Fourier-transform mid-infrared spectroscopy for high-throughput phenotyping of total dietary fiber in pulse crops

Authors: MADURAPPERUMAGE, AMOD - Clemson University; THAVARAJAH, PUSHPARAJAH - Clemson University; TANG, LEUNG - Agilent Technologies, Inc; Vandemark, George; THAVARAJAH, DIL - Clemson University

Submitted to: The Plant Phenome Journal
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 4/2/2025
Publication Date: 6/1/2025
Citation: Madurapperumage, A., Thavarajah, P., Tang, L., Vandemark, G.J., Thavarajah, D. 2025. Fourier-transform mid-infrared spectroscopy for high-throughput phenotyping of total dietary fiber in pulse crops. The Plant Phenome Journal. 8(1). Article e70022. https://doi.org/10.1002/ppj2.70022.
DOI: https://doi.org/10.1002/ppj2.70022

Interpretive Summary: Dietary fiber is an important nutritional component of food and is composed of chains of cahbohydrates that are resistant to breakdown by digestive enzymes. Dietary fiber ferments in the upper intestine and promotes a "gut" microbiome that confers a range of human health benefits. Adequate consumption of dietary fiber has been associated with several health benefits, including reduced obesity and incidence of coronary artery disease. However, less than 10% of Americans consume the recommended daily amount of dietary fiber. Increased consumption of "pulse" crops including chickpea, lentil, and pea has been proposed to address the fiber gap in American diets. Increasing the concentration of dietary fiber is a target for breeders of pulses and other crops. Unfortunately, the most widely used methods for determining dietary fiber concentration in plant samples have several limitations. These include high costs per sample (upwards of $300/sample) for analysis by commercial laboratories, long processing times, and generatation of hazardous waste. Fourier transform mid-infrared (FT-MIR) spectroscopy is a technique that measures how chemical bonds vibrate when exposed to infrared light. Each type of compound that contributes to the nutritional quality of a food source, such as protein, minerals, carbohydrates, and fiber produces its own chemical signature for FT-MIR. The objective of this study was to develop a method to use FT-MIR to estimate the concentration of dietary fiber in samples of chickpea, lentil, and pea. First, at least 60 seed samples of each crop were analyzed by conventional laboratory methods to determine concentrations of dietary fiber. Then, small samples of 2-3 seeds were ground to flour and the chemical signature of the flour determined by FT-MIR. Statistical approaches were used to compare the chemical signatures of flour with the amount of dietary fiber determined by conventional laboratory methods. The FT-MIR method was approximately 90% as accurate as conventional laboratory methods at determining dietary fiber concentrations from small samples of chickpea, lentil, and pea flour. FT-MIR method has several advantages over other laboratory methods used to determine dietary fiber concentration including lower costs per sample, more rapid analysis on a per sample basis, less material required for analysis, and no accumulation of hazardous wastes. This new method provides breeders of pulses and other crops with a rapid, cost-effective, and accurate way to determine dietary fiber concentration that will accelerate the development of more nutritious varieties.

Technical Abstract: This study uses Fourier-transform mid-infrared (FT-MIR) spectroscopy as a high-throughput phenotyping tool to quantify total dietary fiber (TDF) in chickpea (Cicer arietinum L.), dry pea (Pisum sativum L.), and lentil (Lens culinaris Medik.) for pulse crop breeding purposes. The standard analytical approach for TDF analysis is AOAC method 985.29, which requires extensive sample preparation with extended analysis times of up to 30 h. The FT-MIR approach was developed to enhance rapid and non-destructive analysis and minimize the traditional workload associated with phenotyping TDF in pulse crops by accomplishing the same task in a shorter time and at minimal cost. Partial least squares regression (PLSR) was applied with chemometric modeling in mid-infrared (MIR) regions (650-1480 and 2771-3700 cm-1), encompassing spectral bands associated with undigested polysaccharides and partially or indigested protein and fatty acid methyl ester (FAME) fractions that fingerprint TDF. K-fold cross-validation was used for PLSR modeling to enhance computational speeds with large-scale data processing. These PLSR models for chickpea, dry pea, and lentil have regression coefficients (R2) 0.91, 0.96, and 0.94 with root mean square errors of prediction less than 1. This technique supports rapid phenotyping of TDF (~1–2 min) from raw flour. Thus, the FT-MIR technique can relieve the phenotyping bottleneck in pulse breeding and pulse-based food and feed industries, targeting the measurements of TDF and ensuring a rapid and high-throughput pipeline for plant breeding and cultivar development.