1,720,990 research outputs found
ISIde : A rice modelling platform for in silico ideotyping
No full textEcophysiological models can be successfully used to analyze genotype by environment interactions, thus supporting breeders in identifying key traits for specific growing conditions. This is especially true for traits involved with resistance/tolerance to biotic and abiotic stressors, which occurrence can vary greatly both in time and space. However, no modelling tools are available to be used directly by breeders, and this is one of the reasons that prevents an effective integration of modelling activities within breeding programs. ISIde is a software platform specifically designed for district-specific rice ideotyping targeting (i) resistance/tolerance traits and (ii) breeders as final users. Platform usability is guaranteed by a highly intuitive user interface and by exposing to users only settings involved with genetic improvement. Other information needed to run simulations (i.e., data on soil, climate, management) is automatically provided by the platform once the study area, the variety to improve and the climate scenario are selected. Ideotypes indeed can be defined and tested under current and climate change scenario, thus supporting the definition of strategies for breeding in the medium-long term. Comparing the performance of current and improved genotype, the platform provides an evaluation of the yield benefits exclusively due to the genetic improvement introduced. An example of the application of the ISIde platform in terms of functionalities and results that can be achieved is reported by means of a case study concerning the improvement of tolerance to heat stress around flowering in the Oristanese rice district (Italy). The platform is currently available for the six Italian rice districts. However, the software architecture allows its extension to other growing areas – or to additional genotypes – via dedicated tools available at the application page
Tailoring parameter distributions to specific germplasm : impact on crop model-based ideotyping
Full text linkCrop models are increasingly used to identify promising ideotypes for given environmental and management conditions. However, uncertainty must be properly managed to maximize the in vivo realizability of ideotypes. We focused on the impact of adopting germplasm-specific distributions while exploring potential combinations of traits. A field experiment was conducted on 43 Italian rice varieties representative of the Italian rice germplasm, where the following traits were measured: light extinction coefficient, radiation use efficiency, specific leaf area at emergence and tillering. Data were used to derive germplasm-specific distributions, which were used to re-run a previous modelling experiment aimed at identifying optimal combinations of plant trait values. The analysis, performed using the rice model WARM and sensitivity analysis techniques, was conducted under current conditions and climate change scenarios. Results revealed that the adoption of germplasm-specific distributions may markedly affect ideotyping, especially for the identification of most promising traits. A re-ranking of some of the most relevant parameters was observed (radiation use efficiency shifted from 4th to 1st), without clear relationships between changes in rankings and differences in distributions for single traits. Ideotype profiles (i.e., values of the ideotype traits) were instead more consistent, although differences in trait values were found
Ideotype definition to adapt legumes to climate change : A case study for field pea in Northern Italy
Full text linkOne of the key strategies to alleviate negative impacts of climate change on crop production is the development of new cultivars better adapted to the conditions expected in the future. Despite the role of legumes as protein sources, medium- and long-term strategies currently debated mainly focus on agricultural policies and on improved management practices, whereas ideotyping studies using climate projections are scarcely reported. The objective of this study was to define pea ideotypes improved for yield and irrigation water productivity targeting current climate and four future projections centred on 2040, resulting from the combination of two General Circulation Models (HadGEM2 and GISS-ES) and two Representative Concentration Pathways (RCP4.5 and RCP8.5). The STICS model was used, with the default pea parameterization refined using data from two years of dedicated field experiments. Ideotypes were defined by combining STICS and the E-FAST sensitivity analysis method focusing on model parameters representing traits on which breeding programs are ongoing. Results showed that climate change is expected to decrease the productivity of current pea cultivars (up to -12.6%), and that increasing irrigation (to cope with the expected less favourable rainfall distribution) would not avoid yield losses. The proposed ideotypes, characterized by a shorter vegetative phase and by increased tolerance to high temperature, performed better than current varieties, providing higher yields (+4.5%) and reduced water consumption (-20%). For the first time, we demonstrated the suitability of STICS for ideotyping purposes and used a simulation model to define pea breeding strategies targeting future climate conditions
A new approach for modeling crop-weed interaction targeting management support in operational contexts: A case study on the rice weeds barnyardgrass and red rice
