Nitric oxide (NO), a versatile molecule, plays multiple roles in plant growth and development and is a key signaling molecule in plant response to abiotic stress. Nutrient management strategy is critical for abiotic stress alleviation in plants. Sulfur (S) is important under stress conditions, as its assimilatory products neutralize the imbalances in cells created by excessive generation of reactive oxygen species (ROS). NO abates the harmful effects of ROS by enhancing antioxidant enzymes, stimulating S assimilation, and reacting with other target molecules, and regulates the expression of various stress-responsive genes under salt stress. This review focuses on the role of NO and S in responses of plants to salt stress, and describes the crosstalk between NO and S assimilation in salt tolerance. The regulation of NO and/or S assimilation using molecular biology tools may help crops to withstand salinity stress.
Abiotic stresses including drought, salinity, heat, cold, flooding, and ultraviolet radiation causes crop losses worldwide. In recent times, preventing these crop losses and producing more food and feed to meet the demands of ever-increasing human populations have gained unprecedented importance. However, the proportion of agricultural lands facing multiple abiotic stresses is expected only to rise under a changing global climate fueled by anthropogenic activities. Identifying the mechanisms developed and deployed by plants to counteract abiotic stresses and maintain their growth and survival under harsh conditions thus holds great significance. Recent investigations have shown that phytohormones, including the classical auxins, cytokinins, ethylene, and gibberellins, and newer members including brassinosteroids, jasmonates, and strigolactones may prove to be important metabolic engineering targets for producing abiotic stress-tolerant crop plants. In this review, we summarize and critically assess the roles that phytohormones play in plant growth and development and abiotic stress tolerance, besides their engineering for conferring abiotic stress tolerance in transgenic crops. We also describe recent successes in identifying the roles of phytohormones under stressful conditions. We conclude by describing the recent progress and future prospects including limitations and challenges of phytohormone engineering for inducing abiotic stress tolerance in crop plants.
Metabolite composition is strongly affected by genotype, environment, and interactions between genotype and environment, although the extent of variation caused by these factors may depend upon the type of metabolite. To characterize the complexity of genotype, environment, and their interaction in hybrid seeds, 50 genetically diverse non-genetically modified (GM) maize hybrids were grown in six geographically diverse locations in North America. Polar metabolites from 553 harvested corn grain samples were isolated and analyzed by gas chromatography-mass spectrometry and 45 metabolites detected in all samples were used to generate a data matrix for statistical analysis. There was moderate variation among biological replicates and across genotypes and test sites. The genotype effects were detected by univariate and Hierarchical clustering analyses (HCA) when environmental effects were excluded. Overall, environment exerted larger effects than genotype, and polar metabolite accumulation showed a geographic effect. We conclude that it is possible to increase seed polar metabolite content in hybrid corn by selection of appropriate inbred lines and growing regions.
The purpose of this study was to characterize Ta14S homoeologs and assess their functions in wheat seed development. The genomic and cDNA sequences of three Ta14S homoeologous genes encoding 14-3-3 proteins were isolated. Sequence analysis revealed that the three homoeologs consisted of five exons and four introns and were very highly conserved in the coding regions and in exon/intron structure, whereas the cDNA sequences were variable in the 5′ and 3′-UTR. The three genes, designated as Ta14S-2A, Ta14S-2B and Ta14S-2D, were located in homoeologous group 2 chromosomes. The polypeptide chains of the three Ta14S genes were highly similar. These genes were most homologous to Hv14A from barley. Real-time quantitative PCR indicated that the three Ta14S genes were differentially expressed in different organs at different developmental stages and all exhibited greater expression in primary roots of 1-day-old germlings than in other tissues. Comparison of the expression patterns of the three homoeologous genes at different times after pollination also revealed that their expression was developmentally regulated. The transcription of Ta14S-2B was clearly higher during seed germination, whereas expressions of Ta14S-2A and Ta14S-2D were up-regulated at the beginning of seed imbibition (0-12 h), but declined thereafter. The results suggested that the three Ta14S homoeologous genes have regulatory roles in seed development and germination.
Ethylene response factor proteins play an important role in regulating a variety of stress responses in plants, but their exact functions in submergence stress are not well understood. In this study, we isolated BnERF2.4 from Brassica napus L. to study its function in submergence tolerance. The expression of the BnERF2.4 gene in B. napus and the expression of antioxidant enzyme genes in transgenic Arabidopsis were analyzed by quantitative RT-PCR. The expression of BnERF2.4 was induced by submergence in B. napus and the overexpression of BnERF2.4 in Arabidopsis increased the level of tolerance to submergence and oxidative stress. A histochemical method detected lower levels of H2O2, O2•− and malondialdehyde (MDA) in transgenic Arabidopsis. Compared to the wild type, transgenic lines also had higher soluble sugar content and higher activity of antioxidant enzymes, which helped to protect plants against the oxidative damage caused by submergence. It was concluded that BnERF2.4 increased the tolerance of plants to submergence stress and may be involved in regulating soluble sugar content and the antioxidant system in defense against submergence stress.
