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

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 6 r 6 0.999, p 6 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 lm; 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.