Effects of ensiling time on corn silage starch ruminal degradability evaluated in situ or in vitro

Accurate measurements of concentration and ruminal degradability of corn silage starch is necessary for formulation of diets that meet the energy requirements of dairy cows. Five corn silage hybrids ensiled for 0 (unfermented), 30, 60, 120, and 150 d were used to determine the effects of ensiling time on starch degradability of corn silage. In addition, the effects of grind size of silage samples on 7-h in vitro starch degradability and the relationship between in vitro, in situ and near-infrared reflectance spectroscopy (NIRS) starch degradability were studied. In situ disappearance of corn silage starch increased from 0 to 150 d of ensiling, primarily as a result of an increase in the washout or rapidly degraded fraction of starch, particularly during the first 60 d of ensiling. When analyzed in vitro and by NIRS, ensiling time increased corn silage starch degradability either linearly or to a greater extent during the first 2 mo of ensiling. Differences in in situ starch disappearance among corn silage hybrids were apparent during the first 2 mo of ensiling but were attenuated as silages aged. No differences among hybrids were detected using a 7-h in vitro starch digestibility approach. Results from the in vitro subexperiment indicate that 7-h in vitro starch degradability was increased by reducing grind size of corn silage from 4 to 1 mm, regardless of ensiling duration. Fine grinding corn silages samples (i.e., 1-mm sieve) allowed distinguishing low- from medium- and high-starch degradability rated hybrids. Correlations among in situ, in vitro and NIRS measurements for starch degradability were medium to high (r ≥0.57); however, agreement among methods was low (concordance correlation coefficient ≤0.15). In conclusion, ensiling time linearly increased degradation rate of corn silage resulting in greater in situ starch disappearance after 150 d of ensiling. Reductions in grind size from 4 to 1 mm resulted in greater in vitro starch degradability, regardless of ensiling duration. Strong correlation but low agreement between starch degradability methods suggest that absolute estimations of corn silage starch degradability will vary, but all methods can be used to assess the effect of ensiling time on starch degradability.

Milk metabolome reveals pyrimidine and its degradation products as the discriminant markers of different corn silage-based nutritional strategies

The purpose of this study was to evaluate the effect of 6 different feeding systems (based on corn silage as the main ingredient) on the chemical composition of milk and to highlight the potential of untargeted metabolomics to find discriminant marker compounds of different nutritional strategies. Interestingly, the multivariate statistical analysis discriminated milk samples mainly according to the high-moisture ear corn (HMC) included in the diet formulation. Overall, the most discriminant compounds, identified as a function of the HMC, belonged to AA (10 compounds), peptides (71 compounds), pyrimidines (38 compounds), purines (15 compounds), and pyridines (14 compounds). The discriminant milk metabolites were found to significantly explain the metabolic pathways of pyrimidines and vitamin B₆. Interestingly, pathway analyses revealed that the inclusion of HMC in the diet formulation strongly affected the pyrimidine metabolism in milk, determining a significant up-accumulation of pyrimidine degradation products, such as 3-ureidopropionic acid, 3-ureidoisobutyric acid, and 3-aminoisobutyric acid. Also, some pyrimidine intermediates (such as l-aspartic acid, N-carbamoyl-l-aspartic acid, and orotic acid) were found to possess a high discrimination degree. Additionally, our findings suggested that the inclusion of alfalfa silage in the diet formulation was potentially correlated with the vitamin B₆ metabolism in milk, being 4-pyridoxic acid (a pyridoxal phosphate degradation product) the most significant and up-accumulated compound. Taken together, the accumulation trends of different marker compounds revealed that both pyrimidine intermediates and degradation products are potential marker compounds of HMC-based diets, likely involving a complex metabolism of microbial nitrogen based on total splanchnic fluxes from the rumen to mammary gland in dairy cows. Also, our findings highlight the potential of untargeted metabolomics in both foodomics and foodomics-based studies involving dairy products.

Assessment of feed and economic efficiency of dairy farms based on multivariate aggregation of partial indicators measured on field