Wheat biomass can be estimated using appropriate spectral vegetation indices. However, the accuracy of estimation should be further improved for on-farm crop management. Previous studies focused on developing vegetation indices, however limited research exists on modeling algorithms. The emerging Random Forest (RF) machine-learning algorithm is regarded as one of the most precise prediction methods for regression modeling. The objectives of this study were to (1) investigate the applicability of the RF regression algorithm for remotely estimating wheat biomass, (2) test the performance of the RF regression model, and (3) compare the performance of the RF algorithm with support vector regression (SVR) and artificial neural network (ANN) machine-learning algorithms for wheat biomass estimation. Single HJ-CCD images of wheat from test sites in Jiangsu province were obtained during the jointing, booting, and anthesis stages of growth. Fifteen vegetation indices were calculated based on these images. In-situ wheat above-ground dry biomass was measured during the HJ-CCD data acquisition. The results showed that the RF model produced more accurate estimates of wheat biomass than the SVR and ANN models at each stage, and its robustness is as good as SVR but better than ANN. The RF algorithm provides a useful exploratory and predictive tool for estimating wheat biomass on a large scale in Southern China.
Spike number per m2 (SN), kernel number per spike (KNPS) and thousand-kernel weight (TKW) are the three main components determining wheat (Triticum aestivum L.) yield. To evaluate the relationships among them a doubled haploid (DH) population consisting of 168 lines grown at three locations for three years was analyzed by unconditional and conditional QTL mapping. Thirty-three unconditional QTL and fifty-nine conditional QTL were detected. Among them, two QTL (QSN-DH-2B and QSN-DH-3A-1.1) improved SN, with no effect on KNPS. QKNPS-DH-2B-2.1 improved KNPS, with no effect on SN. QKNPS-DH-1A-1.1, QKNPS-DH-2D-1.1 and QKNPS-DH-6A improved KNPS, with no effect on SN or TKW. QKNPS-DH-6B was associated with increased SN and TKW. In addition, QTKW-DH-4B, QTKW-DH-5B and QTKW-DH-7B increased TKW without decreasing KNPS. These results provide useful information for marker assisted selection (MAS) and improvement in wheat yield.
Nearly half of the world population suffers from micronutrient malnutrition, particularly Zn deficiency. It is important to understand genetic variation for uptake and translocation behaviors of Zn in relevant crop species to increase Zn concentration in edible parts. In the present study, genetic variation in grain Zn concentration of 319 finger millet genotypes was assessed. Large genetic variation was found among the genotypes, with concentrations ranging from 10 to 86 μg g− 1 grain. Uptake and translocation studies with Zn/65Zn application in 12 selected low-Zn genotypes showed wide variation in root uptake and shoot translocation, with genotypes GEC331 and GEC164 showing greater uptake and translocation. Genotypes GEC164 and GEC543 showed increased grain Zn concentration. Genotypes GEC331 and GEC164 also showed improved yield under Zn treatment. Appreciable variation in grain Zn concentration among finger millet genotypes found in this study offers opportunities to improve Zn nutrition through breeding.
Understanding the effects of shading after pollination on kernel filling and physicochemical properties of waxy maize could improve kernel quality. Experiments were conducted to investigate the effects of shading (30% and 50% light deprivation, taken plants without shading as control) on kernel weight, size, and physicochemical properties during kernel development in 2013 and 2014 using two waxy maize varieties (Suyunuo 5 and Yunuo 7). Results indicated that shading reduced kernel filling rate and decreased kernel size and weight, and the influence was large under severe light deprivation conditions. The large reduction in kernel weight and volume of Suyunuo 5 in response to shading indicated that it was more sensitive to shading than Yunuo 7. Starch content was reduced and protein content was increased by shading, especially under severe shading after 22 days after pollination (DAP). The iodine binding capacity of Yunuo 7 was not affected by shading at fresh and maturity stages but was gradually decreased by shading at the newly formed stage, while the values for Suyunuo 5 were decreased at 7 and 40 DAP only by moderate shading and were similar among three treatments at 22 DAP. Severe shading decreased crystallinity at all kernel development stages, whereas moderate shading decreased crystallinity at fresh stage and increased it at mature stage for Suyunuo 5. Crystallinity in Yunuo 7 was increased by shading at 7 DAP and decreased by shading at 40 DAP, whereas the value at 22 DAP was increased by moderate shading and reduced by severe shading, respectively. The average gelatinization temperatures at different stages were decreased by shading and showed no difference between two shading levels. The retrogradation percentage at 7 DAP for both varieties was increased by shading. The value at 22 DAP was increased by moderate shading for Suyunuo 5 and decreased by severe shading for Yunuo 7, respectively. The retrogradation percentage at 40 DAP was decreased by shading treatments for Suyunuo 5 and reduced only by moderate shading for Yunuo 7. Peak viscosity was decreased by shading at fresh stage for Yunuo 7 and at maturity for Suyunuo 5. In conclusion, shading after pollination inhibited kernel filling of waxy maize and reduced paste viscosity quality, but kernel retrograde quality, crystallinity and starch iodine binding capacity in response to shading were dependent on stage and variety.
