Behavioral Adaptations in Tropical Dairy Cows: Insights into Calving Day Predictions.

This study examined changes in the activity patterns of tropical dairy cows during the transition period to assess their potential for predicting calving days. This study used the AfiTag-II biosensor to monitor activity, rest time, rest per bout, and restlessness ratio in 298 prepartum and 347 postpartum Holstein Friesian cows across three lactation groups (1, 2, and ≥3). The data were analyzed using generalized linear mixed models in SPSS, and five machine learning models, including random forest, decision tree, gradient boosting, Naïve Bayes, and neural networks, were used to predict the calving day, with their performance evaluated via ROC curves and AUC metrics. For all lactations, activity levels peak on the calving day, followed by a gradual return to prepartum levels within two weeks. First-lactation cows displayed the shortest rest duration, with a prepartum rest time of 568.8 ± 5.4 (mean ± SE), which is significantly lower than higher-lactation animals. The random forest and gradient boosting displayed an effective performance, achieving AUCs of 85% and 83%, respectively. These results indicate that temporal changes in activity behavior have the potential to be a useful indicator for calving day prediction, particularly in tropical climates where seasonal variations can obscure traditional prepartum indicators.

Enhancing Raw Bovine Milk Quality using Ultraviolet-C (UV-C) Irradiation: A Microbial and Lipid Peroxidation Study.

This study investigated the efficacy of ultraviolet-C (UV-C) irradiation in enhancing the quality of raw bovine milk by targeting microbial populations and lipid peroxidation, both of which are key factors in milk spoilage. We categorized the raw milk samples into three groups based on initial bacterial load: low (<3 Log 10 CFU/mL), medium (3-4 Log 10 CFU/mL), and high (>4 Log 10 CFU/mL). Using a 144 W thin-film UV-C reactor, we treated the milk with a flow rate of 3 L/min. We measured the bacterial count including standard plate count, coliform count, coagulase-negative staphylococci count, and lactic acid bacteria count and lipid peroxidation (via thiobarbituric acid reactive substances assay) pre- and post-treatment. Our results show that UV-C treatment significantly reduced bacterial counts, with the most notable reductions observed in high and medium initial load samples (>4 and 3-4 Log 10 CFU/mL, respectively). The treatment was particularly effective against coliforms, showing higher reduction efficiency compared to coagulase-negative staphylococci and lactic acid bacteria. Notably, lipid peroxidation in UV-C treated milk was significantly lower than in pasteurized or untreated milk, even after 72 hours. These findings demonstrate the potential of UV-C irradiation as a pre-treatment method for raw milk, offering substantial reduction in microbial content and prevention of lipid peroxidation, thereby enhancing milk quality.

Epidemiology of foot-and-mouth disease outbreaks in Thailand from 2011 to 2018.

Foot-and-mouth disease (FMD) is one of the most important animal diseases hindering livestock production in Thailand. In this study, a temporal and spatial analysis at the subdistrict level was performed on FMD outbreak reports in Thailand from 2011 to 2018. Risk factors associated with FMD outbreaks were furthermore investigated using generalized estimating equations. The results showed that the incidence of FMD outbreaks was the highest in 2016 and was affected by season, with a peak in FMD outbreaks occurring in the rainy-winter season, during October to December. FMD outbreaks were mostly distributed in small clusters within a few subdistricts. Some high-risk areas with repeated outbreaks were detected in the central regions. Risk factors, including the increase of subdistrict's size of the dairy population, beef population or pig population, the low percentage of forest area, subdistricts in the provinces adjacent to Malaysia, the presence of a livestock market and the occurrence of an FMD outbreak in a neighbouring subdistrict in the previous month significantly increased the odds of having an FMD outbreak. The increase in proximity to the nearest subdistrict with an FMD outbreak in the previous month decreased the odds of having FMD outbreaks. This study helped to identify high-risk areas and periods of FMD outbreaks in Thailand. Together with the identified risk factors, its results can be used to optimize the FMD control programme in Thailand and in other countries having a similar livestock industry and FMD situation.

Analysis of Epidemiological and Economic Impact of Foot-and-Mouth Disease Outbreaks in Four District Areas in Thailand.

Foot and mouth disease (FMD) is one of the most important infectious animal diseases impacting livestock production in Thailand. Despite a national vaccination program, FMD outbreaks are reported every year. We studied the epidemiological impacts of FMD outbreaks in four districts of Thailand between 2015 and 2016. Epidemiological data were collected from 193 FMD-affected dairy farms, 55 FMD-affected beef farms, and 25 FMD-affected pig farms. A significant difference in morbidity rates were observed between the dairy farms in the different areas, which could be explained by the differences in FMD outbreak management in each area. The morbidity rates in dairy and beef cattle also significantly differed between each animal age category, with the lowest morbidity rate observed in calves. Remarkably, vaccination was not significantly associated with the morbidity rate. In addition, the economic impact of FMD was calculated for 60 dairy farms in Muak Lek district. The economic losses were determined as the sum of milk production loss, mortality loss, additional labor costs, and veterinary service and medical costs, which averaged 56 USD per animal on the farm (ranging from 2 to 377 USD). Milk loss had the largest economic impact, although it varied substantially between farms. The farm size and outbreak duration were significantly associated with the total economic losses per farm. These results affirm the substantial epidemiological and economic impact of FMD on farms in Thailand, emphasizing the importance of FMD control.

