Journal of Animal Science and Technology最新文献

Livestock production depends on the utilization of nutrients, and when this is accomplished, there is accelerated momentum toward growth with a low cost-to-feed ratio. Public concern over the consumption of pork with antibiotic residues in animals fed antibiotic growth promoters (AGP) has paved the way for using other natural additives to antibiotics, such as herbs and their products, probiotics, prebiotics, etc. Numerous feed additives are trending to achieve this goal, and a classic example is vitamins and minerals. Vitamins and minerals represent a relatively small percentage of the diet, but they are critical to animal health, well-being, and performance; both play a well-defined role in metabolism, and their requirements can vary depending on the physiological stage of the animals. At the same time, the absence of these vitamins and minerals in animal feed can impair the growth and development of muscles and bones. Most commercial feeds contain vitamins and trace minerals that meet nutrient requirements recommended by National Research Council and animal feeding standards. However, the potential variability and bioavailability of vitamins and trace elements in animal feeds remain controversial because daily feed intake varies, and vitamins are degraded by transportation, storage, and processing. Accordingly, the requirement for vitamins and minerals may need to be adjusted to reflect increased production levels, yet the information presented on this topic is still limited. Therefore, this review focuses on the role and function of different sources of minerals, the mode of action, the general need for micro and macro minerals in non-ruminant diets, and how they improve animal performance.

As the population and income levels rise, meat consumption steadily increases annually. However, the number of farms and farmers producing meat decrease during the same period, reducing meat sufficiency. Information and Communications Technology (ICT) has begun to be applied to reduce labor and production costs of livestock farms and improve productivity. This technology can be used for rapid pregnancy diagnosis of sows; the location and size of the gestation sacs of sows are directly related to the productivity of the farm. In this study, a system proposes to determine the number of gestation sacs of sows from ultrasound images. The system used the YOLOv7-E6E model, changing the activation function from sigmoid-weighted linear unit (SiLU) to a multi-activation function (SiLU + Mish). Also, the upsampling method was modified from nearest to bicubic to improve performance. The model trained with the original model using the original data achieved mean average precision of 86.3%. When the proposed multi-activation function, upsampling, and AutoAugment were applied, the performance improved by 0.3%, 0.9%, and 0.9%, respectively. When all three proposed methods were simultaneously applied, a significant performance improvement of 3.5% to 89.8% was achieved.

The Lactococcus taiwanensis strain K_LL004 was isolated from the gut of a grasshopper (Oxya chinensis sinuosa) collected from local farm in Korea. L. taiwanensis strain K_LL004 is the functional probiotic candidate with an ability to hydrolyse plant polysaccharides. The complete genome of the L. taiwanensis strain K_LL004 contains one circular chromosome (1,995,099 bp) with a guanine + cytosine (GC) content of 38.8%. Moreover, 1,929 Protein-coding sequence, 19 rRNA genes, and 62 tRNA genes were identified based on results of annotation. L. taiwanensis strain K_LL004 has a gene, which encodes hydrolytic enzymes such as beta-glucosidase and beta-xylosidase, that hydrolyzes plant polysaccharides.

Feed safety is needed to produce and provide safe animal feeds for consumers, animals, and the environment. Although feed safety regulations have been set for each country, there is a lack of clear feed safety regulations for each livestock. Feed safety regulations are mainly focused on heavy metals, mycotoxins, and pesticides. Each country has different safe levels of hazardous materials in diets. Safe levels of hazardous materials in diets are mostly set for mixed diets of general livestock. Although there is a difference in the metabolism of toxic materials among animals, the safe level of feed is not specific for individual animals. Therefore, standardized animal testing methods and toxicity studies for each animal are needed to determine the correct safe and toxic levels of hazardous materials in diets. If this goal is achieved, it will be possible to improve livestock productivity, health, and product safety by establishing appropriate feed safety regulations. It will also provide an opportunity to secure consumer confidence in feed and livestock products. Therefore, it is necessary to establish a scientific feed safety evaluation system suitable for each country's environment. The chance of outbreaks of new hazardous materials is increasing. Thus, to set up appropriate toxic levels or safe levels in feed, various toxicity methods have been used to determine toxic levels of hazardous materials for humans and animals. Appropriate toxic testing methods should be developed and used to accurately set up and identify toxicity and safe levels in food and feed.

