass ejection (CME) propagation that allows us to estimate CME speed and its arrival time at Earth. The algorithm may be used either to forecast the CME’s arrival on the day of the forecast or to update the CME tracking information for the next day’s forecast. In our case study, we successfully tracked CME propagation using the algorithm based on g-values of interplanetary scintillation (IPS) observation provided by the Institute for Space- Earth Environmental Research (ISEE). We were able to forecast the arrival time (Δt = 0.30 h) and speed (Δv = 20 km/s) of a CME event on October 2, 2000. From the CME-interplanetary CME (ICME) pairs provided by Cane & Richardson (2003), we selected 50 events to evaluate the algorithm’s forecast capability. Average errors for arrival time and speed were 11.14 h and 310 km/s, respectively. Results demonstrated that g-values obtained continuously from any single station observation were able to be used as a proxy for CME speed. Therefore, our algorithm may give stable daily forecasts of CME position and speed during propagation in the region of 0.2–1 AU using the IPS g-values, even if IPS velocity observations are insufficient. We expect that this algorithm may be widely accepted for use in space weather forecasting in the near future.