Early origin and global colonisation of foot-and-mouth disease virus.

In this study, we compiled 84-year worth (1934-2017) of genomic and epidemiological data of foot-and-mouth disease virus (FMDV), and performed comprehensive analyses to determine its early origin and transmission route. We found that recombination is a key feature of FMDV, and that the genomic regions coding for structural and non-structural proteins have markedly different evolutionary histories, and evolve at different rates. Despite all of these differences, analyses of both structural and non-structural protein coding regions consistently suggested that the most recent common ancestor of FMDV could be dated back to the Middle Age, ~ 200 to 300 years earlier than previously thought. The ancestors of the Euro-Asiatic and SAT strains could be dated back to the mid-seventeenth century, and to the mid-fifteenth to mid-sixteenth century, respectively. Our results implicated Mediterranean counties as an early geographical origin of FMDV before spreading to Europe and subsequently to Asia and South America.

Spatiotemporal analyses of foot and mouth disease outbreaks in cattle farms in Chiang Mai and Lamphun, Thailand.

BACKGROUND: Foot and mouth disease (FMD) is a highly infectious and contagious febrile vesicular disease of cloven-hoofed livestock with high socio-economic consequences globally. In Thailand, FMD is endemic with 183 and 262 outbreaks occurring in the years 2015 and 2016, respectively. In this study, we aimed to assess the spatiotemporal distribution of FMD outbreaks among cattle in Chiang Mai and Lamphun provinces in the northern part of Thailand during the period of 2015-2016. A retrospective space-time scan statistic including a space-time permutation (STP) and the Poisson and Bernoulli models were applied in order to detect areas of high incidence of FMD. RESULTS: Results have shown that 9 and 8 clusters were identified by the STP model in 2015 and 2016, respectively, whereas 1 and 3 clusters were identified by the Poisson model, and 3 and 4 clusters were detected when the Bernoulli model was applied for the same time period. In 2015, the most likely clusters were observed in Chiang Mai and these had a minimum radius of 1.49 km and a maximum radius of 20 km. Outbreaks were clustered in the period between the months of May and October of 2015. The most likely clusters in 2016 were observed in central Lamphun based on the STP model and in the eastern area of Chiang Mai by the Poisson and Bernoulli models. The cluster size of the STP model (8.51 km) was smaller than those of the Poisson and Bernoulli models (> 20 km). The cluster periods in 2016 were approximately 7 months, while 4 months and 1 month were identified by the Poisson, Bernoulli and STP models respectively. CONCLUSIONS: The application of three models provided more information for FMD outbreak epidemiology. The findings from this study suggest the use of three different space-time scan models for the investigation process of outbreaks along with the follow-up process to identify FMD outbreak clusters. Therefore, active prevention and control strategies should be implemented in the areas that are most susceptible to FMD outbreaks.

Intention to adopt and diffuse innovative ultraviolet light C system to control the growth of microorganisms in raw milk among Thais Dairy Farmers.

This research aims to investigate the factors affecting Thai dairy farmers' intention to use ultraviolet C technology (UV-C) to reduce the number of microorganisms in raw milk. The researcher applied the innovation and diffusion theory (IDT) and the technology acceptance model 2 (TAM2) to evaluate dairy farmer's intention. The 477 dairy farmers in the central part of Thailand were interviewed using questionnaires. The collected data were analyzed using multinomial logistic regression (MLR). It was found that the intention to adopt UV-C can accurately predict the factors affecting the intention to use the technology based on the intention levels to create diffusion and promote acceptance. To increase the diffusion and acceptance of UV-C, the perceived usefulness to increase the milk price was the major influenced factor to promote technology acceptance. Providing facilities for maintenance, the use of this innovation and reporting news about the benefits of new technology to create positive attitudes and confidence lead to the spread of technology driven by early adopters. The technology developers should consider and design technology compatible with existing systems. However, the collaboration of all related parties is also needed to encourage Thai dairy farmers to try the new technology and observe the actual results.

Bovine viral diarrhea virus (BVDV) infection in dairy cattle herds in northeast Thailand.

