4.6 Article

Proposal and validation of integrated alfalfa silage quality index (ASQI) method for the quality assessment of alfalfa silage for lactating dairy cows

Journal

ANIMAL FEED SCIENCE AND TECHNOLOGY
Volume 289, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j.anifeedsci.2022.115339

Keywords

Silage quality index; Minimum data set; Milk yield; Dairy cow; Silage-based diet

Funding

  1. Key Research and Development Program of the Ningxia Hui Autonomous Region [2021BEF02018]
  2. Scientific Research Project for Major Achievements of the Agricultural Science and Technology Innovation Program (ASTIP) [ASTIP-IAS07-1, CAAS-XTCX2016011-01]
  3. Beijing Dairy Industry Innovation Team [BAIC06-2022]

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This study analyzed the variability of alfalfa silage quality and identified key parameters for predicting milk yield in lactating dairy cows fed alfalfa silage-based diets. The study also proposed an Alfalfa Silage Quality Index (ASQI) and a grading system for evaluating silage quality. The results showed that the ASQI has a positive correlation with daily milk yield and is an effective tool for assessing silage quality.
Understanding the variability of alfalfa silage quality, milk production of lactating dairy cows fed alfalfa silage-based diets and the nexus between alfalfa silage quality and milk yield is vital for silage quality improvement while contributing to profitable milk production. This study presented and analyzed the variations of 20 silage quality parameters, including dry matter (DM), neutral detergent fiber (NDF) assayed with a heat-stable amylase and expressed exclusive of residual ash (aNDFom), pH, crude protein (CP), acid detergent fiber (ADF), acid detergent insoluble CP (ADICP), neutral detergent insoluble CP (NDICP), ammonia, lignin, indigestible NDF (iNDF), starch, ether extract (EE), 30-h in vitro neutral detergent digestibility, iNDF corrected digestible aNDFom fraction after 30-h in vitro incubation, ash, lactic acid, acetic, propionic acid, lactic: propionic acid ratio and butyric acid which were determined on 134 samples collected from dairy farms located in north and northeast China. The key silage quality parameters that best predicted milk yield of lactating dairy cows fed alfalfa silage-based diets were determined and weighted using the Multiple Regression Analysis technique and parameters were normalized using standard scoring functions. Weighted and normalized silage parameters were then integrated into the Alfalfa Silage Quality Index (ASQI). The ASQI has subsequently been converted into Alfalfa Silage Quality Scores (ASQS, 0-100). The index model consists of seven crucial parameters, i.e., CP, iNDF-corrected digestible aNDFom fraction after 30-h in vitro incubation, ADF and ash as nutritional quality parameters and ammonia-N, lactic acid and acetic acid (on DM basis) as fermentation quality parameters. Based on the index scores, silages were grouped into five quality grades; poor, fair, average, good , excellent having grade mean index scores of 16, 32, 49, 69 and 83, respectively. Overall, 85% of the experimental samples were graded as or above average silage quality indicating that the quality of the alfalfa silage produced in the largest dairy-producing areas in China were above average in quality. The new ASQI has a positive correlation with daily milk yield (r = 0.62) and least error in the prediction of silage quality (Root mean square error-observations standard deviation ratio, RSR = 0.31 , concordance correlation coefficient, CCC = 0.71), showing that the proposed ASQI model is an effective and practical tool for assessing silage quality.

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