SoyMAGIC: An Unprecedented Platform for Genetic Studies and Breeding Activities in Soybean

Variation Analysis of Starch Properties in Tartary Buckwheat and Construction of Near-Infrared Models for Rapid Non-Destructive Detection

Due to the requirements for quality testing and breeding Tartary buckwheat (Fagopyrum tartaricum Gaerth), it is necessary to find a method for the rapid detection of starch content in Tartary buckwheat. To obtain samples with a continuously distributed chemical value, stable Tartary buckwheat recombinant inbred lines were used. After scanning the near-infrared spectra of whole grains, we employed conventional methods to analyze the contents of Tartary buckwheat. The results showed that the contents of total starch, amylose, amylopectin, and resistant starch were 532.1-741.5 mg/g, 176.8-280.2 mg/g, 318.8-497.0 mg/g, and 45.1-105.2 mg/g, respectively. The prediction model for the different starch contents in Tartary buckwheat was established using near-infrared spectroscopy (NIRS) in combination with chemometrics. The Kennard-Stone algorithm was used to split the training set and the test set. Six different methods were used to preprocess the spectra in the wavenumber range of 4000-12,000 cm-1. The Competitive Adaptive Reweighted Sampling algorithm was then used to extract the characteristic spectra, and the prediction model was built using the partial least squares method. Through a comprehensive analysis of each parameter of the model, the best model for the prediction of each nutrient was determined. The correlation coefficient of calibration (Rc) and the correlation coefficient of prediction (Rp) of the best models for total starch and amylose were greater than 0.95, and the Rc and Rp of the best models for amylopectin and resistant starch were also greater than 0.93. The results showed that the NIRS-based prediction model fulfilled the requirement for the rapid determination of Tartary buckwheat starch, thus providing an effective technical approach for the rapid and non-destructive testing of starch content in the food science and agricultural industry.

Biocultural diversity and crop improvement

Biocultural diversity is the ever-evolving and irreplaceable sum total of all living organisms inhabiting the Earth. It plays a significant role in sustainable productivity and ecosystem services that benefit humanity and is closely allied with human cultural diversity. Despite its essentiality, biodiversity is seriously threatened by the insatiable and inequitable human exploitation of the Earth's resources. One of the benefits of biodiversity is its utilization in crop improvement, including cropping improvement (agronomic cultivation practices) and genetic improvement (plant breeding). Crop improvement has tended to decrease agricultural biodiversity since the origins of agriculture, but awareness of this situation can reverse this negative trend. Cropping improvement can strive to use more diverse cultivars and a broader complement of crops on farms and in landscapes. It can also focus on underutilized crops, including legumes. Genetic improvement can access a broader range of biodiversity sources and, with the assistance of modern breeding tools like genomics, can facilitate the introduction of additional characteristics that improve yield, mitigate environmental stresses, and restore, at least partially, lost crop biodiversity. The current legal framework covering biodiversity includes national intellectual property and international treaty instruments, which have tended to limit access and innovation to biodiversity. A global system of access and benefit sharing, encompassing digital sequence information, would benefit humanity but remains an elusive goal. The Kunming-Montréal Global Biodiversity Framework sets forth an ambitious set of targets and goals to be accomplished by 2030 and 2050, respectively, to protect and restore biocultural diversity, including agrobiodiversity.

Discovering useful genetic variation in the seed parent gene pool for sorghum improvement

Multi-parent populations contain valuable genetic material for dissecting complex, quantitative traits and provide a unique opportunity to capture multi-allelic variation compared to the biparental populations. A multi-parent advanced generation inter-cross (MAGIC) B-line (MBL) population composed of 708 F6 recombinant inbred lines (RILs), was recently developed from four diverse founders. These selected founders strategically represented the four most prevalent botanical races (kafir, guinea, durra, and caudatum) to capture a significant source of genetic variation to study the quantitative traits in grain sorghum [Sorghum bicolor (L.) Moench]. MBL was phenotyped at two field locations for seven yield-influencing traits: panicle type (PT), days to anthesis (DTA), plant height (PH), grain yield (GY), 1000-grain weight (TGW), tiller number per meter (TN) and yield per panicle (YPP). High phenotypic variation was observed for all the quantitative traits, with broad-sense heritabilities ranging from 0.34 (TN) to 0.84 (PH). The entire population was genotyped using Diversity Arrays Technology (DArTseq), and 8,800 single nucleotide polymorphisms (SNPs) were generated. A set of polymorphic, quality-filtered markers (3,751 SNPs) and phenotypic data were used for genome-wide association studies (GWAS). We identified 52 marker-trait associations (MTAs) for the seven traits using BLUPs generated from replicated plots in two locations. We also identified desirable allelic combinations based on the plant height loci (Dw1, Dw2, and Dw3), which influences yield related traits. Additionally, two novel MTAs were identified each on Chr1 and Chr7 for yield traits independent of dwarfing genes. We further performed a multi-variate adaptive shrinkage analysis and 15 MTAs with pleiotropic effect were identified. The five best performing MBL progenies were selected carrying desirable allelic combinations. Since the MBL population was designed to capture significant diversity for maintainer line (B-line) accessions, these progenies can serve as valuable resources to develop superior sorghum hybrids after validation of their general combining abilities via crossing with elite pollinators. Further, newly identified desirable allelic combinations can be used to enrich the maintainer germplasm lines through marker-assisted backcross breeding.