Agglomeration of turmeric powder and its effect on physico-chemical and microstructural characteristics

• RRB model fits well for particle size distribution data of agglomerates.
• Size of agglomerates ranges between 50 and 160 μm.
• Shape of agglomerates varies from spheriod to elongated ellipsoids.
• ANN having a structure of 2–10-8–4 has been developed with a rms error of 7.6%.

Agglomerated foods have gained attention in recent years due to their convenience in use. Turmeric powder has been subjected to agglomeration process at different moisture contents (10–28%) and steaming times (0–60 min). Experimental cumulative particle size distribution data of agglomerated samples can be predicted well (0.951 ⩽ r ⩽ 0.999, p ⩽ 0.01) with Rosin–Rammler–Bennett model. The functional properties related to hydration characteristics like wetting time (10–35 s) and sinking time (15–115 s) of agglomerated samples decrease with an increase in moisture content and/or steaming time. Microstructural observation shows that the non-agglomerated sample possesses spheroids and ellipsoids of different sizes. The size of agglomerates ranges between 50 and 160 μm; their shape varies from spheroid to elongated ellipsoids. Image analysis infers that the size related parameters increase with an increase in moisture content/steaming time. A four-layered artificial neural network having a structure of 2–10-8–4 has been developed to predict the agglomeration process of turmeric powder.