Ratooning is the cultivation practice of two harvests in one cropping season by producing a second crop from the original stubble, which could provide higher resource use efficiency and economic benefit compared with direct sown crops. Nitrogen (N) fertilizer and planting density (D) play a vital role in sorghum (Sorghum bicolor L.) production; however, limited information is available on the effects on yield and quality of the sorghum-ratoon system. To address this question, field experiments were conducted with three N treatments (120 kg N ha^–1, N1; 180 kg N ha^–1, N2; and 255 kg N ha^–1, N3) and three D treatments (82,500 plant ha^–1, D1; 105,000 plant ha^–1, D2; and 127,500 plant ha^–1, D3). The yield of the main crop was significantly higher than that of the ratoon crop. Increasing N could increase the yield and yield attributes of both main and ratoon crops, and the effect on the ratoon crop was greater than the main crop. With increasing D, the grain yield of both main and ratoon crops increased, though 1,000-grain weight and grain weight per ear decreased. The sorghum grain of the ratoon crop contained higher starch, protein, and tannin contents but lower fat content, indicating a better quality for liquor production. The quality traits were significantly affected by N and D, but the differences between treatments were smaller than that between the main and ratoon crop. Our results indicated that increasing the yield of ratoon crops could obtain a high yield and quality of the sorghum-ratoon system. It was recommended that 120 kg N ha^–1 with 127,500 plant ha^–1 for the main crop and a small amount of N be top-dressed in three new buds left on stubble in each hill for the ratoon crop.

Soybean (Glycine max) is an important crop, rich in proteins, vegetable oils and several other phytochemicals, which is often affected by light during growth. However, the specific regulatory mechanisms of leaf development under shade conditions have yet to be understood. In this study, the transcriptome and metabolome sequencing of leaves from the shade-tolerant soybean ‘Nanxiadou 25′ under natural light (ND1) and 50% shade rate (SHND1) were carried out, respectively. A total of 265 differentially expressed genes (DEGs) were identified, including 144 down-regulated and 121 up-regulated genes. Meanwhile, KEGG enrichment analysis of DEGs was performed and 22 DEGs were significantly enriched in the top five pathways, including histidine metabolism, riboflavin metabolism, vitamin B6 metabolism, glycerolipid metabolism and cutin, suberine and wax biosynthesis. Among all the enrichment pathways, the most DEGs were enriched in plant hormone signaling pathways with 19 DEGs being enriched. Transcription factors were screened out and 34 differentially expressed TFs (DETFs) were identified. Weighted gene co-expression network analysis (WGCNA) was performed and identified 10 core hub genes. Combined analysis of transcriptome and metabolome screened out 36 DEGs, and 12 potential candidate genes were screened out and validated by quantitative real-time polymerase chain reaction (qRT-PCR) assay, which may be related to the mechanism of shade tolerance in soybean, such as ATP phosphoribosyl transferase (ATP-PRT2), phosphocholine phosphatase (PEPC), AUXIN-RESPONSIVE PROTEIN (IAA17), PURPLE ACID PHOSPHATASE (PAP), etc. Our results provide new knowledge for the identification and function of candidate genes regulating soybean shade tolerance and provide valuable resources for the genetic dissection of soybean shade tolerance molecular breeding.

Soybeans are the main source of vegetable protein and edible oil for humans, with an average content of about 40% crude protein and 20% crude fat. Soybean quality traits are mostly quantitative traits controlled by multiple genes. The quantitative trait loci (QTL) for soybean quality traits and mining related candidate genes are of great significance for the molecular breeding of soybean quality traits and understanding the genetic mechanism of protein/fat metabolism. In this study, the F₂ population was derived from the high-protein material Changjiang Chun 2 and Jiyu 166. On the basis of a genetic linkage map constructed in our previous study, the QTL of crude protein content, crude oil content and fatty acid fractions were detected using the multiple-QTL model (MQM) mapping method. The results show that a total of 92 QTL were obtained affecting quality traits under three environments, including 14 QTL of crude oil content, 9 QTL of crude protein content, and 20, 20, 11, 10 and 8 QTL for the content of palmitic, stearic, oleic, linoleic and linolenic acids, respectively. Sixteen QTL clusters were identified, among which Loci01.1, Loci06.1 and Loci11.1 were identified as stable QTL clusters with phenotypic contribution rates of 16.5%, 16.4% and 12.1%, respectively, and candidate genes were mined in their regions. A total of 32 candidate genes related to soybean quality were finally screened via GO enrichment and gene annotation. The present study lies the foundations for understanding the genetic mechanism and elite germplasm innovation of seed quality in soybean.

Soybean, a primary vegetable protein source, boasts favorable amino acid profiles; however, its composition still falls short of meeting human nutritional demands. The soybean amino acid content is a quantitative trait controlled by multiple genes. In this study, an F₂ population of 186 individual plants derived from the cross between ChangJiangChun2 and JiYu166 served as the mapping population. Based on the previously published genetic map of our lab, we increased the density of the genetic map and constructed a new genetic map containing 518 SSR (simple sequence repeats) markers and 64 InDel (insertion-deletion) markers, with an average distance of 5.27 cm and a total length of 2881.2 cm. The content of eight essential amino acids was evaluated in the F_2:5, F_2:6, and BLUP (best linear unbiased prediction). A total of 52 QTLs (quantitative trait loci) were identified, and 13 QTL clusters were identified, among which loci02.1 and loci11.1 emerged as stable QTL clusters, exploring candidate genes within these regions. Through GO enrichment and gene annotation, 16 candidate genes associated with soybean essential amino acid content were predicted. This study would lay the foundation for elucidating the regulatory mechanisms of essential amino acid content and contribute to germplasm innovation in soybeans.