Excessive usage of chemicals in crops, especially in leafy vegetables, caused people exposed to health and environmental risks. In Iran, spinach used as a winter vegetable that believed has high Iron and is useful for anemia. The objective of the experiment was to determine the optimum use of each macronutrients to obtain safe maximum growth and yield for scaling up among farmers. Treatments were chemical fertilizers including ammonium sulfate, triple superphosphate and potassium sulfate at 50, 100, 150 and 200 kg/h against control in a randomized complete block design. Results showed that nitrogen caused elevation of fresh and dry weight in spinach as the maximum obtained in 200 kg/h ammonium sulfate. Results obtained from effect of phosphorus showed that super phosphate increased fresh and dry weight of spinach; but potassium sulfate had no effect on its growth and yield. Analysis of variance on cross effect of data showed significant differences in fresh and dry weight, number of leaves, chlorophyll content and nitrate, and non-significant differences in length and wide of leaves.
Objective: The influence of climate on forest stands cannot be ignored, but most of the previous forest stand growth models were constructed under the presumption of invariant climate and could not estimate the stand growth under climate change. The model was constructed to provide a theoretical basis for forest operators to take reasonable management measures for fir under the influence of climate. Methods: Based on the survey data of 638 cedar plantation plots in Hunan Province, the optimal base model was selected from four biologically significant alternative stand basal area models, and the significant climate factors without serious covariance were selected by multiple stepwise regression analysis. The optimal form of random effects was determined, and then a model with climatic effects was constructed for the cross-sectional growth of fir plantations. Results: Richards formula is the optimal form of the basic model of stand basal area growth. The coefficient of adjustment was 0.8355; the average summer maximum temperature and the water vapor loss in Hargreaves climate affected the maximum and rate of fir stand stand growth respectively, and were negatively correlated with the stand growth. The adjusted coefficient of determination of the fir stand area break model with climate effects was 0.8921, the root mean square error (RMSE) was 3.0792, and the mean relative error absolute value (MARE) was 9.9011; compared with the optimal base model, improved by 6.77%, RMSE decreased by 19.04%, and MARE decreased by 15.95%. Conclusion: The construction of the stand cross-sectional area model with climate effects indicates that climate has a significant influence on stand growth, which supports the rationality of considering climate factors in the growth model, and it is important for the regional stand growth harvest and management of cedar while improving the accuracy and applicability of the model.
The significance of remittances to the Vietnamese economy necessitates investigating how they affect the value of the Vietnamese currency and other macroeconomic factors. Macroeconomic articles struggle to discover their impact on economic development, but measured remittances by migrant workers have recently soared. There is no academic study that has examined this phenomenon in Vietnam. This study uses wavelet frameworks to analyze the lead-lag nexus between exchange rates, remittances, and economic growth in Vietnam in time-frequency domains from 1995 to 2020. Overall, we find that: (i) remittances enhance economic growth in the short and medium run; (ii) exchange rates boost remittances in the short and medium run; (iii) exchange rates promote GDP in all frequency and time domains. Moreover, the partial wavelet coherence and multiple wavelet coherence frameworks also offered evidence supporting the wavelet coherence approach. More importantly, the outcomes of wavelet-based Granger causality unveil that there is two-way causality between the selected indicators, which means that all the indicators can predict each other at different frequencies. Our empirical results provide meaningful information for market participants and policymakers.
This study investigates the intricate relationship between a nation’s GDP growth rate and three key variables: the number of granted patents, research and development (R&D) expenditure, and education expenditure. The purpose of the research is to discern the impact of these factors on GDP growth rates. Drawing on theoretical frameworks, including Dynamic Ordinary Least Squares (DOLS), Fully Modified Ordinary Least Squares (FMOLS), and Canonical Correlation Regression (CCR) techniques, the paper employs a robust methodological approach to unveil insights into the dynamics of economic growth. Contrary to conventional assumptions, the results reveal a negative correlation between R&D expenditure and GDP growth rate. In contrast, the number of patents granted and education expenditure shows a positively significant effect on the GDP growth rate, underscoring the pivotal roles of intellectual property creation and education investment in fostering economic growth. The conclusion emphasizes the importance of a nuanced understanding of these relationships for policymakers. The research’s implications highlight the need for balanced investments in innovation and education. The originality and value of this study lie in its unique findings challenging established beliefs about the impact of R&D expenditure on economic growth.
This research paper aims to examine the association between financial development and environmental quality in 31 European Union (EU) countries from 2001 to 2020. This study proposed an estimation model for the study by combining regression models. The regression model has a dependent variable, carbon emissions, and five independent variables, including Urbanization (URB), Total population (POP), Gross domestic product (GDP), Credit to the private sector (FDB), and Foreign direct investment (FDI). This research used regression methods such as the Fixed Effects Model, Random Effects Model, and Feasible generalized least squaresThe findings reveal that URB, POP, and GDP positively impact carbon emissions in EU countries, whereas the FDB variable exhibits a contrary effect. The remaining variable, FDI, is not statistically significant. In response to these findings, we advocate for adopting transformative green solutions that aim to enhance the quality of health, society, and the environment, offering comprehensive strategies to address Europe’s environmental challenges and pave the way for a sustainable future.
The objective of this study was to evaluate the growth of four lettuce cultivars in Southern Piauí to recommend the best ones for the region. The experiment was conducted in a greenhouse with randomized blocks, with evaluation in subdivided time plots, evaluated in six seasons (20, 24, 28, 32, 36, 40 days after sowing—DAS) and with treatments corresponding to four cultivars (Americana Rafaela®, Grand Rapids TBR®, Crespa Repolhuda® and Repolhuda Todo ano®) with five repetitions. Leaf area, number of leaves, collar diameter, aboveground fresh mass, aboveground dry mass, root dry mass and total and the physiological indices of growth analysis were evaluated. The lettuce cultivars interfered significantly in the studied parameters, being that Americana Rafaela® and Repolhuda todo ano®, in the conditions that they were submitted, presented better performances and bigger morphophysiological indexes, cultivated in pot. The cultivars Americana Rafaela® and Repolhuda todo ano® can be produced under the conditions of the south of Piauí.
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