1H NMR Milk Metabolomics Response from Goats Supplemented with Date (Phoenix Dactylifera L.) Pit Powder: Benefiting from Agricultural Waste Byproduct
DOI:
https://doi.org/10.37934/araset.65.1.1432Keywords:
Agricultural productivity, date pit powder, goat milk, 1H NMR, process innovation, metabolomics, PCAAbstract
Utilizing a systems biology approach through metabolomics is crucial for analyzing milk quality. Continual animal supplementing is crucial for enhancing milk quality to ensure high food quality and agricultural productivity. Date pits are agricultural waste byproducts that can be used as active components in cosmetics, as a coffee substitute, and as animal feed. The study investigated the impact of adding date pit powder (DPP) to dairy goats' diet on the milk metabolites to determine possible benefits. Saanen-Boer crossed dairy goats were divided into six groups: control (untreated), 10g and 20g of Ajwa DPP (high quality), 10 g and 20 g of Mariami DPP (agricultural waste byproduct), and 30g of Mariami DPP exclusively. DPP supplementation was administered daily for 12 weeks. The goat milk obtained was analyzed using 1H NMR and then subjected to chemometric studies, namely PCA and PLS. Metabolites were analyzed using tools such as BAYESIL, Chenomx profiler and HMDB. Principal Component Analysis (PCA) showed that milk metabolites changed over time (month), and that supplementing breastfeeding goats with DPP did not result in distinct clusters. However, BAYESIL identified L-Proline, L-Carnitine, and myoinositol as molecules with less than 30 % biological variance at months 1 and 3 of the research, indicating good conservation. Only the levels of L-Carnitine and acetoacetate in the milk showed significant differences between the treatments. Ultimately, the DPP dosages were insufficient to impact the goat's metabolism, resulting in no impacts on milk metabolites. An adaptive response to DPP cultivars and doses was indicated by the results. Overall, these findings might help dairy goat and other ruminant breeders in predicting milk quality by utilizing metabolites as markers for food security (production and quality).