Search

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 e

The volatile organic compounds (VOC) are the fermentation products and used to assess the quality of ensiled forages. The study aimed to monitor the VOC concentrations in silage and haylage by GC/FID system and to reveal the relationships among these different end-fermentation products by carrying out a multivariate analysis. Forty-six compounds were quantified by GC/FID system in a single chromatographic run. The average repeatability and reproducibility coefficients of variation obtained on standard solutions, composed by 0.1 mL/L of each VOC (solution A) or volatile fatty acids (VFA, solution B), were 0.028 and 0.017 (absolute value), respectively. The average repeatability and reproducibility coefficients of variation obtained on silage samples were 0.026 and 0.027, respectively. Mean values of recovery obtained on the standard solutions at different concentration levels of compounds were in the range 0.95–1.04 (absolute values), and no effect of analyte concentration was observed on recovery. When multivariate analysis was carried out on whole database, 7 factors were retained and they explained 0.50 of the total variability. The factors were interpreted for their biological meanings, based on specific VOC loading on each extracted latent structure. Alfalfa haylage and ryegrass silage were characterized by higher contents of valeric and butyric acids, methyl and ethyl butyrate, 2,3-butaneldiol, 1-butanol, and 2-butanol compared with the other fermented products. Except for mixture crop silage, all the fermented products containing legume crops had higher levels of 2-methyl-1-propanol, 2-methyl-1-butanol, 3-methyl-1-butanol, 2-phenyl ethanol, and methanol and lower contents of ethanol, ethyl lactate, and ethyl acetate compared with the other fermented products. Silage containing grass crops had higher levels of acetic and lactic acids, and 1,2-propanediol respect to the other investigated products. The most part of the investigated fermented products were charac

In this work, milk samples collected in a cohort of intensive dairy farms of the Po Valley (Italy) were screened for their (poly)-phenolic profile to check the occurrence of phenolic metabolites of biological interest. The selected dairy farms were previously classified on the basis of their cow feeding system, considering the utilization of corn silage as the main ingredient of the rations. Overall, ultra-high-pressure liquid chromatography coupled with mass spectrometry using an Orbitrap analyzer, followed by unsupervised and supervised statistics, allowed identifying clear different phenolic distributions in the milk samples. Accordingly, a great variability in the phenolic profiles of the different milk samples was observed, with two main phenolic clusters outlined by the unsupervised hierarchical clustering approach and not fully correlated to the nutritional strategy considered. The variables’ importance in the projection approach allowed selecting the most important metabolites, resulting in samples’ discrimination. Among the most discriminative compounds, we found phenolic metabolites (such as hippuric acid and 4-hydroxyhippuric acid), followed by lignans (such as enterolactone) and isoflavonoids (such as equol and O-desmethylangolensin). Taken together, our findings suggested that both the feeding systems and the ability of dairy cows to process parent phenolic compounds were the main factors providing the final (poly)-phenolic profile of the milk samples. Future targeted and ad hoc studies appear of great interest to evaluate the potential biological effects of these compounds on cow health

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 studie

Sixty-six dairy farms (as average, 167.0 ± 106.5 milking cows and milk yield of 31.4 ± 5.1) were visited to identify different nutritional approaches adopted in dairy cows diet formulation. Forage, TMR, faecal, and milk samples from lactating herds were collected and diet composition, in vitro methane production, in vivo nutrient digestibility, faecal fermentation profile and milk yield and milk quality were characterised. A hierarchical cluster analysis was applied and six nutritional approaches in diet formulation corresponding with six different clusters (CL) were identified. The CL discriminated the farm feeding choices in the following nutritional strategies, based on high use of: (i) high moisture corn (HMC) and legume silage, (ii) compound feed, (iii) corn and soy meals, (iv) HMC and soy meal, (v) corn meal and protein compound feeds, or (vi) HMC and protein compound feed strategies, respectively for CL1 to CL6. The milk yield tended (p =.061) to differ among CL. The greatest (>1.60) feed efficiency was calculated for CL1 and 5, whereas the lowest (<1.45) for CL 2. The CL2 and 5 had the highest feed costs (i.e. 0.24 or 0.22 €/kg of milk, respectively). Interestingly, the high use of HMC or steam flaked corn resulted associated to higher farm performances. Particularly, HMC and legume silage (CL1), HCM and soy meal (CL4) and HCM and protein compound feed (CL6) nutritional strategies resulted more efficient and profitable, having the greatest feed efficiency, protein and starch degradability as well as income over feed costs. Differentiate carbohydrates in dairy cow diets seems highly convenient.HIGHLIGHTS Six different nutritional strategies were identified based on use of single ingredients and a great variability in both economic and feed efficiency was observed for dairy farms clustering into different groups The use of high moisture ear corn in substitution of corn meal increased dry matter intake, feed efficiency, milk yield and lactose co

