Spoilage \u3ci\u3ePseudomonas\u3c/i\u3e survive common thermal processing schedules and grow in emulsified meat during extended vacuum storage

Some Pseudomonas species are common meat spoilage bacteria that are often associated with the spoilage of fresh meat. The recently reported ability of these bacteria to also spoil cooked and vacuum packaged meat products has created the need to investigate all potential routes of spoilage they may be able to utilize. The objective of this experiment was to determine if spoilage Pseudomonas spp. survive thermal processing and grow during refrigerated storage under vacuum. Pseudomonas spp. isolates collected from spoiled turkey products were inoculated into a salted and seasoned meat emulsion that was vacuum sealed and thermally treated to final temperatures of 54.4 and 71.1◦C to mimic thermal processes commonly used in the meat industry. Samples were stored for a total of 294 days at 4 and 10◦C and plated using Pseudomonas spp. specific agar plates. Pseudomonas spp. concentrations were below the detection limit (0.18 log10 CFU/g) immediately after thermal processing andwere first recovered from thermally processed samples after 14 days of storage. The final concentrationwas greater than 2 log10 CFU/g (p \u3c 0.05 compared to post-thermal processing) in thermally processed treatment groups at the end of storage, indicating that these Pseudomonas spp. isolateswere able to survive thermal processing and growduring extended vacuum storage. This raises concerns about the ability of spoilage bacteria to survive the thermal processing schedules commonly used in the meat industry and confirms that some Pseudomonas spp. are capable of thriving in products other than aerobically stored fresh meat

Rumen Bacterial Community Composition in Holstein and Jersey Cows Is Different under Same Dietary Condition and Is Not Affected by Sampling Method

The rumen microbial community in dairy cows plays a critical role in efficient milk production. However, there is a lack of data comparing the composition of the rumen bacterial community of the main dairy breeds. This study utilizes 16S rRNA gene sequencing to describe the rumen bacterial community composition in Holstein and Jersey cows fed the same diet by sampling the rumen microbiota via the rumen cannula (Holstein cows) or esophageal tubing (both Holstein and Jersey cows). After collection of the rumen sample via esophageal tubing, particles attached to the strainer were added to the sample to ensure representative sampling of both the liquid and solid fraction of the rumen contents. Alpha diversity metrics, Chao1 and observed OTUs estimates, displayed higher (P = 0.02) bacterial richness in Holstein compared to Jersey cows and no difference (P \u3e 0.70) in bacterial community richness due to sampling method. The principal coordinate analysis displayed distinct clustering of bacterial communities by breed suggesting that Holstein and Jersey cows harbor different rumen bacterial communities. Family level classification of most abundant (\u3e1%) differential OTUs displayed that OTUs from the bacterial families Lachnospiraceae and p-2534- 18B5 to be predominant in Holstein cows compared to Jersey cows. Additionally, OTUs belonging to family Prevotellaceae were differentially abundant in the two breeds. Overall, the results from this study suggest that the bacterial community between Holstein and Jersey cows differ and that esophageal tubing with collection of feed particles associated with the strainer provides a representative rumen sample similar to a sample collected via the rumen cannula. Thus, in future studies esophageal tubing with addition of retained particles can be used to collect rumen samples reducing the cost of cannulation and increasing the number of animals used in microbiome investigations, thus increasing the statistical power of rumen microbial community evaluations

Rumen Bacterial Community Composition in Holstein and Jersey Cows Is Different under Same Dietary Condition and Is Not Affected by Sampling Method

The rumen microbial community in dairy cows plays a critical role in efficient milk production. However, there is a lack of data comparing the composition of the rumen bacterial community of the main dairy breeds. This study utilizes 16S rRNA gene sequencing to describe the rumen bacterial community composition in Holstein and Jersey cows fed the same diet by sampling the rumen microbiota via the rumen cannula (Holstein cows) or esophageal tubing (both Holstein and Jersey cows). After collection of the rumen sample via esophageal tubing, particles attached to the strainer were added to the sample to ensure representative sampling of both the liquid and solid fraction of the rumen contents. Alpha diversity metrics, Chao1 and observed OTUs estimates, displayed higher (P = 0.02) bacterial richness in Holstein compared to Jersey cows and no difference (P \u3e 0.70) in bacterial community richness due to sampling method. The principal coordinate analysis displayed distinct clustering of bacterial communities by breed suggesting that Holstein and Jersey cows harbor different rumen bacterial communities. Family level classification of most abundant (\u3e1%) differential OTUs displayed that OTUs from the bacterial families Lachnospiraceae and p-2534- 18B5 to be predominant in Holstein cows compared to Jersey cows. Additionally, OTUs belonging to family Prevotellaceae were differentially abundant in the two breeds. Overall, the results from this study suggest that the bacterial community between Holstein and Jersey cows differ and that esophageal tubing with collection of feed particles associated with the strainer provides a representative rumen sample similar to a sample collected via the rumen cannula. Thus, in future studies esophageal tubing with addition of retained particles can be used to collect rumen samples reducing the cost of cannulation and increasing the number of animals used in microbiome investigations, thus increasing the statistical power of rumen microbial community evaluations

