Drought is a multifaceted stress condition that inhibits crop growth. Seed germination is one of the critical and sensitive stages of plants, and its process is inhibited or even entirely prevented by drought. Polyamines (PAs) are closely associated with plant resistance to drought stress and seed germination. However, little is known about the effect of PA on the seed germination of wheat under drought stress. This study investigated the involvement of PAs in regulating wheat seed germination under drought stress. Six wheat genotypes differing in drought resistance were used, and endogenous PA levels were measured during seed germination under different water treatments. In addition, external PA was used for seed soaking and the variation of hormones, total soluble sugar and starch were measured during the seed germination under different water treatments. These results indicated that the free spermidine (Spd) accumulation in seeds during the seed germination period favored wheat seed germination under drought stress; however, the free putrescine (Put) accumulation in seeds during the seed germination period may work against wheat seed germination under drought stress. In addition, seed soaking in Spd and spermine (Spm) significantly relieved the inhibition of seed germination by drought stress; however, soaking seeds in Put had no significant effect on seed germination under drought. External Spd and Spm significantly increased the endogenous indole-3-acetic acid (IAA), zeatin (Z)+zeatin riboside (ZR), abscisic acid (ABA), and gibberellins (GA) contents in seeds and accelerated the seed starch degradation and increased the concentration of soluble sugars in seeds during seed germination. This may promote wheat seed germination under drought stress. In conclusion, free Spd and Put are key factors for regulating wheat seed germination under drought stress and the effects of Spd and Put on seed germination under drought notably related to hormones and starch metabolism.

The biological chemistry would be responsible for the meat quality. This study tried to investigate the transcript expression profile and explain the characteristics of differentially expressed genes between the Wujin and Landrace pigs. The results showed that 526 differentially expressed genes were found by comparing the transcript expression profile of muscle tissue between Wujin and Landrace pigs. Among them, 335 genes showed up-regulations and 191 genes showed down-regulations in Wujin pigs compared with the Landrace pigs. Gene ontology (GO) analysis indicated that the differentially expressed genes were clustered into three groups involving in protein synthesis, energy metabolism and immune response. Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis found that these differentially expressed genes participated in protein synthesis metabolism, energy metabolism and immune response pathway. The Database for Annotation, Visualization and Integrated Discovery (DAVID) analysis of protein function and protein domains function also confirmed that differentially expressed genes belonged to protein synthesis, energy metabolism and immune response. Genes related protein synthesis metabolism pathway in Landrace was higher than in Wujin pigs. However, differentially expressed genes related energy metabolism and immune response was up-regulated in Wujin pigs compared with Landrace pigs. Quantitative real-time RT-PCR on selected genes was used to confirm the results from the microarray. These suggested that the genes related to protein synthesis, energy metabolism and immune response would contribute to the growth performance, meat quality as well as anti-disease capacity.

Normalized Difference Vegetation Index (NDVI) is a very useful feature for differentiating vegetation and non-vegetationin remote sensed imagery. In the light of the function of NDVI and the spatial patterns of the vegetation landscapes, weproposed the lacunarity texture derived from NDVI to characterize the spatial patterns of vegetation landscapes concerningthe “gappiness” or “emptiness” characteristics. The NDVI-based lacunarity texture was incorporated into object-orientedclassification for improving the identification of vegetation categories, especially Torreya which was the targeted treespecies in the present research. A three-level hierarchical network of image objects was defined and the proposed texturewas integrated as potential sources of information in the rules base. A knowledge base of rules created by classifierC5.0 indicated that the texture could potentially be applied in object-oriented classification. It was found that the additionof such texture improved the identification of every vegetation category. The results demonstrated that the texture couldcharacterize the spatial patterns of vegetation structures, which could be a promising approach for vegetation identification.