This study investigated the effects of corn resistant starch (RS) on the anti-obesity properties, nutrient digestibility, and blood parameters in healthy beagles. Four spayed and six castrated beagle dogs were divided into a control group (CON) with a diet comprising rice and chicken meal and a treatment group (TRT) with a diet comprising corn with an increased RS content by heating-cooling and chicken meal. All dogs in the CON and TRT groups were fed a 1.2-fold higher energy diet than the daily recommended energy requirement for 16 weeks. Throughout the study period, the body weight of dogs in CON increased, whereas no change in body weight was observed in TRT, resulting in a significant difference in body weight between the two groups at the end of the experiment. Moreover, a significant reduction in the apparent total tract digestibility was observed upon the analysis of dry matter, nitrogen-free extract, and organic matter in TRT compared with that in CON. The complete blood cell composition and biochemical parameters were within the reference range in both groups. A significant increase in the concentration of serum adiponectin was found in TRT at the end of the experiment. These results suggest that the corn RS may be beneficial for weight management owing to its reduced nutrient digestibility.

This study was to investigate the effects of different phytogenic feed additives (PFA) dosage levels in growing- finishing pigs stressed by high stocking density. A total of 72 mix sexed 12 weeks growing pigs ([Landrace × Yorkshire] × Duroc) with initial body weight (BW) of 49.28 ± 4.58 kg were used for 8 weeks. There were 3 replicate pens in each treatment group, with 3 pigs per pen. The dietary treatment groups consisted of basal diets in animal welfare density (negative control [NC]), basal diet in high stocking density (positive control [PC]), PC + 0.04% essential oil (ES1), PC + 0.08% essential oil (ES2), PC + 0.10% bitter citrus extract & essential oil (CES1), PC + 0.20% bitter citrus extract & essential oil (CES2), PC + 0.05% grape pomace extract (GP1), PC + 0.10% grape pomace extract (GP2). The reduction of space allowance decreased (p < 0.05) average daily gain, feed efficiency, and digestibility of dry matter, crude protein, and gross energy. Also, the fecal score of PC groups increased (p < 0.05) compared with other groups. Basic behaviors (feed intake, standing, lying) were inactive (p < 0.05) and singularity behavior (biting) was increased (p < 0.10) under high stocking density. There was no difference in blood profile. However, the supplementation of PFA alleviated the negative effects such as reduced growth performance, nutrient digestibility, and some increasing stress indicators in th blood (cortisol) and animal behavior (biting). In conclusion, the negative effect of high stocking density was most effectively mitigated by the normal dosage of the mixture of bitter citrus extract and essential oil additive (CES1).

Focusing high marble deposition, Hanwoo feedlot system uses high-energy diet over the prolonged fattening period. However, due to the individual genetic variation, around 40% of them are graded into inferior quality grades (QG), despite they utilized the same resources. Therefore, focusing on development of a nutrigenomic based precision management model, this study was to evaluated the response to the divergent selection on genetic merit for marbling score (MS), under different dietary total digestible nutrient (TDN) levels. Total of 111 calves were genotyped and initially grouped according to estimated breeding value (high and low) for marbling score (MS-EBV). Subsequently, managed under two levels of feed TDN%, over the calf period, early, middle, and final fattening periods following 2 × 2 factorial arrangement. Carcasses were evaluated for MS, Back fat thickness (BFT) and Korean beef quality grading standard. As the direct response to the selection was significant, the results confirmed the importance of initial genetic grouping of Hanwoo steers for MS-EBV. However, dietary TDN level did not show an effect (p > 0.05) on the MS. Furthermore, no genetic-by-nutrition interaction for MS (p > 0.05) was also observed. The present results showed no correlation response on BFT (p > 0.05), which indicates that the selection based on MS-EBV can be used to enhance the MS without undesirable effect on BFT. Ultimate turnover of the Hanwoo feedlot operation is primarily determined by the QGs. The present model shows that the initial grouping for MS-EBV increased the proportion of carcasses graded for higher QGs (QG1⁺⁺ and QG1⁺) by approximately 20%. Moreover, there appear to be a potential to increase the proportion of QG 1⁺⁺ animals among the high-genetic group by further increasing the dietary energy content. Overall, this precision management strategy suggests the importance of adopting an MS based initial genetic grouping system for Hanwoo steers with a subsequent divergent management based on dietary energy level.

