Development Of Crop Cultivars Research Articles

Exploiting Induced Plant Resistance for Sustainable Pest Management: Mechanisms, Elicitors, and Applications: A Review

Plants and phytophagous (plant-eating) arthropods have coevolved over millions of years, leading to the development of both constitutive and inducible defense mechanisms in plants. Despite this long history of coexistence, it remains unclear how to precisely regulate each host-arthropod interaction to achieve an equilibrium that maximizes crop yield. The defensive chemicals produced by plants can significantly affect herbivores’ feeding behaviour, growth, and survival. These chemicals may be generated constitutively (continuously) or induced in response to herbivore damage. Induced resistance, a strategy where plants enhance their defences after being attacked, holds potential for reducing the number of insecticides needed in pest management. Chemical elicitors, which trigger the production of secondary metabolites that confer resistance to insects, can be used to manipulate host plant resistance, specifically by inducing resistance. By understanding the mechanisms underlying induced resistance, it is possible to predict which herbivores will be impacted by these responses. Applying induced response elicitors to crop plants can strengthen their natural defences against herbivore damage. Additionally, it is possible to genetically modify plants so that they constitutively produce defense chemicals, providing continuous protection in areas where herbivory is a constant threat. As part of integrated pest management, induced resistance can be used to develop crop cultivars that readily trigger an inducible response in the event of a mild infestation, contributing to sustainable agricultural practices and reducing reliance on chemical pesticides.

Evaluation of Morpho-Physiological Traits of Oat (Avena sativa L.) under Drought Stress

The increase in intensity and frequency of drought due to global climate change has increased the urgency of developing crop cultivars suitable for dry environments. Drought tolerance is a complex trait that involves numerous physiological, biochemical, and morphological responses. A better understanding of those mechanisms is critical to develop drought tolerant cultivars. In this study, we aimed to understand the morphophysiological changes at the shoot and root levels in response to drought stress of ten oat genotypes with diverse root morphological characteristics. Twenty-one-day old plants were subjected to drought stress in a greenhouse by withholding water for two weeks. Several characteristics including chlorophyll content, relative water content (RWC), stomatal conductance, stomata number, shoot dry weight (SDW), root dry weight (RDW), root-to-shoot biomass ratio (RSR), root length, root area, and root volume were measured on well-watered, and drought-stressed plants. Grain yield was evaluated by continuing the drought treatment with a drying and rewatering cycle every 15 days until physiological maturity. The water regime had a significant impact on all traits evaluated. A significant interaction between genotype and water treatment was observed for RWC, chlorophyll content, stomatal conductance, stomata number, and grain yield but not for root traits, suggesting that the root system of all genotypes responded similarly to drought stress. Hayden, the cultivar with the lowest reduction in grain yield from the drought treatment, was among the genotypes with the lowest reduction in RWC and chlorophyll content but with a sharp decrease in stomata number, thus indicating that regulating the plant water status and maintaining the photosynthesis level are important for oat plants to maintain grain yield under drought stress. The size of the root system was not correlated with grain yield under drought, but the RWC and grain yield were significantly correlated under drought, thus suggesting that maintaining the RWC is an important characteristic for oat plants to maintain yield under drought stress.

Explainable deep learning in plant phenotyping.

The increasing human population and variable weather conditions, due to climate change, pose a threat to the world's food security. To improve global food security, we need to provide breeders with tools to develop crop cultivars that are more resilient to extreme weather conditions and provide growers with tools to more effectively manage biotic and abiotic stresses in their crops. Plant phenotyping, the measurement of a plant's structural and functional characteristics, has the potential to inform, improve and accelerate both breeders' selections and growers' management decisions. To improve the speed, reliability and scale of plant phenotyping procedures, many researchers have adopted deep learning methods to estimate phenotypic information from images of plants and crops. Despite the successful results of these image-based phenotyping studies, the representations learned by deep learning models remain difficult to interpret, understand, and explain. For this reason, deep learning models are still considered to be black boxes. Explainable AI (XAI) is a promising approach for opening the deep learning model's black box and providing plant scientists with image-based phenotypic information that is interpretable and trustworthy. Although various fields of study have adopted XAI to advance their understanding of deep learning models, it has yet to be well-studied in the context of plant phenotyping research. In this review article, we reviewed existing XAI studies in plant shoot phenotyping, as well as related domains, to help plant researchers understand the benefits of XAI and make it easier for them to integrate XAI into their future studies. An elucidation of the representations within a deep learning model can help researchers explain the model's decisions, relate the features detected by the model to the underlying plant physiology, and enhance the trustworthiness of image-based phenotypic information used in food production systems.