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 p

The chemical composition of milk can be significantly affected by different factors across the dairy supply chain, including primary production practices. Among the latter, the feeding system could drive the nutritional value and technological properties of milk and dairy products. Therefore, in this work, a combined foodomics approach based on both untargeted metabolomics and metagenomics was used to shed light onto the impact of feeding systems (i.e., hay vs. a mixed ration based on hay and fresh forage) on the chemical profile of raw milk for the production of hard cheese. In particular, ultra-high-performance liquid chromatography quadrupole time-of-flight mass spectrometry (UHPLC-QTOF) was used to investigate the chemical profile of raw milk (n = 46) collected from dairy herds located in the Po River Valley (Italy) and considering different feeding systems. Overall, a total of 3320 molecular features were putatively annotated across samples, corresponding to 734 unique compound structures, with significant differences (p < 0.05) between the two feeding regimens under investigation. Additionally, supervised multivariate statistics following metabolomics-based analysis allowed us to clearly discriminate raw milk samples according to the feeding systems, also extrapolating the most discriminant metabolites. Interestingly, 10 compounds were able to strongly explain the differences as imposed by the addition of forage in the cows’ diet, being mainly glycerophospholipids (i.e., lysophosphatidylethanolamines, lysophosphatidylcholines, and phosphatidylcholines), followed by 5-(30,40-Dihydroxyphenyl)-gamma-valerolactone-40-O-glucuronide, 5a-androstan-3a,17b-diol disulfuric acid, and N-stearoyl glycine. The markers identified included both feed-derived (such as phenolic metabolites) and animal-derived compounds (such as lipids and derivatives). Finally, although characterized by a lower prediction ability, the metagenomic profile was found to be significantly correlat

In this study, an untargeted metabolomics approach based on ultra-high-performance liquid chromatography coupled with high-resolution mass spectrometry (UHPLC-HRMS) was used for investigating changes in chemical profiles of cow milk considering diets based on mycotoxins-contaminated corn silages. For this purpose, 45 milk samples were classified into five clusters according to the corn silage contamination profile, namely (1) low levels of Aspergillus-and Penicillium-mycotoxins; (2) low levels of fumonisins and other Fusarium-mycotoxins; (3) high levels of Aspergillus-mycotoxins; (4) high levels of non-regulated Fusarium-mycotoxins; (5) high levels of fumonisins and their metabolites, and subsequently analyzed by UHPLC-HRMS followed by a multivariate statistical analysis (both unsupervised and supervised statistical approaches). Overall, the milk metabolomic profile highlighted potential correlations between the quality of contaminated corn silages (as part of the total mixed ration) and milk composition. Metabolomics allowed to identify 628 significant milk metabolites as affected by the five levels of corn silage contamination considered, with amino acids and peptides showing the highest metabolite set enrichment (134 compounds). Additionally, 78 metabolites were selected as the best discriminant of the prediction model built, possessing a variable importance in projection score >1.2. The average Log Fold-Change variations of the discriminant metabolites provided evidence that sphingolipids, together with purine and pyrimidine-derived metabolites were the most affected chemical classes. Also, metabolomics revealed a significant accumulation of oxidized glutathione in milk samples belonging to the silage cluster contaminated by emerging Aspergillus toxins, likely involved in the oxidative imbalance. These preliminary findings provide new insights into the potential role of milk metabolomics to provide chemical indicators of mycotoxins-contaminated corn silage fe

