No abstract

Nitrogen excretion in dairy manure is a precursor for N2O and NH3 formation in livestock housing, manure storage facilities, and after manure is applied to land. Nitrous oxide is a major contributor to greenhouse gas emissions, and reducing N output from dairy production facilities can reduce the amount of anthropogenic N2O entering the atmosphere. The objective of the study was to conduct a comprehensive evaluation of extant prediction models for N excretion in feces and urine using extensive literature data. A total of 45 N excretion equations were evaluated for lactating cows, heifers, and nonlactating cows and steers. These equations were evaluated with 215 treatment means from 69 published studies collected over 20 yr from 1995 to 2015. Two evaluation methods were used: the root mean square prediction error and the concordance correlation coefficient. Equations constructed using a more rigorous development process fared better than older extant equations. Equations for heifers and nonlactating cows had greater error of prediction compared with equations used for lactating cows. This could be due to limited amount of data available for construction and evaluation of the equations. Urinary N equations had greater prediction errors than other forms of excretion, possibly due to high variability in urinary N excretion and challenges in urine collection. Fecal N equations had low error bias and reached an acceptable level of precision and accuracy.

No abstract

Cyathostomins are a multispecies parasite ubiquitous in Equids. Cyathostomins have developed resistance to all but one class of anthelmintics, but species-level sensitivity to anthelmintics has not been shown. This study measured reinfection rates of cyathostomin species following the administration of three commercial dewormers. Nine treated horses were compared with 90 untreated controls during June-September 2017–2019. Ivermectin (IVM) (n = 6), Moxidectin (MOX) (n = 8) or Pyrantel (PYR) (n = 8) were orally administered. Fecal samples were collected every 14 d for 98 d. Fecal egg count reductions (FECR) were calculated using a modified McMaster technique. Nineteen cyathostomin species were identified by 5.8S-ITS-2 profiling using amplicon sequencing. Data were analyzed in QIIME1 and R statistical software using presence/absence methods. MOX had the lowest numbers of species present over the time course, followed by PYR then IVM (7.14, 10.17, 11.09, respectively); however, FECR was fastest for PYR. The presence of seven species: Coronocyclus labiatus, Cyathostomum catinatum, Cyathostomum tetracanthum, Cylicocylus elongatus, Cylicodontophorus bicoronatus, Cylicostephanus minutus, and Cylicostephanus goldi were unaffected by treatment (p > 0.05) points to species-specific differences in dewormer sensitivity and environmental persistence. Identifying resistance patterns at the species level will enable mechanistic understandings of cyathostomin anthelmintic resistance and targeted approaches to control them.

Gastrointestinal disease is the number one killer of horses. Little is known about the maintenance of microbes in the equine hindgut and how to distinguish a healthy gut in a live horse. Utilization of internal and external digestibility markers and starch fermentation has been extensively studied in ruminants and is the basis for research conducted on horses. The aims of this study were to investigate the effects of two equine feed digestive aid supplements on hindgut health (HGH) as reflected in fecal pH and digestibility and to compare and validate DM digestibility measurements through the use of internal and external markers such as chromium oxide (CR), lignin (Lig), indigestible ADF (iADF), indigestible NDF (iNDF), and indigestible lignin (iLig). Nine mature Quarter horses (six geldings, three mares) were used in a crossover design, three feeding periods of 17 d (51 d total), using three treatments: control, no feed additive (CON), Smartpak (SP; Plymouth, MA), or Platinum Performance (PP; Buellton, CA). Both SP and PP contained a strain of Lactobacillus, whereas SP further supplied mannanoligosaccharides (MOS) and fructooligosaccharides (FOS) and PP supplied Saccharomyces boulardii. Within the 17-d period, horses were offered orchard grass hay and sweet cob grain and the assigned treatment daily and four CR cookies to deliver 8 g/d of CR for the last 7 d of each period. Total feces were collected from 15 to 17 d. Feed and fecal samples were dried, ground, and sent to ANALAB (Fulton, IL) for nutrient analysis. Duplicate samples of feed and feces were placed in ruminally cannulated cows for in situ determination of iADF, iNDF, and iLig to estimate digestibility. Estimated CR fecal output, CR DMI, and DM digestibilities were evaluated using the root mean square prediction error percentage of the observed mean (RMSPE), concordance correlation coefficient (CCC), and Nash–Sutcliffe efficiency methods. Marker predictive ability tests showed iADF to have the least amount of bias with the smallest RMSPE (4%), largest CCC (0.43), and the largest amount of random bias (error of dispersion = 0.45). Supplementation of PP decreased CR DM digestibility (P < 0.02). Smartpak increased fecal pH (P < 0.09), but PP had no effect on fecal pH. Therefore, SP had a beneficial effect on HGH that is believed to be due to MOS and FOS.

Thriftiness in horses has been associated with more efficient nutrient harvesting in digestion, absorption and/or utilization, but the relative contribution of the gut microbiome to host metabolic tendency is not well understood. Recognizing the unreliability of owner reported assignment of keeper status, this research describes a novel tool for calculating whether a horse is an easy (EK) or hard (HK) keeper and then characterizes microbiome differences in these groups. The Equine Keeper Status Scale (EKSS) was developed and validated based on data gathered from 240 horses. Estimates of dietary energy intakes and requirements to achieve the optimal BCS score of 5 were used in EKSS assignments. Sixty percent of owners’ characterizations disagreed with EKSS identified keeper assignments. Equine fecal 16S rRNA profiles (n = 73) revealed differences in α and β diversities and taxa abundances based on EKSS assignments. EK communities had more Planctomycetes and fewer Euryarcheaota, Spirochaetes and Proteobacteria than HK indicating functional differences in nutrient harvesting between groups. Differences in the gut microbiomes of horses based on keeper assignment point to host/microbial interactions that may underlie some differences in metabolic tendency. The EKSS enables robust, repeatable determination of keeper status which can be used by researchers and horse owners.

No abstract

This study reports the differential response of the equine gut microbiome to protein and/or carbohydrate based on keeper status (easy keeper (EK), medium keeper (MK), hard keeper (HK)). Anaerobic equine fecal samples (n = 12 total, n = 3 / EK, MK, HK of four breeds) inoculated microcosms with three dietary conditions (C = Carb (cornmeal), P = Protein (soybean meal), and M = mix (50% C, 50% P)). Over 48 hours, fermentation products were measured using colorimetric assays and high-performance liquid chromatography. Microbial populations were surveyed using 16S rRNA gene sequencing analyzed by QIIME2. Linear mixed models were fit with fixed effects of Treatment and Keeper status and their interactions, with random effects of HorseID. Differences in fermentation products by keeper status included: MK had higher pH and greater gas production, EK produced higher hydrogen sulfide, and HK had greater total protein. Total SCFA was not different between keeper status (P = 0.89) but the acetate: propionate ratio was highest for HK (2.45mM) and lowest for EK (1.85mM) (P = 0.05). Isobutyrate production was highest in HK (2.34mM) compared to MK (0.85mM) and EK (0.17mM). Treatment had significant effects across all measurements; M and C treatment values were similar reflecting microbial preferences for carbohydrates before protein. P treated trials had increased fermentation outputs due to lower acidity effects. Keeper status had no effect on α-diversity (P > 0.05) however HK horses were least affected by treatments. P treated samples were more diverse than C and M (P < 0.001). Spearman correlation of Keeper x Treatment identified Oligosphaeria spp. in EK (r = 0.49) and Fusobacteria spp. in HK whole fecal samples (r = 0.37). These data suggest that while the compositions of the gut microbiomes of keeper groups were similar, they were functionally different in processing key nutrients.