The objective of this study was to quantitatively estimate the level of grazing area damage in outdoor free-range pig production using a Unmanned Aerial Vehicles (UAV) with an RGB image sensor. Ten corn field images were captured by a UAV over approximately two weeks, during which gestating sows were allowed to graze freely on the corn field measuring 100 × 50 m². The images were corrected to a bird's-eye view, and then divided into 32 segments and sequentially inputted into the YOLOv4 detector to detect the corn images according to their condition. The 43 raw training images selected randomly out of 320 segmented images were flipped to create 86 images, and then these images were further augmented by rotating them in 5-degree increments to create a total of 6,192 images. The increased 6,192 images are further augmented by applying three random color transformations to each image, resulting in 24,768 datasets. The occupancy rate of corn in the field was estimated efficiently using You Only Look Once (YOLO). As of the first day of observation (day 2), it was evident that almost all the corn had disappeared by the ninth day. When grazing 20 sows in a 50 × 100 m² cornfield (250 m²/sow), it appears that the animals should be rotated to other grazing areas to protect the cover crop after at least five days. In agricultural technology, most of the research using machine and deep learning is related to the detection of fruits and pests, and research on other application fields is needed. In addition, large-scale image data collected by experts in the field are required as training data to apply deep learning. If the data required for deep learning is insufficient, a large number of data augmentation is required.

In this study, rumen temperature and environment in estral and non-estral Korean Native breeding cattle were evaluated by using a bolus sensor. Behavioral and physiological changes in study animals were also assessed. To assess the rumen temperature and environment, we inserted bolus sensors into 12 Korean Native cattle with an average age of 35.5 months, then measured temperature and activity within the rumen using the wireless bolus sensor. Drinking, feeding and mounting behavior, and measured vaginal temperature and levels of intravaginal mucus resistance were recorded. We found that cattle in estrus exhibited more acts of mounting (37.4 vs. 0 times/day), increased vaginal temperature (39.0°C vs. 38.4°C), and decreased vaginal mucus resistance (136.3 Ω vs 197.4 Ω), compared with non-estral animals. Furthermore, increased levels of rumen activity were most significant in estrus cattle at the highest activity levels (p < 0.01). Overall, the estrus group exhibited increased rumen temperature (p = 0.01), compared with the non-estrus group. In conclusion, the results of this study not only provide basic physiological data related to estrus in improved Korean Native breeding cattle, but also suggest that monitoring of rumen temperature and activity might be used as an effective smart device for estrus detection.

Rumination in cattle is closely related to their health, which makes the automatic monitoring of rumination an important part of smart pasture operations. However, manual monitoring of cattle rumination is laborious and wearable sensors are often harmful to animals. Thus, we propose a computer vision-based method to automatically identify multi-object cattle rumination, and to calculate the rumination time and number of chews for each cow. The heads of the cattle in the video were initially tracked with a multi-object tracking algorithm, which combined the You Only Look Once (YOLO) algorithm with the kernelized correlation filter (KCF). Images of the head of each cow were saved at a fixed size, and numbered. Then, a rumination recognition algorithm was constructed with parameters obtained using the frame difference method, and rumination time and number of chews were calculated. The rumination recognition algorithm was used to analyze the head image of each cow to automatically detect multi-object cattle rumination. To verify the feasibility of this method, the algorithm was tested on multi-object cattle rumination videos, and the results were compared with the results produced by human observation. The experimental results showed that the average error in rumination time was 5.902% and the average error in the number of chews was 8.126%. The rumination identification and calculation of rumination information only need to be performed by computers automatically with no manual intervention. It could provide a new contactless rumination identification method for multi-cattle, which provided technical support for smart pasture.