Yield Performance and Stability Analysis of Promising Soybean Genotypes under Contrasting Environments in the Semi-arid Zone of Sudan

Background: The challenge to food security posed by climate change and coupled with the substantial rise in the global population, necessitate a shift in crop improvement programmes towards developing crop cultivars with stable and high yield potentials across a wide range of agro-ecological conditions. Methods: New high yielding crop varieties with stable performance across environments are enabling the expansion of their production area into non-traditional environments with semi-arid climates. Soybean (Glycine max L.), a tropical leguminous crop, has received significant attention as a target crop in breeding programmes for adaptation to semi-arid environments, due to its low water content, high nutritive value and the capacity to produce a variety of products. The objective of this study was to asses yield performance and stability of promising soybean genotypes under contrasting environments in the semi-arid zone of Sudan. We evaluated five soybean genotypes using a split plot design with environment as the main plot and genotype as the subplot. Result: Combined ANOVA showed significant differences among the genotypes, environment and genotype x environment interaction. Moreover, significant positive relationships were observed between seed yield and number of days to 95% flowering, 100-seed weight, leaf area and number of pods per plant. AMMI stability values revealed significant differences among the genotypes and genotype-by-environment main effects for seed yield. Similarly, results of GGE biplot showed significant contributions of genotypes and genotype-by-environment main effects. The stability models enabled us to identify genotypes with superior performance to specific environments. TGX 1904-6F, was found to be the most stable genotype with appreciable seed yield and adaptability across all environments that can be recommended for release to farmers in semi-arid Sudan.

Plasticity of maternal environment-dependent expression-QTLs of tomato seeds

Seeds are essential for plant reproduction, survival, and dispersal. Germination ability and successful establishment of young seedlings strongly depend on seed quality and on environmental factors such as nutrient availability. In tomato (Solanum lycopersicum) and many other species, seed quality and seedling establishment characteristics are determined by genetic variation, as well as the maternal environment in which the seeds develop and mature. The genetic contribution to variation in seed and seedling quality traits and environmental responsiveness can be estimated at transcriptome level in the dry seed by mapping genomic loci that affect gene expression (expression QTLs) in contrasting maternal environments. In this study, we applied RNA-sequencing to construct a linkage map and measure gene expression of seeds of a tomato recombinant inbred line (RIL) population derived from a cross between S. lycopersicum (cv. Moneymaker) and S. pimpinellifolium (G1.1554). The seeds matured on plants cultivated under different nutritional environments, i.e., on high phosphorus or low nitrogen. The obtained single-nucleotide polymorphisms (SNPs) were subsequently used to construct a genetic map. We show how the genetic landscape of plasticity in gene regulation in dry seeds is affected by the maternal nutrient environment. The combined information on natural genetic variation mediating (variation in) responsiveness to the environment may contribute to knowledge-based breeding programs aiming to develop crop cultivars that are resilient to stressful environments.

ASRpro: A machine-learning computational model for identifying proteins associated with multiple abiotic stress in plants.

One of the thrust areas of research in plant breeding is to develop crop cultivars with enhanced tolerance to abiotic stresses. Thus, identifying abiotic stress-responsive genes (SRGs) and proteins is important for plant breeding research. However, identifying such genes via established genetic approaches is laborious and resource intensive. Although transcriptome profiling has remained a reliable method of SRG identification, it is species specific. Additionally, identifying multistress responsive genes using gene expression studies is cumbersome. Thus, endorsing the need to develop a computational method for identifying the genes associated with different abiotic stresses. In this work, we aimed to develop a computational model for identifying genes responsive to six abiotic stresses: cold, drought, heat, light, oxidative, and salt. The predictions were performed using support vector machine (SVM), random forest, adaptive boosting (ADB), and extreme gradient boosting (XGB), where the autocross covariance (ACC) and K-mer compositional features were used as input. With ACC, K-mer, and ACC + K-mer compositional features, the overall accuracy of ∼60-77, ∼75-86, and ∼61-78% were respectively obtained using the SVM algorithm with fivefold cross-validation. The SVM also achieved higher accuracy than the other three algorithms. The proposed model was also assessed with an independent dataset and obtained an accuracy consistent with cross-validation. The proposed model is the first of its kind and is expected to serve the requirement of experimental biologists; however, the prediction accuracy was modest. Given its importance for the research community, the online prediction application, ASRpro, is made freely available (https://iasri-sg.icar.gov.in/asrpro/) for predicting abiotic SRGs and proteins.

