Fecal Microbial Communities in a Large Representative Cohort of California Dairy Cows.

Improved sequencing and analytical techniques allow for better resolution of microbial communities; however, the agriculture field lacks an updated analysis surveying the fecal microbial populations of dairy cattle in California. This study is a large-scale survey to determine the composition of the bacterial community present in the feces of lactating dairy cattle on commercial dairy operations. For the study, 10 dairy farms across northern and central California representing a variety of feeding and management systems were enrolled. The farms represented three typical housing types including five freestall, two drylot and three pasture-based management systems. Fresh feces were collected from 15 randomly selected cows on each farm and analyzed using 16S rRNA gene amplicon sequencing. This study found that housing type, individual farm, and dietary components significantly affected the alpha diversity of the fecal microbiota. While only one Operational Taxonomic Unit (OTU) was common among all the sampled individuals, 15 bacterial families and 27 genera were shared among 95% of samples. The ratio of the families Coriobacteriaceae to Bifidobacteriaceae was significantly different between housing types and farms with pasture fed animals having a higher relative abundance of Coriobacteriaceae. A majority of samples were positive for at least one OTU assigned to Enterobacteriaceae and 31% of samples contained OTUs assigned to Campylobacter. However, the relative abundance of both taxa was <0.1%. The microbial composition displays individual farm specific signatures, but housing type plays a role. These data provide insights into the composition of the core fecal microbiota of commercial dairy cows in California and will further generate hypotheses for strategies to manipulate the microbiome of cattle.

Optimizing accuracy of sampling protocols to measure nutrient content of solid manure.

Precise applications of manure to cropland can help optimize productivity and minimize environmental nutrient losses. Applying manure precisely is a challenge because the nutrient content of manures is inherently variable and the accuracy of sampling protocols are unknown. This study aimed to quantify the accuracy of sampling protocols for static solid manure piles considering both the number and depth of grab samples entering a composite sample. Over 35 grab samples were collected from each of ten static piles of dairy manure in California's Central Valley. Grab samples were individually analyzed for dry matter (DM), ash, total nitrogen, potassium, and phosphorous concentrations. Resampling simulations quantified the precision and bias of sampling protocols varying in both grab sample number and depth. Results showed that number of grab samples required for measurements to meet an accuracy standard of ±10% of the true value varied significantly by pile makeup. Over 25 grab samples were often required for multi-source manure piles, where an average of six grab samples were required from single source piles. The DM concentration of manure piles decreased at depths greater than 0.4 m, and sampling simulations showed that measurements were biased unless 70-80% of grab samples were collected from the pile interior. Both the number and location of grab samples necessary to create a representative composite require resource investments by farmers, and should be considered to manage nutrient applications cropland.

Optimizing accuracy of protocols for measuring dry matter and nutrient yield of forage crops.

Farmers around the world must precisely manage nutrients applied to and removed from crop fields to maintain production and without causing nutrient pollution. This study is the first to quantify the baseline accuracy of current industry measurement protocols and achievable accuracy from intensifying protocols for measuring dry matter (DM), nitrogen (N), potassium (K), and phosphorus (P) yields from forage crops harvested for silage. The 'true' DM and nutrient yields of three fields each of corn, sorghum, and small grain were intensively measured by weighing and sampling every truckload of harvested forage. Simulations quantified the accuracy of practical sampling protocols by repeatedly subsampling the complete dataset for each field to measure average truckload weight and average DM and nutrient concentrations. Then uncertainty was propagated to DM, N, P, and K yield calculations using standard error equations. Yields measured using current industry protocols diverged from the true yields of some fields by more than ±40%, emphasizing the need for improved protocols. This study shows that improving average DM and nutrient concentration measurements is unlikely to improve accuracy of yield measurements if average load weight is not precisely measured. Accuracy did not come within 27% of true yields without weighing all truckloads on some fields even when DM and nutrient concentration measurements were perfectly accurate. Once all truckloads were weighed, the timing of forage sample collection to measure average DM concentration had the greatest impact on accuracy; precision improved by an average of 6.2% when >3 samples were evenly spaced throughout the harvest compared to the same number of consecutive samples. All crop fields are affected by within field variation in growing conditions that results in heterogeneity in DM and nutrient yield. Globally, this study provides foundational methodology to quantitatively evaluate and improve yield measurement protocols that ultimately support sustainable crop production.

Mass balance analyses of nutrients on California dairies to evaluate data quality for regulatory review.

Effective regulations may help reduce nitrate contamination of groundwater from agriculture. Dairy farmers in California must maintain a ratio below 1.4 of total nitrogen (N) applied to total N-removed (N-Ratio) on cropland receiving manure application. In annual reports to the regulatory agency, farmers detail nutrients applied to cropland, removed in harvests, and exported off farm. Data were extracted from all available annual reports for 62 dairies from 2011, 2012, and 2013. Excretions of N, phosphorus (P), and potassium (K) were calculated using reported herd demographics and standard excretion equations from the American Society of Agricultural and Biological Engineers. Calculated nutrient excretion values were compared to the reported values of manure nutrients applied to cropland and exported off farm. Reported N-Ratios were compared to mass balance simulations exploring variable crop yields and alfalfa management. In the nutrient excretion balance, the distribution of the percent of N and P recovered in manures applied or exported peaked at 24% (median=31%) and 26% (median=53%) of excreted, respectively. The distribution of recovered K was fairly uniform from 0% to 300% (median=146%) of excreted K. In N-ratio simulations, 62% and 66% of all reported N-ratios were lower than their respective simulated N-ratio, assuming alfalfa crops received no N fertilization and minimal fertilization (26% of N-removed in harvest) respectively. When simulated crop yields were normally (sd=0.25) or Student's t distributed (df=154) around expected crop yields, 28% and 57% of all reported ratios fell within the 95% confidence interval of the simulations, respectively. Low and erratic recovery rates of excreted P and K existed. Additionally, reported N-Ratios were generally lower and more varied than necessary for farmers to maintain crop yields while complying with regulations. Greater understanding of low recovery rates is needed before data are used to assess the impact of regulations.