Bovine viral diarrhea virus causes a wide range of clinical manifestation with subsequent economic losses in dairy production worldwide. Our study of a population of dairy cattle in Thailand based on 933 bulk tank milk samples from nine public milk collection centers aimed to monitor infective status and to evaluate the effect of the infection in cows as well as to examine the reproductive performance of heifers to provide effective recommendations for disease control in Thailand. The results showed a moderate antibody-positive prevalence in the herd (62.5 %), with the proportion of class-3 herd, actively infected stage, being 17.3 %. Fourteen persistently infected (PI) animals were identified among 1196 young animals from the class-3 herds. Most of the identified PI animals, 11/14, were born in one sub-area where bovine viral diarrhea virus (BVDV) investigation has not been performed to date. With respect to reproductive performance, class-3 herds also showed higher median values of reproductive indices than those of class-0 herds. Cows and heifers in class-3 herds had higher odds ratio of calving interval (CI) and age at first service (AFS) above the median, respectively, compared to class-0 herds (OR = 1.29; P = 0.02 and OR = 1.63; P = 0.02). Our study showed that PI animals were still in the area that was previously studied. Furthermore, a newly studied area had a high prevalence of BVDV infection and the infection affected the reproductive performance of cows and heifers. Although 37.5 % of the population was free of BVDV, the lack of official disease prevention and less awareness of herd biosecurity may have resulted in continuing viral spread and silent economic losses have potentially occurred due to BVDV. We found that BVDV is still circulating in the region and, hence, a national control program is required.

White spot disease risk factors associated with shrimp farming practices and geographical location in Chanthaburi province, Thailand.

Over the past 2 decades, shrimp aquaculture in Thailand has been impacted by white spot disease (WSD) caused by white spot syndrome virus (WSSV). Described here are results of a survey of 157 intensive shrimp farms in Chanthaburi province, Thailand, to identify potential farm management and location risk factors associated with the occurrence of WSD outbreaks. Logistic regression analysis of the survey responses identified WSD risks to be associated with farms sharing inlet water and culturing shrimp year round and with a single owner operating more than 1 farm. The analysis also showed WSD risks to be reduced at farms that used probiotics and applied lime to pond bottoms when fallow to neutralize acidity and kill microorganisms. Regression modeling identified no association of geographical location with WSD. The data should assist shrimp farms in mitigating the effects of WSD in Thailand.

The association of ruminal pH and some metabolic parameters with conception rate at first artificial insemination in Thai dairy cows.

The objective of this study was to determine the association of metabolic parameters and cow associated factors with the conception rate at first insemination (FCR) in Thai dairy cows. The investigation was performed with 529 lactations from 32 smallholder dairy farms. At 3-6 weeks after parturition, blood samples and ruminal fluid were collected. Body condition scores (BCS) of cows were scored 1 week before expected calving date and at blood sampling date. Ruminal pH was measured at 2-4 h after morning feeding in ruminal fluid collected by ruminocentesis. Serum beta-hydroxybutyrate and serum urea nitrogen were measured by kinetic enzyme method. Cows with first insemination (AI) between 41 and 114 days postpartum were identified after pregnancy diagnosis for FCR. Breed, parity, interval from calving to first AI, BCS before calving, BCS after calving, loss in BCS after calving, SBHB, SUN, ruminal pH, and postpartum problems were selected as independent variables for a model with FCR as a dependent variable. A multivariable logistic regression model was used with farm as a random effect. Overall FCR was 27.2 %. The FCR depended on interval from calving to first AI, BCS before calving, and ruminal pH. The FCR between 69 and 91 days postpartum was significantly highest (45 %). Before calving, a cow with high BCS (≥ 3.5) had significantly greater FCR than a cow with low BCS (≤ 3.25; P<0.01). An increased ruminal pH raised significantly FCR (OR=2.53; P=0.03).

The effect of a catastrophic flood disaster on livestock farming in Nakhon Sawan province, Thailand.

In 2011, a catastrophic flood disaster in Thailand affected not only humans but also took animal lives. Data on livestock losses, including death, loss, and decreased production, were collected in Nakhon Sawan province. The time-series map of the flooded area from August to December 2011 was available online from the Geo-informatics and Space Technology Development Agency. To evaluate the high-density areas of livestock loss, a spatial hot spot analysis was performed. The Getis-Ord Gi statistic with weighted zone of indifference and the Euclidean distance measurement were employed to identify spatial clusters of species that were affected by the flood. The results indicated that the majority of livestock losses were from poultry and swine farms. The density of poultry and swine loss was significantly different between sub-districts with clusters of high-density loss alongside the river, particularly in Chum Saeng and Kao Liew. Using spatial hot spot analysis as a tool to classify and rank the areas with high flood risks provides an informative outline for farmers to be aware of potential flood damage. To avoid unexpected loss from flooding, poultry and swine farms in risk areas should be properly managed, particularly during the flooding season between August and December.