Advances in Plant Lipid Metabolism Responses to Phosphate Scarcity.

Low phosphate (Pi) availability in soils severely limits crop growth and production. Plants have evolved to have numerous physiological and molecular adaptive mechanisms to cope with Pi starvation. The release of Pi from membrane phospholipids is considered to improve plant phosphorus (P) utilization efficiency in response to Pi starvation and accompanies membrane lipid remodeling. In this review, we summarize recent discoveries related to this topic and the molecular basis of membrane phospholipid alteration and triacylglycerol metabolism in response to Pi depletion in plants at different subcellular levels. These findings will help to further elucidate the molecular mechanisms underlying plant adaptation to Pi starvation and thus help to develop crop cultivars with high P utilization efficiency.

Multi‐objective optimization of root phenotypes for nutrient capture using evolutionary algorithms

SUMMARYRoot phenotypes are avenues to the development of crop cultivars with improved nutrient capture, which is an important goal for global agriculture. The fitness landscape of root phenotypes is highly complex and multidimensional. It is difficult to predict which combinations of traits (phene states) will create the best performing integrated phenotypes in various environments. Brute force methods to map the fitness landscape by simulating millions of phenotypes in multiple environments are computationally challenging. Evolutionary optimization algorithms may provide more efficient avenues to explore high dimensional domains such as the root phenotypic space. We coupled the three‐dimensional functional–structural plant model, SimRoot, to the Borg Multi‐Objective Evolutionary Algorithm (MOEA) and the evolutionary search over several generations facilitated the identification of optimal root phenotypes balancing trade‐offs across nutrient uptake, biomass accumulation, and root carbon costs in environments varying in nutrient availability. Our results show that several combinations of root phenes generate optimal integrated phenotypes where performance in one objective comes at the cost of reduced performance in one or more of the remaining objectives, and such combinations differed for mobile and non‐mobile nutrients and for maize (a monocot) and bean (a dicot). Functional–structural plant models can be used with multi‐objective optimization to identify optimal root phenotypes under various environments, including future climate scenarios, which will be useful in developing the more resilient, efficient crops urgently needed in global agriculture.

CerealESTDb: A Comprehensive Resource for Abiotic Stress-Responsive Annotated ESTs With Predicted Genes, Gene Ontology, and Metabolic Pathways in Major Cereal Crops.

Cereals are the most important food crops and are considered key contributors to global food security. Loss due to abiotic stresses in cereal crops is limiting potential productivity in a significant manner. The primary reasons for abiotic stresses are abrupt temperature, variable rainfall, and declining nutrient status of the soil. Varietal development is the key to sustaining productivity under influence of multiple abiotic stresses and must be studied in context with genomics and molecular breeding. Recently, advances in a plethora of Next Generation Sequencing (NGS) based methods have accelerated the enormous genomic data generation associated with stress-induced transcripts such as microarray, RNAseq, Expressed Sequenced Tag (ESTs), etc. Many databases related to microarray and RNA-seq based transcripts have been developed and profusely utilized. However, an abundant amount of transcripts related to abiotic stresses in various cereal crops arising from EST technology are available but still remain underutilized in absence of a consolidated database. In this study, an attempt has been made with a primary goal to integrate, analyse, and characterise the available resources of ESTs responsive to abiotic stresses in major cereals. The developed CerealESTdb presents a customisable search in two different ways in the form of searchable content for easy access and potential use. This database comprises ESTs from four major cereal crops, namely rice (Oryza sativa L.), wheat (Triticum aestivum L.), sorghum (Sorghum bicolour L.), and maize (Zea mays L.), under a set of abiotic stresses. The current statistics of this cohesive database consists of 55,826 assembled EST sequences, 51,791 predicted genes models, and their 254,609 gene ontology terms including extensive information on 1,746 associated metabolic pathways. We anticipate that developed CerealESTdb will be helpful in deciphering the knowledge of complex biological phenomena under abiotic stresses to accelerate the molecular breeding programs towards the development of crop cultivars resilient to abiotic stresses. The CerealESTdb is publically available with the URL http://cabgrid.res.in/CerealESTDb.

