Alshammari Fanar, Alam Md Badrul, Naznin Marufa, Javed Ahsan, Kim Sunghwan, Lee Sang-Han
Department of Food Science and Biotechnology, Graduate School, Kyungpook National University, Daegu 41566, Republic of Korea.
Food and Bio-Industry Research Institute, Inner Beauty/Antiaging Center, Kyungpook National University, Daegu 41566, Republic of Korea.
Pharmaceuticals (Basel). 2023 Feb 20;16(2):319. doi: 10.3390/ph16020319.
The date palm ( L.) is a popular edible fruit consumed all over the world and thought to cure several chronic diseases and afflictions. The profiling of the secondary metabolites of optimized ripe Ajwa date pulp (RADP) extracts is scarce. The aim of this study was to optimize the heat extraction (HE) of ripe Ajwa date pulp using response surface methodology (RSM) and artificial neural network (ANN) modeling to increase its polyphenolic content and antioxidant activity. A central composite design was used to optimize HE to achieve the maximum polyphenolic compounds and antioxidant activity of target responses as a function of ethanol concentration, extraction time, and extraction temperature. From RSM estimates, 75.00% ethanol and 3.7 h (extraction time), and 67 °C (extraction temperature) were the optimum conditions for generating total phenolic content (4.49 ± 1.02 mgGAE/g), total flavonoid content (3.31 ± 0.65 mgCAE/g), 2,2-diphenyl-1-picrylhydrazyl (11.10 ± 0.78 % of inhibition), and cupric-reducing antioxidant capacity (1.43 µM ascorbic acid equivalent). The good performance of the ANN was validated using statistical metrics. Seventy-one secondary metabolites, including thirteen new bioactive chemicals (hebitol II, 1,2-di-(syringoyl)-hexoside, naringin dihydrochalcone, erythron-guaiacylglycerol-β-syringaresinol ether hexoside, erythron-1-(4'--hexoside-3,5-dimethoxyphenyl)-2-syrngaresinoxyl-propane-1,3-diol, 2-deoxy-2,3-dehydro-N-acetyl-neuraminic acid, linustatin and 1-deoxynojirimycin galactoside), were detected using high-resolution mass spectroscopy. The results revealed a significant concentration of phytoconstituents, making it an excellent contender for the pharmaceutical and food industries.
海枣（Phoenix dactylifera L.）是一种广受欢迎的可食用水果，在世界各地都有消费，并且被认为可以治愈多种慢性疾病和病痛。目前对优化成熟的阿久哇海枣果肉（RADP）提取物的次生代谢产物的分析较少。本研究的目的是使用响应面法（RSM）和人工神经网络（ANN）建模来优化成熟阿久哇海枣果肉的热提取（HE），以提高其多酚含量和抗氧化活性。采用中心复合设计来优化热提取，以实现目标响应的最大多酚化合物和抗氧化活性，该目标响应是乙醇浓度、提取时间和提取温度的函数。根据响应面法估计，75.00%乙醇、3.7小时（提取时间）和67°C（提取温度）是产生总酚含量（4.49±1.02毫克没食子酸当量/克）、总黄酮含量（3.31±0.65毫克儿茶素当量/克）、2,2-二苯基-1-苦基肼（11.10±0.78%抑制率）和铜还原抗氧化能力（1.43微摩尔抗坏血酸当量）的最佳条件。使用统计指标验证了人工神经网络的良好性能。使用高分辨率质谱检测到71种次生代谢产物，包括13种新的生物活性化学物质（己糖醇II、1,2-二（丁香酰基）-己糖苷、柚皮苷二氢查耳酮、赤藓醇-愈创木基甘油-β-丁香树脂醇醚己糖苷、赤藓醇-1-（4'-己糖苷-3,5-二甲氧基苯基）-2-丁香树脂氧基丙烷-1,3-二醇、2-脱氧-2,3-脱氢-N-乙酰神经氨酸、亚麻抑素和1-脱氧野尻霉素半乳糖苷）。结果显示出大量的植物成分，使其成为制药和食品工业的优秀候选者。
