Beet and cane molasses are produced worldwide as a by-product of sugar extraction and are widely used in animal nutrition. Due to their composition, they are fed to ruminants as an energy source. However, molasses has not been properly characterized in the literature; its description has been limited to the type (sugarcane or beet) or to the amount of dry matter (DM), total or water-soluble sugars, crude protein, and ash. Our objective was to better characterize the composition of cane and beet molasses, examine possible differences, and obtain a proper definition of such feeds. For this purpose, 16 cane and 16 beet molasses samples were sourced worldwide and analyzed for chemical composition. The chemical analysis used in this trial characterized 97.4 and 98.3% of the compounds in the DM of cane and beet molasses, respectively. Cane molasses contained less DM compared with beet molasses (76.8 ± 1.02 vs. 78.3 ± 1.61%) as well as crude protein content (6.7 ± 1.8 vs. 13.5 ± 1.4% of DM), with a minimum value of 2.2% of DM in cane molasses and a maximum of 15.6% of DM in beet molasses. The amount of sucrose differed between beet and cane molasses (60.9 ± 4.4 vs. 48.8 ± 6.4% of DM), but variability was high even within cane molasses (39.2-67.3% of DM) and beet molasses. Glucose and fructose were detected in cane molasses (5.3 ± 2.7 and 8.1 ± 2.8% of DM, respectively), showing high variability. Organic acid composition differed as well. Lactic acid was more concentrated in cane molasses than in beet molasses (6.1 ± 2.8 vs. 4.5 ± 1.8% of DM), varying from 1.6 to 12.8% of DM in cane molasses. Dietary cation-anion difference showed numerical differences among cane and beet molasses (7 ± 53 vs. 66 ± 45 mEq/100 g of DM, on average). It varied from -76 to +155 mEq/100 g of DM in the cane group and from +0 to +162 mEq/100 g of DM in the beet group. Data obtained in this study detailed differences in composition between sources of molasses and suggested that a more complete characterization could improve the use of molasses in ration formulation.

The objective of this study was to investigate the effects of 2 alfalfa hays differing in undigested neutral detergent fiber content and digestibility used as the main forage source in diets fed to high producing cows for Parmigiano-Reggiano cheese production. Diets were designed to have 2 different amounts of undigestible NDF [high (Hu) and low (Lu)], as determined by 240-h in vitro analysis (uNDF240). Alfalfa hay in vitro digestibility [% of amylase- and sodium sulfite-treated NDF with ash correction (aNDFom)] at 24 and 240 h was 40.2 and 31.2% and 53.6 and 45.7% for low- (LD) and high-digestibility (HD) hays, respectively. The 4 experimental diets (Hu-HD, Lu-HD, Hu-LD, and Lu-LD) contained 46.8, 36.8, 38.8, and 30.1% of alfalfa hay, respectively, 8.6% wheat straw, and 35.3% corn (50% flake and 50% meal; DM basis). Soy hulls and soybean meal were used to replace hay to balance protein and energy among diets. Eight multiparous Holstein cows (average milk production = 46.0 ± 5.2 kg/d, 101 ± 38 d in milk, and 662 ± 42 kg of average body weight) were assigned to a 4 × 4 Latin square design, with 2 wk of adaptation and a 1-wk collection period. Dry matter and water intake, rumination time, ruminal pH, and milk production and composition were measured. Diets and feces were analyzed for NDF on an organic matter basis (aNDFom), acid detergent fiber, acid detergent lignin, and uNDF240 to estimate total-tract fiber digestibility. Dry matter intake and rumination times were higher in HD diets compared with LD diets, regardless of forage amount. Rumination time was constant per unit of dry matter intake but differed when expressed as a function of uNDF240, aNDFom, or physically effective NDF intake. No differences were found among treatments on average ruminal pH, but the amount of time with pH <5.8 was lower in Hu-HD diets. Milk production and components were not different among diets. Total-tract aNDFom and potentially digestible neutral detergent fiber fraction digestibility was higher for the LD diets (88.3 versus 85.8% aNDFom in HD), for which lower feed intakes were also observed. The Hu-HD diet allowed greater dry matter intake, longer rumination time, and higher ruminal pH, suggesting that the limiting factor for dry matter intake is neutral detergent fiber digestibility and its relative rumen retention time.

Ruminants play an important part in the food supply chain, and manipulating rumen microbiota is important to maximising ruminants' production. Rumen microbiota through rumen fermentation produces as major end products volatile fatty acids that provide animal's energy requirements, and microbial CP. Diet is a key factor that can manipulate rumen microbiota, and each variation of the physical and chemical composition creates a specific niche that selects specific microbes. Alteration in the chemical composition of forage, the addition of concentrates in the diet, or the inclusion of plant extract and probiotics, can induce a change in rumen microbiota. High-throughput sequencing technologies are the approaches utilised to investigate the microbial system. Also, the application of omics technologies allows us to understand rumen microbiota composition and these approaches are useful to improve selection programmes. The aim of this review was to summarise the knowledge about rumen microbiota, its role in nutrient metabolism, and how diet can influence its composition.

