Diagnostics,genetic diversity and pathogenic variation of ascochyta blight of cool season food and feed legumes

Molecular diagnostic techniques have been developed to differentiate the Ascochyta pathogens that infect cool season food and feed legumes, as well as to improve the sensitivity of detecting latent infection in plant tissues. A seed sampling technique was developed to detect a 1% level of infection by Ascochyta rabiei in commercial chickpea seed. The Ascochyta pathogens were shown to be genetically diverse in countries where the pathogen and host have coexisted for a long time. However, where the pathogen was recently introduced, such as A. rabiei to Australia, the level of diversity remained relatively low, even as the pathogen spread to all chickpea-growing areas. Pathogenic variability of A. rabiei and Ascochyta pinodes pathogens in chickpea and field pea respectively, appears to be quantitative, where measures of disease severity were based on aggressiveness (quantitative level of infection) rather than on true qualitative virulence. In contrast, qualitative differences in pathogenicity in lentil and faba bean genotypes indicated the existence of pathotypes of Ascochyta lentis and Ascochyta fabae. Therefore, reports of pathotype discrimination based on quantitative differences in pathogenicity in a set of specific genotypes is questionable for several of the ascochyta-legume pathosystems such as A. rabiei and A. pinodes. This is not surprising since host resistance to these pathogens has been reported to be mainly quantitative, making it difficult for the pathogen to overcome specific resistance genes and form pathotypes. For robust pathogenicity assessment, there needs to be consistency in selection of differential host genotypes, screening conditions and disease evaluation techniques for each of the Ascochyta sp. in legume-growing countries throughout the world. Nevertheless, knowledge of pathotype diversity and aggressiveness within populations is important in the selection of resistant genotypes.     

Projecting species distributions using fishery-dependent data

Many marine species are shifting their distributions in response to changing ocean conditions, posing significant challenges and risks for fisheries management. Species distribution models (SDMs) are used to project future species distributions in the face of a changing climate. Information to fit SDMs generally comes from two main sources: fishery-independent (scientific surveys) and fishery-dependent (commercial catch) data. A concern with fishery-dependent data is that fishing locations are not independent of the underlying species abundance, potentially biasing predictions of species distributions. However, resources for fishery-independent surveys are increasingly limited; therefore, it is critical we understand the strengths and limitations of SDMs developed from fishery-dependent data. We used a simulation approach to evaluate the potential for fishery-dependent data to inform SDMs and abundance estimates and quantify the bias resulting from different fishery-dependent sampling scenarios in the California Current System (CCS). We then evaluated the ability of the SDMs to project changes in the spatial distribution of species over time and compare the time scale over which model performance degrades between the different sampling scenarios and as a function of climate bias and novelty. Our results show that data generated from fishery-dependent sampling can still result in SDMs with high predictive skill several decades into the future, given specific forms of preferential sampling which result in low climate bias and novelty. Therefore, fishery-dependent data may be able to supplement information from surveys that are reduced or eliminated for budgetary reasons to project species distributions into the future.     

Identification and Analysis of Genetic Diversity Structure Within Pisum Genus Based on Microsatellite Markers