Il capitolo affronta il tema della sostenibilità dell’industria mangimistica evidenziando il sistema mangimistico come parte integrante del ciclo produttivo degli alimenti ed anello di congiunzione tra le produzioni vegetali ed animali. Il mangimificio ha il ruolo principale di valorizzare i sottoprodotti dell’industria molitoria, divenendo parte attiva nella filiera produttiva, non solo da un punto di vista economico, sociale ed ambientale, ma anche come valorizzatore di risorse provenienti da altre filiere produttive in un’ottica di economia circolare. Nel capitolo viene trattato il contesto produttivo italiano legato al mercato dei mangimi, dall’acquisto delle materie prime alla produzione delle varie tipologie di mangimi in funzione delle categorie animali a cui sono destinati. Il sistema mangimistico attuale non è solo un produttore di mangimi, ma occupa una fondamentale funzione di ottimizzatore nell’utilizzo di risorse agro-industriali, di trasferimento di tecnologia, conoscenza e servizi al sistema zootecnico, determinando importanti riflessi positivi di carattere ambientale a livello aziendale, locale e nazionale. La valutazione dell’impronta carbonica di 1 kg di mangime, in rapporto alla provenienza geografica delle materie prime ed alle fonti energetiche impiegate nei processi tecnologici, evidenzia come l’attività del mangimificio abbia un impatto molto basso rispetto alla produzione degli input necessari ed ai relativi trasporti in entrata ed uscita al mangimificio stesso e come le ricadute ambientali positive dell’industria mangimistica meritino attenzione e riconoscimento. Il mangimificio svolge, inoltre, un ruolo economico-sociale molto importante come strumento di sviluppo del territorio, necessario all’economia e alle produzioni animali. In conclusione viene mostrata l’analisi SWOT con cui è possibile individuare i punti di forza, di debolezza, le opportunità e le minacce dell’intero sistema mangimistico.

The purpose of this preliminary study was to discriminate the chemical fingerprints of Protected Designation of Origin (PDO) Grana Padano cheeses from non-PDO “Grana-type” cheeses by means of an untargeted metabolomic approach based on ultra-high-pressure liquid chromatography coupled to quadrupole time-of-flight mass spectrometer (UHPLC/QTOF-MS). Hierarchical cluster analysis and Orthogonal Projections to Latent Structures Discriminant Analysis (OPLS-DA) allowed discriminating PDO vs. non-PDO cheeses. Lipids (fatty acids and their derivatives, phospholipids and monoacylglycerols), amino acids and oligopeptides, together with plant-derived compounds were the markers having the highest discrimination potential. It can be postulated that Grana Padano value chain, as strictly defined in the PDO production specification rules, can drive the biochemical processes involved in cheese making and ripening in a distinct manner, thus leaving a defined chemical signature on the final product. These preliminary findings provide the basis for further authenticity studies, aiming to protect the designation of origin of PDO Grana Padano cheese by applying a comprehensive foodomics-based approach.

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.

The feeding system represents one of the main factors driving raw milk composition, thus determining differences in nutritional value and technological properties. In this preliminary study, untargeted metabolomics with ultra-high-performance liquid chromatography quadrupole time-of-flight mass spectrometry (UHPLC-QTOF) coupled with both unsupervised and supervised multivariate statistics was used to investigate the chemical profile of bulk milk collected from dairy cows (n = 103) following different feeding regimens, being corn silage (MS-FS, n = 51), hay (H-FS, n = 35) and a mixed ration consisted in fresh forage and hay (MR-FS, n = 17). Overall, a total of 1686 metabolites was identified by means of UHPLC-QTOF, with significant differences (p < 0.05) between the three feeding regimens under investigation. The metabolites detected mainly belonged to lipids (mainly glycerophospholipids and triglycerides), followed by oligopeptides, steroid derivatives, and secondary metabolites (such as phenolic compounds and terpenoids). Interestingly, multivariate statistics applied to the metabolomics data revealed intriguing differences in the discriminant markers detected. The markers identified included both feed-derived (such as phenolic metabolites) but also animal-derived compounds (such as fatty acids). Therefore, our results provide comprehensive insights into the metabolomics profile of different bulk milk samples, suggesting also an indirect influence of feeding regimens on its chemical signature.

