4.6 Article

Nutritional composition patterns and application of multivariate analysis to evaluate indigenous Pearl millet ((Pennisetum glaucum (L.) R. Br.) germplasm

Journal

JOURNAL OF FOOD COMPOSITION AND ANALYSIS
Volume 103, Issue -, Pages -

Publisher

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.jfca.2021.104086

Keywords

Millet; Pearl millet; Proximate composition; Multivariate data analysis; PCA; Heat map; HCA

Funding

  1. Division of Agricultural Education, ICAR under the Niche Area of Excellence (NAE) Programme (Scheme Strengthening and Development of Higher Agricultural Education in India) [Edn. 5(22)/2017-EPHS, 12/223]
  2. Global Environment Facility (GEF) of the United Nations Environment Program (UNEP)

Ask authors/readers for more resources

The study analyzed the nutritional composition of 87 different Pearl millet germplasm, showing significant variations in carbohydrate, protein, lipid, antinutritional factors, phenols, and minerals. Multivariate data analysis was used to identify the diversity of these attributes across germplasm, revealing distinct variations in different nutritional contents.
The nutritional composition of 87 diverse Pearl millet (Pennisetum glaucum (L.) R. Br.) germplasm including landraces and commercial varieties was assessed through standard protocols. The results indicated a substantial variability in total carbohydrates [starch (50.37-63.25), amylose (19.26-27.90), sucrose (0.58-1.53), glucose (0.32-0.75), resistant starch (RS) (1.49-3.52), total soluble sugars (TSS) (1.53-3.22), expressed as g/100 g], protein (8.07-18.15 g/100 g), total dietary fibre (TDF) (7.68-16.18 g/100 g), lipids and fatty acids [total lipid (5.24-9.99), palmitic (20.30-32.49), linoleic (32.11-46.91), oleic (21.99-33.43) and stearic acid (3.28-7.91) expressed as g/100 g], antinutritional factors [phytic acid (0.54-1.43 g/100 g) and raffinose family oligosaccharides (RFOs) (0.27-2.08 mmol/100 g)], phenols (0.04-0.21 g/100 g), and minerals. Multivariate analysis using hierarchical clustering analysis (HCA), and principal component analysis (PCA) was used to decipher the diversity of these attributes across germplasm. Multivariate data analysis (MVDA) can be applied for deciphering the differences/ similarities between multiple nutritional attributes, sample types or for projecting the object in a two/ three-dimensional factor-plane, determined based on various distinct characteristics. HCA revealed that Cluster I, II and III showed higher content of amylose, starch, moisture, cluster III had higher lipid content. cluster I, II, III and IV showed higher RS. Cluster II and III had higher TSS, cluster III showed higher sucrose content. Cluster V and VII were indicated by higher glucose and protein content. Cluster II, III, IV and VI showed phytic acid content and cluster III showed higher mineral content. The germplasm displayed distinct regiospecific variations in their nutritional content. Those derived from Gujarat, Maharashtra and Uttarakhand showed higher protein content. Those derived from Haryana, Karnataka, New Delhi, Punjab, Tamil Nadu and Uttar Pradesh showed high carbohydrates. Those from New Delhi, Punjab, Tamil Nadu and Uttarakhand showed high Iron content and high copper was found in germplasm from Maharashtra, Punjab and Tamil Nadu. High zinc was found in germplasms from Maharashtra, Punjab, Tamil Nadu and Uttar Pradesh. More calcium was found in germplasm from Maharashtra, Punjab, New Delhi, and Tamil Nadu. The analysis can form the basis for the commercialization and utilization of pearl millet using efficacious breeding strategies.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.6
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available