Aphid-Induced Volatiles and Subsequent Attraction of Natural Enemies Varies among Sorghum Cultivars.

The production of herbivore-induced plant volatiles (HIPVs) is a type of indirect defense used by plants to attract natural enemies and reduce herbivory by insect pests. In many crops little is known about genotypic variation in HIPV production or how this may affect natural enemy attraction. In this study, we identified and quantified HIPVs produced by 10 sorghum (Sorghum bicolor) cultivars infested with a prominent aphid pest, the sorghum aphid (Melanaphis sorghi Theobald). Volatiles were collected using dynamic headspace sampling techniques and identified and quantified using GC-MS. The total amounts of volatiles induced by the aphids did not differ among the 10 cultivars, but overall blends of volatiles differed significantly in composition. Most notably, aphid herbivory induced higher levels of methyl salicylate (MeSA) emission in two cultivars, whereas in four cultivars, the volatile emissions did not change in response to aphid infestation. Dual-choice olfactometer assays were used to determine preference of the aphid parasitoid, Aphelinus nigritus, and predator, Chrysoperla rufilabris, between plants of the same cultivar that were un-infested or infested with aphids. Two aphid-infested cultivars were preferred by natural enemies, while four other cultivars were more attractive to natural enemies when they were free of aphids. The remaining four cultivars elicited no response from parasitoids. Our work suggests that genetic variation in HIPV emissions greatly affects parasitoid and predator attraction to aphid-infested sorghum and that screening crop cultivars for specific predator and parasitoid attractants has the potential to improve the efficacy of biological control.

Non-Destructive Direct Pericarp Thickness Measurement of Sorghum Kernels Using Extended-Focus Optical Coherence Microscopy.

Non-destructive measurements of internal morphological structures in plant materials such as seeds are of high interest in agricultural research. The estimation of pericarp thickness is important to understand the grain quality and storage stability of seeds and can play a crucial role in improving crop yield. In this study, we demonstrate the applicability of fiber-based Bessel beam Fourier domain (FD) optical coherence microscopy (OCM) with a nearly constant high lateral resolution maintained at over ~400 µm for direct non-invasive measurement of the pericarp thickness of two different sorghum genotypes. Whereas measurements based on axial profiles need additional knowledge of the pericarp refractive index, en-face views allow for direct distance measurements. We directly determine pericarp thickness from lateral sections with a 3 µm resolution by taking the width of the signal corresponding to the pericarp at the 1/e threshold. These measurements enable differentiation of the two genotypes with 100% accuracy. We find that trading image resolution for acquisition speed and view size reduces the classification accuracy. Average pericarp thicknesses of 74 µm (thick phenotype) and 43 µm (thin phenotype) are obtained from high-resolution lateral sections, and are in good agreement with previously reported measurements of the same genotypes. Extracting the morphological features of plant seeds using Bessel beam FD-OCM is expected to provide valuable information to the food processing industry and plant breeding programs.

Genetic control of source-sink relationships in grain sorghum.

MAIN CONCLUSION: QTL hotspots identified for selected source-sink-related traits provide the opportunity for pyramiding favorable alleles for improving sorghum productivity under diverse environments. A sorghum bi-parental mapping population was evaluated under six different environments at Hays and Manhattan, Kansas, USA, in 2016 and 2017, to identify genomic regions controlling source-sink relationships. The population consisted of 210 recombinant inbred lines developed from US elite post-flowering drought susceptible (RTx430) and a known post-flowering drought tolerant cultivar (SC35). Selected physiological traits related to source (effective quantum yield of photosystem II and chlorophyll index), sink (grain yield per panicle) and panicle neck diameter were recorded during grain filling. The results showed strong phenotypic and genotypic association between panicle neck diameter and grain yield per panicle during mid-grain filling and at maturity. Multiple QTL model revealed 5-12 including 2-5 major QTL for each trait. Among them 3, 7 and 8 QTL for quantum yield, panicle neck diameter and chlorophyll index, respectively, have not been identified previously in sorghum. Phenotypic variation explained by QTL identified across target traits ranged between 5.5 and 25.4%. Panicle neck diameter and grain yield per panicle were positively associated, indicating the possibility of targeting common co-localized QTL to improve both traits simultaneously through marker-assisted selection. Three major QTL hotspots, controlling multiple traits were identified on chromosome 1 (52.23-61.18 Mb), 2 (2.52-11.43 Mb) and 3 (1.32-3.95 Mb). The identified genomic regions and underlying candidate genes can be utilized in pyramiding favorable alleles for improving source-sink relationships in sorghum under diverse environments.

