This study was conducted to investigate the effects of dietary supplementation with fermented and non-fermented brown algae by-products on the laying performance, egg quality, relative organ weight, and blood profile of laying hens. Hy-Line Brown chickens (n = 180; 70-week-old) were randomly divided into 5 groups with 4 replicates per group (3 hens per cage, 4 cages per replicate), and fed with 5 experimental diets, namely the basal control diet (CON) or the control diet supplemented with 0.5% brown seaweed (BS), 0.5% seaweed fusiforme (SF), 0.5% fermented brown seaweed (FBS), or 0.5% fermented seaweed fusiforme (FSF), for 4 weeks. Egg production rate and egg mass were greater in the BS group than in the other groups (p<0.05), and the SF and FSF groups had greater egg production than the control group (p<0.05). Egg weight was higher in the BS group than in the other groups (p<0.05). There were no differences in eggshell color, egg yolk color, eggshell strength, or eggshell thickness among the groups. There was no difference in Haugh units among the treatment groups, except for the FSF group, which had a significantly lower value (p<0.05). The non-fermented groups had greater relative organ weights, particularly the liver and cecum, than the other groups (p<0.05). Regarding blood profile, the supplemented-diet groups had higher albumin levels than the control group (p<0.05). The FBS group had higher total cholesterol and triglyceride levels than the other groups (p<0.05). The BS and FBS groups had higher glutamic pyruvic transaminase levels than the other groups (p<0.05). This study demonstrated that dietary brown algae supplementation can improve egg-laying performance; however, supplementation with fermented seaweeds had no positive effect on the egg-laying performance of hens.

The objective of this study was to identify Hanwoo cattle via a deep-learning model using muzzle images. A total of 9230 images from 336 Hanwoo were used. Images of the same individuals were taken at four different times to avoid overfitted models. Muzzle images were cropped by the YOLO v8-based model trained with 150 images with manual annotation. Data blocks were composed of image and national livestock traceability numbers and were randomly selected and stored as train, validation test data. Transfer learning was performed with the tiny, small and medium versions of Efficientnet v2 models with SGD, RMSProp, Adam and Lion optimizers. The small version using Lion showed the best validation accuracy of 0.981 in 36 epochs within 12 transfer-learned models. The top five models achieved the best validation accuracy and were evaluated with the training data for practical usage. The small version using Adam showed the best test accuracy of 0.970, but the small version using RMSProp showed the lowest repeated error. Results with high accuracy prediction in this study demonstrated the potential of muzzle patterns as an identification key for individual cattle.

This study was conducted to evaluate the effects of high-temperature stress on dairy cow productivity and the correlation between rumen sensors. The data were collected on the temperature, humidity, milk productivity, milk components, blood components, and rumen sensor data from 125 dairy cows during the experimental period (1 May 2020 to 30 October 2020). High-temperature stress of dairy cows was evaluated based on the temperature–humidity index (THI). The correlations between the high-temperature stress, productivity, and sensor data were analyzed using SAS and R programs. The THI ranged from 46.9 to 81.0 during the experimental period, and a significant decrease was observed in the milk production of dairy cows during August (p < 0.05). Milk production was evaluated to decrease by 1.8% because of high-temperature stress during the experimental period. There was a significantly high negative correlation between the THI ratio of day and rumen temperature (r = 0.744; p < 0.001). The other rumen sensor data did not show a significant correlation with the productivity of dairy cows. The results can be utilized as a guideline for managing temperature and humidity to maintain dairy cow productivity on farms in high-temperature stress conditions.

