Assessment of sugarcane varieties for their stability and yield potential in Fiji

The Sugar Research Institute of Fiji breeds and produces new varieties of sugarcane for the Fiji sugar industry for commercial production. The development of sugar cane varieties that show superior performance in different environments is a major challenge for breeders due to the response of genotypes across environments. This study was to evaluate the relative performance the genotypes during breeding program and identify promising ones that could be released for cultivation. Thus, an investigation was carried out to determine the magnitude of Genotype Environment interactions and the stability analysis of the genotypes cultivated in Fiji. Seventeen genotypes including three commercial varieties were evaluated in five locations using a randomized block design with three replications. The pooled analysis of variance carried out for the effect of environments, genotypes, and their interactions. The stability analysis was also performed using the Eberhart & Russell’s (1966) model. Further, a cluster analysis was proposed for identifying the similar and stable genotypes. The results showed that there were highly significant (p < 0.001) variations among the genotypes (G), environments (E) and GE interactions. Two genotypes LF82-2122 and LF60-3917 had higher yield and stability statistics for the two most important traits: cane and sugar yields. Thus, the genotypes can be recommended for adoption and cultivation on all soil types in Fiji

TRY plant trait database – enhanced coverage and open access

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Truncating Variants in NAA15 Are Associated with Variable Levels of Intellectual Disability, Autism Spectrum Disorder, and Congenital Anomalies

Genetics of disease, diagnosis and treatmen

Stability analysis in elite sugarcane varieties of Fiji

The present investigation was conducted to identify the stable cultivars across different environmental condition. Seventeen genotypes of which fourteen were in the final stage of multi-location secondary adaptation trials of the plant breeding program and three commercial varieties were evaluated in five different locations. The stability parameters regression coefficients (βi) and mean square deviations (S2di) were estimated for cane yield using the Eberhart & Russell's (1966) model. The pooled analysis of variance showed highly significant variances for environments (E), Genotypes (G), and GxE interactions. The results showed that there were highly significant (p <; 0.001) variations among the genotypes, environments and GxE interaction for cane yield. The top four high yielding genotypes were found to be LF82-2122, LF60-3917, LF82-2244 and LF57-5104. The first two genotypes had higher yield and stability statistics. Thus, from the present study it is concluded that for cane yield, the genotypes LF82-2122 and LF60-3917 can be recommended for adoption as the two most superior promising varieties for cultivation on all soil types in Fiji

The innovativeness of Born-Globals and customer orientation: Learning from Indian Born-Globals

Born-Global firms, a newly emerging organizational form targeting international markets as a primary source of business from their inception, have innovativeness, requiring an intimate knowledge of their customer, as a primary feature. This study explores how a Born-Global's customer orientation leads to innovativeness through technological capability for customer relationship management (CRM) and external customer information management. Our empirical results, based on responses from 154 Indian managers, indicate that a Born-Global's customer orientation is an effective enabler of its innovativeness, whose effects are mediated by technological capability for CRM and external customer information management. Although significantly affected by customer orientation, the results further indicate that relationship quality with the buyer does not influence a Born-Global's innovativeness. When CRM technology and managing customer information obtained from external sources are employed, customer orientation significantly helps maintain the innovativeness of Born-Globals according to the results.Born-Globals Customer orientation Innovativeness

Biogeochemistry of trace elements

International audienc

The Mass of the Milky Way from the H3 Survey

The mass of the Milky Way is a critical quantity that, despite decades of research, remains uncertain within a factor of two. Until recently, most studies have used dynamical tracers in the inner regions of the halo, relying on extrapolations to estimate the mass of the Milky Way. In this paper, we extend the hierarchical Bayesian model applied in Eadie & Juri to study the mass distribution of the Milky Way halo; the new model allows for the use of all available 6D phase-space measurements. We use kinematic data of halo stars out to 142 kpc, obtained from the H3 survey and Gaia EDR3, to infer the mass of the Galaxy. Inference is carried out with the No-U-Turn sampler, a fast and scalable extension of Hamiltonian Monte Carlo. We report a median mass enclosed within 100 kpc of (68% Bayesian credible interval), or a virial mass of , in good agreement with other recent estimates. We analyze our results using posterior predictive checks and find limitations in the model's ability to describe the data. In particular, we find sensitivity with respect to substructure in the halo, which limits the precision of our mass estimates to ∼15%. © 2022. The Author(s). Published by the American Astronomical Society..Open access articleThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]