The increasing cost of energy and fi nite oil and gas reserves has created a need to develop alternative fuels from renewable sources. Currently, the development of a renewable transportation fuel is ethanol based. Ethanol production is now sugar/starch based, but use of these carbohydrates is limited; they are also required as a food and feed source. The need to generate a large and sustainable supply of biomass to make biofuels generation from lignocellulose profi table will require the development of crops grown specifi cally for bioenergy production. There will be several different species used as dedicated bioenergy crops, and for several reasons; it is expected that sorghum (Sorghum bicolor L. Moench) will be one of these species. Sorghum is a highly productive, drought-tolerant species with a history of improvement and production of lignocellulose, sugar and starch. Given this history and the existing genetic improvement infrastructure available for the species, it is logical to expect that sorghum hybrids for dedicated bioenergy production can be developed in the near-term future and will be grown and used for bioenergy production.

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.is a C4 grass native to Africa that provides an indispensable food source for over 300 million people inhabiting food-insecure regions worldwide (1). Although primarily grown for its grain and forage, highbiomass sorghum is also an excellent drought-tolerant energy crop for sustainable production of lignocellulosic-based biofuels (2). Forage and energy sorghums are selected for delayed flowering to increase biomass yield through longer duration of vegetative growth, whereas grain sorghums are selected for early flowering to ensure sufficient time for grain maturation and to avoid drought and frost. Optimal production of each of these sorghum crops requires the precise regulation of flowering time, which varies depending on planting location and climate. Differences in photoperiod sensitivity confer a wide range of flowering times on diverse accessions of the sorghum germplasm collection (3). Due to its critical importance to crop yield and hybrid seed production, photoperiodic regulation of flowering has been an important trait characterized by sorghum improvement programs dating back to the early 1900s (4).In Arabidopsis, flowering is induced in long days (LD) that expose plants to light in the evening during a phase of circadian clock oscillation required for induction of floral genes, consistent with the external coincidence model (5-7). Rhythmic expression of the core circadian clock components CIRCADIAN CLOCK ASSOCIATED 1 (CCA1)/LATE ELONGATED HYPOCOTYL (LHY) and TIMING OF CAB 1...

Association mapping is a powerful strategy for identifying genes underlying quantitative traits in plants. We have assembled and characterized genetic and phenotypic diversity of a sorghum [Sorghum bicolor (L.) Moench] panel suitable for association mapping, comprised of 377 accessions representing all major cultivated races (tropical lines from diverse geographic and climatic regions), and important U.S. breeding lines and their progenitors. Accessions were phenotyped for eight traits, and levels of population structure and familial relatedness were assessed with 47 simple sequence repeat (SSR) loci. The panel exhibited substantial morphological variation and little genotypic differentiation was observed between the converted tropical and breeding lines. The phenotypic and genotypic data were used to evaluate the performance of several association models in controlling for spurious associations. Our analysis indicated that association models that accounted for both population structure and kinship performed better than those that did not. In addition, we found that the optimal number of subpopulations used to correct for population structure was trait dependent. Although augmentation of the genotypic data with additional SSR loci may be necessary, the association models, genotypic data, and germplasm panel described here provide a starting point for sorghum researchers to begin association studies of traits and markers or candidate genes of interest.

Genetic improvement of sorghum [Sorghum bicolor (L.) Moench] has traditionally focused on a single nonstructural carbohydrate, either grain starch or stem sugar. Sorghum starch and sugar may both be used as feedstocks for biofuel production. To investigate genetic tradeoffs between grain and stem sugar, a population derived from sweet sorghum cultivar Rio and grain sorghum ‘BTx623’ was evaluated for 27 traits related to grain and stem sugar yield and composition. Across three environments, a total of 129 quantitative trait loci (QTL) were identified. Tradeoffs identified between grain and stem sugar yield QTL colocalized with height and flowering time QTL. Most importantly, QTL were identified that increased yield and altered the composition of stem sugar and grain without pleiotropic effects. For example, a QTL on chromosome 3 that explained 25% of the genetic variance for stem sugar concentration did not colocalize with any grain QTL. These results suggest that total nonstructural carbohydrate yield could be increased by selecting for major QTL from both grain and sweet sorghum types. We conclude that altering grain and stem sugar genetic potential for yield traits should lead to greater feedstock improvement than altering composition traits.

