Geographical variability in morphology and nutritional composition of Moringa oleifera seeds: a meta-analysis

Abstract

The miracle tree, M. oleifera, is valued for its nutritional composition, climate adaptability, industrial and environmental usefulness. Despite well-known benefits, nutritional composition varies with the geographical location. The seeds of Moringa are rich in high-quality oil and protein and are also a source of carbohydrates, but their relative quantities vary among geographical locations. A meta-regression analysis was carried out using PRISMA guidelines, to explore the variability, and deciding factors in Moringa seeds. A systematic search of Scopus and google Scholar identified reports that mentioned morphological or nutritional or both traits was carried out. After removing duplicates and reviews, total 31 original research articles were included in the study. Two independent datasets, morphological and nutritional, were prepared by extracting numerical data of mature seeds. Statistical framework included Pearson's correlation to quantify trait relationship and ANCOVA to assess covariate effects on nutritional components. Datasets were analyzed using R software. Random effect meta regression model was employed to assess the heterogeneity in nutrient composition across climatic zones. The crude fat, total carbohydrates and crude protein were highly variable (σ = 14.56, 14.54 and 12.08 respectively). The variabilities in ash and moisture were low (σ =1.41 and 2.48 respectively) while crude fiber showed intermediate variability (σ = 2.87). Although, there was a trend in nutritional composition of M. oleifera seeds along the latitude and climatic zones, statistical model fitting was non-significant for these variables. Pearson's correlation among nutritional components was pronounced and significant, supported by carbon-nitrogen metabolism. This study did not find any trend in the highly variable morphological components (CV 38.52% and 43.12% for length and width respectively) of Moringa seeds with geographical location.