Research Proposal: Fertilizer Effects on Corn Height and Chlorophyll

This research proposal, submitted for ERS301/501, investigates the impact of poultry manure, rock phosphate, and super phosphate on the growth of corn variety A. The study aims to determine how these fertilizers affect plant height and chlorophyll levels, which are crucial indicators of plant health and photosynthetic efficiency. The research includes a detailed scientific background highlighting the importance of food security and the role of efficient agricultural practices. The methodology involves statistical analysis using R with the R commander package to analyze data obtained from the ERS301/501 Moodle site. The study will employ numerical summaries, statistical graphs (histograms and scatter plots), and regression models to examine the relationship between fertilizer type, plant height, and chlorophyll levels. ANOVA tests will be conducted to compare the impact of different fertilizers. The budget includes costs for stationery, internet, computer/software hire, and wages for an assistant. The author's ethos emphasizes the use of data to address global issues like poverty and food insecurity. The research is expected to provide insights into optimizing fertilizer use for improved crop yields and contribute to the development of sustainable agricultural practices.

ERS301/501: Applied Research Skills
Research Proposal Form
SECTION 1. PROJECT TITLE.
Exploring the consequences of poultry manure, rock phosphate and super phosphate
on height and chlorophyll in corn variety A.
SECTION 2. SCIENTIFIC BACKGROUND AND MERIT
The escalating levels of hunger and food insecurity are among the major pandemics
facing third world and developing nations. High levels of poverty, malnourishment and
deaths have been reported as a result of these epidemics. Most nations have tried to
fight these issues through undertaking research in efficient and effective agricultural
methods that promote quantity and quality production (Lipton & Saghai, 2017). The
production of quality and enough agricultural food presents both short term and long-
term merits that help in curbing hunger and promote food security.
The quantity and quality of agricultural products yielded is dependent upon the fertility of
the direct producer. In plants fertility is directly proportional to the rate at which the
process of photosynthesis occurs. This rate is determined by the amount of chlorophyll
within the leaves of the plant. A well-nourished plant has sufficient amount of chlorophyll
to facilitate the photosynthesis process (Ghimire, Timsina & Nepal, 2015). Moreover, a
plant that has attained the specified height has the capability to hold as much required
leaves as possible ensuring that respiration and photosynthesis processes within the
plant are taking place sufficiently to ensure quality food productions.
The most common method of promoting plant fertility include the application of manure
and fertilizer of varied nutrient components at different specifications. Precursory
research studies have attempted to promote plant production through accessing the
impact of the application of different types of artificial fertilizers and natural manure at
different stages of the plant growth. Results have indicated that different types of
manure and fertilizer and manure have different impact of on the height and leaf quality
of the plant (Vijayan, 2017).

The determination of plant height has previously been based upon the use of physical
methods of measurement whereas assessment of leaf quality to examine the
chlorophyll levels has been based on physical observation and scientific methods
(Szeles, Megyes & Nagy, 2012). Physical methods of observing leaf quality are not
accurate and hence the scientific method is the most preferred. Since previous research
has indicated a correlation between type of fertilizer, the height of plant and the
chlorophyll level, research is continuously being undertaken for the purposes of
developing the best hybrid fertilizer type that would have the optimum positive impact in
the amount of yields plants a give at any particular agricultural season.
SECTION 3. HYPOTHESES
Hypothesis tests are grouped in two categories; the ‘group’ analysis hypothesis test and
the ‘association’ analysis hypothesis test. The group analysis hypothesis test will relate
to whether there is any significant relationship between height, chlorophyll and fertilizer
type. On the other hand, the association analysis hypothesis test will involve testing
whether all the fertilizer types have the same impact on height and chlorophyll or
whether they have different impacts.
The null hypothesis for group analysis is that there is no significant relationship between
chlorophyll, height and the fertilizer applied while the alternative hypothesis is that there
is significant relationship between height, chlorophyll and fertilizer applied.
The null hypothesis for association analysis is that all the fertilizer types have the same
impact on height and chlorophyll whereas the alternative hypothesis is that the different
fertilizers have different impacts on height and chlorophyll.
SECTION 4. METHODS
This study performs the comparison of height and chlorophyll level for corn variety A
when different types of nourishments are applied during plants growth. The data used
has been obtained from ERS301/501 Moodle site. The data has a total of sixty-four
samples of corn from different varieties labelled A to D. Even though the data supplied
comprises different varieties of corn, of interest to this study is corn variety A and
therefore, all the other varieties have been discarded. Moreover, the data has a number