To assesse the genetic diversity among wild and cultivated accessions of 8 taxonomic groups in 2 species, and 5 subspecies under Pisum genus, and to analyze population structure and their genetic relationships among various groups of taxonomy, the study tried to verify the fitness of traditionally botanical taxonomic system under Pisum genus and to provide essential information for the exploration and utilization of wild relatives of pea genetic resources. 197 Pisum accessions from 62 counties of 5 continents were employed for SSR analysis using 21 polymorphic primer pairs in this study. Except for cultivated field pea Pisum sativum ssp. sativum var. sativum （94 genotypes）, also included were wild relative genotypes that were classified as belonging to P. fulvum, P. sativum ssp.abyssinicum, P. sativum ssp. asiaticum, P. sativum ssp. transcaucasicum, P. sativum ssp. elatius var. elatius, P. sativum ssp. elatius var. pumilio and P. sativum ssp. sativum var. arvense （103 genotypes）. The PCA analyses and 3-dimension PCA graphs were conducted and drawn by NTSYSpc 2.2d statistical package. Nei78 genetic distances among groups of genetic resources were calculated, and cluster analysis using UPGMA method was carried out by using Popgene V1.32 statistical package, the dendrogram was drawn by MEGA3.1 statistical package. Allelic statistics were carried out by Popgene V1.32. The significance test between groups of genotypes was carried out by Fstat V2.9.3.2 statistical package. 104 polymorphic bands were amplified using 21 SSR primer pairs with unambiguous unique polymorphic bands. 4.95 alleles were detected by each SSR primer pair in average, of which 65.56% were effective alleles for diversity. PSAD270, PSAC58, PSAA18, PSAC75, PSAA175 and PSAB72 were the most effective SSR pairs. SSR alleles were uniformly distributed among botanical taxon units under Pisum genus, but significant difference appeared in most pairwise comparisons for genetic diversity between taxon unit based groups of genetic resources. Genetic diversity level of wild species P. fulvum was much lower than the cultivated species P. sativum. Under species P. sativum, P. sativum ssp. sativum var. sativum and P. sativum ssp. asiaticum were the highest in gentic diversity, followed by P. sativum ssp. elatius var. elatius and P. sativum ssp. transcaucasicum, P. sativum ssp. elatius var. pumilio, P. sativum ssp. sativum vat. arvense and P. sativum ssp. abyssinicum were the lowest. Four gene pool clusters were detected under Pisum genus by using PCA analysis. Gene pool ＂fulvum＂ mainly consisted of wild species Pisum fulvum, gene pool ＂abyssinicum＂ mainly consisted of P. sativum ssp. abyssinicum, and gene pool ＂arvense＂ mainly consisted of P. sativum ssp. sativum var. arvense. While gene pool ＂sativum＂ were composed by 5 botanical taxon units, they are P. sativum ssp. asiaticum, P. sativum ssp. elatius var. elatius, P. sativum ssp. transcaucasicum, P. sativum ssp. elatius var. pumilio and P. sativum ssp. sativum var. sativum. ＂sativum＂ gene pool constructed the primary gene pool of cultivated genetic resources; ＂fulvum＂ gene pool, ＂abyssinicum＂ gene pool and ＂arvense＂ gene pool together constructed the secondary gene pool of cultivated genetic resources. Pairwise Nei78 genetic distance among botanical taxon based groups of pea genetic resources ranged from 7.531 to 35.956, 3 large cluster groups were identified based on the UPGMA dendrogram. Group Ⅰ equals to ＂sativum＂ and ＂arvense＂ gene pools, Group Ⅱ equals to ＂abyssinicum＂ gene pool, and Group Ⅲ equals to ＂fulvum＂ gene pool. The UPGMA clustering results generally supporting the PCA clusting results. There were significant differences among most botanical groups under Pisum genus, with clear separation of four gene pools for genetic diversity structure. The research results partially support the traditional botanical taxonomy under Pisum genus, and pointed out its advantage and shortcoming. In order to broaden the genetic bases of pea varieties, the genetic potentials in the four gene pools should be thoroughly exploited.     

Selection of wheat genotypes for biomass allocation to improve drought tolerance and carbon sequestration into soils

The biomass allocation pattern of plants to shoots and roots is a key in the cycle of elements such as carbon, water and nutrients with, for instance, the greatest allocations to roots fostering the transfer of atmospheric carbon to soils through photosynthesis. Several studies have investigated the root to shoot ratio (R:S) biomass of existing crops but variation within a crop species constitutes an important information gap for selecting genotypes aiming for increasing soil carbon stocks for climate change mitigation and food security. The objectives of this study were to evaluate agronomic performance and quantify biomass production and allocation between roots and shoots, in response to different soil water levels to select promising genotypes for breeding. Field and greenhouse experiments were carried out using 100 genotypes including wheat and Triticale under drought‐stressed and non‐stressed conditions. The experiments were set‐up using a 10 × 10 alpha lattice design with two replications under water stress and non‐stress conditions. The following phenotypic traits were collected: number of days to heading (DTH), number of productive tillers per plant (NPT), plant height (PH), days to maturity (DTM), spike length (SL), kernels per spike (KPS), thousand kernel weight (TKW), root biomass (RB), shoot biomass (SB), root to shoot ratio (R:S) and grain yield (GY). There was significant (p < 0.05) variation for grain yield and biomass production because of genotypic variation. The highest grain yield of 247.3 g/m² was recorded in the genotype LM52 and the least was in genotype Sossognon with 30 g/m². Shoot biomass ranged from 830 g/m² (genotype Arenza) to 437 g/m² (LM57), whilst root biomass ranged between 603 g/m² for Triticale and 140 g/m² for LM15 across testing sites and water regimes. Triticale also recorded the highest R:S of 1.2, whilst the least was 0.30 for wheat genotype LM18. Overall, drought stress reduced total biomass production by 35% and R:S by 14%. Genotypic variation existed for all measured traits useful for improving drought tolerance, whilst the calculated R:S values can improve accuracy in estimating C sequestration potential of wheat. Wheat genotypes LM26, LM47, BW140, LM70, LM48, BW152, LM75, BW162, LM71 and BW141 were selected for further development based on their high total biomass production, grain yield potential and genetic diversity under drought stress.     