Adapting to climate change precisely through cultivars renewal for rice production across China: When, where, and what cultivars will be required?

Climate change is projected to have an important impact on crop productivity at broad regions of the world. Crop breeders across the globe have continuously been working on development of crop cultivars to adapt to climate change, the detailed information is necessary on when and where the adaptability of current cultivars will be broken and what cultivar traits will be required. Here, we developed a novel hybrid crop modelling approach that coupled a process-based crop model with machine learning and systematically assessed the impacts of climate change on rice productivity for 36 representative cultivars in China. We identified when, where, and what cultivars would be required for rice production to adapt to climate change precisely across China. We showed substantial differences in climate change impacts amongst cultivars. Current cultivars replacement could only alleviate but not offset the potential yield loss due to climate change in the future. Without adaptations and CO2 effect, nearly 67% of single rice and 46% of double rice cultivation areas would require cultivar renewal before 2050. Only two decades of leading time remain in the mid-lower reaches of the Yangtze River. The cultivars with a medium growth cycle, long grain-filling period, high photosynthetic capacity, and less spikelets should be breeding targets to adapt to climate change, although the ideotypic traits could be different for a specific environment and rice type.

Transcriptome revealed the molecular mechanism of Glycyrrhiza inflata root to maintain growth and development, absorb and distribute ions under salt stress

BackgroundSoil salinization extensively hampers the growth, yield, and quality of crops worldwide. The most effective strategies to counter this problem are a) development of crop cultivars with high salt tolerance and b) the plantation of salt-tolerant crops. Glycyrrhiza inflata, a traditional Chinese medicinal and primitive plant with salt tolerance and economic value, is among the most promising crops for improving saline-alkali wasteland. However, the underlying molecular mechanisms for the adaptive response of G. inflata to salinity stress remain largely unknown.ResultG. inflata retained a high concentration of Na+ in roots and maintained the absorption of K+, Ca2+, and Mg2+ under 150 mM NaCl induced salt stress. Transcriptomic analysis of G. inflata roots at different time points of salt stress (0 min, 30 min, and 24 h) was performed, which resulted in 70.77 Gb of clean data. Compared with the control, we detected 2645 and 574 differentially expressed genes (DEGs) at 30 min and 24 h post-salt-stress induction, respectively. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses revealed that G. inflata response to salt stress post 30 min and 24 h was remarkably distinct. Genes that were differentially expressed at 30 min post-salt stress induction were enriched in signal transduction, secondary metabolite synthesis, and ion transport. However, genes that were differentially expressed at 24 h post-salt-stress induction were enriched in phenylpropane biosynthesis and metabolism, fatty acid metabolism, glycerol metabolism, hormone signal transduction, wax, cutin, and cork biosynthesis. Besides, a total of 334 transcription factors (TFs) were altered in response to 30 min and 24 h of salt stress. Most of these TFs belonged to the MYB, WRKY, AP2-EREBP, C2H2, bHLH, bZIP, and NAC families.ConclusionFor the first time, this study elucidated the salt tolerance in G. inflata at the molecular level, including the activation of signaling pathways and genes that regulate the absorption and distribution of ions and root growth in G. inflata under salt stress conditions. These findings enhanced our understanding of the G. inflata salt tolerance and provided a theoretical basis for cultivating salt-tolerant crop varieties.

Transcriptome Analysis Reveals Different Responsive Patterns to Nitrogen Deficiency in Two Wheat Near-Isogenic Lines Contrasting for Nitrogen Use Efficiency

Simple SummaryNitrogen (N) limitation is the key factor for wheat production worldwide. Therefore, the development of genotypes with improved nitrogen use efficiency (NUE) is a prerequisite for sustainable and productive agriculture. Exploring the molecular mechanisms of low N stress tolerance is significant for breeding wheat cultivars with high NUE. To clarify the underlying molecular mechanisms of enhanced resilience to low N in high-NUE wheat, we performed an RNA sequencing (RNA-seq) analysis. In the current research, two wheat near-isogenic lines (NILs) differing dramatically in NUE were used to measure gene expression differences under different N treatments. There was a dramatic difference between two wheat NILs in response to N deficiency at the transcriptional level, and the classification of identified candidate genes may provide new valuable insights into the resilience mechanism of wheat.The development of crop cultivars with high nitrogen use efficiency (NUE) under low-N fertilizer inputs is imperative for sustainable agriculture. However, there has been little research on the molecular mechanisms underlying enhanced resilience to low N in high-NUE plants. The comparison of the transcriptional responses of genotypes contrasting for NUE will facilitate an understanding of the key molecular mechanism of wheat resilience to low-N stress. In the current study, the RNA sequencing (RNA-seq) technique was employed to investigate the genotypic difference in response to N deficiency between two wheat NILs (1Y, high-NUE, and 1W, low-NUE). In our research, high- and low-NUE wheat NILs showed different patterns of gene expression under N-deficient conditions, and these N-responsive genes were classified into two major classes, including “frontloaded genes” and “relatively upregulated genes”. In total, 103 and 45 genes were identified as frontloaded genes in high-NUE and low-NUE wheat, respectively. In summary, our study might provide potential directions for further understanding the molecular mechanism of high-NUE genotypes adapting to low-N stress.

