Sterculia foetida Seed Kernel Proximate Principles, Minerals, Secondary Metabolites and Phytochemicals Vary among Landscapes of South Gujarat, India

Abstract

Sterculia foetida is valued in the food, cosmetic, medicine, pesticides, bio-oil, beverage, and furniture industries and seed kernels are eaten fresh by the local people. Therefore, present study with intended objective to find out the variation in proximate principles, micro-macro minerals, secondary metabolite, and volatile phytochemical composition of Sterculia foetida across different landscapes (L1 & L8-arboreal; L2-agricultural and L3-L7-city avenue plantations) of South Gujarat, India. The objective was also to find out the superior genotypes for future improvement. Data sets generated on all attributes were analyzed using Complete Randomized Design (CRD) and F-test was done and ANOVA was constructed. Findings deduced significant (P ≤ 0.05) variations in S. foetida seed morpho-metric and kernel proximate principles namely moisture content, dry matter, crude protein, crude fiber, ether extract, acid insoluble ash, nitrogen free extract, total ash and organic matter (85.68, 14.32, 15.16, 8.81, 35.59, 2.78, 37.46, 97.02 and 2.98%, respectively).  The micro minerals viz. calcium (0.30), phosphorus (0.15) and magnesium (0.66) percentage and macro minerals namely zinc (88.59), iron (33.17), copper (14.56) and manganese (10.86) content (ppm) also exhibited significant variation except nitrogen (2.43). Seed kernel secondary metabolite like total phenols (0.70) and tannins (0.67) percentage, except saponin (0.27), varied significantly across the landscapes. Further, the gas-chromatography mass-spectrometry analysis revealed 14 volatile compounds in seed kernel methanol extract. 9-Octadecanone, nonanoic acid and stigmasterol, and 9-Octadecanone, stigmasterol and 2-Decanone were top most three compounds in seed kernel and kernel oil, respectively. Findings revealed that S. foetida seed kernel is energy rich, good amount of fat source and soluble carbohydrates. These findings on landscape variations in studied attributes would be helpful in selecting the landscapes/genotypes with higher nutritive seed kernels for further improvement.