• Asian-Australasian Journal of Animal Sciences
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• v.30 no.11
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• pp.1643-1650
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• 2017

Objective: The control of psychrotrophic bacteria causing milk spoilage and illness due to toxic compounds is an important issue in the dairy industry. In South Korea, Gangwon-do province is one of the coldest terrains in which eighty percent of the area is mountainous regions, and mainly plays an important role in the agriculture and dairy industries. The purposes of this study were to analyze the indigenous microbiota of raw milk in Gangwon-do and accurately investigate a putative microbial group causing deterioration in milk quality. Methods: We collected raw milk from the bulk tank of 18 dairy farms in the Hoengseong and Pyeongchang regions of Gangwon-do. Milk components were analyzed and the number of viable bacteria was confirmed. The V3 and V4 regions of 16S rRNA gene were amplified and sequenced on an Illumina Miseq platform. Sequences were then assigned to operational taxonomic units, followed by the selection of representative sequences using the QIIME software package. Results: The milk samples from Pyeongchang were higher in fat, protein, lactose, total solid, and solid non-fat, and bacterial cell counts were observed only for the Hoengseong samples. The phylum Proteobacteria was detected most frequently in both the Hoengseong and Pyeongchang samples, followed by the phyla Firmicutes and Actinobacteria. Notably, Corynebacterium, Pediococcus, Macrococcus, and Acinetobacter were significantly different from two regions. Conclusion: Although the predominant phylum in raw milk is same, the abundances of major genera in milk samples were different between Hoengseong and Pyeongchang. We assumed that these differences are caused by regional dissimilar farming environments such as soil, forage, and dairy farming equipment so that the quality of milk raw milk from Pyeongchang is higher than that of Hoengseong. These results could provide the crucial information for identifying the microbiota in raw milk of South Korea.

• Journal of Veterinary Science
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• v.23 no.3
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• pp.33.1-33.10
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• 2022

Background: Endemic circulation of human-specific hepatitis E virus (HEV) genotypes 1 and 2 may occult the importance of sporadic zoonotic HEV transmissions in Africa. Increasing numbers of studies reporting anti-HEV antibodies in cattle and the discovery of infectious HEV in cow milk has raised public health concern, but cattle exposure has seldom been investigated in Africa. Objectives: This study aimed at investigating the role of cows in the epidemiology of HEV in Burkina Faso and farmers habits in terms of dairy product consumption as a prerequisite to estimate the risk of transmission to humans. Methods: Sera from 475 cattle and 192 pigs were screened for the presence of anti-HEV antibodies while HEV RNA in swine stools was detected by reverse transcription polymerase chain reaction. Data on mixed farming, dairy product consumption and selling habits were gathered through questionnaires. Results: The overall seroprevalence in cattle was 5.1% and herd seroprevalence reached 32.4% (11/34). Herd seropositivity was not associated with husbandry practice or presence of rabbits on the farms. However, herd seropositivity was associated with on-site presence of pigs, 80.7% of which had anti-HEV antibodies. The majority of farmers reported to preferentially consume raw milk based dairy products. Conclusions: Concomitant presence of pigs on cattle farms constitutes a risk factor for HEV exposure of cattle. However, the risk of HEV infections associated with raw cow dairy product consumption is currently considered as low.

• Asian-Australasian Journal of Animal Sciences
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• v.12 no.1
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• pp.68-76
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• 1999