This study focused on changes in fibrous and protein fractions, changes in fiber digestibility and amount of indigestible neutral detergent fiber (NDF) as a consequence of increased maturity in alfalfa. A total area of 720 m(2) was divided in 18 blocks randomly assigned to 3 treatments, differing in cutting intervals. Treatment 1 was harvested with a 21-d cutting schedule, at a prebloom stage; treatment 2 with a 28-d schedule, at about first-bloom stage; whereas a full bloom was observed in treatment 3, harvested with a 35-d cutting schedule. Treatments were replicated 4 times through the spring-summer period for 2 subsequent years, 2011 and 2012. Statistical differences were observed for crude protein [treatment 1: 20.8%, treatment 2: 17.3%, and treatment 3: 17.0%; standard error of the mean (SEM)=0.83], soluble protein, and nonprotein nitrogen among treatments on a dry matter basis. Similar results were observed for acid detergent lignin (6.3, 6.9, and 7.3%, respectively; SEM=0.39), lower in treatment 1 compared with others, and in vitro NDF digestibility at 24 or 240 h. Indigestible NDF at 240 h resulted in lower values for treatment 1 compared with treatments 2 and 3 (15.5, 17.2, and 18.3%, respectively; SEM=1.54). Moreover, the indigestible NDF:acid detergent lignin ratio varied numerically but not statistically among treatments, being as much as 9% greater than the 2.4 fixed value applied for rate of digestion calculation and Cornell Net Carbohydrate Protein System (Cornell University, Ithaca, NY)-based model equations. Assuming the diet composition remained unchanged, treatment 3 (35-d cutting interval) would be expected to yield 1.4 kg less milk per day based on energy supply, and 2.8 kg less milk daily based on protein supply than treatment 1.

The role of indigestible NDF is essential in relation to OM digestibility prediction, total tract digestibility, rumen fill, passage rate, and digestion kinetics. Moreover, the truly indigestible NDF (iNDF) represents a core point in dynamic models used for diet formulations. However, despite its wide possible applications, few trials have been conducted to quantify iNDF and even fewer to investigate whether or not it is consistent among different forage sources. The objective of this study was to predict the iNDF by measuring the residual NDF after 240-h in vitro fermentation to determine the unavailable NDF (uNDF₂₄₀) within and among various forage types. Finally, a mathematical approach was investigated for the estimation of the uNDF₂₄₀ fraction. In all, 688 forages were analyzed in this study. This pool included 122 alfalfa hays, 282 corn silages, and 284 grass hays. Values of uNDF₂₄₀ varied among different forages and within the same type (22.7% ± 4.48%, 20.1% ± 4.23%, and 11.8% ± 3.5% DM for grass hay, alfalfa hay, and corn silages, respectively). The relationship among uNDF₂₄₀ and ADL was not constant and, for grass hay and corn silage, was different (P < 0.05) from the 2.4 × lignin value applied by the traditional Chandler equation. The observed uNDF₂₄₀:ADL ratio was 3.22 for grass hay and 3.11 for corn silage. Relationships among chemical and biological parameters and uNDF₂₄₀ were investigated via simple and multiple regression equations. The greatest correlation with a single variable was obtained by ADL and ADF when applied to the whole data set (R² = 0.63). Greater coefficients of determination resulted from a multiple regression equation for the whole data set (R² = 0.80) and within each forage type (R² = 0.65, 0.77, and 0.54 for grass hay, alfalfa hay, and corn silage, respectively). In conclusion, a regression approach requires specific equations and different regression coefficients for each forage type. The direct measurement of uNDF₂₄₀ represented the best approach to obtain an accurate prediction of the iNDF and to optimize its specific purpose in dynamic nutrition models. Copyright © 2016. American Society of Animal Science .

Dairy cows are exposed to multiple stressors during the productive cycle, such as metabolic challenges, overcrowding, grouping change, environmental stress and dietary errors. Thus, it is essential to study reliable markers able to detect stress conditions in dairy farms. This study evaluates dairy cows' immunologic and metabolic markers after the sudden and combined exposition to a high‐grain diet (75% concentrates) and the abrupt change of the housing system (from free stall to tie stall). A group of twenty‐four Holstein cows were enrolled in a challenge study of 28 days duration. Several immunological and metabolic blood markers were evaluated over the trial. Blood samples were taken at day 0 (normal value) and day 1, 3, 7, 14, 21, and 28 (challenge). Data were submitted to a mixed model for repeated measures, including time as fixed and cows as random effects. The nutritional and environmental challenge had heavy effects on animal welfare and cows responded with a dramatic rumination drop. Our results suggest that the most responsive markers after abiotic stressors in cows were as follows: Serum Amyloid A and ROM in the acute response; Ceruloplasmin and GGT in the mid acute and Albumin, Paroxonase and FRAP in the chronic phase. Serum Amyloid A, Ceruloplasmin, Paraoxonase, GGT and ROM resulted as positive phase proteins, while, Albumin and FRAP resulted as negative phase proteins. Preliminary obtained results could concur to develop strategies able to mitigate stressor effects; moreover, the proposed design can be used as a model to test stress nutritional modulators.