scholarly journals Effects of the higher concentrate ratio on the production performance, ruminal fermentation, and morphological structure in male cattle‐yaks

Author(s):  
Yahui Jiang ◽  
Peng Dai ◽  
Qindan Dai ◽  
Jian Ma ◽  
Zhisheng Wang ◽  
...  
2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Kacper Libera ◽  
Malgorzata Szumacher-Strabel ◽  
Mina Vazirigohar ◽  
Wiktor Zieliński ◽  
Rafal Lukow ◽  
...  

AbstractThe starch content of triticale and oat grains provides much of their readily available energy. Synchronizing energy and nitrogen in the rumen is important in optimizing profitability; for this reason, ammonia processing of these grains was evaluated for its potential to modify ruminal fermentation and to improve milk production performance. A mixture of ground triticale and oats (CONG, in a 60:40 ratio 40 by DM) was treated with urea (5 kg/1000 kg) and urease additive (20 kg/1000 kg) containing 200 g/kg of moisture, for 2 wk (UREG). The urea treatment enhanced the pH and CP content of grains by 34% and 52%, respectively. In a batch culture study, CONG or UREG as the only substrate was incubated in a buffered ruminal fluid. Compared to CONG, UREG increased pH, total VFA concentration, total gas, and disappearance of DM, while reducing CH4 production, whereas NH3 concentration increased and entodiniomorph counts tended to increase. In the in vivo study, cows were randomly allocated to two dietary groups (n = 24) and were offered TMR based on maize and grass silage, containing either 155 g/kg of CONG and 80 g/kg of soybean meal (CONT) or 155 g/kg of UREG and 59 g/kg of soybean meal (URET) for 31 d. Ruminal fluid was collected (n = 10) using rumenocentesis. The relative abundances of Streptococcus bovis decreased, but Megasphaera elsdenii, methanogens, and ammonia-producing bacteria increased by URET. Entodiniomorph and holotrich counts were decreased by URET. Feeding with URET increased ruminal pH and concentrations of total VFA, acetate, branched-chain VFA, and NH3. Feeding with URET also increased milk yield. These results demonstrate that replacing untreated triticale and oat grains with urea-treated grains can beneficially modulate ruminal microbiota and fermentation, consequently improving production performance and profitability.


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Yajing Ban ◽  
Le Luo Guan

AbstractDirect-fed microbials (DFMs) are feed additives containing live naturally existing microbes that can benefit animals’ health and production performance. Due to the banned or strictly limited prophylactic and growth promoting usage of antibiotics, DFMs have been considered as one of antimicrobial alternatives in livestock industry. Microorganisms used as DFMs for ruminants usually consist of bacteria including lactic acid producing bacteria, lactic acid utilizing bacteria and other bacterial groups, and fungi containing Saccharomyces and Aspergillus. To date, the available DFMs for ruminants have been largely based on their effects on improving the feed efficiency and ruminant productivity through enhancing the rumen function such as stabilizing ruminal pH, promoting ruminal fermentation and feed digestion. Recent research has shown emerging evidence that the DFMs may improve performance and health in young ruminants, however, these positive outcomes were not consistent among studies and the modes of action have not been clearly defined. This review summarizes the DFM studies conducted in ruminants in the last decade, aiming to provide the new knowledge on DFM supplementation strategies for various ruminant production stages, and to identify what are the potential barriers and challenges for current ruminant industry to adopt the DFMs. Overall literature research indicates that DFMs have the potential to mitigate ruminal acidosis, improve immune response and gut health, increase productivity (growth and milk production), and reduce methane emissions or fecal shedding of pathogens. More research is needed to explore the mode of action of specific DFMs in the gut of ruminants, and the optimal supplementation strategies to promote the development and efficiency of DFM products for ruminants.


Author(s):  
H. Mirzaei-Alamouti ◽  
A. Mohammad ◽  
M. Vazirigohar ◽  
P. Rezamand ◽  
M. Mansouryar

