Hexanol is a major compound contributing to the off-flavors (the bean-like odor) of soybean derived soymilk. The most effective way to reduce the off-flavors of soymilk is the screening and utilization of soybean cultivars with improved hexanol content. However, no genome-wide genetic analysis for this particular trait has been conducted to date. The objective of the present study was to dissect the genetic basis of hexanol content in soybean seed through genome-wide association analysis (GWAS). A total of 105 soybean accessions were analyzed for hexanol content in a three-year experiments and genotyped by sequencing using the specific locus amplified fragment sequencing (SLAF-seq) approach. A total of 25 724 single nucleotide polymorphisms (SNPs) were obtained with minor allele frequencies (MAF)>5%. GWAS showed that 25 quantitative trait nucleotides (QTNs) were significantly associated with the hexanol concentration in soybean seed. These identified QTNs distributed on different genomic regions of the 15 chromosomes. A total of 91 genes were predicted as candidate genes underlying the seed hexanol level and six candidates were predicted possibly underlying the seed hexanol by gene based association. In this study, GWAS has been proven to be an effective way to dissect the genetic basis of the hexanol concentration in multiple genetic backgrounds. The identified beneficial alleles and candidate genes might be valuable for the improvement of marker-assisted breeding efficiency for low hexanol level and help to explore possible molecular mechanisms underlying hexanol content in soybean seed.

    Crop growth and yield depend on canopy light interception (LI). To identify a low-cost and relatively efficient index for measuring LI, several color attributes of red-green-blue (RGB), hue-saturation-intensity (HSI), hue-saturation-value (HSV) color models and the component values of color attributes in the RGB color model were investigated using digital images at six cotton plant population densities in 2012–2014. The results showed that the LI values followed downward quadratic curves after planting. The red (R), green (G) and blue (B) values varied greatly over the years, in accordance with Cai’s research demonstrating that the RGB model is affected by outside light. Quadratic curves were fit to these color attributes at six plant population densities. Additionally, linear regressions of LI on every color attribute revealed that the hue (H) values in HSI and HSV were significantly linearly correlated with LI with a determination coefficient (R²)≥0.89 and a root mean square error (RMSE)=0.05. Thus, the H values in the HSI and HSV models could be used to measure LI, and this hypothesis was validated. The H values are new indexes for quantitatively estimating the LI of heterogeneous crop canopies, which will provide a theoretical basis for optimizing the crop canopy structure. However, further research should be conducted in other crops and under other growing and environmental conditions to verify this finding.

     Yield and fiber quality of cotton even varies within locules in a boll, but it is not clear how yield components and quality parameters are altered across seed positions of a locule (SPL). A field experiment was arranged in a split plot design with transgenic insect resistant Bt (Bacillus thuringiensis) cotton hybrid cultivar CRI75 and conventional cultivar SCRC28 as the main plots, and three plant densities (15 000, 51 000 and 87 000 plants ha^–1) as the subplots in 2012 and 2013 at Anyang, Henan Province, China. Cotton was hand harvested by node and fruiting position, and then seeds of the first fruiting position bolls from nodes 6–10 were separated by SPL. The effects of plant density on lint yield, fiber quality, especially across SPL were determined. It was showed that plant densities of 51 000 and 87 000 plants ha^–1 increased lint yield by 61.3 and 65.3% in 2012 and 17.8 and 15.5% in 2013 relative to low plant density (15 000 plants ha^–1), however, no significant difference was observed between 51 000 and 87 000 plants ha^–1. The number of bolls (boll density) increased while boll weight decreased as plant density raised, and no significant changes occured in lint percentage in 2013 but increased with plant density in 2012. The number of bolls in upper nodes and distal fruiting positions, the number of seeds per boll, seed area (SA) and seed vigor index increased with decreasing plant density. Seed area was found to be greater from the base to the middle compared to the apex of a locule. Mote frequency (MF) increased as plant density increased, and fiber quality was the best at the middle of the locule regardless of plant density. As the number of fibers per seed area is genetically determined, adjusting plant density to produce more seeds and greater seed area can be a potentially promising alternative to improve lint yield in cotton. These findings might be of great importantance to cotton breeding and filed management.

Rice panicles are composed of many branches with two types of extreme grains, the superior and the inferior. Traditionally, it has been well accepted that earlier flowers result in superior grains and late flowers generate inferior grains. However, these correlations have never been strictly examined in practice. In order to determine the accurate relationship between superior and inferior grains and the flowering order, we localized all the seeds in a panicle in four distinct rice species and systematically documented the rice flowering order, flower locations and the final grain weight for their relationships. Our results demonstrated that the grain weight is more heavily determined by the position of the seeds than by the flowering order. Despite earlier flowering has a positive correlation with the grain weight in general, grains from flowers blooming on the second day after anthesis generally gained the highest weight. This suggests earlier flowers may not result in superior grains. Therefore, we concluded that superior and inferior grains, commonly determined by grain weight, are not fully correlated with the flowering order in rice. Following the order of the grain weight, the superior grains are generally localized at the middle parts of the primary branches, whereas inferior grains were mainly on the last two secondary branches of the lower half part of the panicle. In addition, the weight of inferior grains were affected by spikelet thinning and spraying with exogenous plant growth regulators, indicating that physiological incompetence might be the major reason for the occurrence of the inferior grains.

