Dataset Information

Authenticity of Hay Milk vs. Milk from Maize or Grass Silage by Lipid Analysis.

ABSTRACT: Hay milk is a traditional dairy product recently launched on the market. It is protected as "traditional specialty guaranteed" (TSG) and subjected to strict regulations. One of the most important restrictions is that the cow's feed ration must be free from silage. There is the need for analytical methods that can discriminate milk obtained from a feeding regime including silage. This study proposes two analytical approaches to assess the authenticity of hay milk. Hay milk and milk from cows fed either with maize or grass silage were analyzed by targeted GC-MS for cyclopropane fatty acid (dihydrosterculic acid, DHSA) detection, since this fatty acid is strictly related to the bacterial strains found in silage, and by HPLC-HRMS. The presence of DHSA was correlated to the presence of maize silage in the feed, whereas it was ambiguous with grass silage. HPLC-HRMS analysis resulted in the identification of 14 triacylglycerol biomarkers in milk. With the use of these biomarkers and multivariate statistical analysis, we were able to predict the use of maize and grass silage in the cow's diet with 100% recognition. Our findings suggest that the use of analytical approaches based on HRMS is a viable authentication method for hay milk.

SUBMITTER: Imperiale S

PROVIDER: S-EPMC8700964 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature

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Authenticity of Hay Milk vs. Milk from Maize or Grass Silage by Lipid Analysis.

Imperiale Sebastian S Kaneppele Elke E Morozova Ksenia K Fava Federico F Martini-Lösch Demian D Robatscher Peter P Peratoner Giovanni G Venir Elena E Eisenstecken Daniela D Scampicchio Matteo M

Foods (Basel, Switzerland) 20211126 12

Hay milk is a traditional dairy product recently launched on the market. It is protected as "traditional specialty guaranteed" (TSG) and subjected to strict regulations. One of the most important restrictions is that the cow's feed ration must be free from silage. There is the need for analytical methods that can discriminate milk obtained from a feeding regime including silage. This study proposes two analytical approaches to assess the authenticity of hay milk. Hay milk and milk from cows fed ...[more]

PMID: 34945477

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Project description:Maize silage is a key component of feed rations in dairy systems due to its high forage and grain yield, water use efficiency, and energy content. However, maize silage nutritive value can be compromised by in-season changes during crop development due to changes in plant partitioning between grain and other biomass fractions. The partitioning to grain (harvest index, HI) is affected by the interactions between genotype (G) × environment (E) × management (M). Thus, modelling tools could assist in accurately predicting changes during the in-season crop partitioning and composition and, from these, the HI of maize silage. Our objectives were to (i) identify the main drivers of grain yield and HI variability, (ii) calibrate the Agricultural Production Systems Simulator (APSIM) to estimate crop growth, development, and plant partitioning using detailed experimental field data, and (iii) explore the main sources of HI variance in a wide range of G × E × M combinations. Nitrogen (N) rates, sowing date, harvest date, plant density, irrigation rates, and genotype data were used from four field experiments to assess the main drivers of HI variability and to calibrate the maize crop module in APSIM. Then, the model was run for a complete range of G × E × M combinations across 50 years. Experimental data demonstrated that the main drivers of observed HI variability were genotype and water status. The model accurately simulated phenology [leaf number and canopy green cover; Concordance Correlation Coefficient (CCC)=0.79-0.97, and Root Mean Square Percentage Error (RMSPE)=13%] and crop growth (total aboveground biomass, grain + cob, leaf, and stover weight; CCC=0.86-0.94 and RMSPE=23-39%). In addition, for HI, CCC was high (0.78) with an RMSPE of 12%. The long-term scenario analysis exercise showed that genotype and N rate contributed to 44% and 36% of the HI variance. Our study demonstrated that APSIM is a suitable tool to estimate maize HI as one potential proxy of silage quality. The calibrated APSIM model can now be used to compare the inter-annual variability of HI for maize forage crops based on G × E × M interactions. Therefore, the model provides new knowledge to (potentially) improve maize silage nutritive value and aid genotype selection and harvest timing decision-making.

Project description:The aim of this study was to evaluate the relationship of milk odd- and branched-chain fatty acids (OBCFA) with urinary purine derivates and estimated ruminal microbial crude protein (MCP) synthesis. Forty-four lactating Holstein cows were used in a 4 × 4 Latin square design with 21-day periods comprised of a 13-day adaptation phase to diet followed by an 8-day sampling phase. Differences in estimated MCP yield and milk OBCFA composition were found by feeding total mixed rations containing forage (maize silage, MS; red clover silage, RCS) and concentrates (0.75:0.25) with targeted proportions of RCS to MS of 0.15:0.60, 0.30:0.45, 0.45:0.30, and 0.60:0.15 on a dry matter basis. The MCP was estimated from the total urinary purine derivate (PD) excretion (MCPPD) and intakes of metabolizable energy (MCPME) or digestible organic matter (MCPdOM). The Pearson correlations of individual OBCFA with urinary parameters (uric acid, allantoin, PD and nitrogen) were generally weak (r = -0.37 to 0.55). Yields of individual OBCFA correlated positively with MCPME and MCPdOM (r = 0.21 to 0.55). The prediction of urinary PD concentration was moderate (R2 = 0.64) when including the proportion of iso-C17:0. The prediction of total PD excretion was low (R2 = 0.21) with yields of iso-C15:0, anteiso-C17:0, and iso-C16:0. The prediction of MCPPD was high (R2 = 0.99) when including the iso-C16:0 and cis-9 C17:1 concentrations, while those of MCPME and MCPdOM were low (R2 = 0.37 and 0.36, respectively) when including yields of iso-C15:0, cis-9 C17:1, and iso-C18:0. The correlations and regression analyses demonstrate that the estimated MCP synthesis and urinary PD excretion can be only moderately predicted by yields and concentrations of individual or total OBCFA in cow's milk. However, milk OBCFA can still be seen as a promising, non-invasive method for predicting rumen function and microbial protein supply in dairy cows because MCP flow was not directly measured in this study but instead indirectly estimated probably comprising considerable deviations of the assumed values from the true ones.

Dataset Information

Authenticity of Hay Milk vs. Milk from Maize or Grass Silage by Lipid Analysis.

Publications

Authenticity of Hay Milk vs. Milk from Maize or Grass Silage by Lipid Analysis.

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