Low-field magnetic resonance imaging of roots in intact clayey and silty soils.

The development of a robust method to non-invasively visualize root morphology in natural soils has been hampered by the opaque, physical, and structural properties of soils. In this work we describe a novel technology, low field magnetic resonance imaging (LF-MRI), for imaging energy sorghum (Sorghum bicolor (L.) Moench) root morphology and architecture in intact soils. The use of magnetic fields much weaker than those used with traditional MRI experiments reduces the distortion due to magnetic material naturally present in agricultural soils. A laboratory based LF-MRI operating at 47 mT magnetic field strength was evaluated using two sets of soil cores: 1) soil/root cores of Weswood silt loam (Udifluventic Haplustept) and a Belk clay (Entic Hapluderts) from a conventionally tilled field, and 2) soil/root cores from rhizotrons filled with either a Houston Black (Udic Haplusterts) clay or a sandy loam purchased from a turf company. The maximum soil water nuclear magnetic resonance (NMR) relaxation time T2 (4 ms) and the typical root water relaxation time T2 (100 ms) are far enough apart to provide a unique contrast mechanism such that the soil water signal has decayed to the point of no longer being detectable during the data collection time period. 2-D MRI projection images were produced of roots with a diameter range of 1.5-2.0 mm using an image acquisition time of 15 min with a pixel resolution of 1.74 mm in four soil types. Additionally, we demonstrate the use of a data-driven machine learning reconstruction approach, Automated Transform by Manifold Approximation (AUTOMAP) to reconstruct raw data and improve the quality of the final images. The application of AUTOMAP showed a SNR (Signal to Noise Ratio) improvement of two fold on average. The use of low field MRI presented here demonstrates the possibility of applying low field MRI through intact soils to root phenotyping and agronomy to aid in understanding of root morphology and the spatial arrangement of roots in situ.

Multifunctional Ground Control Points with a Wireless Network for Communication with a UAV.

Ground control points (GCPs) are commonly used for georeferencing in remote sensing. Precise position measurement of the GCPs typically requires careful ground surveying, which is time-consuming and labor-intensive and thus excessively costly if it needs to be repeated multiple times in a season. A system of multifunctional GCPs and a wireless network for communication with an unmanned aerial vehicle (UAV) was developed to improve the speed of GCP setup and provide GCP data collection in real-time during the flight. While testing the system, a single-board computer on a fixed-wing UAV used in the study successfully recorded position data from all the GCPs during the flight. The multifunctional GCPs were also tested for use as references for calibration of reflectance and height for field objects like crops. The test of radiometric calibration resulted in an average reflectance error of 2.0% and a strong relationship (R2 = 0.99) between UAV-based estimates and ground reflectance. Furthermore, the average height difference between UAV-based height estimates and ground measurements was within 10 cm.

Measurement and Calibration of Plant-Height from Fixed-Wing UAV Images.

Continuing population growth will result in increasing global demand for food and fiber for the foreseeable future. During the growing season, variability in the height of crops provides important information on plant health, growth, and response to environmental effects. This paper indicates the feasibility of using structure from motion (SfM) on images collected from 120 m above ground level (AGL) with a fixed-wing unmanned aerial vehicle (UAV) to estimate sorghum plant height with reasonable accuracy on a relatively large farm field. Correlations between UAV-based estimates and ground truth were strong on all dates (R² > 0.80) but are clearly better on some dates than others. Furthermore, a new method for improving UAV-based plant height estimates with multi-level ground control points (GCPs) was found to lower the root mean square error (RMSE) by about 20%. These results indicate that GCP-based height calibration has a potential for future application where accuracy is particularly important. Lastly, the image blur appeared to have a significant impact on the accuracy of plant height estimation. A strong correlation (R² = 0.85) was observed between image quality and plant height RMSE and the influence of wind was a challenge in obtaining high-quality plant height data. A strong relationship (R² = 0.99) existed between wind speed and image blurriness.

Genomic characterization of a core set of the USDA-NPGS Ethiopian sorghum germplasm collection: implications for germplasm conservation, evaluation, and utilization in crop improvement.

