Hydrothermal conversion of ice‐cream wastewater

Mapping the meltdown behavior of frozen dairy desserts

The meltdown test is an efficient tool widely and commonly used to characterize structural changes in frozen desserts resulting from different ingredients and processing conditions. The meltdown is commonly determined by a gravimetric test, and it is used to obtain the onset (Mon), rate (Mrate), and maximum (MMax) meltdown. However, these parameters are calculated ambiguously due to inconsistencies in the methodology. This work aims to model the meltdown curves (weight vs. time) of different commercial frozen dessert samples (36 commercial samples). Samples of commercial frozen desserts (40-60 g) was placed on a 304 stainless wire cloth (1.50 mm opening size and 52% open area) suspended ∼15 cm above an analytical balance, and the dripped portion of the melted sample was continuously recorded throughout the duration of the test. The meltdown test was conducted at room temperature. Each meltdown test generated between 3,000 to 4,000 data points and was modeled using 4 equations: the logistic model, the Gompertz model, the Richard model, and the Hill model. All the meltdown curves were sigmoidal in shape, regardless of the type of frozen dessert. The experimental meltdown curves were adequately represented by the logistic model, judging by several criteria (R2 = 0.999, RAdj2 = 0.999, Akaike information criterion = 6,582, and F-value = 1.88 × 106). Thus, the logistic model was shown to be an effective tool for predicting the meltdown curves of frozen desserts, and it can be used to unambiguously define Mon, Mrate, and MMax. Moreover, a dimensionless response (meltdown behavior, MBe) that combines Mon, Mrate, and MMax was developed and used for mapping the meltdown of different commercial frozen desserts.

Microalgal-bacterial treatment of ice-cream wastewater to remove organic waste and harvest oil-rich biomass

The diversity of microalgae and bacteria allows them to form beneficial consortia for efficient wastewater treatment and nutrient recovery. This study aimed to evaluate the feasibility of a new microalgal-bacterial combination in the treatment of ice cream wastewater for biomass harvest. The bacterium Novosphingobium sp. ICW1 was natively isolated from ice cream wastewater and the microalga Vischeria sp. WL1 was a terrestrial oil-producing strain of Eustigmatophyceae. The ice cream wastewater was diluted 4 folds for co-cultivation, which was relatively less inhibitory for the growth of Vischeria sp. WL1. Four initial algal-bacterial combinations (v:v) of 150:0 (single algal cultivation), 150:1, 150:2, and 150:4 were assessed. During 24 days of co-cultivation, algal pigmentation was dynamically changed, particularly at the algal-bacterial combination of 150:4. Algal growth (in terms of cell number) was slightly promoted during the late phase of co-cultivation at the combinations of 150:2 and 150:4, while in the former the cellular oil yield was obviously elevated. Treated by these algal-bacterial combinations, total carbon was reduced by 67.5 ~ 74.5% and chemical oxygen demand was reduced by 55.0 ~ 60.4%. Although single bacterial treatment was still effective for removing organic nutrients, the removal efficiency was obviously enhanced at the algal-bacterial combination of 150:4. In addition, the harvested oils contained 87.1 ~ 88.3% monounsaturated fatty acids. In general, this study enriches the biotechnological solutions for the sustainable treatment of organic matter-rich food wastewater.