Moisture effects on robustness of sorghum grain protein near‐infrared spectroscopy calibration

Impact of germination pre-treatments on buckwheat and Quinoa: Mitigation of anti-nutrient content and enhancement of antioxidant properties

This study evaluated the effects of pre-germination treatments on the nutritional and anti-nutritional values of buckwheat and quinoa during germination. Pre-germination method was effective on the chemical composition and phenolic profile of buckwheat and quinoa samples (p < 0.05). During the germination, color changes were notable, particularly in the alkali-treated samples. The decrease in tannin content reached the highest rate in germinated buckwheat (83 %) and quinoa (20 %) by alkali treatment. The highest antioxidant and total phenolic content were measured in germinated pseudocereals treated by ultrasound. However, the lowest phytic acid content was determined after germination in the quinoa sample treated by ultrasound. Rutin was the major flavonoid in buckwheat while quercetin, galangin, ellagic, syringic, and p-coumaric acids were only synthesized after 72 h of germination. Catechin and epicatechin were decreased only in the alkali-treated buckwheat sample. Controlled germination processes can enhance the antioxidant activity and development of functional foods from whole grains.

Performance of a Handheld MicroNIR Instrument for Determining Protein Levels in Sorghum Grain Samples

Near infrared (NIR) spectroscopy is widely used for evaluating quality traits of cereal grains. For evaluating protein content of intact sorghum grains, parallel NIR calibrations were developed using an established benchtop instrumentation (Perten DA-7250) as a baseline to test the efficacy of an adaptive handheld instrument (VIAVI MicroNIR OnSite-W). Spectra were collected from 59 grain samples using both instruments at the same time. Cross-validated calibration models were validated with 33 test samples. The selected calibration model for DA-7250 with a coefficient of determination (R2) = 0.98 and a root mean square error of cross validation (RMSECV) = 0.41% predicted the protein content of a test set with R2 = 0.94, root mean square error of prediction (RMSEP) = 0.52% with a ratio of performance to deviation (RPD) of 4.13. The selected model for the MicroNIR with R2 = 0.95 and RMSECV = 0.62% predicted the protein content of the test set with R2 = 0.87, RMSEP = 0.76% with an RPD of 2.74. In comparison, the performance of the DA-7250 was better than the MicroNIR, however, the performance of the MicroNIR was also acceptable for screening intact sorghum grain protein levels. Therefore, the MicroNIR instrument may be used as a potential tool for screening sorghum samples where benchtop instruments are not appropriate such as for screening samples in the field or as a less expensive option compared with benchtop instruments.

Variations in Total Protein and Amino Acids in the Sequenced Sorghum Mutant Library

Sorghum (Sorghum bicolor) is the fifth most important cereal crop worldwide; however, its utilization in food products can be limited due to reduced nutritional quality related to amino acid composition and protein digestibility in cooked products. Low essential amino acid levels and digestibility are influenced by the composition of the sorghum seed storage proteins, kafirins. In this study, we report a core collection of 206 sorghum mutant lines with altered seed storage proteins. Wet lab chemistry analysis was conducted to evaluate the total protein content and 23 amino acids, including 19 protein-bound and 4 non-protein amino acids. We identified mutant lines with diverse compositions of essential and non-essential amino acids. The highest total protein content in these lines was almost double that of the wild-type (BTx623). The mutants identified in this study can be used as a genetic resource to improve the sorghum grain quality and determine the molecular mechanisms underlying the biosynthesis of storage protein and starch in sorghum seeds.

Compositional analysis in sorghum (Sorghum bicolor) NIR spectral techniques based on mean spectra from single seeds

Sorghum (Sorghum bicolor) is an economically important cereal crop that can be used as human food, animal feed, and for industrial use such as bioenergy. In sorghum breeding programs, development of cultivars with desirable seed quality characteristics is important and development of rapid low-cost screening methods for seed nutritional traits are desired, since most standard methods are destructive, slow, and less environmentally friendly. This study investigates the feasibility of single kernel NIR spectroscopy (SKNIRS) for rapid determination of individual sorghum seed components. We developed successful multivariate prediction models based on partial least squares (PLS) regression for protein, oil, and weight in sorghum. The results showed that for sorghum protein content ranging from 8.92% to 18.7%, the model coefficients of determination obtained were R C A L 2 = 0.95 (RMSEC= 0.44) and R P R E D 2 = 0.87 (RMSEP= 0.69). The model coefficients of determination for oil prediction were R C A L 2 = 0.92 (RMSEC= 0.23) and R P R E D 2 = 0.71 (RMSEP= 0.41) for oil content ranging from 1.96% to 5.61%. For weight model coefficients of determination were R C A L 2 = 0.81 (RMSEC= 0.007) and R P R E D 2 = 0.63 (RMSEP= 0.007) for seeds ranging from 4.40 mg to 77.0 mg. In conclusion, mean spectra SKNIRS can be used to rapidly determine protein, oil, and weight in intact single seeds of sorghum seeds and can provide a nondestructive and quick method for screening sorghum samples for these traits for sorghum breeding and industry use.