A formal survey was carried out in Nharira-Lancashire areas located in Chivhu to assess the calf rearing systems practiced in smallholder dairy farming areas of Zimbabwe. A total of 47 farmers, collectively owning 305 cows and 194 calves of various breeds, participated in the survey. All the farmers allowed their calves to suckle their dams all day to obtain colostrum. The colostrums intake period was significantly (p < 0.05) shorter (5.2 vs 4.1 days) in the small scale commercial area (SSCA) compared to communal area (CA). Milk was first sold to the Nharira-Lancashire Milk Centre a day after the colostrum intake period ended. Most of the CA (91.3%) and SSCA (77.8%) farmers penned their cows and calves together at night during the colostrum intake period. Thereafter the calves were penned separate from their dams. After colostrum intake, two types of calf suckling systems were practised; twice a day suckling and twice a day then changed to once a day suckling. In both systems, suckling was allowed for 30 minutes after the cows had been hand milked. There was no significant (p < 0.05) difference in the mean weaning age of calves between the CA and SSCA (5.8 vs 5.4 months). The most common weaning method was through separation of the calves from the dams. The limitaitions to calf production in Chivhu were the prohibitively high costs of calf meals, poor feed resources during the dry season, a general lack of knowledge on calf rearing diseases and inappropriate calf housing.

• Asian-Australasian Journal of Animal Sciences
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• v.26 no.8
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• pp.1119-1126
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• 2013

The objective of this study was to compare the goodness of fit of four lactation curve models: Wood's Gamma model (WD), Wilmink (WL), and Pollott's multiplicative two (POL2) and three parameters (POL3) and to determine the environmental factors affecting the complete lactation curve of F1 dairy sheep under organic management. A total of 5,382 weekly milk yields records from 150 ewes, under organic management were used. Residual mean square (RMS), determination coefficients ($R^2$), and correlation (r) analysis were used as an indicator of goodness of fit for each model. WL model best fitted the lactation curves as indicated by the lower RMS values (0.019), followed by WD (0.023), POL2 (0.025) and POL3 (0.029). The four models provided total milk yield (TMY) estimations that were highly correlated (0.93 to 0.97) with observed TMY (89.9 kg). The four models under estimated peak yield (PY), whereas POL2 and POL3 gave nearer peak time lactation estimations. Ewes lambing in autumn had higher TMY and showed a typical curve shape. Higher TMY were recorded in second and third lambing. Season of lambing, number of lambing and type of lambing had a great influenced over TMY shaping the complete lactation curve of F1 dairy sheep. In general terms WL model showed the best fit to the F1 dairy sheep lactation curve under organic management.

• Asian-Australasian Journal of Animal Sciences
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• v.8 no.5
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• pp.481-487
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• 1995

A survey of physical inputs was conducted on the total population of dairy farms supplying milk to the Rewa cooperative dairy company in Fiji. The critical inputs associated with total farm milk production were determined using multiple regression, with analyses being conducted for each of the three identified supplier groups, bulk milk, canned milk and cream. Mean annual milk production per cow averaged 1460 (s.d. = 319), 889 (s.d. = 321) and 800 (s.d. = 451) litres for the bulk milk, canned milk and cream suppliers respectively. Stocking rate averaged 1.37 (s.d. = 1.18) cows per hectare over all farms. Inputs to pasture were universally low and Navua sedge (Cyperus aromaticus) was identified as a major weed. The average amount of supplement fed annually on a grain equivalent basis was 700 (s.d. = 984) kg per cow for bulk milk, 84 (s.d. = 198) kg per cow for canned milk and 146 (s.d. = 542) kg per cow for cream suppliers. The analysis of data from a small group of farms using nitrogen fertiliser indicated that their production levels were higher than the general population. This suggests that there is potential for the Fijian dairy industry to increase milk production through the use of higher inputs to cows and pastures. The regression models relating annual milk production from farms to the two key inputs of number of cows milked and the amount of supplement fed were all significant (p < 0.001). The coefficients of determination for these models ranged from 56.9 to 89.4 percent.