BACKGROUND: The USDA Agriculture Research Service National Plant Germplasm System (NPGS) preserves the largest sorghum germplasm collection in the world, which includes 7,217 accessions from the center of diversity in Ethiopia. The characterization of this exotic germplasm at a genome-wide scale will improve conservation efforts and its utilization in research and breeding programs. Therefore, we phenotyped a representative core set of 374 Ethiopian accessions at two locations for agronomic traits and characterized the genomes. RESULTS: Using genotyping-by-sequencing, we identified 148,476 single-nucleotide polymorphism (SNP) markers distributed across the entire genome. Over half of the alleles were rare (frequency < 0.05). The genetic profile of each accession was unique (i.e., no duplicates), and the average genetic distance among accessions was 0.70. Based on population structure and cluster analyses, we separated the collection into 11 populations with pairwise F ST values ranging from 0.11 to 0.47. In total, 198 accessions (53%) were assigned to one of these populations with an ancestry membership coefficient of larger than 0.60; these covered 90% of the total genomic variation. We characterized these populations based on agronomic and seed compositional traits. We performed a cluster analysis with the sorghum association panel based on 26,026 SNPs and determined that nine of the Ethiopian populations expanded the genetic diversity in the panel. Genome-wide association analysis demonstrated that these low-coverage data and the observed population structure could be employed for the genomic dissection of important phenotypes in this core set of Ethiopian sorghum germplasm. CONCLUSIONS: The NPGS Ethiopian sorghum germplasm is a genetically and phenotypically diverse collection comprising 11 populations with high levels of admixture. Genetic associations with agronomic traits can be used to improve the screening of exotic germplasm for selection of specific populations. We detected many rare alleles, suggesting that this germplasm contains potentially useful undiscovered alleles, but their discovery and characterization will require extensive effort. The genotypic data available for these accessions provide a valuable resource for sorghum breeders and geneticists to effectively improve crops.

Genetic architecture of kernel composition in global sorghum germplasm.

BACKGROUND: Sorghum [Sorghum bicolor (L.) Moench] is an important cereal crop for dryland areas in the United States and for small-holder farmers in Africa. Natural variation of sorghum grain composition (protein, fat, and starch) between accessions can be used for crop improvement, but the genetic controls are still unresolved. The goals of this study were to quantify natural variation of sorghum grain composition and to identify single-nucleotide polymorphisms (SNPs) associated with variation in grain composition concentrations. RESULTS: In this study, we quantified protein, fat, and starch in a global sorghum diversity panel using near-infrared spectroscopy (NIRS). Protein content ranged from 8.1 to 18.8%, fat content ranged from 1.0 to 4.3%, and starch content ranged from 61.7 to 71.1%. Durra and bicolor-durra sorghum from Ethiopia and India had the highest protein and fat and the lowest starch content, while kafir sorghum from USA, India, and South Africa had the lowest protein and the highest starch content. Genome-wide association studies (GWAS) identified quantitative trait loci (QTL) for sorghum protein, fat, and starch. Previously published RNAseq data was used to identify candidate genes within a GWAS QTL region. A putative alpha-amylase 3 gene, which has previously been shown to be associated with grain composition traits, was identified as a strong candidate for protein and fat variation. CONCLUSIONS: We identified promising sources of genetic material for manipulation of grain composition traits, and several loci and candidate genes that may control sorghum grain composition. This survey of grain composition in sorghum germplasm and identification of protein, fat, and starch QTL contributes to our understanding of the genetic basis of natural variation in sorghum grain nutritional traits.

Genetic dissection of sorghum grain quality traits using diverse and segregating populations.

