在这项研究中,基于Lallemantiaroyleana粘液(LRM)的可食用涂层,包含1.5×108和3×109CFU/mL干酪乳杆菌XN18(Lbc1.5和Lbc3),旨在提高新鲜开心果的质量和保质期。新鲜的开心果涂有LRM+Lbc及其理化成分,微生物,和感官性能在1-,5-,15-,25-,在4℃下储存35天在存储日结束时,与控制相比,可食用涂层中益生菌分离物的存在(特别是LRM+Lbc3)导致真菌生长显着下降(3.1与5.8对数CFU/g),体重减轻(6.7vs.8.1%),和脂肪氧化(0.19vs.0.98meqO2/kg),和保存的总叶绿素(8.1vs.5.85mg/kg)和酚(31.5vs.20.32毫克GAE/100克),和抗氧化活性(38.95vs.15.18%)的样品在存储期间。此外,LRM+Lbc3包被的样品在整个储存过程中具有高于推荐水平(6.85-9.29logCFU/g)的益生菌数。小组成员极大地接受了涂有富含益生菌的可食用涂层的开心果。在下一节中,高斯过程回归(GPR)用于预测一些参数,包括:体重减轻,TSS,脂肪含量,PV,可溶性碳水化合物含量,活力,总酚类化合物,抗氧化活性,霉菌和酵母,总叶绿素,总类胡萝卜素,颜色,气味和整体接受度。结果表明,探地雷达模型的实际数据与预测数据有很好的一致性,可用于类似情况,降低实验室测试成本,增加分析响应。
In this
study, Lallemantia royleana mucilage (LRM) based edible coating containing 1.5 × 108 and 3 × 109 CFU/mL Lacticaseibacillus casei XN18 (Lbc1.5 and Lbc3) was designed to improve the quality and shelf-life of fresh pistachio. The fresh pistachios were coated with LRM + Lbc and their physicochemical, microbial, and sensory properties were evaluated after 1-, 5-, 15-, 25-, and 35-day storage at 4 °C. By the end of storage day, in comparison to control, the presence of probiotic isolate in the edible coating (particularly LRM + Lbc3) led to a marked decrease in fungal growth (3.1 vs. 5.8 Log CFU/g), weight loss (6.7 vs. 8.1%), and fat oxidation (0.19 vs. 0.98 meq O2/kg), and preserved total chlorophylls (8.1 vs. 5.85 mg/kg) and phenols (31.5 vs. 20.32 mg GAE/100 g), and antioxidant activity (38.95 vs. 15.18%) of samples during storage period. Furthermore, LRM + Lbc3-coated samples had a probiotic number above the recommended level (6.85-9.29 log CFU/g) throughout storage. The pistachios coated with probiotic-enriched edible coatings were greatly accepted by panelists. In the next section, Gaussian Process Regression (GPR) was used for predicting some parameters including: weight loss, TSS, Fat content, PV, Soluble carbohydrate content, Viability, Total phenolic compounds, Antioxidant activity, Mold and yeast, Total chlorophylls, Total carotenoids, Color, Odor and Overall acceptance. The results indicated that, there is a good agreement between the actual and predicted data by GPR model and it can be used for similar situation to decrease the cost of laboratory tests and increase the respond of analysis.