Cooking by boiling dry pasta could have varying degrees of influence on nutritional and functional components. In the present study, its effect on total phenolic content and antioxidant capacity, as well as on the comprehensive profile of free and bound phenolics, was investigated in six commercial gluten-free (GF) pasta products. Overall, the heat treatment caused a significant reduction (P < 0.01) of the total phenolic content as well as FRAP reducing power and ORAC radical scavenging, with significant differences among the pasta samples considered. The highest values were recorded in free phenolic fraction remaining in black rice (41 mg gallic acid equivalents 100 g− 1 and 25 mmol Trolox Equivalents 100 g− 1) and quinoa (24 mg gallic acid equivalents 100 g− 1 and 14 mmol Trolox Equivalents 100 g− 1) cooked GF pasta. Significant correlations (P < 0.01) could be found between total phenolics and both the antioxidant capacity assays performed. UHPLC-ESI/QTOF-MS mass profiling allowed confirming the spectrophotometric results, while identifying the amount of free and bound fractions. Among phenolic classes, lignans exhibited the highest decrease during the cooking process, followed by stilbenes and flavonoids. However, phenolic acids and other phenolics showed the highest stability. Furthermore, cooking by boiling strongly lowered the bound-to-free ratio of phenolic compounds, by an averaged factor ranging from 14-folds for flavonoids to 5-folds for other classes of phenolics.

BACKGROUND: Considering that water availability for agricultural needs is being restricted, an alternative to corn in animal nutrition should be explored in the Po Valley. The present study aimed to evaluate the effects of either a partial (Trial I) or a total (Trial II) corn silage substitution with barley silage in dairy cows' diet on milk yield and composition, its coagulation properties, cheese yield and the sensorial profile of 16-month-aged Grana Padano cheese. RESULTS: A partial or a total substitution of corn silage with barley silage had no effect on milk yield. Milk fat content in Trial I and milk urea content in both trials were higher with barley silage based diets than in corn silage based diets. No effects were observed concerning the lactodinamographic profile for milk aptitude to cheese-making, cheese yield and its organoleptic traits between feed treatments in Trials I and II. In both trials, hardness, friability and solubility scores were generally lower than reference values, whereas deformability, elasticity and stickiness scores were generally higher than reference values. CONCLUSION: A partial or a total substitution of corn silage with barley silage in diets for dairy cows did not induce any negative effects on animal performance, nor on milk-quality traits, cheese quality and yield.

The fate of phenolic compounds, along with short-chain fatty acids (SCFAs) production kinetics, was evaluated on six different commercial gluten-free (GF) pasta samples varying in ingredient compositions, focussing on the in vitro faecal fermentation after the gastrointestinal digestion. A general reduction of both total phenolics and reducing power was observed in all samples, together with a substantial change in phenolic profile over 24 h of faecal fermentation, with differences among GF pasta samples. Flavonoids, hydroxycinnamics and lignans degraded over time, with a concurrent increase in low-molecular-weight phenolic acids (hydroxybenzoic acids), alkylphenols, hydroxybenzoketones and tyrosols. Interestingly, discriminant analysis also identified several alkyl derivatives of resorcinol as markers of the changes in phenolic profile during in vitro fermentation. Furthermore, degradation pathways of phenolics by intestinal microbiota have been proposed. Considering the total SCFAs and butyrate production during the in vitro fermentation, different fermentation kinetics were observed among GF pasta post-hydrolysis residues.

