Accurate prediction of nutritional value of sorghum grain using image analysis

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.

Genetic characterization of a Sorghum bicolor multiparent mapping population emphasizing carbon-partitioning dynamics

Sorghum bicolor, a photosynthetically efficient C₄ grass, represents an important source of grain, forage, fermentable sugars, and cellulosic fibers that can be utilized in myriad applications ranging from bioenergy to bioindustrial feedstocks. Sorghum’s efficient fixation of carbon per unit time per unit area per unit input has led to its classification as a preferred biomass crop highlighted by its designation as an advanced biofuel by the U.S. Department of Energy. Due to its extensive genetic diversity and worldwide colonization, sorghum has considerable diversity for a range of phenotypes influencing productivity, composition, and sink/source dynamics. To dissect the genetic basis of these key traits, we present a sorghum carbon-partitioning nested association mapping (NAM) population generated by crossing 11 diverse founder lines with Grassl as the single recurrent female. By exploiting existing variation among cellulosic, forage, sweet, and grain sorghum carbon partitioning regimes, the sorghum carbon-partitioning NAM population will allow the identification of important biomass-associated traits, elucidate the genetic architecture underlying carbon partitioning and improve our understanding of the genetic determinants affecting unique phenotypes within Poaceae. We contrast this NAM population with an existing grain population generated using Tx430 as the recurrent female. Genotypic data are assessed for quality by examining variant density, nucleotide diversity, linkage decay, and are validated using pericarp and testa phenotypes to map known genes affecting these phenotypes. We release the 11-family NAM population along with corresponding genomic data for use in genetic, genomic, and agronomic studies with a focus on carbon-partitioning regimes.