Many of the metrics used to evaluate farm performance are only partial indicators of farm operations, which are assumed to be best predictors of the whole farm efficiency. The main objective of this work was to identify aggregated multiple indexes of profitability using common partial indicators that are routinely available from individual farms to better support the short-term decision-making processes of the cattle-feeding process. Data were collected from face-to-face interviews with farmers from 90 dairy farms in Italy and used to calculate 16 partial indicators that covered almost all indicators currently used to target feeding and economic efficiency in dairy farms. These partial indicators described feed efficiency, energy utilization, feed costs, milk-to-feed price ratio, income over feed costs, income equal feed cost, money-corrected milk, and bargaining power for feed costs. Calculations of feeding costs were based on lactating cows or the whole herd, and income from milk deliveries was determined with or without considering the milk quality payment. Multivariate factor analysis was then applied to the 16 partial indicators to determine simplified and latent structures. The results indicated that 5 factors explained 70% of the variability. Each of the original partial indicator was associated with all factors in different proportions, as indicated by loading scores from the multivariate factor analysis. Based on the loading scores, we labeled these 5 factors as "economic efficiency," "energy utilization," "break-even point," "milk-to-feed price," and "bargaining power of the farm," in decreasing order of explained communality. The first 3 factors shared 83% of the total communality. Feed efficiency was similarly associated with factor 1 (53% loading) and factor 2 (66% loading). Only factor 4 was significantly affected by farm location. Milk production and herd size had significant effects on factor 1 and factor 2. Our multivariate approach eliminated the problem of multicollinearity of partial indicators, providing simple and effective descriptions of farm feeding economics. The proposed method allowed the evaluation, benchmarking, and ranking of dairy herd performance at the level of single farms and at territorial level with high opportunity to be used or replicated in other areas.

Kinetics of gas production in the presence of Fusarium mycotoxins in rumen fluid of lactating dairy cows

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Toxins produced by Fusarium can be commonly detected in ruminant diets.

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Deoxynivalenol and fumonisins in the diet interfere with rumen microbiota.

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The presence of a mycotoxin-deactivating product counteracted negative effects.

Little is known about the effects of Fusarium mycotoxins on the fermentation potential of rumen fluid sampled from lactating dairy cows ingesting diets contaminated at regular levels of these mycotoxins (i.e., contamination levels that can normally be found on dairy farms). In the current experiment, rumen donor animals received diets contaminated with both deoxynivalenol (DON) and fumonisins (FB) with or without a mycotoxin-deactivating product. The rumen fluid donor animals were 12 lactating Holstein dairy cows that received one of 3 experimental diets in agreement with a 3 × 3 Latin square design (3 periods and 3 treatments). The 3 diets were as follows: (1) a TMR contaminated with a regular level of Fusarium mycotoxins [340.5 ± 161.0 µg of DON/kg of dry matter (DM) and 127.9 ± 43.9 µg of FB/kg of DM; control diet, CTR], (2) a TMR contaminated with Fusarium mycotoxins at levels higher than CTR but below US and European Union guidelines (733.0 ± 213.6 µg of DON/kg of DM and 994.4 ± 323.2 µg of FB/kg of DM; MTX), and (3) the MTX diet (897.3 ± 230.4 µg of DON/kg of DM and 1,247.1 ± 370.2 µg of FB/kg of DM) supplemented with a mycotoxin-deactivator product (Mycofix, Biomin Holding GmbH; 35 g/animal per day; MDP). Each experimental period lasted 21 d, and rumen fluid was individually sampled from all cows on the last day of each intoxication period. Then, the 4 rumen fluids sampled from cows receiving the same experimental diets were pooled into a single rumen inoculum, which was used in the in vitro gas production test. For the gas production test, 3 different rumen inocula (i.e., CTR, MTX, and MDP) were buffered (buffer:rumen ratio of 2:1, vol/vol) and then used in 3 fermentation runs to evaluate gas production dynamics in the presence of 8 feeds (i.e., corn meal, barley meal, corn silage, sorghum silage, alfalfa hay, ryegrass hay, dry brewers barley grains, and dried distillers grains with solubles). The kinetic parameters of gas production and volatile fatty acid concentrations were evaluated at the end of fermentation. The block run (i.e., fermentation day) effect influenced all of the fermentative and kinetic parameters. Greater final volumes or rates of gas production over time were observed for MDP compared with MTX rumen inocula (i.e., 172.6 vs. 147.8 mL/g of organic matter or 0.078 vs. 0.063 h⁻¹, respectively). However, the increase in rate of gas production was not consistent among tested feeds, meaning that a treatment by feed interaction was observed. Volatile fatty acid concentrations were not different among treatments, except for a slight increase of acetic acid in CTR compared with MTX (i.e., 71.0 vs. 67.9 mmol/L). This study showed that Fusarium-produced mycotoxins negatively affected the kinetics of gas production in feeds, whereas the presence of the mycotoxin-deactivator product in the diets of donor animals resulted in an increase in rumen fermentation potential, thus safeguarding the rumen environment.