A survey regarding crop enterprise management, forages cost of production, dairy cattle management including reproductive management, housing, heat abatement, body condition scoring, nutrition, grouping strategies, and income over feed cost performance, was carried out from December 2016 to January 2018 on 50 dairy farms by the Department of Animal Science, Food and Nutrition of Università Cattolica del Sacro Cuore (Piacenza, Italy). A total of 41 herds (82%) completed the survey. Average herd size was 327 ± 162 lactating cows with the average land size of 160 ± 94 ha per farm. Herds were located in the provinces of Cremona (17), Brescia (8), Mantova (7), Piacenza (5), Cuneo (4), Bergamo (3), Lodi (3), Torino (2), and Venezia (1). These farms sold 32.8 ± 2.01 kg of milk/day per cow, had an annual culling rate of 34.0 ± 4.00%, a calving interval of 14.16 ± 0.58 months., and a 21-days pregnancy rate of 17.05 ± 2.58%. Implementing effective management strategies to contrast the damage caused by Ostrinia nubilalis, Diabrotica spp. and Myocastor coypus were identified as the main crop enterprise challenges. Main forages cultivated were alfalfa and corn silage second seeding with a total cost of production of (€/ha) 1968 ± 362 and 2,581 ± 221, with an average yield of 9.61 ± 1.24 and 17.22 ± 2.46 ton of DM per hectare, respectively. Results of this study can provide useful benchmark or reference for dairy management practices, crops and dairy performances, forages production costs on very well-managed North Italian dairy farms at the present time.Highlights benchmarks for dairy farms management practices, economic and reproductive performance cost of production of forages in northern Italy.

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 regre

Gluten free 'tagliatelle' were prepared with teff flour and increasing levels (0, 20 and 40%, w/w; indicating control, T20 and T40, respectively) of a new developed white-seeded low phytic acid and lectin free (ws+lpa+lf) common bean flour. On a dry matter (DM) basis, total starch decreased (p < 0.05) from 72.2 to 65.1 and 60.2%, while protein and dietary fibre increased (p < 0.05) from 9.9 to 13.3% and 16.5% and from 8.5 to 11.8% and 15.7% for control, T20 and T40, respectively. The chemical score of protein increased (p < 0.05) from 46 for control to 65 for T40. The colour was influenced (p < 0.05) by bean inclusion, whereas no difference was reported for texture properties. The ws+lpa+lf bean inclusion increased (p < 0.05) the resistant starch content (from 6.6% DM for control to 18.6% DM for T40) while decreased from 60 for control to 39 for T40 (p < 0.05) the in vitro glycaemic index. The partial replacement of teff flour with bean flour can favourably be used in gluten free pasta formulation.

The objective of this study was to verify the effect of mean particle size (mPS) on both gas production and in vitro rumen starch degradability (IVSD) of corn and barley meals (Cm and Bm, respectively). Batches of the same Cm or Bm were separately processed through 2 different mills (i.e., a cutter mill or a rotor speed mill) equipped with or without different screens to achieve different mPS for each tested meal. Samples were analyzed accordingly to a completely randomized design and the main tested effect of model was mPS (n = 11, from 0.46 to 3.50 mm mPS for Cm or n = 10, from 0.11 to 2.98 mm mPS for Bm). For both in vitro assays, the rumen inocula were collected from 2 rumen-fistulated Holstein lactating dairy cows fed a total mixed ration with 16.2% crude protein, 28.5% starch, and 35.0% neutral detergent fiber on a dry matter basis. To fit gas production data, 1-pool exponential model and 1-pool or 2-pool Gompertz models were adopted. The rate of gas production decreased and lag increased by increasing mPS of both Cm and Bm, irrespective of adopted 1-pool models. When the 2-pool Gompertz model was used to fit gas production data, a shift of particles from fast to slow fermentable pools was measured by increasing mPS. In particular, the ratio between fast and slow final volumes ranged from 0.90 at 0.11 mm mPS to 0.10 at 2.98 mm mPS for Bm. For Cm, the ratio between fast and slow final volumes decreased quadratically by increasing mPS, with the highest value (i.e., 0.58) measured at the lowest tested mPS. Values lower than 0.10 were measured for mPS greater than 1.93 mm for Cm. Concerning IVSD data, linear decreases in rate of starch degradation equal to -0.049 or -0.092 h-1 for each 1-mm increase in mPS were achieved for Cm and Bm, respectively. The 7-h IVSD decreased by 6.3 or 6.5% starch for each 1-mm increase in mPS of Cm or Bm, respectively. Present findings supported the hypothesis that different particle sizes within the same starch source represent an im