The objective of the study was to determine the effect of fermented spent coffee ground (FSCG) on nutrient digestibility and nitrogen utilization in sheep. Fermentation of spent coffee ground (SCG) was conducted using Lactobacillus plantrum. Fermentation was performed at moisture content of 70% and temperature of 39°C with anaerobic air tension for 48 h. Four adult rams (initial body weight = 56.8±0.4 kg) were housed in a respiration-metabolism chamber and the treatments were: i) control (Basal diet; 0% SCG or FSCG), ii) 10% level of SCG, iii) 10% level of FSCG, and iv) 20% level of FSCG in 4×4 Latin square design. Each dietary experiment period lasted for 18-d with a 14-d of adaptation period and a 4-d of sample collection period. In SCG fermentation experimental result, acid detergent insoluble nitrogen (ADIN) concentration of FSCG (64.5% of total N) was lower than that of non-fermented SCG (78.8% of total N). Digestibility of dry matter and organic matter was similar among treatment groups. Although crude protein (CP) digestibility of the control was greater than FSCG groups (p< 0.05), the 10% FSCG group showed greater CP digestibility and nitrogen retention than non-fermented 10% SCG group (p<0.05). Body weight gain and average daily gain were linearly decreased with increasing FSCG feeding level (p<0.05). When the feeding level of FSCG was increased, water intake was linearly increased (p<0.05). With an increasing FSCG level, dry matter intake did not differ among groups, although the gain to feed ratio tended to decrease with increasing level of FSCG (p<0.10). Microbial fermentation of SCG can improve protein digestibility, thereby increasing CP digestibility and nitrogen utilization in sheep. Fermentation using microorganisms in feed ingredients with low digestibility could have a positive effect on improving the quality of raw feed.

Two experiments were conducted to determine the effects of forage-to-concentrate (F:C) ratio on the nutrient digestibility and enteric methane (CH4) emission in growing goats and Sika deer. Three male growing goats (body weight [BW] = 19.0±0.7 kg) and three male growing deer (BW = 19.3±1.2 kg) were respectively allotted to a 3×3 Latin square design with an adaptation period of 7 d and a data collection period of 3 d. Respiration-metabolism chambers were used for measuring the enteric CH4 emission. Treatments of low (25:75), moderate (50:50), and high (73:27) F:C ratios were given to both goats and Sika deer. Dry matter (DM) and organic matter (OM) digestibility decreased linearly with increasing F:C ratio in both goats and Sika deer. In both goats and Sika deer, the CH4 emissions expressed as g/d, g/kg BW0.75, % of gross energy intake, g/kg DM intake (DMI), and g/kg OM intake (OMI) decreased linearly as the F:C ratio increased, however, the CH4 emissions expressed as g/kg digested DMI and OMI were not affected by the F:C ratio. Eight equations were derived for predicting the enteric CH4 emission from goats and Sika deer. For goat, equation 1 was found to be of the highest accuracy: CH4 (g/d) = 3.36+4.71×DMI (kg/d)-0.0036×neutral detergent fiber concentrate (NDFC, g/kg)+0.01563×dry matter digestibility (DMD, g/kg)-0.0108×neutral detergent fiber digestibility (NDFD, g/kg). For Sika deer, equation 5 was found to be of the highest accuracy: CH4 (g/d) = 66.3+27.7×DMI (kg/d)-5.91×NDFC (g/kg)-7.11× DMD (g/kg)+0.0809×NDFD (g/kg). Digested nutrient intake could be considered when determining the CH4 generation factor in goats and Sika deer. Finally, the enteric CH4 prediction model for goats and Sika deer were estimated.

This study was conducted to evaluate the fermentation characteristics under low mesophilic temperature of spent instant coffee ground (SICG) and to estimate the effect of fermented SICG (FSICG) as alternative feed ingredient on milk productivity of dairy cows. In the fermentation trial, fermentation of SICG was performed to investigate changes in characteristics using the microbial mixture (Lactobacillus plantarum, Saccharomyces cerevisiae, and Bacillus subtilis = 1:1:1) for 21 days at 20°C under anaerobic conditions. Molasses was added at 5% of dry mass. In the animal trial, eighteen Holstein Friesian cows were used to evaluate the nutritive value of the FSICG which was fermented for 14 days under the same condition as the fermentation trial. In the fermentation trial, the dry matter (DM) and organic matter content linearly decreased with fermentation time (p<0.001 and p = 0.008, respectively). The acid detergent insoluble nitrogen content linearly decreased with fermentation time (p = 0.037). The microorganism counts linearly increased for Lactobacillus plantarum, Saccharomyces cerevisiae, and Bacillus subtilis across fermentation time (p<0.001). In the animal trial, the DM intake of the control and FSICG treatment were not significantly different, as were milk yield, 4% fat corrected milk, fat-protein corrected milk, and feed to milk conversion content. Fat, protein, lactose, non-fat solids, milk urea nitrogen, and somatic cell counts were also not significantly different in milk composition between treatments. FSICG should be considered a sufficient substitute for cottonseed as a feed component, and 5% DM of a dietary FSICG level was appropriate for dairy cow diets.