1,720,958 research outputs found
Agronomic and Physiological Traits Response of Three Tropical Sorghum (<i>Sorghum bicolor</i> L.) Cultivars to Drought and Salinity
No full textSorghum holds the potential for enhancing food security, yet the impact of the interplay of water stress and salinity on its growth and productivity remains unclear. To address this, we studied how drought and salinity affect physiological traits, water use, biomass, and yield in different tropical sorghum varieties, utilizing a functional phenotyping platform, Plantarray. Cultivars (Kuali, Numbu, Samurai2) were grown under moderate and high salinity, with drought exposure at booting stage. Results showed that Samurai2 had the most significant transpiration reduction under moderate and high salt (36% and 48%) versus Kuali (22% and 42%) and Numbu (19% and 16%). Numbu reduced canopy conductance (25% and 15%) the most compared to Samurai2 (22% and 33%) and Kuali (8% and 35%). In the drought*salinity treatment, transpiration reduction was substantial for Kuali (54% and 57%), Samurai2 (45% and 60%), and Numbu (29% and 26%). Kuali reduced canopy conductance (36% and 53%) more than Numbu (36% and 25%) and Samurai2 (33% and 49%). Biomass, grain yield, and a-100 grain weight declined in all cultivars under both salinity and drought*salinity, and Samurai2 was most significantly affected. WUEbiomass significantly increased under drought*salinity. Samurai2 showed reduced WUEgrain under drought*salinity, unlike Kuali and Numbu, suggesting complex interactions between water limitation and salinity in tropical sorghum
Insights from utilizing data of different quality levels for simulating barley performance under Nordic conditions:The Agricultural Production Systems SIMulator model evaluation
No full textCrop model-aided ideotyping can accelerate the breeding of resilient barley cultivars. Yet, the accuracy of process descriptions in the crop models still requires substantial improvement, which is only possible with high-quality (HQ) experimental data. Despite being demanded frequently, such data are still rarely available, especially for Northern European barley production. This study is one of the first to contribute to closing this existing data gap through the targeted collection of HQ experimental data in pluri-annual, multi-location spring barley field trials in Denmark. With this data, the prediction accuracy of Agricultural Production Systems SIMulator significantly increased in contrast to commonly utilized lower quality datasets. Using this data for model calibration resulted in more accurate predictions of in-season plant development and important state variables (e.g. final grain yield and biomass). The model's prediction accuracy can ultimately be further improved by examining remaining model weaknesses that were discoverable with the HQ data. Process descriptions regarding, for example, early and late leaf development, soil water dynamics and respective plant response appeared to require further improvement. By illustrating the effect of data quality on model performance we reinforce the need for more model-guided field experiments. </p
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
Projected impacts of sowing date and cultivar choice on the timing of heat and drought stress in spring barley grown along a European transect
Full text link202
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
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
Linking crop modelling and experimentation to fully exploit genotypic diversity in barley for climate change adaptation in Europe
No full textSummary
Future barley production in Europe is projected to face severer and more frequent climate extreme events. Projections have also shown that potential climate-change induced yield losses can be significantly counteracted through implemented autonomous adaptation options and genetic improvement. Designing barley ideotypes supported by crop simulation models (CSMs), which can simulate genotype x environment x management interactions, can accelerate the breeding of cultivars that are better adapted to future conditions, yet this approach still has various limitations. This thesis shows, how a better linkage between modelling and experimentation can contribute to overcoming these limitations and hence to accelerating progress in climate change adaptation for barley production in Europe. Designing ideotypes starts with understanding the conditions of the target environment. We used agroclimatic indicators to provide a detailed target environment description focusing on projected heat and drought stress conditions at three contrasting barley production sites along a European transect (Chapter II). At all sites (Zaragoza, Dundee, Helsinki), temperatures were projected to increase during the future (2031-50) heading and grain filling periods, however heat stress could be avoided by advancing the heading date (through early sowing, choosing early flowering cultivars). Cultivation risks could arise from summer droughts at Helsinki, terminal droughts interrupted by a few high-rainfall events at Zaragoza and, possibly heavy rainfall and waterlogging at Dundee. As autonomous adaptation options were only partly successful in avoiding drought stress, combining those measures with resilient cultivars is crucial.
For reliable CSM-aided ideotype design, CSMs need to accurately capture impacts of climate extremes on crops, which they are still not able to do satisfactorily. The reason is that the data required to improve respective model deficiencies is not sufficiently available. A better linkage between modelling and experimentation can contribute significantly to providing these data as shown in the systematic review (Chapter III) and in model-guided experimental work in the field (Chapter IV) and a semi-controlled environment (Chapter V). Both experiments were conducted within the framework of European research projects that facilitated close collaboration between breeders, crop modelers and plant physiologists.
We collected high quality field data for model evaluation and improvement at a Nordic barley cultivation site, where such data is most rarely available (Chapter IV). The obtained dataset was of high temporal and spatial detail, containing multiple in-season above- and belowground data points. As its quality meets the highest standards for modelling it is well suitable for CSM improvement and contributes to closing a long existing data gap. APSIM calibrated with this high quality data captured in-season growth processes and final outputs most accurately. With these data we could also detect potential areas for model improvement, such as inaccurate soil water dynamics or leaf area development.
The greenhouse trial aimed at increasing our understanding of plant physiological processes to improve CSMs regarding e.g. simulated responses to climate extremes, like drought. In this experiment (Chapter V), we used a high-throughput functional phenotyping platform to examine the water use behavior of four European spring barley cultivars and their response to intermediate drought. The best performing cultivar (cv. RGT Planet) with high and stable yields under drought showed a dynamic (flexible) water use behavior: its high transpiration/assimilation rate under well-watered conditions made it more productive than the water-conserving cultivars which had a much lower transpiration rate. At the onset of drought cv. RGT Planet switched to a more water-conserving behavior allowing it to be more productive than the non-conserving cultivar. A drought ideotype could have such dynamic water use traits combined with high drought resilience (as observed in cv. RGT Planet) and beneficial root traits.
To further support model-guided experimentation all resources including new measurement tools and techniques, robotics, phenotyping and machine learning should be exploited and interdisciplinary research collaborations should be further promoted (as discussed in Chapter VI).2023-12-0
- …