No full textDespite their potential to support the optimization of weed management, available ecophysiological models for the simulation of crop-weed interaction are still not adopted in operational contexts. For some of them the reasons deal with the insufficient validation in farming conditions, whereas others are either too complex for being used in operational contexts or too empiric for being free from site- or context-specific effects. Here we present a new approach (WeedyCoSMo) to support strategic decisions on weed management, derived from the CoSMo process-based model for the simulation of phytocoenosis dynamics. The model dynamically reproduces on a yearly basis the interaction between crop and weeds at canopy level through the daily quantification of the suitability of each species to weather conditions and management practices, as well as to the simulated system state variables. Dynamically predicted outputs are the relative abundance of crop and weeds and state variables for each species like, e.g., aboveground biomass, biomass of different plant organs, grain yield, leaf area index, plant height. WeedyCoSMo was calibrated and validated using data from different sites (in the Jiangsu province, China, and in Arkansas, USA) and years (from 1982 to 2014), where different rice varieties and two major rice weeds–i.e., red rice (Oryza sativa L., var. sylvatica) and barnyardgrass (Echinocloa crus-galli L.) – were grown in monoculture or mixture. Model performances were satisfying: for rice crops grown in interaction with weeds, relative root mean square error never exceeded 25.2%, regardless of the variable considered, and Nash-Sutcliffe modeling efficiency was always higher than 0.63. Despite the low number of inputs and parameters needed to run the simulations, the degree of accuracy was similar to the ones achieved with other models for crop-weed interaction. This allows considering WeedyCoSMo as a promising approach in light of the possible integration in decision support systems targeting operational farming conditions
Quantifying the Accuracy of Digital Hemispherical Photography for Leaf Area Index Estimates on Broad-Leaved Tree Species
No full textDigital hemispherical photography (DHP) has been widely used to estimate leaf area index (LAI) in forestry. Despite the advancement in the processing of hemispherical images with dedicated tools, several steps are still manual and thus easily affected by user’s experience and sensibility. The purpose of this study was to quantify the impact of user’s subjectivity on DHP LAI estimates for broad-leaved woody canopies using the software Can-Eye. Following the ISO 5725 protocol, we quantified the repeatability and reproducibility of the method, thus defining its precision for a wide range of broad-leaved canopies markedly differing for their structure. To get a complete evaluation of the method accuracy, we also quantified its trueness using artificial canopy images with known canopy cover. Moreover, the effect of the segmentation method was analysed. The best results for precision (restrained limits of repeatability and reproducibility) were obtained for high LAI values (>5) with limits corresponding to a variation of 22% in the estimated LAI values. Poorer results were obtained for medium and low LAI values, with a variation of the estimated LAI values that exceeded the 40%. Regardless of the LAI range explored, satisfactory results were achieved for trees in row-structured plantations (limits almost equal to the 30% of the estimated LAI). Satisfactory results were achieved for trueness, regardless of the canopy structure. The paired t-test revealed that the effect of the segmentation method on LAI estimates was significant. Despite a non-negligible user effect, the accuracy metrics for DHP are consistent with those determined for other indirect methods for LAI estimates, confirming the overall reliability of DHP in broad-leaved woody canopies
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Surfing parameter hyperspaces under climate change scenarios to design future rice ideotypes
No full textGrowing food crops to meet global demand and the search for more sustainable cropping systems are increasing the need for new cultivars in key production areas. This study presents the identification of rice traits putatively producing the largest yield benefits in five areas that markedly differ in terms of environmental conditions in the Philippines, India, China, Japan and Italy. The ecophysiological model WARM and sensitivity analysis techniques were used to evaluate phenotypic traits involved with light interception, photosynthetic efficiency, tolerance to abiotic stressors, resistance to fungal pathogens and grain quality. The analysis involved only model parameters that have a close relationship with phenotypic traits breeders are working on, to increase the in vivo feasibility of selected ideotypes. Current climate and future projections were considered, in the light of the resources required by breeding programs and of the role of weather variables in the identification of promising traits. Results suggest that breeding for traits involved with disease resistance, and tolerance to cold- and heat-induced spikelet sterility could provide benefits similar to those obtained from the improvement of traits involved with canopy structure and photosynthetic efficiency. In contrast, potential benefits deriving from improved grain quality traits are restricted by weather variability and markedly affected by G × E interactions. For this reason, district-specific ideotypes were identified using a new index accounting for both their productivity and feasibility
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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