Performance of Hybrid Wheat Cultivars Facing Deficit Irrigation under Semi-Arid Climate in Pakistan

Predicted decrease in water availability for crop production and uncertainty in climatic conditions require devising the irrigation strategies to increase water use efficiency (WUE) for sustainable crop production. The development of crop cultivars with higher WUE is a pre-requisite for such strategies, particularly in developing countries, including Pakistan, who face stern food security challenges. A two-year field study was conducted following a split-plot randomized complete block design to understand the effects of wheat cultivars (hybrid cultivars, 18A-1 and 18A-2, and local cultivar Ghaneemat IBGE-2016), sowing dates (15th November, 30th November, and 15th December), and irrigation regimes [I (103 mm), II (175 mm), III (254 mm), and IV (330 mm)] at four different growth stages of tillering, booting, anthesis and grain filling on wheat productivity, biomass production and grain yield, and crop-water relations. Early sown hybrid cultivars 18A-1 and 18A-2 showed significantly higher biological and grain yields compared to the local cultivar (59% and 69% higher than the local cultivar). Trends in biomass production and grain yield were also similar at later sowing dates of 30th November and 15th December. However, biological and grain yields decreased with delay in sowing for each cultivar. The data also revealed that hybrid cultivars were better suited to deficient irrigation and generally produced significantly higher biological and grain yields under each moisture regime. Cultivars, sowing dates, and irrigation regime differed significantly for their effects on the Soil Plant Analysis Development (SPAD) values, chlorophyll a and b contents but not for carotenoids. Sowing dates and irrigation regimes had significant effects on relative water content (RWC), water saturation deficit (WSD), water uptake capacity (WUC), and water retention capacity (WRC); however, only WUC varied significantly between the cultivars. The phenological data show that hybrid cultivars took more days to maturity and grain filling than the local cultivar, and days decreased with delayed sowing. The biological and grain yields show significant positive correlations with SPAD values (p < 0.001) and days to maturity (p < 0.001). Our study shows that hybrid wheat cultivars can be opted for higher biomass production and grain yields under deficit irrigation scenarios of semi-arid climatic conditions in Pakistan. Moreover, the hybrid wheat cultivars can perform better than the indigenous cultivar even for delayed sowing dates of 30th November and 15th December.

Rice mutants with tolerance to multiple abiotic stresses show high constitutive abundance of stress-related transcripts and proteins

Mutation breeding has a long track record in the development of crop cultivars with improved tolerance to abiotic stresses such as heat, salinity and drought. Oryza sativa L. cv IR64 is a very popular high yielding rice, but susceptible to major abiotic stresses, such as low and high temperatures, salinity and drought. We subjected IR64 to gamma irradiation and generated a mutant population (M3) with ~2,000 families. These were screened at the seedling stage for tolerance to high-temperature stress using hydroponics and controlled-environment chambers, resulting in the identification of three mutant lines showing a robust seedling phenotype. Under heat stress, higher CO2 assimilation (10-30%), higher spikelet fertility (40-45%) and higher antioxidant activity (15-20% catalase activity) confirmed superiority of the selected mutant lines over wild type plants at seedling and flowering stages. Upon exposure to salinity and drought stress, the three selected lines also exhibited better tolerance than wild type in terms of higher CO2 assimilation, stomatal conductance, transpiration and chlorophyll fluorescence. Transcript and protein abundance analyses confirmed higher constitutive levels of heat shock proteins and antioxidant enzymes in the mutant lines relative to wild type. Tolerance to multiple abiotic stresses was reflected in higher (25-30%) grain yield than wild type. It is anticipated that the mutant lines identified will be useful for developing new improved cultivars for dry and saline areas and may be exploited to dissect the molecular basis of multiple stress tolerance in crop plants