Stable sorghum grain quality QTL were identified using SC35 × RTx430 mapping population

Understanding the genetic control and inheritance of grain quality traits is instrumental in facilitating end-use quality improvement. This study was conducted to identify and map quantitative trait loci (QTL) controlling protein, starch, and amylose content in grain sorghum [Sorghum bicolor (L.) Moench] grown under variable environmental conditions. A recombinant inbred line (RIL) population derived from a cross between RTx430 and SC35 was evaluated in six environments across Hays and Manhattan, KS. Significant variation was observed in genotype, environment, and genotype × environment interaction for all three quality traits. Unlike the RILs, the two parental lines did not show significant differences for these traits. However, significant transgressive segregation was observed for all traits resulting in phenotypic performance extending beyond the two parents. A total of seven protein, 10 starch, and 10 amylose content QTL were identified. Chromosomal regions and phenotypic variation (PVE) of QTL were variable across growing conditions. Quantitative trait loci hotspots for all three traits were detected on chromosomes 1 (115.2-119.2 cM) and 2 (118.2-127.4 cM). Candidate gene analysis indicated that these QTL hotspots were conditioned by several transcription factors, such as Cytochrome P450 and basic helix-loop-helix DNA binding protein, which regulate starch and protein accumulation in the grain. The identified genomic regions and underlying candidate genes provide a starting point for further validation and marker-assisted gene pyramiding to improve sorghum grain quality.

Potential food applications of sorghum (Sorghum bicolor) and rapid screening methods of nutritional traits by spectroscopic platforms

Sorghum is a drought-resistant crop widely spread in tropical regions of the American, African, and Asian continents. Sorghum flour is considered the main alternative for wheat flour, and it exhibits gluten-free nature. Generally, conventional wet chemical methods are used to analyze the nutritional profile of sorghum. Since many sorghum plants are available in breeding grounds, the application of conventional methods has limitations due to high cost and time consumption. Therefore, rapid screening protocols have been introduced as nondestructive alternatives. The current review highlights novel and portable devices that can be used to analyze the nutritional composition, color parameters, and pest resistance. Sorghum is often a traditional food item with minimal processing, and the review elaborates on emerging food applications and feasible food product developments from sorghum. The demand for gluten-free products has been rapidly increasing in developed countries. In order to develop food products according to market requirements, it is necessary to screen high-quality sorghum plants. Rapid analysis techniques effectively select the best sorghum types, and the novel tools have outperformed existing conventional methods.

Near Infrared Spectroscopic Evaluation of Starch Properties of Diverse Sorghum Populations

Starch, mainly composed of amylose and amylopectin, is the major nutrient in grain sorghum. Amylose and amylopectin composition affects the starch properties of sorghum flour which in turn determine the suitability of sorghum grains for various end uses. Partial least squares regression models on near infrared (NIR) spectra were developed to estimate starch and amylose contents in intact grain sorghum samples. Sorghum starch calibration model with a coefficient of determination (R2) = 0.87, root mean square error of cross validation (RMSECV) = 1.57% and slope = 0.89 predicted the starch content of validation set with R2 = 0.76, root mean square error of prediction (RMSEP) = 2.13%, slope = 0.93 and bias = 0.20%. Amylose calibration model with R2 = 0.84, RMSECV = 2.96% and slope = 0.86 predicted the amylose content in validation samples with R2 = 0.76, RMSEP = 2.60%, slope = 0.98 and bias = −0.44%. Final starch and amylose cross validated calibration models were constructed combining respective calibration and validation sets and used to predict starch and amylose contents in 1337 grain samples from two diverse sorghum populations. Protein and moisture contents of the samples were determined using previously tested NIR spectroscopy models. The distribution of starch and protein contents in the samples of low amylose (<5%) and normal amylose (>15%) and the overall relationship between starch and protein contents of the sorghum populations were investigated. Percent starch and protein were negatively correlated, low amylose lines tended to have lower starch and higher protein contents than lines with high amylose. The results showed that NIR spectroscopy of whole grain can be used as a high throughput pre-screening method to identify sorghum germplasm with specific starch quality traits to develop hybrids for various end uses.