Fourier‐transform infrared spectroscopy (FTIR) as a high‐throughput phenotyping tool for quantifying protein quality in pulse crops

Abstract Fourier‐transform mid‐infrared (FT‐MIR) spectroscopy is a high‐throughput, cost‐effective method to quantify nutritional traits, such as total protein and sulfur‐containing amino acid (SAA) concentrations, in plant matter. This study used the spectroscopic technique FT‐MIR coupled with attenuated total internal reflectance sampling interface to develop multivariate models for total protein concentration in chickpea (Cicer arietinum L.), dry pea (Pisum sativum L.), and lentil (Lens culinaris Medik.), in addition to SAA concentration in lentil. Total nitrogen data from combustion analysis and SAA data from high‐performance liquid chromatography analysis following acid hydrolysis were used for model calibration and validation. Models for the total protein concentration of chickpea (calibration root mean square error [RMSE] = 0.093, R2 = 0.948, prediction RMSE = 0.10), dry pea (calibration RMSE = 0.096, R2 = 0.845, prediction RMSE = 0.093), and lentil (calibration RMSE = 0.13, R2 = 0.845, prediction RMSE = 0.11) utilized infrared regions associated with protein structures, namely amide bands A, I, and II. In sulfur‐related models for lentil total SAA (calibration RMSE = 0.014, R2 = 0.827, prediction RMSE = 0.022) and methionine (calibration RMSE = 0.0075, R2 = 0.815, prediction RMSE = 0.014) models utilized the C‐S and S‐CH3 stretching and bending bands. Study findings support the conclusion that FT‐MIR spectroscopy is a promising high‐throughput and cost‐effective phenotyping technique that will allow quantifying protein traits quickly and easily in pulse crops

Fourier‐transform infrared spectroscopy: An inexpensive, rapid, and less‐destructive tool for starch and resistant starch analysis from pulse flour

Abstract Pulse crops are a rich source of resistant starch (RS) (5–7 g/100 g), a prebiotic carbohydrate that promotes gut health. The standard method to measure total starch (TS) and RS is through enzymatic assay; however, this is both time consuming and expensive. Fourier‐transform mid‐infrared (FT‐MIR) spectroscopy is a high‐throughput, cost‐effective method to quantify nutritional traits in seeds, but models have not been developed for starch in pulse crops. Therefore, this study aimed to develop and validate an FT‐MIR chemometric technique to estimate TS and RS in dry pea (Pisum sativum L.), chickpea (Cicer arietinum L.), and lentil (Lens culinaris, Medikus) flours to accelerate global pulse breeding efforts, support industrial carbohydrate utilization, and develop healthier food‐feed calorie contents. Breeding lines were selected to capture the diversity of starch concentrations in each crop and were analyzed using an enzymatic assay. Models for each trait–crop combination were calibrated using partial least squares regression, resulting in R2 and root means square error of prediction ranging from 0.91 to 0.96 and 0.16 to 4.0 g/100 g, respectively. These results demonstrate that FT‐MIR spectroscopy is a promising tool for estimating TS and RS concentrations in pulse crops at a reduced analysis time and cost, expediting plant breeding and starch use efforts in the food processing industry

Fatty acid composition and genome-wide associations of a chickpea (Cicer arietinum L.) diversity panel for biofortification efforts

Abstract Chickpea is a nutritionally dense pulse crop with high levels of protein, carbohydrates, micronutrients and low levels of fats. Chickpea fatty acids are associated with a reduced risk of obesity, blood cholesterol, and cardiovascular diseases in humans. We measured four primary chickpea fatty acids; palmitic acid (PA), linoleic acid (LA), alpha-linolenic acid (ALA), and oleic acid (OA), which are crucial for human health and plant stress responses in a chickpea diversity panel with 256 accessions (Kabuli and desi types). A wide concentration range was found for PA (450.7–912.6 mg/100 g), LA (1605.7–3459.9 mg/100 g), ALA (416.4–864.5 mg/100 g), and OA (1035.5–1907.2 mg/100 g). The percent recommended daily allowances also varied for PA (3.3–6.8%), LA (21.4–46.1%), ALA (34.7–72%), and OA (4.3–7.9%). Weak correlations were found among fatty acids. Genome-wide association studies (GWAS) were conducted using genotyping-by-sequencing data. Five significant single nucleotide polymorphisms (SNPs) were identified for PA. Admixture population structure analysis revealed seven subpopulations based on ancestral diversity in this panel. This is the first reported study to characterize fatty acid profiles across a chickpea diversity panel and perform GWAS to detect associations between genetic markers and concentrations of selected fatty acids. These findings demonstrate biofortification of chickpea fatty acids is possible using conventional and genomic breeding techniques, to develop superior cultivars with better fatty acid profiles for improved human health and plant stress responses