Enhancement of root architecture and nitrate transporter gene expression improves plant growth and nitrogen uptake under long-term low-nitrogen stress in barley (Hordeum vulgare L.) seedlings

Over application of nitrogen (N) fertilizers to crops ultimately causes N pollution in the ecosphere. Studying the response of plant growth and N uptake to low-N stress may aid in elucidating the mechanism of low N tolerance in plants and developing crop cultivars with high nitrogen use efficiency (NUE). In this study, a high-NUE mutant line A9-29 and the wild-type barley cultivar Hua30 were subjected to hydroponic culture with high and low N supply, and the dry weight, N accumulation, root morphology, and expression levels of the potential genes involved in nitrate uptake and assimilation were measured at seedling stage. The results showed that under low-N conditions, A9-29 had a higher dry weight, N content, N influx rate and larger root uptake area than did Hua30. Under long-term low-N stress, compared with Hua30, A9-29 demonstrated higher expression of the HvNRT2/3 genes, especially HvNRT2.1, HvNRT2.5, and HvNRT3.3. Similarly, the expression levels of N assimilation genes including HvNIA1, HvNIR1, HvGS1_1, HvGS1_3, and HvGLU2 increased significantly in A9-29. Taken together, our results suggested that the larger root area and the upregulation of nitrate transporter and assimilation genes may contribute to stronger N uptake capacity for plant growth and N accumulation in responding to long-term low-N stress. These findings may aid in understanding the mechanism of low N tolerance and developing barley cultivars with high-NUE.

The transcription factor CmLEC1 positively regulates the seed-setting rate in hybridization breeding of chrysanthemum

Distant hybridization is widely used to develop crop cultivars, whereas the hybridization process of embryo abortion often severely reduces the sought-after breeding effect. The LEAFY COTYLEDON1 (LEC1) gene has been extensively investigated as a central regulator of seed development, but it is far less studied in crop hybridization breeding. Here we investigated the function and regulation mechanism of CmLEC1 from Chrysanthemum morifolium during its seed development in chrysanthemum hybridization. CmLEC1 encodes a nucleic protein and is specifically expressed in embryos. CmLEC1’s overexpression significantly promoted the seed-setting rate of the cross, while the rate was significantly decreased in the amiR-CmLEC1 transgenic chrysanthemum. The RNA-Seq analysis of the developing hybrid embryos revealed that regulatory genes involved in seed development, namely, CmLEA (late embryogenesis abundant protein), CmOLE (oleosin), CmSSP (seed storage protein), and CmEM (embryonic protein), were upregulated in the OE (overexpressing) lines but downregulated in the amiR lines vs. wild-type lines. Future analysis demonstrated that CmLEC1 directly activated CmLEA expression and interacted with CmC3H, and this CmLEC1–CmC3H interaction could enhance the transactivation ability of CmLEC1 for the expression of CmLEA. Further, CmLEC1 was able to induce several other key genes related to embryo development. Taken together, our results show that CmLEC1 plays a positive role in the hybrid embryo development of chrysanthemum plants, which might involve activating CmLEA’s expression and interacting with CmC3H. This may be a new pathway in the LEC1 regulatory network to promote seed development, one perhaps leading to a novel strategy to not only overcome embryo abortion during crop breeding but also increase the seed yield.

Nitrogen use efficiency in crops with new and available technologies

Among fertilizers, nitrogen (N) is the one that is used in the largest amounts mainly due to immediate response to the fertilizer-N application. However, the N use efficiency (NUE) is very low leading to high production costs and also a threat to the environment. Therefore, improving NUE is imperative. The 4 R’s (right quantity, right time, right method and right source) should be considered as the first step for enhancing NUE. Best management practices (BMP’s) of production and protection need to be adopted in order to achieve high NUE. Integration of novel N sources and nanofertilizers and better N fertilization products would lead to high NUE. Furthermore, novel techniques such as Precision Nutrient Management and Variable Rate Application to time nutrient application with crop need, and remote sensing are upcoming technologies that will bring about considerable savings in fertilizer-N. Further we should also account for plant physiological processes, including the diversity of mineral nutrient uptake mechanisms, their translocation and metabolism in order to breed and develop crop cultivars that are efficient N users.