Advances in automation and data science have led agriculturists to seek real-time, high-quality, high-volume crop data to accelerate crop improvement through breeding and to optimize agronomic practices. Breeders have recently gained massive data-collection capability in genome sequencing of plants. Faster phenotypic trait data collection and analysis relative to genetic data leads to faster and better selections in crop improvement. Furthermore, faster and higher-resolution crop data collection leads to greater capability for scientists and growers to improve precision-agriculture practices on increasingly larger farms; e.g., site-specific application of water and nutrients. Unmanned aerial vehicles (UAVs) have recently gained traction as agricultural data collection systems. Using UAVs for agricultural remote sensing is an innovative technology that differs from traditional remote sensing in more ways than strictly higher-resolution images; it provides many new and unique possibilities, as well as new and unique challenges. Herein we report on processes and lessons learned from year 1—the summer 2015 and winter 2016 growing seasons–of a large multidisciplinary project evaluating UAV images across a range of breeding and agronomic research trials on a large research farm. Included are team and project planning, UAV and sensor selection and integration, and data collection and analysis workflow. The study involved many crops and both breeding plots and agronomic fields. The project’s goal was to develop methods for UAVs to collect high-quality, high-volume crop data with fast turnaround time to field scientists. The project included five teams: Administration, Flight Operations, Sensors, Data Management, and Field Research. Four case studies involving multiple crops in breeding and agronomic applications add practical descriptive detail. Lessons learned include critical information on sensors, air vehicles, and configuration parameters for both. As the first and most comprehensive project of its kind to date, these lessons are particularly salient to researchers embarking on agricultural research with UAVs.

The effects of plant color, pericarp thickness, pigmented testa, and spreader genes on phenols and antioxidant activity levels of 13 sorghum genotypes were evaluated. Total phenols, condensed tannins, flavan-4-ols, and anthocyanins were measured. Antioxidant activity levels using the 2,2'-azinobis(3-ethyl-benzothiazoline-6-sulfonic acid) and 2,2-diphenyl-1-picrylhydrazyl assays were evaluated. Sorghums with a pigmented testa and spreader genes (B(1)()B(2)()S) had the highest levels of phenols and antioxidant activity. In addition, sorghums with purple/red plants (PQ) and thick pericarp (z) genes had increased levels of phenols and antioxidant activity. Sorghums with a black pericarp had higher levels of flavan-4-ols and anthocyanins than the other varieties. This suggests that genes for plant color, pericarp thickness, presence of a pigmented testa, and spreader genes increase phenols and antioxidant activity levels. This information can be useful in the production of sorghums with increased phenols and antioxidant activity levels.

Sweet sorghum [Sorghum bicolor (L.) Moench], like its close relative, sugarcane (Saccharum spp.), has been selected to accumulate high levels of edible sugars in the stem. Sweet sorghums are tall and produce high biomass in addition to sugar. Little has been documented about the genetic relationships and diversity within sweet sorghums and how sweet sorghums relate to grain sorghum racial types. In this study, a diverse panel of 125 sorghums (mostly sweet) was successfully genotyped with 47 simple sequence repeats (SSRs) and 322 single nucleotide polymorphisms (SNPs). Using both distance-based and modelbased methods, we identifi ed three main genetic groupings of sweet sorghums. Based on observed phenotypes and known origins we classifi ed the three groups as historical and modern syrup, modern sugar/energy types, and amber types. Using SSR markers also scored in an available large grain sorghum germplasm panel, we found that these three sweet groupings clustered with kafi r/bicolor, caudatum, and bicolor types, respectively. Using the information on population structure and relatedness, association mapping was performed for height and stem sugar (brix) traits. Three signifi cant associations for height were detected. Two of these, on chromosomes 9 and 6, support published QTL studies. One signifi cant association for brix, on chromosome 1, 12kb from a glucose-6-phosphate isomerase homolog, was detected.

No abstract