The intestinal microbiota affect various physiological traits of host animals such as brain development, obesity, age, and the immune system. In the swine industry, understanding the relationship between intestinal microbiota and growth stage is essential because growth stage is directly related to the feeding system of pigs, thus we studied the intestinal microbiota of 32 healthy pigs across five sows at 10, 21, 63, 93, and 147 d of ages. The intestinal microbiota were altered with growth of pigs and were separated into three distinct clusters. The relative abundance of several phyla and genera were significantly different between growth stages. We observed co-occurrence pattern of the intestinal microbiota at each growth stage. In addition, we predicted the functions of the intestinal microbiota and confirmed that several KEGG pathways were significantly different between growth stages. We also explored the relationship between the intestinal microbiota and innate factors such as the maternal effect and gender. When pigs were young, innate factors affected on construction of intestinal microbiota, however this tendency was disappeared with growth. Our findings broaden the understanding of microbial ecology, and the results will be used as a reference for investigating host-microbe interactions in the swine industry.

In the poultry industry, many efforts have been undertaken to further improve the growth performance of broilers and identification and modulation of body weight (BW)-related bacteria could be one of the strategies to improve productivity. However, studies regarding the relationship between microbiota and BW are scarce. The objective of the present study was to investigate the relationship between microbiota and BW in different sections of the gastrointestinal tract (GIT). A total of twenty 18-day-old birds were selected based on the BW, and samples were collected from the three different sections of the GIT, which included the crop, ileum and cecum. Bacterial genomic DNA was extracted from the samples, and the V4 region of 16S rRNA gene were amplified. Amplicons were sequenced on Illumina MiSeq, and microbial communities were analyzed by using QIIME. In principal coordinate analysis, bacterial communities were clustered into three groups, based on the sections of GIT. Several BW-related bacterial groups were identified from linear regression analysis. At the genus level, Streptococcus from the ileum as well as Akkermansia in both ileum and cecum, were negatively related to BW, whereas Bifidobacterium in the ileum and Lactococcus in the cecum showed a positive correlation. The results from the present study showed that particular bacterial communities in the GIT were related to BW, and the study has broadened the understanding of the intestinal microbial ecosystem in broiler chickens.Electronic supplementary materialThe online version of this article (doi:10.1186/s40064-016-2604-8) contains supplementary material, which is available to authorized users.

Due to the ban on the use of antimicrobial growth promoters in livestock feeds, understanding the relationship between intestinal microbiota and the physiology of the host has become very important for improving livestock performance. In this study, we investigated the relationship between intestinal microbiota and body weights of weaned piglets. Lighter (n = 9) and heavier (n = 9) 9-week-old weaned piglets were selected from approximately one hundred individuals based on their body weights. Their fecal microbial communities were analyzed by sequencing the V4 region of the 16S rRNA gene. The microbial richness estimators of the heavier piglets were significantly higher than those of the lighter piglets. At the phylum level, the microbiota of the heavier group had significantly higher levels of Firmicutes and a higher Firmicutes-to-Bacteroidetes ratio than that of the lighter group. At the genus level, the levels of several genera, such as Anaerococcus and Lactococcus, were significantly different in the two groups. In particular, the lighter group had significantly higher levels of opportunistic pathogenic bacteria, such as Anaerotruncus and Bacteroides, compared with those of the heavier group. Moreover, the levels of bacteria expressing the components of several metabolic pathways were significantly different in the two groups. The microbiota of the heavier group had a significantly higher involvement in three KEGG pathways concerned with xenobiotic degradation than that of the lighter group. These results may provide insights into host-microbe interactions occurring in the piglet intestine and will be useful in establishing a strategy for improving growth performance in the swine industry.

Double squirrel cage rotor design is employed in induction motor applications that require high starting torque and high efficiency operation. The outer cage of double cage rotors is vulnerable to fatigue failure since it must withstand the large thermal/mechanical stresses experienced during a loaded startup due to the high starting current and long acceleration time. However, there are only a few publications that investigate broken bar detection for double cage induction motors. In this paper, the detectability of broken outer cage bars in double cage motors for the most commonly used rotor bar test methods is evaluated. A finite element and experimental study show that the sensitivity of on-line MCSA is significantly decreased, whereas that of off-line standstill tests is not influenced for broken outer cage bars. This suggests that one should be aware of the insensitivity of MCSA for double cage rotors, and there is a need for development of new on-line monitoring methods.

Unlike single cage rotor fault detection, FFTbased steady state spectrum analysis techniques can fail to detect outer cage faults in double cage induction motors due to the small outer cage current under running conditions. Double cage motors are typically employed in applications that require loaded starts. This makes the outer cage vulnerable to fatigue failure since it must withstand the high starting current and long startup time frequently. However, there are only a few publications that investigate detection techniques specifically for double cage motors. In this paper, considering that the influence of the faulty outer cage is strong at startup due to the large outer cage current, detection of outer cage faults under the startup transient is investigated. A Discrete Wavelet Transform-based method is proposed as a viable solution to detection of outer cage faults for double cage motors. An experimental study on fabricated copper double cage induction motors shows that the proposed method provides sensitive and reliable detection of double cage rotor faults compared to FFT.