1,720,956 research outputs found
Boosting the resilience to drought of crop plants using wood distillate: A pilot study with lettuce (Lactuca sativa L.)
Full text linkIncreasingly severe drought driven by climate change is harming crop quality and productivity, making it crucial to find nature-based solutions like wood distillate (WD) to aid crops withstand these stressful conditions. This study investigated the effects of WD application on the growth and stress responses of lettuce (Lactuca sativa L.) under drought conditions. The experiment included periodic measurements of plant growth-related parameters and stress indices to evaluate the effectiveness of WD in mitigating drought-induced damage. The results showed a significant increase (13–26 %) in fresh biomass of the aboveground portion of lettuce treated with WD, indicating the potential of WD as a biostimulant to promote plant growth. In addition, treatment with WD led to a significant increase in total soluble protein content (14–28 %), showing a possible positive effect on protein synthesis. The enhancement of anti-radical activity (measured in terms of DPPH) following the application of WD up to 42 % reflected the ability of the plant to scavenge harmful reactive oxygen species and alleviate oxidative stress. The observed reduction (up to 19 % in comparison with control) in MDA content also confirmed the effectiveness of WD in protecting the integrity of plant cell membranes from oxidative damage. Despite the beneficial effects on anti-radical activity, the total content of the antioxidant compounds (phenols and flavonoids) decreased with the use of WD (5–14 %), most likely suggesting complex interactions between WD and the biosynthesis of these secondary metabolites. The study showed the positive effect of WD application on the growth and stress tolerance of lettuce plants under drought conditions. These results can provide new insights into sustainable agricultural practices and the potential application of WD as a nature-based and effective means to improve crop productivity, especially in water scarce areas
Bone char outperforms biochar in phosphorus-deficient soils: Comparative analysis of soil fertility enhancement and greenhouse gas mitigation
Full text linkPhosphorus (P) deficiency limits crop yields globally, creating a need for sustainable alternatives to synthetic P fertilizers. This study evaluates the effects of biochar and bone char on maize growth, soil fertility, P availability, and greenhouse gas (GHG) emissions in soils with a moderate or low P content. A 42-day pot experiment was conducted with three treatments: control, conventional biochar, and bone char, each applied at 1 % (w/w). Measurements included plant growth, soil properties, nutrient levels in soil and pore water, and GHG fluxes (N2O, CH4 and CO2). The results showed that bone char significantly enhanced plant growth, especially in P-deficient soils, where shoot biomass was ten times higher than the control. Bone char also dramatically increased P availability in both soil types, outperforming biochar, which had limited effects on P levels. In terms of GHG mitigation, both biochar and bone char reduced N2O and CH4 emissions compared to the control, with bone char showing greater effectiveness in P-deficient soils, potentially due to its slow-release nutrient properties. Biochar promoted methane consumption, especially in P-rich soils. The findings suggest that bone char is an ideal amendment for P-deficient soils, offering dual benefits of nutrient enhancement and GHG reduction, while biochar's advantages lie in improving soil physical properties and mitigating emissions across different soil types. Overall, we conclude that bone char represents a viable option to improve sustainable P cycling and GHG mitigation in agronomic systems, highlighting the circular economy benefits of repurposing waste materials
Promoting early growth in tomato (Solanum lycopersicum L.) by co-application of biochar and beneficial bacteria
No full textThe use of biochar and beneficial bacteria as biofertilizers is gaining increasing attention as a means to reduce the reliance on agrochemical inputs in future agriculture. However, the dynamics of introduced bacteria in biochar-amended soils, as well as the additive effects of bacteria and biochar during the early stages of plant growth, are still poorly characterized. First, a synthetic bacterial community was formulated and its ability to survive was assessed in both non-amended and biochar-amended soils. Secondly, both the individual and combined effects of biochar (applied at 10% (w: w)) and a consortium of five bacteria (Bacillus sp. strain B1, Bacillus velezensis strain Bv1, Bacillus pumilus strain Bp1, Bacillus licheniformis sp. strain Bl1 and Priestia megaterium strain Pm1) isolated from a bio-fertilizer were examined on various biometric and physiological traits of young tomato (Solanum lycopersicum L. var. Principe borghese) plants. At the seedling stage, the sole application of bacteria increased hypocotyl length by 25%, but decreased radicle length compared to non-treated soils. At the plantlet stage, bacteria alone further increased both shoot length by and leaf surface area by 13% and 22%, respectively, but decreased leaf chlorophyll content. On the other hand, co-application of biochar and bacteria partially restored leaf chlorophyll content to control levels, and showed additive effects improving the fresh and dry weight of aboveground tissues by ~ 30% compared to untreated soils. Biochar amendment decreased leaf N content both in the presence and absence of bacteria, suggesting a possible N immobilization in biochar particles which could reduce its availability for the plant. These results point biochar as a suitable material for the survival and viability of synthetic bacterial communities, and show that biochar and the tested inoculum can additively improve key attributes in young tomato plants
Modeling Soil Erosion Susceptibility Using Machine Learning Techniques: Rud‐e‐Faryab Basin, Iran
Full text linkSoil erosion poses a significant threat to water and soil resources, affecting agricultural productivity, infrastructure, and environmental stability. This study models erosion susceptibility in the Rud-e-Faryab basin (Bushehr province, Iran) using the BIOMOD-2 package in R (an ensemble of 10 machine learning algorithms) applied to 10 important environmental variables. Field data on erosion events were used to train and validate the model, and the performance of the model was evaluated using ROC, KAPPA, and TSS coefficients. The results indicate different accuracies for different erosion types, highlighting the GLM, RF, ANN, SRE, and MARS models. Geological formation, slope, and soil resources were found to be the most important factors for erosion susceptibility in the study. Key innovations of this study include (1) the first-time adaptation of the BIOMOD-2 package for soil erosion assessment, (2) the introduction of a stability analysis framework with 10 repeated model runs to test reproducibility, and (3) a comprehensive comparison of 10 machine learning models to identify context-specific optimal approaches. These contributions provide a robust, replicable framework for erosion risk mapping that is particularly valuable in regions with sparse data, and provide actionable insights for sustainable land use planning and resource management
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
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
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