KEY MESSAGE: Coordinated association and linkage mapping identified 25 grain quality QTLs in multiple environments, and fine mapping of the Wx locus supports the use of high-density genetic markers in linkage mapping. There is a wide range of end-use products made from cereal grains, and these products often demand different grain characteristics. Fortunately, cereal crop species including sorghum [Sorghum bicolor (L.) Moench] contain high phenotypic variation for traits influencing grain quality. Identifying genetic variants underlying this phenotypic variation allows plant breeders to develop genotypes with grain attributes optimized for their intended usage. Multiple sorghum mapping populations were rigorously phenotyped across two environments (SC Coastal Plain and Central TX) in 2 years for five major grain quality traits: amylose, starch, crude protein, crude fat, and gross energy. Coordinated association and linkage mapping revealed several robust QTLs that make prime targets to improve grain quality for food, feed, and fuel products. Although the amylose QTL interval spanned many megabases, the marker with greatest significance was located just 12 kb from waxy (Wx), the primary gene regulating amylose production in cereal grains. This suggests higher resolution mapping in recombinant inbred line (RIL) populations can be obtained when genotyped at a high marker density. The major QTL for crude fat content, identified in both a RIL population and grain sorghum diversity panel, encompassed the DGAT1 locus, a critical gene involved in maize lipid biosynthesis. Another QTL on chromosome 1 was consistently mapped in both RIL populations for multiple grain quality traits including starch, crude protein, and gross energy. Collectively, these genetic regions offer excellent opportunities to manipulate grain composition and set up future studies for gene validation.

Sugarcane Aphid (Hemiptera: Aphididae): Host Range and Sorghum Resistance Including Cross-Resistance From Greenbug Sources.

The graminous host range and sources of sorghum [Sorghum bicolor (L.) Moench.] plant resistance, including cross-resistance from greenbug, Schizaphis graminum (Rondani), were studied for the newly emerging sugarcane aphid, Melanaphis sacchari (Zehntner), in greenhouse no-choice experiments and field evaluations. The sugarcane aphid could not survive on field corn, Zea mays (L.), Teff grass, Eragrostis tef (Zucc.), proso millet, Panicum miliaceum L., barley, Hordeum vulgare L., and rye, Secale cereale L. Only sorghum genotypes served as hosts including Johnsongrass, Sorghum halepense (L.), a highly suitable noncrop host that generates high numbers of sugarcane aphid and maintains moderate phenotypic injury. The greenbug-resistant parental line RTx2783 that is resistant to greenbug biotypes C and E was resistant to sugarcane aphid in both greenhouse and field tests, while PI 55607 greenbug resistant to biotypes B, C, and E was highly susceptible. PI 55610 that is greenbug resistant to biotypes B, C, and E maintained moderate resistance to the sugarcane aphid, while greenbug-resistant PI 264453 was highly susceptible to sugarcane aphid. Two lines and two hybrids from the Texas A&M breeding program B11070, B11070, AB11055-WF1-CS1/RTx436, and AB11055-WF1-CS1/RTx437 were highly resistant to sugarcane aphid, as were parental types SC110, SC170, and South African lines Ent62/SADC, (Macia/TAM428)-LL9, (SV1*Sima/IS23250)-LG15. Tam428, a parental line that previously showed moderate resistance in South Africa and India, also showed moderate resistance in these evaluations. Overall, 9 of 20 parental sorghum entries tested for phenotypic damage in the field resulted in good resistance to the sugarcane aphid and should be utilized in breeding programs that develop agronomically acceptable sorghums for the southern regions of the United States.

Coincident light and clock regulation of pseudoresponse regulator protein 37 (PRR37) controls photoperiodic flowering in sorghum.

Optimal flowering time is critical to the success of modern agriculture. Sorghum is a short-day tropical species that exhibits substantial photoperiod sensitivity and delayed flowering in long days. Genotypes with reduced photoperiod sensitivity enabled sorghum's utilization as a grain crop in temperate zones worldwide. In the present study, Ma(1), the major repressor of sorghum flowering in long days, was identified as the pseudoresponse regulator protein 37 (PRR37) through positional cloning and analysis of SbPRR37 alleles that modulate flowering time in grain and energy sorghum. Several allelic variants of SbPRR37 were identified in early flowering grain sorghum germplasm that contain unique loss-of-function mutations. We show that in long days SbPRR37 activates expression of the floral inhibitor CONSTANS and represses expression of the floral activators Early Heading Date 1, FLOWERING LOCUS T, Zea mays CENTRORADIALIS 8, and floral induction. Expression of SbPRR37 is light dependent and regulated by the circadian clock, with peaks of RNA abundance in the morning and evening in long days. In short days, the evening-phase expression of SbPRR37 does not occur due to darkness, allowing sorghum to flower in this photoperiod. This study provides insight into an external coincidence mechanism of photoperiodic regulation of flowering time mediated by PRR37 in the short-day grass sorghum and identifies important alleles of SbPRR37 that are critical for the utilization of this tropical grass in temperate zone grain and bioenergy production.