Starch content is a key factor affecting sorghum grain quality. The research of sorghum grain starch accumulation and the related synthesis enzyme activities has great significance for understanding the mechanisms of starch metabolisms. The differences between a high and a low starch content sorghum hybrids (Tieza 17 and Liaoza 11, respectively) in grain starch accumulation and the related synthesis enzyme activities were assessed following imposition of water stress during flowering stage. The total starch, amylase and amylopectin accumulation all decreased at the mid-late stage of grain filling under drought stress during flowering stage. The maximum and mean accumulation rates also decreased. During grain filling, soluble starch synthase (SSS), granule-bound starch synthase (GBSS), starch branching enzyme (SBE), and starch debranching enzymes (DBE) activities were all affected, though differently. Drought stress reduced starch accumulation in a larger extent for Tieza 17 than Liaoza 11. Drought stress during flowing stage reduced starch synthesis enzyme activities, thus reducing starch accumulation in grains, and the differences between starch components were also demonstrated under drought stress.

The importance of microRNA (miRNA) at the post-transcriptional regulation level has recently been recognized in both animals and plants. In recent years, many studies focused on miRNA target identification and functional analysis. However, little is known about the transcription and regulation of miRNAs themselves. In this study, the transcription start sites (TSSs) for 11 miRNA primary transcripts of soybean from 11 miRNA loci (of 50 loci tested) were cloned by a 5´ rapid amplification of cDNA ends (5´ RACE) procedure using total RNA from 30-d-old seedlings. The features consistent with a RNA polymerase II mechanism of transcription were found among these miRNA loci. A position weight matrix algorithm was used to identify conserved motifs in miRNA core promoter regions. A canonical TATA box motif was identified upstream of the major start site at 8 (76%) of the mapped miRNA loci. Several cis-acting elements were predicted in the 2 kb 5´ to the TSSs. Potential spatial and temporal expression patterns of the miRNAs were found. The target genes for these miRNAs were also predicted and further elucidated for the potential function of the miRNAs. This research provides a molecular basis to explore regulatory mechanisms of miRNA expression, and a way to understand miRNAmediated regulatory pathways and networks in soybean.

EST-derived SSR marker has been developed in many species, but few methods of high efficiency have been reported for the exploitation of EST-SSR markers. Thus, a high efficiency method for mining millions of redundant EST data is needed. A modified method for the EST-SSR development with high efficiency was established based on the redundant EST data of soybean in this study. The method achieved its function through classifying ESTs according to the same SSR motif and detected candidate loci with redundant sequences. In this study, a total of 80 polymorphic EST-SSR markers of soybean were developed, 50 of them were exploited by this modified method which proved the higher speed and efficiency of this method. All the 80 polymorphic EST-SSRs were mapped on soybean physical map through in silico mapping and 15 markers were integrated on a genetic map constructed in previous study. A software named hpSSR (high polymorphic SSR) was programmed based on the concept of the up-built method for EST-SSR development. This method is not only pragmatic for EST-SSR exploitation in soybean, but also effective for the development of the marker in other species if the redundancy EST data is available.

Soyasaponins are valuable compounds in certain drugs, industry, food additives and surfactants. Selecting cultivars with higher-soyasaponin content along with agronomic traits is a main goal for many soybean breeders. The aim of the present study was to identify the quantitative trait loci (QTLs) associated with total soyasaponin content through a F2 population, which was derived from a cross between Ha 91016 (higher soyasaponin content cultivar, 16.8 mg g-1) and N98-9445A (lower soyasaponin content, only 5.7 mg g-1). A genetic linkage map including a total of 162 simple sequence repeat markers was constructed, which covered the total length 2 735.5 cM, and the average distance between markers was 16.96 cM. Two QTLs associated with total soyasaponin content were identified. One, qSAP_1 (located in sat_044-satt102 of linkage group (LG) K), could explain 12.6% of phenotypic variance. The other, qSAP_2, was located between satt368 and sat_413 of LG D1a, which could explain 15.8% of phenotypic variance. It was concluded that the two QTLs would have some potential value for marker-assisted selection for high-soyasaponin content breeding in soybeans.

The importance of microRNAs (miRNAs) at the post-transcriptional regulation level has recently been recognized in bothanimals and plants. In this study, the simple and most effective method of comparative genomic approach was used. Firstknown plants miRNAs BLAST against the soybean genome, and then the located candidates were searched for novelmiRNAs by RNA folding method in the vicinity (±400 nt) of the candidates. The results showed that a total of 521 novelsoybean miRNA genes, including 236 mature miRNAs, were identified. All these mature miRNAs were grouped into 58families, of which 21 of them were novel family in soybean. The upstream 2 000 nt of potential pre-miRNAs was used forpromoter prediction, in order to investigate prediction of miRNAs and detect transcript unit and clustering. In this study,miRNA genes less tend to be present as clusters in soybean. Only 9 clusters, containing 21 miRNA genes (accounted for4.0% of the total), were observed as part of polycistronic transcripts. Detailed analysis of sequence characteristics ofnovel miRNAs in soybean and all previous known plants miRNAs, were carried out. These results of this study providea reference point for further study on miRNAs identification in plants, and improve the understanding of genome insoybean.