Development of a linear programming model for the optimal allocation of nutritional resources in a dairy herd

A linear programming model that selects the optimal cropping plan and feeds allocation for diets to minimize the whole dairy farm feed costs was developed. The model was virtually applied on 29 high-yielding Holstein-Friesian herds, confined, total mixed ration dairy farms. The average herd size was 313.2 ± 144.1 lactating cows and the average land size was 152.2 ± 92.5 ha. Farm characteristics such as herd structure, nutritional grouping strategies, feed consumption, cropping plan, intrinsic farm limitations (e.g., silage and hay storage availability, water for irrigation, manure storage) and on farm produced forage costs of production were collected from each farm for the year 2017. Actual feeding strategies, land availability, herd structure, crop production costs and yields, and milk and feed market prices for the year 2017 were used as model inputs. Through optimization, the feeding system was kept equal to the actual farm practice. The linear program formulated diets for each animal group to respect actual herd dry matter intake and fulfill actual consumption of crude protein, rumen-degradable and rumen-undegradable fractions of crude protein, net energy for lactation, neutral detergent fiber, acid detergent fiber, forage neutral detergent fiber, and nonfiber carbohydrate. Production levels and herd composition were considered to remain constant as the nutritional requirement would remain unchanged. The objective function was set to minimize the whole-farm feed costs including cash crop sales as income, and crop production costs and purchased feed costs as expenses. Optimization improved income over feed costs by reducing herd feed costs by 7.8 ± 6.4%, from baseline to optimized scenario, the improved was explained by lower feed costs per kilogram of milk produced due to a higher feed self-sufficiency and higher income from cash crop. In particular, the model suggested to maximize, starting from baseline to optimized scenario, the net energy for lactation (+8.5 ± 6.3%) and crude protein (+3.6 ± 3.1%) produced on farm, whereas total feed cost (€/100 kg of milk) was greater in the baseline (20.4 ± 2.3) than the optimized scenario (19.0 ± 1.9), resulting in a 6.7% feed cost reduction with a range between 0.49% and 21.6%. This meant €109 ± 96.9 greater net return per cow per year. The implementation of the proposed linear programming model for the optimal allocation of the nutritional resources and crops in a dairy herd has the potential to reduce feed cost of diets and improve the farm feed self-sufficiency.

Technical note: Evaluation of a novel enzymatic method to predict in situ undigested neutral detergent fiber of forages and nonforage fibrous feeds

The purpose of this study was to optimize the conditions of a previously proposed enzymatic method used to estimate in situ undigested neutral detergent fiber (uNDF). We used a multi-step enzymatic approach, in which samples were first solubilized in NaOH solutions as a preincubation (PreInc) phase. After rinsing, samples were incubated (24 h at 39°C) in a buffered solution (pH 6) containing hemicellulase, cellulase, and Viscozyme L enzymes (Sigma-Aldrich s.r.l., Milan, Italy), followed by incubation (24 h at 39°C) in a buffered solution (pH 5) containing xylanase. Two sets of experiments were performed: a calibration trial (that tested different PreInc conditions on 9 selected forages) and a validation trial (that verified the results by testing multiple samples of 6 different forage types and a group of fibrous by-products). In the calibration trial, samples (300 mg in Ankom F57 filter bags; Ankom Technology Corp., Fairport, NY) were preincubated at 39°C in a 0.1 M NaOH solution for 90, 180, or 240 min, or in 0.2, 0.5, 1.0, or 2.0 M NaOH solution for 90 min. The results indicated that the best PreInc method, in terms of intra-laboratory repeatability and estimation of reference in situ values, was 90 min in a 0.2 M NaOH solution. Thus, we used this PreInc condition to determine enzymatic uNDF of 257 samples in the validation trial. Although the selected method generally had good accuracy in predicting in situ uNDF, inconsistencies were noted for certain forage types. Overall, when enzymatic uNDF was used to predict the in situ uNDF of all samples, the regression was satisfactory (intercept = 7.098, slope = 0.920, R² = 0.73). The regression models developed for alfalfa hays, corn silages, and small grain silages had also acceptable regression performances and mean square error of prediction (MSEP) values, and the main sources of MSEP variation were error due to incomplete (co)variation and random error. Even when R² values were >0.70, the MSEP value of the regression model for grass hays was 149.55, and that for nonforage fibrous feeds was 155.16. Although enzymatic uNDF partially overestimated the in situ uNDF, particularly in grass silages, the proposed procedure seems to be promising for accurately predicting in situ uNDF, because it generally had good repeatability and provided satisfactory estimates of in situ uNDF.