Evaluating and Predicting the Performance of Sorghum Lines in an Elite by Exotic Backcross-Nested Association Mapping Population.

Maintaining or introducing genetic diversity into plant breeding programs is necessary for continual genetic gain; however, diversity at the cost of reduced performance is not something sought by breeders. To this end, backcross-nested association mapping (BC-NAM) populations, in which the recurrent parent is an elite line, can be employed as a strategy to introgress diversity from unadapted accessions while maintaining agronomic performance. This study evaluates (i) the hybrid performance of sorghum lines from 18 BC1-NAM families and (ii) the potential of genomic prediction to screen lines from BC1-NAM families for hybrid performance prior to phenotypic evaluation. Despite the diverse geographical origins and agronomic performance of the unadapted parents for BC1-NAM families, many BC1-derived lines performed significantly better in the hybrid trials than the elite recurrent parent, R.Tx436. The genomic prediction accuracies for grain yield, plant height, and days to mid-anthesis were acceptable, but the prediction accuracies for plant height were lower than expected. While the prediction accuracies increased when including more individuals in the training set, improvements tended to plateau between two and five lines per family, with larger training sets being required for more complex traits such as grain yield. Therefore, genomic prediction models can be optimized in a large BC1-NAM population with a relatively low fraction of individuals needing to be evaluated. These results suggest that genomic prediction is an effective method of pre-screening lines within BC1-NAM families prior to evaluation in extensive hybrid field trials.

Near-infrared reflectance spectroscopy phenomic prediction can perform similarly to genomic prediction of maize agronomic traits across environments.

For nearly two decades, genomic prediction and selection have supported efforts to increase genetic gains in plant and animal improvement programs. However, novel phenomic strategies for predicting complex traits in maize have recently proven beneficial when integrated into across-environment sparse genomic prediction models. One phenomic data modality is whole grain near-infrared spectroscopy (NIRS), which records reflectance values of biological samples (e.g., maize kernels) based on chemical composition. Predictions of hybrid maize grain yield (GY) and 500-kernel weight (KW) across 2 years (2011-2012) and two management conditions (water-stressed and well-watered) were conducted using combinations of reflectance data obtained from high-throughput, F2 whole-kernel scans and genomic data obtained from genotyping-by-sequencing within four different cross-validation (CV) schemes (CV2, CV1, CV0, and CV00). When predicting the performance of untested genotypes in characterized (CV1) environments, genomic data were better than phenomic data for GY (0.689 ± 0.024-genomic vs. 0.612 ± 0.045-phenomic), but phenomic data were better than genomic data for KW (0.535 ± 0.034-genomic vs. 0.617 ± 0.145-phenomic). Multi-kernel models (combinations of phenomic and genomic relationship matrices) did not surpass single-kernel models for GY prediction in CV1 or CV00 (prediction of untested genotypes in uncharacterized environments); however, these models did outperform the single-kernel models for prediction of KW in these same CVs. Lasso regression applied to the NIRS data set selected a subset of 216 NIRS bands that achieved comparable prediction abilities to the full phenomic data set of 3112 bands predicting GY and KW under CV1 and CV00.

Evaluating Introgression Sorghum Germplasm Selected at the Population Level While Exploring Genomic Resources as a Screening Method.

To exploit the novel genetic diversity residing in tropical sorghum germplasm, an expansive backcross nested-association mapping (BC-NAM) resource was developed in which novel genetic diversity was introgressed into elite inbreds. A major limitation of exploiting this type of genetic resource in hybrid improvement programs is the required evaluation in hybrid combination of the vast number of BC-NAM populations and lines. To address this, the utility of genomic information was evaluated to predict the hybrid performance of BC-NAM populations. Two agronomically elite BC-NAM populations were chosen for evaluation in which elite inbred RTx436 was the recurrent parent. Each BC1F3 line was evaluated in hybrid combination with an elite tester in two locations with phenotypes of grain yield, plant height, and days to anthesis collected on all test cross hybrids. Lines from both populations were found to outperform their recurrent parent. Efforts to utilize genetic distance based on genotyping-by-sequence (GBS) as a predictive tool for hybrid performance was ineffective. However, utilizing genomic prediction models using additive and dominance GBLUP kernels to screen germplasm appeared to be an effective method to eliminate inferior-performing lines that will not be useful in a hybrid breeding program.

Use of genomic prediction to screen sorghum B-lines in hybrid testcrosses.