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

BACKGROUND: To investigate corn silage fermentative quality, a principal factor analysis was carried out on a database consisting of 196 corn silages sampled from the core, lateral and apical parts of silo feed-out face and characterised by 36 variables. Eleven principal factor components (PCs) were retained and interpreted. Two PCs were related to chemical and digestibility variables; four PCs were characterised by end-products associated with clostridia, heterolactic, homolactic or aerobic fermentations; two PCs were associated with mycotoxins produced by Penicillium roqueforti or by Aspergillus fumigatus and Fusarium spp., while three PCs explained ensiling procedures adopted to store corn silages. RESULTS: Lower (P < 0.05) yeast or mould counts and greater (P < 0.05) aerobic stability were measured in core than in peripheral samples. Excluding PCs related to ensiling procedures, other PCs were able to predict microbiological counts, aerobic stability or biogenic amine content as verified by multiple linear regression analysis. Based on these results, several corn silage quality index calculations were computed by using a summative equation approach in which different PCs as well as diverse relative weights multiplying each PCs were combined. To compute definitive index calculation, only PCs explaining clostridia, heterolactic and homolactic fermentations were used with relative weights of 30%, 50% and 20%. CONCLUSIONS: The new proposed fermentative quality index was highly correlated to parameters related to corn silage fermentative quality, such as microbiological counts, aerobic stability or biogenic amines and it properly discriminated well- and poorly preserved forages.

The objective of this work was to reduce the predictor dimensionality and to develop a model able to forecast Clostridium tyrobutyricum 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 C. tyrobutyricum cell and spore counts by adoption of a molecular DNA–based method. A partial least squares (PLS) regression with a leaveone- out cross-validation method was used to reduce the dimensionality of the original predictors (n = 30) by projecting the independent variables into latent constructs. In a first step of the model development, the importance of independent variables in predicting C. tyrobutyricum 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 an

BACKGROUND: A survey on 68 dairy farms was carried out to evaluate the ensiling procedures adopted to store corn silage. Samples from core, lateral and apical zones of the feed-out face of silos were analysed. A principal factor analysis (PFA) was carried out on the entire database (196 silage samples and 36 variables) and 11 principal factor components (PCs)were retained and interpreted. RESULTS: Ensiling procedures influenced the area exposed to risk of air penetration. Cores had higher dry matter, starch and lactic acid content or lower pH, fibre, propionate and butyrate concentrations than peripheral samples (P < 0.05). The highest (P < 0.05) mycophenolic acid and roquefortina C concentrations were detected in lateral samples. Chemical and digestibility variables loaded on two PCs; four PCs were characterized by end-products associated with clostridia, heterolactic, homolactic and aerobic fermentations; two PCs were associated withmycotoxins, whereas three PCs explained ensiling procedures. CONCLUSION: The main quality traits of corn silages differed throughout the entire silo face. Minimization of the area exposed to risk of air penetration represents the best strategy to preserve the nutritional value and safety of corn silages. PFA allowed a clusterization of original variables into 11 PCs, appearing able to discriminate well and poorly preserved corn silages.

In pig nutrition, the analysis of starch is merely focused on assessing total quantity. However, indications suggest that a certain fraction of starch, defined as resistant starch (RS), can escape digestion in the upper gastrointestinal tract therefore passing into the large bowel where can act as fermentative substrate. Nutritionally RS, along with other nonstarch polysaccharides and non-digestible oligosaccharides, is regarded as non-digestible carbohydrate. As for humans, the concept of RS has gained increasing attention also in pig nutrition. As a consequence, research to obtain a deeper knowledge on how different RS levels and types may affect energy metabolism, nutrient availability, pig performance and induce positive effects on pigs through fermentation has progressed recently. Therefore, this review comprises updated data on: (i) factors related to the RS content in feed; (ii) systemic effects of RS from various sources in pigs; (iii) aspects associated to the RS fermentation process and role of RS in the pig large intestine; (iv) possible implications of RS on the environmental load of pig facilities. Since the digestibility of starch is compromised in the early period after weaning, the present discussion will be mainly restricted to older animals (especially growing pigs). (C) 2015 Elsevier B.V. All rights reserved.

The study was performed on forages (n = 8), nonforage fibrous feeds (n = 10), and crop residues (n = 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 (P < 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 (P < 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 (R2> 0.80, P < 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 metho