Use of principal factor analysis to generate a corn silage fermentative quality index to rank well- or poorly preserved forages

Clostridium tyrobutyricum occurrence in silages and cattle feed: Use of molecular and simulation data to optimize predictive models

Introduction

Poor quality silage can derive from the presence of deleterious microorganisms such as clostridia. Their dissemination along the food chain, especially in milk, causes issues such as the cheese late-blowing defect, particularly triggered by Clostridium tyrobutyricum. The scope of our study was to determine the C. tyrobutyricum occurrence in three different farms across four time periods in relation to the animal diets, specifically the Total Mixed Ration (TMR), by using real-time PCR.

Methods

For this purpose, molecular-derived data were exploited to optimize a predictive model that simulated the farm conditions favoring the growth of butyric acid bacteria such as C. tyrobutyricum.

Results

Our results showed that the originally utilized predictive model strongly underestimated the growth of C. tyrobutyricum in comparison to the molecular data. At the same time, our findings uncovered an additional source of contamination in the TMR related to silage and dietary residues that represent a reservoir of microbial contamination during successive TMR preparation. Based on these findings, the optimization of the model parameters such as growth rate range and the inclusion of the residues in the model, allowed a more accurate prediction of the contamination levels. Therefore, this study revealed that proper hygiene practices such as the removal of silage and TMR residues within the farm environment is essential to control the contamination by C. tyrobutyricum and avoid food waste and economic losses.

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.

Changes of Milk Metabolomic Profiles Resulting from a Mycotoxins-Contaminated Corn Silage Intake by Dairy Cows

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 feeding systems.

Co-Occurrence of Regulated and Emerging Mycotoxins in Corn Silage: Relationships with Fermentation Quality and Bacterial Communities

Sixty-four corn silages were characterized for chemicals, bacterial community, and concentrations of several fungal metabolites. Silages were grouped in five clusters, based on detected mycotoxins, and they were characterized for being contaminated by (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. Altersetin was detected in clusters 1, 3, and 5. Rugulusovin or brevianamide F were detected in several samples, with the highest concentration in cluster 3. Emodin was detected in more than 50.0% of samples of clusters 1, 3 and 5, respectively. Kojic acid occurred mainly in clusters 1 and 2 at very low concentrations. Regarding Fusarium mycotoxins, high occurrences were observed for FB3, FB4, FA1, whereas the average concentrations of FB6 and FA2 were lower than 12.4 µg/kg dry matter. Emerging Fusarium-produced mycotoxins, such as siccanol, moniliformin, equisetin, epiequisetin and bikaverin were detected in the majority of analyzed corn silages. Pestalotin, oxaline, phenopirrozin and questiomycin A were detected at high incidences. Concluding, this work highlighted that corn silages could be contaminated by a high number of regulated and emerging mycotoxins.

Effects of Different Parts on the Chemical Composition, Silage Fermentation Profile, In Vitro and In Situ Digestibility of Paper Mulberry

Simple Summary

Paper mulberry (Broussonetia papyrifera, PM) is a potential roughage source widely distributed in Asia, but the chemical composition, silage fermentation, and digestibility are not fully understood. Here, we compared the chemical composition, silage fermentation, and digestibility of leaf, stem, and whole plant of PM to evaluate its feeding value. The result showed that the leaf had lower fiber content and higher protein content than the stem and whole plant. Meanwhile, the stem silage had the lowest pH value and lactate content, while those in the leaf were the highest. The in vitro and in situ digestibility showed the leaf was more digestible. Our study gives the reference of different parts of PM to be used as a feedstuff.