Use of trifluoromethanesulfonamide (TFMSA), a male gametocide, increases the opportunities to identify promising B-lines because large quantities of F1 seed can be generated prior to the laborious task of B-line sterilization. Combining TFMSA technology with genomic selection could efficiently evaluate sorghum B-lines in hybrid combination to maximize the rates of genetic gain of the crop. This study used two recombinant inbred B-line populations, consisting of 217 lines, which were testcrossed to two R-lines to produce 434 hybrids. Each population of testcross hybrids were evaluated across five environments. Population-based genomic prediction models were assessed across environments using three different cross-validation (CV) schemes, each with 70% training and 30% validation sets. The validation schemes were as follows: CV1-hybrids chosen randomly for validation; CV2-B-lines were randomly chosen, and each chosen B-line had one of the two corresponding testcross hybrids randomly chosen for the validation; and CV3-B-lines were randomly chosen, and each chosen B-line had both corresponding testcross hybrids chosen for the validation. CV1 and CV2 presented the highest prediction accuracies; nonetheless, the prediction accuracies of the CV schemes were not statistically different in many environments. We determined that combining the B-line populations could improve prediction accuracies, and the genomic prediction models were able to effectively rank the poorest 70% of hybrids even when genomic prediction accuracies themselves were low. Results indicate that combining genomic prediction models and TFMSA technology can effectively aid breeders in predicting B-line hybrid performance in early generations prior to the laborious task of generating A/B-line pairs.

Genomic prediction can be used to screen sorghum B-lines for hybrid grain yield and days to mid-anthesis. Using genomic prediction and the chemical gametocide TFMSA can increase the rate of genetic gain in sorghum B-lines. Using testers to screen sorghum B-line populations is an effective method for screening with genomic prediction. Genomic prediction can effectively predict hybrid performance within and across populations of sorghum B-lines. The ability to accurately rank hybrid performance remained relatively consistent regardless of prediction accuracy.

Genetic Diversity and Classification of Colletotrichum sublineola Pathotypes Using a Standard Set of Sorghum Differentials.

Anthracnose, incited by Colletotrichum sublineola, is the most destructive foliar disease of sorghum and, under severe conditions, yield losses can exceed 80% on susceptible cultivars. The hyper-variable nature of the pathogen makes its management challenging despite the occurrence of several resistant sources. In this study, the genetic variability and pathogenicity of 140 isolates of C. sublineola, which were sequenced using restriction site-associated sequencing (RAD-Seq), resulted in 1244 quality SNPs. The genetic relationship based on the SNP data showed low to high genetic diversity based on isolates' origin. Isolates from Georgia and North Carolina were grouped into multiple clusters with some level of genetic relationships to each other. Even though some isolates from Texas formed a cluster, others clustered with isolates from Puerto Rico. The isolates from Puerto Rico showed scattered distribution, indicating the diverse nature of these isolates. A population structure and cluster analysis revealed that the genetic variation was stratified into eight populations and one admixture group. The virulence pattern of 30 sequenced isolates on 18 sorghum differential lines revealed 27 new pathotypes. SC748-5, SC112-14, and Brandes were resistant to all the tested isolates, while BTx623 was susceptible to all. Line TAM428 was susceptible to all the pathotypes, except for pathotype 26. Future use of the 18 differentials employed in this study, which contains cultivars/lines which have been used in the Americas, Asia, and Africa, could allow for better characterization of C. sublineola pathotypes at a global level, thus accelerating the development of sorghum lines with stable resistance to the anthracnose pathogen.

Biophysical, Nutraceutical, and Technofunctional Features of Specialty Cereals: Pigmented Popcorn and Sorghum.

Different pigmented corn and sorghum types were evaluated to characterize their biophysical, nutraceutical, and technofunctional properties for the first time. Commercially pigmented (blue, purple, red, black, and yellow) popcorn (Zea mays var. everta) and sorghum (Sorghum bicolor L.) of yellow and red colors were analyzed. Biophysical and proximal analyses were performed using official methods. The nutraceutical profile included the total phenolic and anthocyanin content. In addition, rheological, structural, and morphological studies were conducted. The results demonstrated significant differences between the popcorn samples and grain types, especially in terms of their biophysical and proximate features. The nutraceutical profile revealed that these specialty grains contained higher concentrations of antioxidant compounds (up to 3-fold when compared with the other grains). The rheological analysis demonstrated that sorghum grains developed higher peak viscosities than popcorn. According to the structural assessments, the type A pattern displayed peaks at the interplanar spaces corresponding to the crystalline and amorphous regions in all the samples. The data obtained in this study provides a base to further investigate the products obtained using these biomaterials.