Short communication: In vitro rumen gas production and starch degradation of starch-based feeds depend on mean particle size

Our objective was to model the effect of mean particle size (mPS) on in vitro rumen starch degradation (IVSD) and the kinetics of gas production for different starch-based feeds. For each feed, 2 batches of the same grains were separately processed through 2 different mills (cutter or rotor speed mills), with or without different screens to achieve a wide range of mPS (0.32 to 3.31 mm for corn meals; 0.19 to 2.81 mm for barley meals; 0.16 to 2.13 mm for wheat meals; 0.28 to 2.32 mm for oat meals; 0.21 to 2.36 mm for rye meals; 0.40 to 1.79 for sorghum meals; 0.26 to 4.71 mm for pea meals; and 0.25 to 4.53 mm for faba meals). The IVSD data and gas production kinetics, obtained by fitting to a single-pool exponential model, were analyzed using a completely randomized design, in which the main tested effect was mPS (n = 6 for all tested meals, except n = 7 for corn meals and n = 5 for sorghum meals). Rumen inocula were collected from 2 fistulated Holstein dairy cows that were fed a total mixed ration consisting of 16.2% crude protein, 28.5% starch, and 35.0% neutral detergent fiber on a dry matter basis. The IVSD, evaluated after 7 h of rumen incubation, decreased linearly with increasing mPS for corn, barley, wheat, rye, pea, and faba meals, and decreased quadratically with increasing mPS for the other meals. The y-axis intercept for 7-h IVSD was below 90% starch for corn, barley, and rye feeds and greater than 90% for the other tested feeds. The mPS adjustment factors for the rate of rumen starch degradation varied widely among the different tested feeds. We found a linear decrease in starch degradation with increasing mPS for barley, wheat, rye, and pea meals, whereas we noted a quadratic decrease in starch degradation for the other tested meals. Further, we observed a linear decrease in the rate of gas production with increasing mPS in each tested feed, except for pea meal, which had a quadratic relationship. For each 1 mm increase in mPS, the gas production was adjusted by -0.009 h^-1 for corn, -0.011 h^-1 for barley, -0.008 h^-1 for wheat, and -0.006 h^-1 for faba, whereas numerically greater adjustments were needed for oat (-0.022 h^-1), rye (-0.017 h^-1), and sorghum (-0.014 h^-1). These mPS adjustment factors could be used to modify the starch-based feed energy values as a function of mean particle size, although in vivo validation is required.

Technical note: Relationship between in situ NDF degradability and enzymatic NDF hydrolysis in forages, nonforage fibrous feeds, and crop residues

The study was performed on forages ( = 8), nonforage fibrous feeds ( = 10), and crop residues ( = 2). Samples were characterized for in situ NDF degradability (NDFD) at 6, 12, 18, 24, 30, 36, 48, 72, 96, 120, and 240 h of ruminal incubation. Then, samples were characterized for enzymatic NDFD by adopting a multistep enzymatic method consisting of a preincubation (PreInc) phase followed by enzymatic incubation (EnzInc) steps. In the PreInc phase, samples were incubated in a NaOH solution for 0, 30, 60, or 90 min. Then, in the EnzInc phase, samples were first incubated in a buffered enzymatic solution containing hemicellulase, cellulase, and Viscozyme L enzymes. Then, samples were incubated in a xylanase-buffered enzymatic solution. These 2-step EnzInc lasted for a total of 16 (8 h for the first enzymatic step + 8 h for the second enzymatic step), 32 (16 + 16 h), or 48 h (24 + 24 h). The enzymatic NDFD coefficients were increased by increasing both PreInc and EnzInc incubation times, and no PreInc × EnzInc interaction was observed, except for ryegrass hay. On average, enzymatic NDFD increased ( < 0.05) by 0.35, 0.54, or 0.68, respectively, for 30-, 60-, or 90-min PreInc compared with 0-min PreInc. The enzymatic NDFD increased ( < 0.05), on average, by 0.11 in 32-h EnzInc or 0.16 in 48-h EnzInc with respect to 16-h EnzInc. Enzymatic NDFD were used to predict in situ NDFD coefficients by adopting single regression equations. High coefficients of regression ( > 0.80, < 0.05) and low errors of prediction were measured when specific enzymatic conditions were performed to predict in situ NDFD at intermediate (from 24 to 48 h) ruminal incubation. Generally, worse regression performances were obtained when enzymatic NDFD were used to predict in situ NDFD evaluated after shorter or longer incubation times. The direct prediction of the rate of NDF degradation was not possible using enzymatic NDFD coefficients. Even if the proposed multistep enzymatic method appeared promising, further studies are required to improve enzymatic NDFD prediction ability within specific forage types or nonforage fibrous feeds.

