Factors related to productivity and persistence of lucerne (Medicago sativa) genotypes with different fall dormancy levels: A review

The lucerne productive and nutritional potential make it the most used forage legume worldwide. This wide use leads genetic improvement programs to increasingly select the main requirements for a given edaphoclimatic condition. However, in Brazil, the research on genetic improvement of lucerne has been limited over the years, which has hindered the production of this species and the domination of other legumes in animal production, as estilosantes and pigeon pea. This literature review aimed to present results from countries such as New Zealand and Australia that lead the world ranking, as well as Argentina, in the cultivation of this crop and that can be used as showcase to understand the management of lucerne. From extensive bibliometry analyses in the period between 1963 and 2021, variables as persistence and phyllochron in these countries indicate that it is possible to produce lucerne with similar productivity, longevity and quality in Brazil. Nevertheless, to leverage this production, not only genetic improvement should be aimed, but also research and dissemination of knowledge on the ideal management of defoliation and, mainly, on the choice of the genotype and dormancy level to be cropped by the producer

Identification of Functional Differences in Metabolic Networks Using Comparative Genomics and Constraint-Based Models

Genome-scale network reconstructions are useful tools for understanding cellular metabolism, and comparisons of such reconstructions can provide insight into metabolic differences between organisms. Recent efforts toward comparing genome-scale models have focused primarily on aligning metabolic networks at the reaction level and then looking at differences and similarities in reaction and gene content. However, these reaction comparison approaches are time-consuming and do not identify the effect network differences have on the functional states of the network. We have developed a bilevel mixed-integer programming approach, CONGA, to identify functional differences between metabolic networks by comparing network reconstructions aligned at the gene level. We first identify orthologous genes across two reconstructions and then use CONGA to identify conditions under which differences in gene content give rise to differences in metabolic capabilities. By seeking genes whose deletion in one or both models disproportionately changes flux through a selected reaction (e.g., growth or by-product secretion) in one model over another, we are able to identify structural metabolic network differences enabling unique metabolic capabilities. Using CONGA, we explore functional differences between two metabolic reconstructions of Escherichia coli and identify a set of reactions responsible for chemical production differences between the two models. We also use this approach to aid in the development of a genome-scale model of Synechococcus sp. PCC 7002. Finally, we propose potential antimicrobial targets in Mycobacterium tuberculosis and Staphylococcus aureus based on differences in their metabolic capabilities. Through these examples, we demonstrate that a gene-centric approach to comparing metabolic networks allows for a rapid comparison of metabolic models at a functional level. Using CONGA, we can identify differences in reaction and gene content which give rise to different functional predictions. Because CONGA provides a general framework, it can be applied to find functional differences across models and biological systems beyond those presented here

Global patterns and drivers of ecosystem functioning in rivers and riparian zones

River ecosystems receive and process vast quantities of terrestrial organic carbon, the fate of which depends strongly on microbial activity. Variation in and controls of processing rates, however, are poorly characterized at the global scale. In response, we used a peer-sourced research network and a highly standardized carbon processing assay to conduct a global-scale field experiment in greater than 1000 river and riparian sites. We found that Earth's biomes have distinct carbon processing signatures. Slow processing is evident across latitudes, whereas rapid rates are restricted to lower latitudes. Both the mean rate and variability decline with latitude, suggesting temperature constraints toward the poles and greater roles for other environmental drivers (e.g., nutrient loading) toward the equator. These results and data set the stage for unprecedented "next-generation biomonitoring" by establishing baselines to help quantify environmental impacts to the functioning of ecosystems at a global scale.peerReviewe

Canopy dynamics of lucerne (Medicago sativa L.) genotypes of three fall dormancies grown under contrasting defoliation frequencies

This study evaluated the canopy dynamics of three lucerne (Medicago sativa L.) genotypes of different fall dormancy (FD) ratings when grown under three contrasting defoliation regimes over five regrowth seasons at Lincoln University, Canterbury, New Zealand. Crops were sown in October 2014 in a split-plot design with main plots as defoliation frequencies (28 days [DF 28], 42 days [DF 42] and 84 days [DF 84]) and genotypes as subplots. Genotypes varied in fall dormancy (FD) rating and were classified as dormant (cv. AgR Palatable, FD2), semi-dormant (cv. Grassland Kaituna, FD5), or non-dormant (cv. SARDI 10, FD10). All crops were grown through an establishment phase until January 2015, when defoliation treatments were imposed. The experiment terminated in May 2019. Defoliation treatments were imposed from early spring (August-September) to autumn (May) with a single clean-up graze in late June/July. Defoliation frequency x genotype interactions showed FD10 was the most productive in regrowth season 1 but least persistent and productive in regrowth season 5, particularly under the DF 28 and DF 42 treatments. Results suggest different partitioning responses amongst genotypes. In a decreasing photoperiod, the growth rate of FD2 decreased by 0.77 ± 0.07 kg DM ha‾¹ °Cd‾¹ compared with 0.67 ± 0.09 kg DM ha‾¹ °Cd‾¹ for FD5 and FD10. However, FD10 showed no response to an increasing photoperiod under the DF28 defoliation regime. The lower rate of partitioning to perennial biomass of FD10 was suggested by the rapid decline in shoot density (−0.000112 shoot m‾² °Cd‾¹) over time compared with − 0.000049 shoot m‾² °Cd‾¹ for FD2 and FD5. FD10 had heavier individual shoot mass over the last two years, but its canopy plasticity was insufficient to control the shoot size/density balance, so there was greater weed ingress. The DF 84 treatment enabled FD10 to produce > 15 t DM ha‾¹ year‾¹ over the five regrowth seasons, which was not different to FD2 and FD5. Under more frequent defoliations, FD2 and FD5 were more persistent and had higher yields than FD10