Near-infrared reflectance spectroscopy (NIRS): An innovative, rapid, economical, easy and non-destructive whole grain analysis method for nutritional profiling of pearl millet genotypes

被引：1

作者：

Yadav, Sunaina ^{[1
]}

Tomar, Maharishi ^{[2
]}

Singhal, Tripti ^{[1
]}

Joshi, Nilesh ^{[1
]}

Bhargavi, H. A. ^{[1
,5
]}

Aavula, Naveen ^{[1
]}

Langyan, Sapna ^{[3
]}

Joshi, Tanay ^{[4
]}

Satyavathi, C. Tara ^{[5
]}

Rana, Jai Chand ^{[6
]}

Singh, Sumer Pal ^{[1
]}

Bhardwaj, Rakesh ^{[3
]}

Riar, Amritbir ^{[4
]}

机构：

[1] Indian Agr Res Inst, ICAR, New Delhi 110012, India

[2] Indian Grassland & Fodder Res Inst, ICAR, Jhansi 284003, Uttar Pradesh, India

[3] Natl Bur Plant Genet Resources, ICAR, New Delhi 110012, India

[4] FiBL, Res Inst Organ Agr, Dept Int Cooperat, Frick, Switzerland

[5] Indian Inst Millets Res, ICAR, Hyderabad 500030, Telangana, India

[6] Alliance Biovers Int & CIAT, India Off, New Delhi, India

来源：

JOURNAL OF FOOD COMPOSITION AND ANALYSIS | 2025年 / 142卷

关键词：

Pearl millet; Near-infrared reflectance spectroscopy (NIRS); Nutritional composition; Modified partial least squares (MPLS) regression; Biofortification; PHYTIC ACID CONTENT; PHYSICOCHEMICAL PROPERTIES; CEREAL-GRAINS; STARCH; DIGESTIBILITY; PROTEIN;

D O I：

10.1016/j.jfca.2025.107373

中图分类号：

O69 [应用化学];

学科分类号：

081704 ;

摘要：

Pearl millet, known for its nutritional excellence and climatic resilience, is becoming important in addressing food and nutritional security Current work introduces Near Infrared Spectroscopy models to estimate nutrients in pearl millet grains. The model is quick, economic and non-destructive alternative to traditional methods, useful in advancing the single plant progenies for improving nutrient content in segregating generations. Spectra were acquired from 403 varied genotypes, and mathematical optimizations using derivatives were performed to enhance the models. The optimal configurations were "2,36,6,2" (order of derivatives, gap, first smoothing and second smoothing, respectively) for amylose, "2,32,6,2" for starch, "2,32,8,2" for oil and protein, and "3,36,6,2" for phytic acid. The models were refined using modified partial least squares (MPLS) regression on spectra processed to eliminate variations with standard normal variate (SNV) and detrending (DT) techniques. The adjusted MPLS models exhibited impressive coefficients of determination of 0.985, 0.984, 0.986, 0.969 and 0.993 for amylose, protein, oil, starch and phytic acid, respectively. The SEP(C) values for amylose (0.347), starch (0.732), protein (0.313), phytic acid (0.014), and oil (0.162) suggest variable levels of predictive precision. Validation with independent samples showed superior predictive performance with coefficients of determination values ranging from 0.878 for phytic acid to 0.976 for protein, minimal bias, high ratios of prediction to deviation (2.93-5.81), and no significant differences between the predicted and reference values (p > 0.05). These advanced Near-Infrared Spectroscopy models allow quick and cost-effective nutritional assessment of pearl millet germplasm and breeding lines, supporting biofortification initiatives and enhancing nutritional security.

引用

页数：12

共 43 条

[1] Near-infrared spectroscopy (NIRS) for monitoring the nutritional composition of black soldier fly larvae (BSFL) and frass [J].