Relationships among ensiling, nutritional, fermentative, microbiological traits and contamination in corn silages addressed with partial least squares regression

The objective of this work was to reduce the predictor dimensionality and to develop a model able to forecast contamination in corn silages. A survey on 33 dairy farms was performed, and samples from core, lateral, and apical parts of the feed-out face of corn silage bunkers were analyzed for chemical, biological (digestible and indigestible NDF), fermentative (pH, ammonia nitrogen, lactic acid, VFA, and ethanol), and microbiological (yeasts and molds) traits. Corn silage samples were analyzed for cell and spore counts by adoption of a molecular DNA-based method. A partial least squares (PLS) regression with a leave-one-out cross-validation method was used to reduce the dimensionality of the original predictors ( = 30) by projecting the independent variables into latent constructs. In a first step of the model development, the importance of independent variables in predicting contamination was assessed by plotting factor loadings of both dependent and independent variables on the first 2 components and by verifying for each predictor the variable influence on projection values adopting the Wold's criterion as well as the entity of standardized regression coefficients. Three ensiling characteristics (bunker type, presence of lateral wrap plastic film, and penetration resistance as a measurement of the ensiled mass density), a chemical trait (DM), 9 characterizations of the fermentative profile (pH, ammonia nitrogen, acetic acid, butyric acid, isobutyric acid, valeric acid, isovaleric acid, ethanol, and lactic acid), and 2 microbiological traits (yeasts and molds) were retained as important terms in the PLS model. Three reduced-variable PLS (rPLS) regressions-the first based on ensiling, chemical, fermentative, and microbiological retained important variables (rPLSecfm); the second based on chemical, fermentative, and microbiological retained important traits (rPLScfm); and the last based on only chemical and fermentative retained important variables (rPLScf)-were performed. The model that best fit the measurements was rPLSecfm. The rPLScfm and rPLScf models had similar regression performances but higher mean square errors of prediction than rPLSecfm. However, all tested models seemed adequate to rank corn silages for low, medium, and high risks of contamination. To avoid the visit on farm by trained people required to measure penetration resistance, the use of the rPLScf model is suggested as a useful tool to assess the risk of in corn silage.

Estimation of the indigestible fiber in different forage types

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 (uNDF) within and among various forage types. Finally, a mathematical approach was investigated for the estimation of the uNDF 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 uNDF 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 uNDF and ADL was not constant and, for grass hay and corn silage, was different ( 0.05) from the 2.4 × lignin value applied by the traditional Chandler equation. The observed uNDF:ADL ratio was 3.22 for grass hay and 3.11 for corn silage. Relationships among chemical and biological parameters and uNDF 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 ( = 0.63). Greater coefficients of determination resulted from a multiple regression equation for the whole data set ( = 0.80) and within each forage type ( = 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 uNDF represented the best approach to obtain an accurate prediction of the iNDF and to optimize its specific purpose in dynamic nutrition models.

Effect of the inclusion of adsorbents on aflatoxin B1 quantification in animal feedstuffs

The extraction efficiency of aflatoxin B1 (AFB1) in cattle feed containing nine adsorbents (ADSs) was investigated using two organic/aqueous solvents composed of methanol/water (80/20 v/v; MeOH) and acetone/water (85/15 v/v; AC). Samples were obtained including a highly AFB1-contaminated (HC) and a low-level AFB(1)-contaminated (LC) feedstuff (15.33 and 7.57 microg kg(-1), respectively), nine ADSs (four clay minerals; one yeast cell wall-based product; one activated carbon and three commercial ADS products) at two different levels of inclusion (10 and 20 g kg(-1)). After solvent extraction and immunoaffinity column clean-up, all samples were analysed for AFB1 by high-performance liquid chromatography (HPLC) with fluorescence detection. For each contamination level (HC and LC), the data obtained were analysed using a factorial arrangement in a completely randomized design. Means were compared with the correspondent controls using the Dunnett's test. No statistical difference was found in AFB1 levels of feedstuffs not containing ADSs when extracted with AC or MeOH, even if numerically higher values were obtained with AC. A dose-dependent effect (p < 0.01) of ADSs inclusion was observed on AFB1 recoveries that were lower when the higher ADS level (20 g kg(-1)) was included in the HC and LC feedstuffs. Higher AFB(1) recoveries were obtained using AC compared with MeOH, both in HC (75.0% versus 12.0%, respectively) and in LC (84.0% versus 22.8%, respectively) ADSs containing feedstuffs. However, when the activated carbon and the sodium bentonite were included in feeds, lower AFB1 concentrations with respect to control values (p < 0.001 and <0.05, respectively) were obtained also using AC. The data obtained in this study indicate that routine use of the MeOH solvent for AFB1 analysis of unknown feedstuffs, can produce misleading results if they contain an ADS.