of variables considered as factors affected by application of different fertilizer/manure
types. However, the variable selected to be important to the study include; input,
chlorophyll level, and the height of the corn. All the other variables are treated as
miscellaneous. Input is a categorical variable representing the type of nourishment
applied or whether not applied (control), height and chlorophyll are continuous numeric
variable indicating height of corn and chlorophyll level respectively (Shao, 2010).
To draw meaningful conclusions from the data, analysis will be done using statistical
program, R with R commander package (Rugg & Petre, 2017). The measurement and
the distribution of the data will be examined through the use of numerical summaries
and statistical graphs such as histograms and scatter plots (Fowler, 2009). The
histogram will visually express how failure or application of different fertilizers will impact
the height and chlorophyll while the scatter plot will used to indicate relationships and
the strengths of relationship. Regression model will be applied in the investigation of the
relationship between chlorophyll level, the height of the corn and the type of fertilizer
applied (Levie, 2012). Moreover, different ANOVA tests will be conducted to examine
whether the different nourishment applied will have the same or varied impact on height
and chlorophyll (Selvanathan & Keller, 2017). The level of significance of the above
tests will be 0.05.
SECTION 5. BUDGET
Line item Units Unit cost Total
Stationery purchase 20 $10/unit $200
Fast internet connectivity 4weeks $35/week $140
Computer/software hire 4weeks $30/week $120
Wage 30hours $10/hour $300
$760
Stationery purchase covers all the cost that will be incurred in purchase of writing
materials such as notebooks, writing pads, charts, pens and marker pens. The price is
based on the market average price of the most essential stationeries.

Fast internet is essential for quick retrieval of information for literature review. The cost
is based on the average pricing of the fasted internet service provider for the most
convenient bandwidth.
Computer/software hire is based on the market pricing for hiring computers with
convenient software’s. Portable fast processing PC’s with the necessary statistical
software’s for data analysis and word processing software’s for report writing will be
required.
Wage is the cost per hour that will be charged by the assistant who will aid in
accelerating the process of data analysis, report writing and presentation preparation.
SECTION 6. ETHOS
I’m an individual who for years have been interested in utilizing useful data to predict
and provide solution for underlying and anticipated problems. Currently I am a research
student whose area of interest is to leverage the use of data as a mean of assessing
problems and providing impactful solutions for them. The aims and objectives of my
future work involve analysing readily available and collected data to provide solution to
various problems and issues affecting or likely to affect governmental and non-
governmental organizations.
As a research student, the reason for selecting the above particular topic is to address a
range of problems including poverty, food insecurity, and hunger that result from poor
selection of plant nourishment materials in agriculture. Besides, the topic helps uncover
how application of different readily available natural and artificial fertilizers impact
agricultural yield. The results can be used to select the best nourishment that would
result to optimum production. Moreover, the result can be applied in manufacturing
industries to aid in the integration of different fertilizer mix to produce a single hybrid
fertilizer type that would be suitable for the production of the specified plant variety while
ensuring maximum yield.

SECTION 7. REFERENCES
Fowler, F. (2009). Survey research methods. Thousand Oaks, Calif.: Sage.
Ghimire, B., Timsina, D., & Nepal, J. (2015). Analysis of chlorophyll content and its
correlation with yield attributing traits on early varieties of maize. Journal of
Maize Research and Development, 1(1), 134-145. doi:10.3126/jmrd.v1i1.14251
Levie, P.R. (2012). Advanced excel for scientific data analysis (2nd ed). New York, NY:
Oxford University Press.
Lipton, M., & Saghai, Y. (2017). Food security, farmland access ethics, and land
reform. Global Food Security, 12, 59-66. doi: 10.1016/j.gfs.2016.03.004
Rugg, G., & Petre, M. (2017). A gentle guide to research methods. Maidenhead: Open
University Press.
Selvanathan, E. A., & Keller, G. (2017). Business statistics abridged (7th ed). South
Melbourne, Victoria: Cengage Learning.
Shao, J. (2010). Mathematical statistics (2nd ed). New York: Springer.
Szeles, A. V., Megyes, A., & Nagy, J. (2012). Irrigation and nitrogen effects on the leaf
chlorophyll content and grain yield of maize in different crop years. Agricultural
Water Management, 107, 133-144. doi: 10.1016/j.agwat.2012.02.001
Vijayan, R. (2017). Impact of drought stress on leaf chlorophyll content in maize
cultivars. International Journal of Plant Sciences, 12(1), 50-55.
doi:10.15740/has/ijps/12.1/50-55