Abstract

Paper mulberry (Broussonetia papyrifera, PM) is high protein but unutilized as a feed source. The study explores the different parts (leaf, stem, and whole plant) of PM chemical composition, silage fermentation, and in vitro and in situ digestibility, aiming to give some guidelines to PM usage as feed. The result showed that the leaf had a higher fresh weight than the stem (p < 0.05). The dry matter contents of the three groups had no differences. The highest crude protein, ether extract, water-soluble carbohydrate, ash, calcium, phosphorus, amino acid contents, and butter capacity were observed in the leaf (p < 0.05). The stem had the highest (p < 0.05) neutral detergent fiber, acid detergent fiber, and lignin contents. After ensiling, the stem silage had the lowest pH value, ammonia nitrate (NH₃-N), lactate, acetate, and propionate (p < 0.05). The leaf silage had the highest pH value (p < 0.05). The lactate, acetate, and propionate in the leaf and whole plant silage had no difference. The butyrate was not detected in all silage. The in vitro and in situ digestibility experiments showed the leaf had the highest digestibility (p < 0.05), which could produce more volatile fatty acids and have a higher effective digestibility. These results allow a greater understanding of PM to be used as a feedstuff.

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.

Biogenic amines and hygienic quality of lucerne silage

This experiment examined the influence of two different silage additives of biological (Lactococcus lactis, Lactobacillus plantarum, Enterococcus faecium, enzyme xylanase) and chemical (43% formic acid, 30% ammonium formate, 10% propionic acid, 2% benzoic acid) types on biogenic amines concentration, nutrient content, fermentation process, and microbiologic indicators in lucerne (Medicago sativa) silage after 90 days of fermentation. The biological additive significantly (P < 0.05) increased putrescine (+51%), lactic acid (+11%) and protein content (+11%) in comparison with control silage. It significantly decreased cadaverine (−29%), histamine (−57%), spermidine (−15%), spermine (−55%), acetic acid (−40%), ethanol (−55%), ammonium (−25%) and ash (−9%). After the chemical-additive treatment, greater amounts of histamine and tyramine were recorded. Significant decrease was observed in the concentrations of putrescine (−18%), cadaverine (−55%), spermidine (−47%), spermine (−45%), lactic acid (−16%), acetic acid (−46%), ammonium (−59%), ash (−13%) and fat (−24%). Populations of bacteria associated with lactic acid fermentation, moulds, yeasts, enterobacteria and total microorganisms count were also influenced. Both biological and chemical additives can be highly recommended for producing high-quality silages meeting hygienic requirements. In lucerne silage, the chemical preservative showed a stronger effect in achieving the health safety of silage compared to the biological inoculant.

Review on Mycotoxin Issues in Ruminants: Occurrence in Forages, Effects of Mycotoxin Ingestion on Health Status and Animal Performance and Practical Strategies to Counteract Their Negative Effects

Ruminant diets include cereals, protein feeds, their by-products as well as hay and grass, grass/legume, whole-crop maize, small grain or sorghum silages. Furthermore, ruminants are annually or seasonally fed with grazed forage in many parts of the World. All these forages could be contaminated by several exometabolites of mycotoxigenic fungi that increase and diversify the risk of mycotoxin exposure in ruminants compared to swine and poultry that have less varied diets. Evidence suggests the greatest exposure for ruminants to some regulated mycotoxins (aflatoxins, trichothecenes, ochratoxin A, fumonisins and zearalenone) and to many other secondary metabolites produced by different species of Alternaria spp. (e.g., AAL toxins, alternariols, tenuazonic acid or 4Z-infectopyrone), Aspergillus flavus (e.g., kojic acid, cyclopiazonic acid or β-nitropropionic acid), Aspergillus fuminatus (e.g., gliotoxin, agroclavine, festuclavines or fumagillin), Penicillium roqueforti and P. paneum (e.g., mycophenolic acid, roquefortines, PR toxin or marcfortines) or Monascus ruber (citrinin and monacolins) could be mainly related to forage contamination. This review includes the knowledge of mycotoxin occurrence reported in the last 15 years, with special emphasis on mycotoxins detected in forages, and animal toxicological issues due to their ingestion. Strategies for preventing the problem of mycotoxin feed contamination under farm conditions are discussed.