Abrol Ghan Shyam, Singh Amit Kumar, Pal Ranjit, Kumar Ashwani, Sharma Priyanka, Sharma Gaurav
Department of Postharvest Technology, College of Horticulture and Forestry, Rani Lakshmi Bai Central Agricultural University, Jhansi, India.
Department of Postharvest Technology, Banda University of Agriculture and Technology, Banda, India.
Heliyon. 2023 Jul 29;9(8):e18533. doi: 10.1016/j.heliyon.2023.e18533. eCollection 2023 Aug.
Bottle gourd pomace, a waste from vegetable processing industry was used to prepare instant (dessert) mix. In this study, the bottle gourd was procured from the farm, washed, grated, steam blanched and the grits were further divided into two parts. One part of grits was dried without juice extraction (BGFD- Bottle gourd fresh dried), while, the other half (BGPD- Bottle gourd pomace dried) was dehydrated after extraction of juice. The dehydrated grits were used for the preparation of mix and the recipe was optimized using RSM Central Composite Design (CCD). The variables were BGFD and BGPD ranged 3-7 g. The other ingredients with the fixed quantities were milk powder (50 g), sugar (15 g), and small cardamom (1 g). The product was selected based on sensory responses like taste, colour, flavour, texture, and overall acceptability (OAA). The software suggested a mix prepared using 7 g BGFD and 3 g BGPD will produce the best sensory scores. The prepared mix had a moisture, TSS, carbohydrates, reducing sugars, total sugars, titratable acidity, crude protein, and crude fat content of 7.9%, 27 °B, 72.21%, 10.79%, 16.75%, 0.896% CA, 10.76%, and 7.63%, respectively. The product was rich in energy (400.55 kcal/100 g), total phenols (4.99 mg/100 g), and exhibited strong antioxidant activity (46%). The total plate count on the product on nutrient agar medium was 4.3 × 10 CFU/g. The could be prepared by adding 140 mL of water to 70 g of water to kheer mix and cooking it for 10 min. Further, to see the credibility and obtain more clearer patterns, the Canonical Correlation Analysis (CCA) and Principal Component Analysis (PCA) were applied. The overall variation of the BGFD and BGPD on the sensory parameters based on canonical correlation analysis was 92.5%. The sum of Principal Components PC1 and PC2 explained a very high variability (98.2%) among the studied treatments.
葫芦渣是蔬菜加工业的一种废弃物，被用于制备即食（甜点）混合物。在本研究中，葫芦从农场采购，洗净、磨碎、蒸汽热烫，然后将粗粒进一步分成两部分。一部分粗粒不榨汁进行干燥（BGFD - 鲜葫芦干燥），而另一半（BGPD - 葫芦渣干燥）在榨汁后进行脱水。脱水后的粗粒用于制备混合物，并使用响应曲面法中心复合设计（CCD）对配方进行优化。变量为BGFD和BGPD，范围为3 - 7克。其他固定用量的成分是奶粉（50克）、糖（15克）和小豆蔻（1克）。根据口感、颜色、风味、质地和总体可接受性（OAA）等感官反应来选择产品。软件建议使用7克BGFD和3克BGPD制备的混合物将产生最佳感官评分。制备的混合物的水分、总固形物、碳水化合物、还原糖、总糖、可滴定酸度、粗蛋白和粗脂肪含量分别为7.9%、27°B、72.21%、10.79%、16.75%、0.896%（以柠檬酸计）、10.76%和7.63%。该产品富含能量（400.55千卡/100克）、总酚（4.99毫克/100克），并具有较强的抗氧化活性（46%）。在营养琼脂培养基上该产品的总平板计数为4.3×10 CFU/克。通过向70克印度奶糊混合物中加入140毫升水并煮10分钟可制备出印度奶糊。此外，为了验证可信度并获得更清晰的模式，应用了典型相关分析（CCA）和主成分分析（PCA）。基于典型相关分析，BGFD和BGPD对感官参数的总体变化为92.5%。主成分PC1和PC2的总和解释了所研究处理之间非常高的变异性（98.2%）。