• Asian-Australasian Journal of Animal Sciences
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• v.21 no.1
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• pp.42-50
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• 2008

Twenty-four, lactating dairy cows were randomly assigned according to a Rrandomized complete block design (RCBD) to investigate the effect of sunflower oil supplementation (SFOS) with cassava hay based-diets on feed intake, digestibility of nutrients, rumen fermentation efficiency and milk production. The treatments were as follows: T1 = Control, using commercial concentrate as a supplement (CON); T2 = Concentrate with cassava hay (CHSO-0); T3 = Concentrate with cassava hay and 2.5% sunflower oil (CHSO-2.5); T4 = Concentrate with cassava hay and 5% sunflower oil (CHSO-5). The cows were offered concentrate feed at a ratio of concentrate to milk production of 1:2 and urea-treated rice straw was fed ad libitum. The results revealed that feed intake, digestibility of nutrients and ruminal pH were similar among all treatments, while ruminal NH3-N was lower (p<0.05) with SFOS. Blood urea-N (BUN) and milk urea-N (MUN) were not significantly affected by SFOS. The ruminal concentrations of volatile fatty acids were significantly different among the treatments. Sunflower oil supplementation significantly increased concentrations of unsaturated fatty acids, and ratio of unsaturated to saturated fatty acids in the milk, particularly the conjugated fatty acids, was significantly enhanced. Furthermore, production costs of treatments with sunflower oil supplementation were lower than for the control. Based on this study, SFOS in cassava hay based-diets improves rumen ecology, milk yield and milk quality, especially in terms of conjugated linoleic acids.

• Animal Bioscience
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• v.37 no.5
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• pp.944-951
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• 2024

Objective: Parturition is crucial for dams, their calves, and cow managers. The prediction of calving time, which assists cow managers to decide on the relocation of cows to maternity pens and necessity of human supervision, is a pivotal aspect of livestock farming. However, existing methods of predicting calving time in dairy cows based on hormonal changes and clinical symptoms are time-consuming and yield unreliable predictions. Accordingly, we investigated whether heart rate variability (HRV) which is a non-invasive assessment of autonomic nervous system (ANS) activity and behavior during the prepartum period would be useful for predicting calving time in dairy cows. Methods: Eight pregnant cows were surveilled under electrocardiogram and video recordings for HRV and behavioral analyses, respectively. HRV parameters in time and frequency domains were evaluated. A 24-h time budget was calculated for each of six types of behavior (standing and lying with or without rumination, sleeping, and eating). Results: Heart rate on calving day is considerably higher than those recorded on the days preceding calving. Low frequency power declined, whereas high frequency power escalated on the calving day compared to the period between 24 and 48 h before calving. The time budget for ruminating while lying decreased and that while standing increased markedly on the calving day compared to those allocated on the preceding days; nonetheless, the total time budget for ruminating did not differ during the prepartum period. Conclusion: We elucidated the ANS activity and behavioral profiles during prepartum period. Our results confirm that HRV parameters and behavior are useful for predicting calving time, and interestingly indicate that the time budget for ruminating while standing (or lying) may serve as a valuable predictor of calving. Collectively, our findings lay the foundation for future investigations to determine other potential predictors and formulate an algorithm for predicting calving time.

• Korean Journal of Organic Agriculture
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• v.20 no.1
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• pp.21-36
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• 2012

In this study, the assessment of livestock manure nitrogen loading for recycling farming in Yeoju-Gun carried out comparing manure units based on the cultivation areas and the N-amount of manure that are generated from livestock manure. Manure units (MU) are used in the permitting, registration, because they allow equal standards for all animals based on manure nutrient production. An MU is calculated by multiplying the number of animals by manure unit factor for the specific type of animal. The manure unit factor for MU determination was determined by dividing amounts of manure N produced 80kg N/year. In this study, manure unit by nitrogen concentration and amount of animal manure was calculated as follows: Hanwoo multiplied by 0.36, dairy cows multiplied by 0.8. swine multiplied by 0.105. The laying hens and broilers multiplied by 0.0079, 0.0049, respectively. The analysis of liquid manure unit per ha shows that the N loading by LMU is quite different by region. When it comes to nitrogen loading, the LMU per ha of cultivated land in excess of the N-amount was the highest in the Bukne-myeon province with 2.76 MU/ha, which is higher than the appropriate level. The Ganam-myeon province came next with 2.53 LMU. To be utilized as a valid program to build the environmentally friendly agricultural system, diverse measures shall be mapped out to properly determine manure units, evaluate N-loading and to properly manage their nutrient balance of each region.