Abstract This study investigated whether the interaction of protein level and grain type can affect milk production, nutrient digestibility and rumen fermentation in primiparous Holstein cows. Four dietary treatments were used: high-protein with barley as the only grain source, HP-B; (2) high-protein with an equal mix of barley and maize, HP-BM; (3) low-protein with barley as the only grain source, LP-B and (4) low-protein with equal proportions of barley and maize, LP-BM. High-protein diets showed no improvement in milk or protein yield compared with low-protein, but barley and maize mix diets increased energy-corrected milk yield and fat yield compared with barley-only diets. The highest total apparent digestibility of dry matter, organic matter and neutral detergent fibre was observed for LP-BM whereas HP-BM showed the greatest crude protein digestibility. Treatment had no effect on total volatile fatty acid concentrations, molar proportion of acetate and propionate and acetate to propionate ratio. The lowest ruminal pH was observed for LP-B. High-protein diets resulted in greater concentrations of ammonia nitrogen (N), urinary N, blood and milk urea nitrogen compared with low-protein diets, whereas low-protein diets showed better nitrogen utilization efficiency. This study showed that primiparous lactating cows do not benefit from high-protein diets with different fermentation rates of grain sources, but barley and maize diets may improve milk production performance, ruminal fermentation and pH under the present dietary conditions. The current results on milk production performance should be interpreted with caution due to the small number of cows used (eight in each treatment).


2017 ◽  
Vol 30 (10) ◽  
pp. 1416-1424 ◽  
Author(s):  
Jinshun Zhan ◽  
Mingmei Liu ◽  
Xiaoshuang Su ◽  
Kang Zhan ◽  
Chungang Zhang ◽  
...  

2021 ◽  
pp. 1-11
Author(s):  
Basim Refat ◽  
David A. Christensen ◽  
Aya Ismael ◽  
Xin Feng ◽  
María E. Rodríguez-Espinosa ◽  
...  

This study was performed to evaluate the effects of pre-treating a barley-silage-based diet with an exogenous fibrolytic enzyme derived from Trichoderma reesei (FETR, a mixture of xylanase and cellulase) on lactation performance, omasal nutrient flow and digestibility, rumen fermentation characteristics, and rumen pH profile in Holstein dairy cows during early lactation. The dairy trial was conducted using nine Holstein dairy cows (averaging 46 ± 24 days in milk and 697 ± 69 kg body weight, six cows were fitted with a rumen cannula, and three were non-cannulated). Two groups of cows were randomly assigned to each of the dietary treatments in a crossover design: control (without FETR supplementation) and supplemented [with 0.75 mL of FETR·kg−1 dry matter (DM) of the diet based on our previous study]. The application of FETR tended to decrease the DM intake compared with control. There were no effects of FETR (P > 0. 10) on omasal nutrient flow and digestibility, rumen fermentation characteristics, and rumen pH profile. In conclusion, this study lacks evidence that the fibrolytic enzyme (at a level of 0.75 mL of FETR·kg−1 DM) can affect nutrient digestibility, ruminal fermentation, and the performance of early-lactation cows. Further study with larger animal trials are needed.


Author(s):  
James Pawley ◽  
David Joy

The scanning electron microscope (SEM) builds up an image by sampling contiguous sub-volumes near the surface of the specimen. A fine electron beam selectively excites each sub-volume and then the intensity of some resulting signal is measured and then plotted as a corresponding intensity in an image. The spatial resolution of such an image is limited by at least three factors. Two of these determine the size of the interaction volume: the size of the electron probe and the extent to which detectable signal is excited from locations remote from the beam impact area. A third limitation emerges from the fact that the probing beam is composed of a number of discrete particles and therefore that the accuracy with which any detectable signal can be measured is limited by Poisson statistics applied to this number (or to the number of events actually detected if this is smaller). As in all imaging techniques, the limiting signal contrast required to recognize a morphological structure is constrained by this statistical consideration. The only way to overcome this limit is to increase either the contrast of the measured signal or the number of beam/specimen interactions detected. Unfortunately, these interactions deposit ionizing radiation that may damage the very structure under investigation. As a result, any practical consideration of the high resolution performance of the SEM must consider not only the size of the interaction volume but also the contrast available from the signal producing the image and the radiation sensitivity of the specimen.


2020 ◽  
pp. 1-12
Author(s):  
Li Dongmei

English text-to-speech conversion is the key content of modern computer technology research. Its difficulty is that there are large errors in the conversion process of text-to-speech feature recognition, and it is difficult to apply the English text-to-speech conversion algorithm to the system. In order to improve the efficiency of the English text-to-speech conversion, based on the machine learning algorithm, after the original voice waveform is labeled with the pitch, this article modifies the rhythm through PSOLA, and uses the C4.5 algorithm to train a decision tree for judging pronunciation of polyphones. In order to evaluate the performance of pronunciation discrimination method based on part-of-speech rules and HMM-based prosody hierarchy prediction in speech synthesis systems, this study constructed a system model. In addition, the waveform stitching method and PSOLA are used to synthesize the sound. For words whose main stress cannot be discriminated by morphological structure, label learning can be done by machine learning methods. Finally, this study evaluates and analyzes the performance of the algorithm through control experiments. The results show that the algorithm proposed in this paper has good performance and has a certain practical effect.


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