Application of X-ray computed tomography to analyze the structure of sorghum grain.

BACKGROUND: The structural characteristics of whole sorghum kernels are known to affect end-use quality, but traditional evaluation of this structure is two-dimensional (i.e., cross section of a kernel). Current technology offers the potential to consider three-dimensional structural characteristics of grain. X-ray computed tomography (CT) presents one such opportunity to nondestructively extract quantitative data from grain caryopses which can then be related to end-use quality. RESULTS: Phenotypic measurements were extracted from CT scans of grain sorghum caryopses. Extensive phenotypic variation was found for embryo volume, endosperm hardness, endosperm texture, endosperm volume, pericarp volume, and kernel volume. CT derived estimates were strongly correlated with ground truth measurements enabling the identification of genotypes with superior structural characteristics. CONCLUSIONS: Presented herein is a phenotyping pipeline developed to quantify three-dimensional structural characteristics from grain sorghum caryopses which increases the throughput efficiency of previously difficult to measure traits. Adaptation of this workflow to other small-seeded crops is possible providing new and unique opportunities for scientists to study grain in a nondestructive manner which will ultimately lead to improvements end-use quality.

Genetic variation in hydrogen cyanide potential of perennial sorghum evaluated by colorimetry.

Both annual and perennial sorghum biomass serve as important forage for ruminant animals around the world. Unfortunately, sorghum can produce hydrogen cyanide (HCN), which, if occurring in high enough concentrations, can be toxic or lethal to animals that consume it. The objectives of this study were to develop a fast and inexpensive colorimetric assay to measure the hydrogen cyanide potential (HCN-P) as well as to compare this with existing visual assays while assessing the range of variation for HCN-P among perennial and annual sorghum biomass. The HCN-P of 100 sorghum lines derived from an interspecific hybridization program was determined over 2 years (establishment and regrowth) using both visual and colorimetric assays. Visual assessment underestimated the HCN-P and was less accurate than colorimetry. Repeatability for HCN-P across all sampling dates was functionally zero in the visual assessment and low for the colorimetric assay. This was mostly explained by the significant pedigree × year interaction effects and growth stage. Growth stage substantially influenced HCN-P, which should be considered when feeding animals on fresh forage.

Transcriptional regulation of the raffinose family oligosaccharides pathway in Sorghum bicolor reveals potential roles in leaf sucrose transport and stem sucrose accumulation.

Bioenergy sorghum hybrids are being developed with enhanced drought tolerance and high levels of stem sugars. Raffinose family oligosaccharides (RFOs) contribute to plant environmental stress tolerance, sugar storage, transport, and signaling. To better understand the role of RFOs in sorghum, genes involved in myo-inositol and RFO metabolism were identified and relative transcript abundance analyzed during development. Genes involved in RFO biosynthesis (SbMIPS1, SbInsPase, SbGolS1, SbRS) were more highly expressed in leaves compared to stems and roots, with peak expression early in the morning in leaves. SbGolS, SbRS, SbAGA1 and SbAGA2 were also expressed at high levels in the leaf collar and leaf sheath. In leaf blades, genes involved in myo-inositol biosynthesis (SbMIPS1, SbInsPase) were expressed in bundle sheath cells, whereas genes involved in galactinol and raffinose synthesis (SbGolS1, SbRS) were expressed in mesophyll cells. Furthermore, SbAGA1 and SbAGA2, genes that encode neutral-alkaline alpha-galactosidases that hydrolyze raffinose, were differentially expressed in minor vein bundle sheath cells and major vein and mid-rib vascular and xylem parenchyma. This suggests that raffinose synthesized from sucrose and galactinol in mesophyll cells diffuses into vascular bundles where hydrolysis releases sucrose for long distance phloem transport. Increased expression (>20-fold) of SbAGA1 and SbAGA2 in stem storage pith parenchyma of sweet sorghum between floral initiation and grain maturity, and higher expression in sweet sorghum compared to grain sorghum, indicates these genes may play a key role in non-structural carbohydrate accumulation in stems.