• Journal of Animal Science and Technology
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• v.66 no.1
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• pp.31-56
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• 2024

Pig farming, a vital industry, necessitates proactive measures for early disease detection and crush symptom monitoring to ensure optimum pig health and safety. This review explores advanced thermal sensing technologies and computer vision-based thermal imaging techniques employed for pig disease and piglet crush symptom monitoring on pig farms. Infrared thermography (IRT) is a non-invasive and efficient technology for measuring pig body temperature, providing advantages such as non-destructive, long-distance, and high-sensitivity measurements. Unlike traditional methods, IRT offers a quick and labor-saving approach to acquiring physiological data impacted by environmental temperature, crucial for understanding pig body physiology and metabolism. IRT aids in early disease detection, respiratory health monitoring, and evaluating vaccination effectiveness. Challenges include body surface emissivity variations affecting measurement accuracy. Thermal imaging and deep learning algorithms are used for pig behavior recognition, with the dorsal plane effective for stress detection. Remote health monitoring through thermal imaging, deep learning, and wearable devices facilitates non-invasive assessment of pig health, minimizing medication use. Integration of advanced sensors, thermal imaging, and deep learning shows potential for disease detection and improvement in pig farming, but challenges and ethical considerations must be addressed for successful implementation. This review summarizes the state-of-the-art technologies used in the pig farming industry, including computer vision algorithms such as object detection, image segmentation, and deep learning techniques. It also discusses the benefits and limitations of IRT technology, providing an overview of the current research field. This study provides valuable insights for researchers and farmers regarding IRT application in pig production, highlighting notable approaches and the latest research findings in this field.

• Asian-Australasian Journal of Animal Sciences
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• v.28 no.6
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• pp.903-910
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• 2015

To maintain a predominantly pasture-based system, the large herd milked by automatic milking rotary would be required to walk significant distances. Walking distances of greater than 1-km are associated with an increased incidence of undesirably long milking intervals and reduced milk yield. Complementary forages can be incorporated into pasture-based systems to lift total home grown feed in a given area, thus potentially 'concentrating' feed closer to the dairy. The aim of this modelling study was to investigate the total land area required and associated walking distance for large automatic milking system (AMS) herds when incorporating complementary forage rotations (CFR) into the system. Thirty-six scenarios consisting of 3 AMS herds (400, 600, 800 cows), 2 levels of pasture utilisation (current AMS utilisation of 15.0 t dry matter [DM]/ha, termed as moderate; optimum pasture utilisation of 19.7 t DM/ha, termed as high) and 6 rates of replacement of each of these pastures by grazeable CFR (0%, 10%, 20%, 30%, 40%, 50%) were investigated. Results showed that AMS cows were required to walk greater than 1-km when the farm area was greater than 86 ha. Insufficient pasture could be produced within a 1 km distance (i.e. 86 ha land) with home-grown feed (HGF) providing 43%, 29%, and 22% of the metabolisable energy (ME) required by 400, 600, and 800 cows, respectively from pastures. Introduction of pasture (moderate): CFR in AMS at a ratio of 80:20 can feed a 400 cow AMS herd, and can supply 42% and 31% of the ME requirements for 600 and 800 cows, respectively with pasture (moderate): CFR at 50:50 levels. In contrast to moderate pasture, 400 cows can be managed on high pasture utilisation (provided 57% of the total ME requirements). However, similar to the scenarios conducted with moderate pasture, there was insufficient feed produced within 1-km distance of the dairy for 600 or 800 cows. An 800 cow herd required 140 and 130 ha on moderate and high pasture-based AMS system, respectively with the introduction of pasture: CFR at a ratio of 50:50. Given the impact of increasing land area past 86 ha on walking distance, cow numbers could be increased by purchasing feed from off the milking platform and/or using the land outside 1-km distance for conserved feed. However, this warrants further investigations into risk analyses of different management options including development of an innovative system to manage large herds in an AMS farming system.