Nitrate and Phosphate Leaching under Turfgrass Fertilized with a Squid-based Organic Fertilizer

Consumer demand for cleaned squid generates a substantial amount of waste that must be properly disposed of, creating an economic burden on processors. A potential solution to this problem involves converting squid by-products into an organic fertilizer, for which there is growing demand. Because fertilizer application to lawns can increase the risk of nutrient contamination of groundwater, we quantified leaching of NO₃–N and PO₄–P from perennial ryegrass turf (Lolium perenne L.) amended with two types of fertilizer: squid-based (SQ) and synthetic (SY). Field plots were established on an Enfield silt loam, and liquid (L) and granular (G) fertilizer formulations of squid and synthetic fertilizers were applied at 0, 48, 146, and 292 kg N ha⁻¹ year⁻¹. Levels of NO₃–N and PO₄–P in soil pore water from a depth of 60 cm were determined periodically during the growing season in 2008 and 2009. Pore water NO₃–N levels were not significantly different among fertilizer type or formulation within an application rate throughout the course of the study. The concentration of NO₃–N remained below the maximum contaminant level (MCL) of 10 mg L⁻¹ until midSeptember 2009, when values above the MCL were observed for SQG at all application rates, and for SYL at the high application rate. Annual mass losses of NO₃–N were below the estimated inputs (10 kg N ha⁻¹ year⁻¹) from atmospheric deposition except for the SQG and SYL treatments applied at 292 kg N ha⁻¹ year⁻¹, which had losses of 13.2 and 14.9 kg N ha⁻¹ year⁻¹, respectively. Pore water PO₄–P levels ranged from 0 to 1.5 mg P L⁻¹ and were not significantly different among fertilizer type or formulation within an application rate. Our results indicate that N and P losses from turf amended with squid-based fertilizer do not differ from those amended with synthetic fertilizers or unfertilized turf. Although organic in nature, squid-based fertilizer does not appear to be more—or less—environmentally benign than synthetic fertilizers.     

Rewetting and litter addition influence mineralisation and microbial communities in soils from a semi-arid intermittent stream

Nitrogen (N) and carbon (C) mineralisation are triggered by pulses of water availability in arid and semi-arid systems. Intermittent streams and their associated riparian communities are obvious ‘hot spots’ for biogeochemical processes in arid landscapes where water and often C are limiting. Stream landscapes are characterized by highly heterogeneous soils that may respond variably to rewetting. We used a laboratory incubation to quantify how N and C mineralisation in rewetted soils and sediments from an intermittent stream in the semi-arid Pilbara region of north-west Australia varied with saturation level and substrate addition (as ground Eucalyptus litter). Full (100%) saturation was defined as the maximum gravimetric moisture content (%) achieved in free-draining soils and sediments after rewetting, with 50% saturation defined as half this value. We estimated rates and amounts of N mineralised from changes in inorganic N and microbial respiration as CO₂ efflux throughout the incubation. In soils and sediments subject to 50% saturation, >90% of N mineralised accumulated within the first 7 d of incubation, compared to only 48% when soils were fully saturated (100% saturation). Mineralisation rates and microbial respiration were similar in riparian and floodplain soils, and channel sediments. N mineralisation rates in litter-amended soils and sediments (0.73 mg N kg⁻¹ d⁻¹) were only one-third that of unamended samples (3.04 mg N kg⁻¹ d⁻¹), while cumulative microbial respiration was doubled in litter-amended soils, suggesting N was more rapidly immobilized. Landscape position was less important in controlling microbial activity than soil saturation when water-filled pore space (% WFPS) was greater than 40%. Our results suggest that large pulses of water availability resulting in full soil saturation cause a slower release of mineralisation products, compared to small pulse events that stimulate a rapid cycle of C and N mineralisation-immobilization.