BIG DATA ANALYTICS AND PRECISION ANIMAL AGRICULTURE SYMPOSIUM: Machine learning and data mining advance predictive big data analysis in precision animal agriculture

Precision animal agriculture is poised to rise to prominence in the livestock enterprise in the domains of management, production, welfare, sustainability, health surveillance, and environmental footprint. Considerable progress has been made in the use of tools to routinely monitor and collect information from animals and farms in a less laborious manner than before. These efforts have enabled the animal sciences to embark on information technology-driven discoveries to improve animal agriculture. However, the growing amount and complexity of data generated by fully automated, high-throughput data recording or phenotyping platforms, including digital images, sensor and sound data, unmanned systems, and information obtained from real-time noninvasive computer vision, pose challenges to the successful implementation of precision animal agriculture. The emerging fields of machine learning and data mining are expected to be instrumental in helping meet the daunting challenges facing global agriculture. Yet, their impact and potential in “big data” analysis have not been adequately appreciated in the animal science community, where this recognition has remained only fragmentary. To address such knowledge gaps, this article outlines a framework for machine learning and data mining and offers a glimpse into how they can be applied to solve pressing problems in animal sciences

Anaerobic Digestion of Finishing Cattle Manure

Utilizing manure from cattle fed distillers grains in anaerobic digesters improved methane production and DM degradation of manure compared to manure from cattle fed no distillers grains. Manure from cattle fed in open lot pens had soil contamination which decreased OM content and led to decreased total methane production (L/day), but not when expressed as methane/g OM. If ash buildup is avoided, open lot manure can be used as anaerobic digester feedstock

A Survey of the Microbial Communities of Commercial Presliced, Packaged Deli-Style Ham Throughout Storage

The goal of this study was to evaluate the variation in spoilage microbiota associated with sliced, prepackaged deli-style ham from varying processing environments available in the retail market in the United States. Three different brands of presliced ham, water added were purchased at local markets and evaluated every 2 wk beginning 4 wk prior to the sell-by date until 4 wk beyond the sell-by date. Analysis of 16S ribosomal RNA genes using operational taxonomic units showed that Brand A had a different bacterial community structure compared with Brands B and C, according to unweighted (P=0.006) and weighted (P<0.001) UniFrac distance matrices. Brand A had a greater proportion of sequence reads mapping to Carnobacterium, Bacillus, and Prevotella, whereas B and C had greater proportions of Pseudomonas, Photobacterium, and Lactococcus. Brand A also had a lower salt concentration (P<0.007), greater moisture percentage and less fat percentage (P<0.012), and increased aerobic plate count (P=0.017). Differences in spoilage microbiota can in part be attributed to the factors involved with different processing locations, as shown by 3 different brands of ham, as well as slight differences in formulation including salt concentration and organic acid use

Corn Oil Supplementation on Performance and Methane Production in Finishing Steers

A finishing trial was conducted to evaluate the effects of corn oil on animal performance, carcass characteristics, and methane production in finishing cattle. Corn oil was supplemented at 3% of the diet (dry matterbasis) and led to a decrease in intake, a numerical improvement in average daily gain, and improved feed efficiency compared to the control cattle. Dry matter intake while in the methane barn was not decreased between treatments, although it was numerically similar to what was observed outside of the methane barn. Corn oil did not affect any carcass parameters. Methane production (g/d) was reduced with the inclusion of corn oil compared to the control. Methane (g/lb of gain) was also reduced with the inclusion of corn oil compared to the control. A numerical reduction of methane (g/lb of intake) was observed when corn oil was included in the diet. Corn oil appears to be a viable option for both improving performance as well as decreasing methane production in beef cattle finishing diets

Impact of Intake on Methane Production in Growing Steers

A study was conducted to evaluate the impact that level of intake has on methane and carbon dioxide production by growing steers. Two treatments were evaluated that included ad-libitum intake compared to limit-fed steers. The ad-libitum fed cattle had greater gains, similar feed efficiency and produced more methane and carbon dioxide per day, while the limit fed cattle produced more methane and carbon dioxide per pound of intake than the ad-libitum fed cattle

Impact of Intake on Methane Production in Growing Steers

A study was conducted to evaluate the impact that level of intake has on methane and carbon dioxide production by growing steers. Two treatments were evaluated that included ad-libitum intake compared to limit-fed steers. The ad-libitum fed cattle had greater gains, similar feed efficiency and produced more methane and carbon dioxide per day, while the limit fed cattle produced more methane and carbon dioxide per pound of intake than the ad-libitum fed cattle