# Analyzing the Effects of Glyphosate on Resistant and Susceptible Amaranthus Tuberculatus Populations

October 04, 2023
Yasmin Howarth
🇬🇧 United Kingdom
Data Analysis
Yasmin Howarth is a statistics assignment expert with an academic background from the University of York, where she obtained her Ph.D. in Statistics. With 7 years of experience, she has established herself as a leading authority in data analysis.
Key Topics
• Problem Description
• Analysis of Resistant Population
Tip of the day
News

In this in-depth analysis, we delve into the intricate relationship between glyphosate, a commonly used herbicide, and two distinct populations of Amaranthus Tuberculatus—resistant and susceptible. Through rigorous statistical modeling, we uncover their divergent responses to glyphosate exposure, shedding light on how resistant plants exhibit higher LD50 values, indicating reduced susceptibility. These findings emphasize the critical importance of monitoring herbicide resistance and its potential implications for sustainable weed management and agriculture.

## Problem Description

The data analysis assignment required an analysis of the effects of glyphosate, a commonly used herbicide, on the survival of both resistant and susceptible populations of Amaranthus tuberculatus, a weed species. The primary focus was on estimating LD50 values (the glyphosate concentration at which 50% of the plants would die within 21 days) for the two populations and examining how they responded differently to the herbicide. The analysis involved logistic regression models and statistical inferences.

## Analysis of Resistant Population

Statistical Model: The statistical model for the logistic regression curve fitted for the resistant plants is as follows: SurvProp = logit(P) = log(P/(1-P)) = 4.5258 - 0.9360*Dose

• SurvProp: Proportion of surviving plants
• P: Probability of survival
• Dose: Dose of Glyphosate in g per hectare
• Fig 1: logistic regression curve fitted for the resistant plants

Results:

• Glyphosate concentration negatively affects survival (coefficient for Dose: -0.9360).
• The p-value for the coefficient is not statistically significant (0.205).
• The rate of change in the probability of survival with each unit increase in glyphosate dose is 0.9360 (approximately 61%).

Odds of Survival at 1 g glyphosate per hectare:

• The odds of survival are approximately 36.16.

LD50 Estimate:

• Estimated LD50 for resistant plants: 4.84 g/ha (95% confidence interval: 2.97 to 6.70 g/ha).

Analysis of Susceptible Population

Statistical Model: For the susceptible plants, the logistic regression model is given by: ln(p/(1-p)) = 1.992 - 10.16 * Dose

Results:

• Estimated LD50 for susceptible plants: 0.196 g/ha.
• Wide confidence interval (95% CI: 0 - 2.177 g/ha), indicating substantial uncertainty due to a small sample size and no deaths at lower doses.

Summary and Implications

The experiment explored the impact of glyphosate on resistant and susceptible populations of Amaranthus tuberculatus, revealing significant differences in their responses to the herbicide. Key findings and implications include:

1. Divergent Responses: Resistant plants exhibited a higher LD50 value (4.84 g/ha) compared to susceptible plants (0.196 g/ha), indicating that resistant plants are less affected by glyphosate.
2. Monitoring Herbicide Resistance: The study underscores the importance of monitoring weed populations for the development of herbicide resistance, which can have profound implications for weed management and crop production.
3. Exposure Levels: The results hint at herbicide resistance evolving more rapidly in populations exposed to higher herbicide doses. This is evident in the resistant population found in a field with a history of glyphosate use.
4. Sustainable Agriculture: These findings have implications for the development of effective weed management strategies, particularly within the context of sustainable agriculture.

This analysis demonstrates how statistical methods can be employed to assess the effects of glyphosate on different weed populations, shedding light on the dynamics of herbicide resistance and its potential impact on agriculture.

## Related Samples

Dive into a rich pool of sample statistics assignments! Our collection covers diverse topics like probability distributions and data analysis. Whether you're a student seeking guidance or an enthusiast refreshing your knowledge, our samples offer valuable insights. Explore and elevate your understanding of statistics with ease!