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14 results on '"Ghimire, Om"'

5. Tropical root responses to global changes: A synthesis.

Author

Yaffar, Daniela, Lugli, Laynara F., Wong, Michelle Y., Norby, Richard J., Addo‐Danso, Shalom D., Arnaud, Marie, Cordeiro, Amanda L., Dietterich, Lee H., Diaz‐Toribio, Milton H., Lee, Ming Y., Ghimire, Om Prakash, Smith‐Martin, Chris M., Toro, Laura, Andersen, Kelly, McCulloch, Lindsay A., Meier, Ina C., Powers, Jennifer S., Sanchez‐Julia, Mareli, Soper, Fiona M., and Cusack, Daniela F.

Subjects
TROPICAL ecosystems, TROPICAL forests, PLANT metabolism, BIOMASS, PLANT nutrients
Abstract

Tropical ecosystems face escalating global change. These shifts can disrupt tropical forests' carbon (C) balance and impact root dynamics. Since roots perform essential functions such as resource acquisition and tissue protection, root responses can inform about the strategies and vulnerabilities of ecosystems facing present and future global changes. However, root trait dynamics are poorly understood, especially in tropical ecosystems. We analyzed existing research on tropical root responses to key global change drivers: warming, drought, flooding, cyclones, nitrogen (N) deposition, elevated (e) CO2, and fires. Based on tree species‐ and community‐level literature, we obtained 266 root trait observations from 93 studies across 24 tropical countries. We found differences in the proportion of root responsiveness to global change among different global change drivers but not among root categories. In particular, we observed that tropical root systems responded to warming and eCO2 by increasing root biomass in species‐scale studies. Drought increased the root: shoot ratio with no change in root biomass, indicating a decline in aboveground biomass. Despite N deposition being the most studied global change driver, it had some of the most variable effects on root characteristics, with few predictable responses. Episodic disturbances such as cyclones, fires, and flooding consistently resulted in a change in root trait expressions, with cyclones and fires increasing root production, potentially due to shifts in plant community and nutrient inputs, while flooding changed plant regulatory metabolisms due to low oxygen conditions. The data available to date clearly show that tropical forest root characteristics and dynamics are responding to global change, although in ways that are not always predictable. This synthesis indicates the need for replicated studies across root characteristics at species and community scales under different global change factors. [ABSTRACT FROM AUTHOR]

Published
2024
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10. Unlocking the Secrets of Soil: Exploring the Microbiome and Its Applications—Part 1.

Author

Ghimire, Om Prakash, Nepal, Jaya, Poudel, Pratima, and Powar, Suraj

Subjects
*PLANT hormones, *SOIL ecology, *BOTANY, *SOILS, *MONOCULTURE agriculture, *AGRICULTURAL ecology, *COVER crops, *AGRICULTURE
Abstract

This article provides an overview of the microbiome, specifically focusing on soil microbiomes and their applications. It explains that the microbiome consists of microorganisms like fungi, bacteria, and viruses in a specific environment. The article discusses the positive and negative impacts of microbes on human health, ecosystems, and various industries, including agriculture and medicine. It emphasizes the importance of soil microbiomes for plant growth, nutrient cycling, and disease resistance. The article also explores specific types of soil microbes and their roles in plant health and nutrient uptake. It highlights the significance of soil microbes in nutrient recycling, soil decomposition, and soil formation, as well as their interactions with plants in the rhizosphere. The article concludes by stating that further research is needed to optimize beneficial associations between soil microbes and plants for enhanced agricultural systems. [Extracted from the article]

Published
2024
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11. Data Analytical Skills in Agricultural Science: Growing Knowledge, Training in Emerging High‐Throughput Techniques and Machine‐Learning Applications.

Author

Ghimire, Om Prakash and Ghimire, Deepak

Abstract

A United Nations report predicts that the world population will reach 10 billion by 2050 and will require 70% more food than is currently produced. To meet this demand, crop performance and productivity need to be improved through crop improvement and breeding programs. High-throughput phenotyping and sequencing techniques have been adopted to screen crop phenotypes and genetic makeup, allowing for the optimization of crop yield and adaptation to different environments. Data analytical skills are crucial for effectively harnessing the potential of large datasets generated by high-throughput techniques. Machine learning approaches, such as neural networks, support vector machines, regression, clustering, and random forest, are used for data analysis and visualization. However, it is important to understand the issues of correlation and causation when working with big data. Resources and training programs are available to develop data analytical skills, and several programming languages and online learning platforms offer courses in data analytics. The integration of high-throughput methods with machine learning has revolutionized agricultural research and provides opportunities for advancements in agricultural science. [Extracted from the article]

Published
2023
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