English

Food security continues to be affected by global climatic changes which include increase of drought stress. A sustainable solution is to develop crop cultivars that are tolerant to climatic stresses. Among all crops cassava has a high potential to mitigate hunger. A field experiment was conducted to evaluate the performance of 79 cassava (Manihot esculenta) varieties under drought stress. The parameters evaluated were fresh storage root weight (SRFW), number of storage roots (NSR), above ground weight (AGW), plant height (PH), harvest index (HI) and leaf retention (LR). Results showed significant variations among varieties for most traits. Under stressed treatment, positive correlation was expressed between SRFW and NSR (0.373**), AGW (0.301**) and HI (0.560**). The HI and AGW expressed negative significant correlations-0.398**. Under non-stressed treatment, SRFW had a positive and significant with all the traits NSR (0.434**), AGW (0.377**), PH (0.102*), HI (0.437**) and LR (0.184**). There was negative significant correlations between HI and AGW (-0.482**). SRFW was used as a primary trait to select best performing genotypes. Most of the drought tolerant varieties expressed higher HI, NSR and AGW; hence, termed as target traits in selecting drought tolerance in cassava Key words: Phenotype, cassava (Manihot esculenta), drought stress, traits, Kiboko.

Jasmonic Acid at the Crossroads of Plant Immunity and Pseudomonas syringae Virulence.

Sensing of pathogen infection by plants elicits early signals that are transduced to affect defense mechanisms, such as effective blockage of pathogen entry by regulation of stomatal closure, cuticle, or callose deposition, change in water potential, and resource acquisition among many others. Pathogens, on the other hand, interfere with plant physiology and protein functioning to counteract plant defense responses. In plants, hormonal homeostasis and signaling are tightly regulated; thus, the phytohormones are qualified as a major group of signaling molecules controlling the most widely tinkered regulatory networks of defense and counter-defense strategies. Notably, the phytohormone jasmonic acid mediates plant defense responses to a wide array of pathogens. In this review, we present the synopsis on the jasmonic acid metabolism and signaling, and the regulatory roles of this hormone in plant defense against the hemibiotrophic bacterial pathogen Pseudomonas syringae. We also elaborate on how this pathogen releases virulence factors and effectors to gain control over plant jasmonic acid signaling to effectively cause disease. The findings discussed in this review may lead to ideas for the development of crop cultivars with enhanced disease resistance by genetic manipulation.

Functional characterization and regulatory mechanism of wheat CPK34 kinase in response to drought stress

BackgroundDrought is one of the most adverse environmental factors limiting crop productions and it is important to identify key genetic determinants for food safety. Calcium-dependent protein kinases (CPKs) are known to be involved in plant growth, development, and environmental stresses. However, biological functions and regulatory mechanisms of many plant CPKs have not been explored. In our previous study, abundance of the wheat CPK34 (TaCPK34) protein was remarkably upregulated in wheat plants suffering from drought stress, inferring that it could be involved in this stress. Therefore, here we further detected its function and mechanism in response to drought stress.ResultsTranscripts of the TaCPK34 gene were significantly induced after PEG-stimulated water deficiency (20% PEG6000) or 100 μM abscisic acid (ABA) treatments. The TaCPK34 gene was transiently silenced in wheat genome by using barley stripe mosaic virus-induced silencing (BSMV-VIGS) method. After 14 days of drought stress, the transiently TaCPK34-silenced wheat seedlings showed more sensitivity compared with control, and the plant biomasses and relative water contents significantly decreased, whereas soluble sugar and MDA contents increased. The iTRAQ-based quantitative proteomics was employed to measure the protein expression profiles in leaves of the transiently TaCPK34-silenced wheat plants after drought stress. There were 6103 proteins identified, of these, 51 proteins exhibited significantly altered abundance, they were involved in diverse function. And sequence analysis on the promoters of genes, which encoded the above identified proteins, indicated that some promoters harbored some ABA-responsive elements. We determined the interactions between TaCPK34 and three identified proteins by using bimolecular fluorescent complementation (BiFC) method and our data indicated that TaCPK34directly interacted with the glutathione S-transferase 1 and prx113, respectively.ConclusionsOur study suggested that the TaCPK34 gene played positive roles in wheat response to drought stress through directly or indirectly regulating the expression of ABA-dependent manner genes, which were encoding identified proteins from iTRAQ-based quantitative proteomics. And it could be used as one potential gene to develop crop cultivars with improved drought tolerance.