ORCID Profile
0000-0003-2356-4098
Current Organisations
Universidad Complutense de Madrid
,
Consejo Superior de Investigaciones Cientificas
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Publisher: MDPI AG
Date: 15-09-2021
Abstract: The objective of this study was to explore the physical properties of maize seeds in competition with weeds. The basic and complex geometric characteristics of seeds from maize plants, competing with Datura stramonium L. (DS) or Xanthium strumarium (XS) at different weed densities, were studied. It was found that the basic and complex geometric characteristics of maize seeds, such as dimension, aspect ratio, equivalent diameter, sphericity, surface area and volume, were significantly affected by weed competition. The increase in weed density from 0 to 8 plants m2 resulted in an increase in the angle of repose from 27° to 29°, while increasing weed density from 8 to 16 plants m2 caused a diminution of the angle of repose down to 28°. Increasing the density of XS and DS to 16 plants m2 caused a reduction in the maximum 1000 seed weight of maize by 40.3% and 37.4%, respectively. These weed side effects must be considered in the design of industrial equipment for seed cleaning, grading and separation. To our knowledge, this is the first study to consider the effects of weed competition on maize traits, which are important in industrial processing such as seed aeration, sifting and drying.
Publisher: Wiley
Date: 31-12-2019
DOI: 10.1111/GCB.14904
Abstract: 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 bio ersity 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 in idual 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.
Publisher: Wiley
Date: 30-12-2013
DOI: 10.1111/WRE.12065
Publisher: Wiley
Date: 09-05-2014
DOI: 10.1111/WBM.12047
Publisher: MDPI AG
Date: 21-10-2020
Abstract: In weed science and management, models are important and can be used to better understand what has occurred in management scenarios, to predict what will happen and to evaluate the outcomes of control methods. To-date, perspectives on and the understanding of weed models have been disjointed, especially in terms of how they have been applied to advance weed science and management. This paper presents a general overview of the nature and application of a full range of simulation models on the ecology, biology, and management of arable weeds, and how they have been used to provide insights and directions for decision making when long-term weed population trajectories are impractical to be determined using field experimentation. While research on weed biology and ecology has gained momentum over the past four decades, especially for species with high risk for herbicide resistance evolution, knowledge gaps still exist for several life cycle parameters for many agriculturally important weed species. More research efforts should be invested in filling these knowledge gaps, which will lead to better models and ultimately better inform weed management decision making.
Location: Spain
No related grants have been discovered for Jose Luis Gonzalez-Andujar.