Implementing Automation in the Design and Manufacturing of Vetiver Planting System and Analyzing Vetiver Growth Data

The large-scale cultivation of vetiver grass (Chrysopogon zizanioides) plays a crucial role in soil erosion control, land restoration, and sustainable agriculture. However, traditional manual planting methods are labor-intensive, time-consuming, and prone to inconsistencies. This research addresses these challenges through the design and development of a semi-automated vetiver planting system, aimed at improving planting efficiency, consistency, and scalability. In parallel, a comprehensive data analysis was conducted to examine the influence of environmental factors such as soil moisture, pH, nutrient levels, and rainfall on vetiver growth. The study presents a functional prototype that significantly reduces manual effort and enhances planting precision, particularly in terrains where conventional methods are difficult to apply. Key environmental variables were identified, and their correlation with plant health was explored using field collected data. The findings not only demonstrate the viability of semi-automated planting systems but also highlight the potential for future innovations including real-time soil sensing, predictive irrigation, and UAV assisted deployment. This research provides a foundation step toward sustainable, data-driven, and scalable vetiver grass cultivation systems adaptable to diverse field conditions.

Name thesis:degree_name

Master of Science

Level thesis:degree_level

Masters

Discipline thesis:degree_discipline

Engineering

Grantor

Texas State University

Year dc:date.issued

2025

Author dc:creator

• Ullah, Md Hasib

Advisor dc:contributor.advisor

• Asiabanpour, Bahram

Committee members dc:contributor.committeemember

• Kim, Namwon
• Chen, Heping

• vetiver grass
• semi-automated planting system
• soil erosion control
• sustainable agriculture
• scalable cultivation
• terrain adaptability
• data driven agriculture

Language dc:language.iso

en

Handle dc:identifier.uri

https://hdl.handle.net/10877/22112

OAI identifier oai:identifier

oai:digital.library.txst.edu:10877/22112