Course Description
Application of Computers in Technology, PLS 021V
Concepts of computing and applications using personal computers, spreadsheets, database management, word processing and communications.
Key Information
Credit: 3 quarter units /
2 semester units credit
UC Davis, PLSC
Course Credit:
Upon successful completion, all online courses offered through cross-enrollment provide UC unit credit. Some courses are approved for GE, major preparation and/or, major credit or can be used as a substitute for a course at your campus.If "unit credit" is listed by your campus, consult your department, academic adviser or Student Affairs division to inquire about the petition process for more than unit credit for the course.
UC Berkeley:
Unit Credit
UC Davis:
General Education: SciEng | SE, VL.—F, W, S. (F, W, S.)
Major Requirement: required for Plant Sciences Major and many others
UC Irvine:
General Education: II - Science and Technology
UC Los Angeles:
Unit Credit
UC Merced:
Unit Credit (see your Academic Advisor)
UC Riverside:
General Education: Elective units
UC San Diego:
Major Requirement: Computer Science and Engineering (CSE) lower division elective credit
UC San Francisco:
Unit Credit
UC Santa Barbara:
Unit Credit
UC Santa Cruz:
Unit Credit
Prerequisites
High school algebra.
Course Fees
$0
Course Creators
Brian Bailey
Brian Bailey
Bailey, an assistant professor in the Department of Plant Sciences, specializes in computational modeling of crop and plant systems. He completed his Ph.D. in mechanical engineering at the University of Utah. Bailey joined the UC Davis faculty in 2016 after working at the USDA-ARS Horticultural Crops Research Unit in Corvallis, Oregon.
Research interests:
Crop modeling, transport processes in the soil-plant-atmosphere continuum, high-performance computing
Brief overview:
Population growth, climate change, and diminishing resources are all factors driving the agricultural industry to adapt at an unprecedented rate. Traditionally, adoption of new practices or technologies is slow, particularly in perennial crops, as many seasons of trials may be needed before efficacy has been adequately demonstrated. Computer models are widely used in other industries to accelerate the design process and better understand current designs, but they have been underutilized in the agricultural industry.
I am developing the next generation of computational models to design and understand cropping systems. The models seek to provide growers with a virtual environment to simulate potential design and management choices, without the financial risks associated with field trials. For example, growers can use models to test how various management decisions (e.g., irrigation scheduling, pruning, fertilization) would affect their crops.
The computer models are also valuable scientific tools that fill in the gaps between measurements to provide a more complete, three-dimensional representation of important processes such as photosynthesis, water use, or CO2 exchange. The work is transdisciplinary, and relies on collaborations between experts in the fields of plant physiology, epidemiology, engineering, and computer science.
Current projects:
- Developing the next generation of crop and plant simulation tools
- Developing a three-dimensional data visualization system for vineyards
- Understanding the mechanisms influencing airborne dispersion in plant canopies
- Mapping the three-dimensional structure of plants using ground-based LiDAR scanning
Brian Bailey
Bailey, an assistant professor in the Department of Plant Sciences, specializes in computational modeling of crop and plant systems. He completed his Ph.D. in mechanical engineering at the University of Utah. Bailey joined the UC Davis faculty in 2016 after working at the USDA-ARS Horticultural Crops Research Unit in Corvallis, Oregon.
Research interests:
Crop modeling, transport processes in the soil-plant-atmosphere continuum, high-performance computing
Brief overview:
Population growth, climate change, and diminishing resources are all factors driving the agricultural industry to adapt at an unprecedented rate. Traditionally, adoption of new practices or technologies is slow, particularly in perennial crops, as many seasons of trials may be needed before efficacy has been adequately demonstrated. Computer models are widely used in other industries to accelerate the design process and better understand current designs, but they have been underutilized in the agricultural industry.
I am developing the next generation of computational models to design and understand cropping systems. The models seek to provide growers with a virtual environment to simulate potential design and management choices, without the financial risks associated with field trials. For example, growers can use models to test how various management decisions (e.g., irrigation scheduling, pruning, fertilization) would affect their crops.
The computer models are also valuable scientific tools that fill in the gaps between measurements to provide a more complete, three-dimensional representation of important processes such as photosynthesis, water use, or CO2 exchange. The work is transdisciplinary, and relies on collaborations between experts in the fields of plant physiology, epidemiology, engineering, and computer science.
Current projects:
- Developing the next generation of crop and plant simulation tools
- Developing a three-dimensional data visualization system for vineyards
- Understanding the mechanisms influencing airborne dispersion in plant canopies
- Mapping the three-dimensional structure of plants using ground-based LiDAR scanning
